WO2007070021A1

WO2007070021A1 - Detection of calcifying nano-particles, and associated proteins thereon

Info

Publication number: WO2007070021A1
Application number: PCT/US2005/044589
Authority: WO
Inventors: E. Olavia Kajander; Katja Aho; Neve Ciftioglu
Original assignee: Nanobac Pharmaceuticals Inc
Current assignee: Nanobac Pharmaceuticals Inc
Priority date: 2005-12-09
Filing date: 2005-12-09
Publication date: 2007-06-21
Anticipated expiration: 2008-06-09

Abstract

Disclosed are methods and compositions for detecting, analyzing and assessing the significance of calcifying nano-particles. The disclosed methods and compositions generally involve detecting one or more proteins present on a calcifying nano-particle. It has been discovered that particular proteins become associated with calcifying nano-particles. This association provides a means for detecting, classifying, analyzing, categorizing, and assessing calcifying nano-particles. Detecting particular proteins while associated with a calcifying nano-particle can be used to indicate the presence and type of calcifying nano-particle, which can be used to indicate the presence of, or disposition to, diseases or conditions. Multiple proteins on a calcifying particle can be detected. The presence or absence of particular proteins and the pattern of the presence and absence of particular proteins can be used to indicate the presence and type of calcifying nano-particle.

Description

METHODS AND COMPOSITIONS FOR THE DETECTION OF CALCIFYING

NANO-PARTICLES, IDENTIFICATION AND QUANTIFICATION OF ASSOCIATED PROTEINS THEREON, AND CORRELATION TO DISEASE

FIELD OF THE INVENTION The disclosed invention is generally in the field of calcification and calcifying bodies and specifically in the area of calcifying nano-particles. For example, the present invention discloses methods and compositions for the identication of calcifying nano- particles and protein/calcifying nanoparticles complexes and the correlation of said particles to various diseases. BACKGROUND OF THE INVENTION

Calcifying nano-particles (CNPs) are approximately 200 nm in size and appear to multiply in the biological mode, meaning their growth curve has the same characteristics as that of a life form, i.e., certain doubling time (typically around 3 days), plus a lag, a logarithmic, a stationary and even a death phase. The particles are passageable apparently indefinitely in cell culture media (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. USA 95, 8274 (1998)). The main structural component identified, without question, is bonelike apatite (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. USA 95, 8274 (1998); Miller et al., Am. J. Physiol. Heart Circ. Physiol. 287, Hl 115 (2004); Cisar et al., Proc. Natl. Acad. Sci. USA. 97, 11511 (2000); VaIi et al, Geochim. Cosmochim. Acta 65, 63 (2001); Ciftcioglu et al., Kidney Int. 67, 483 (2005)). CNPs have been isolated from kidney stones (Ciftcioglu et al., Kidney Int. 56, 1893 (1999); Khullar et al., Urol. Res. 32, 190 (2004)), gall stones (Wen et al., Chin Med. J. 118, 421 (2005)), calcific cancer (Sedivy and Battistutti, APMIS 111,951 (2003); Hudelist et al., Histopathology 45, 633 (2004)) and pathological calcifications (Miller et al., Am. J. Physiol. Heart Circ. Physiol. 287, Hl 115 (2004)). CNPs have been clearly differentiated from known biological entities: eubacteria, archaea, virus, prions and eukaryotes (Aho and Kajander, J. Clin. Microbiol. 41, 3460 (2003)).

CNPs have been shown to form mineral calcium or hydroxy apatite coatings on their surfaces. The hydroxy apatite surface acts an a mineral calcium substrate for the binding of calcium binding proteins (CaBP). Proteins that associate with the CNP

Hydroxy apatite complex (CNP/HA complex) may undergo a conformational change. Subsequently, the CNP/HA CaBP complex may attract or bind proteins that have an affinity to the aforementioned bound CaBPs. Neoeopitope formation is causal for multiple binding by host proteins. Crosslink formation is causal for multiple binding of host protein and stabilizes the structure so that it is stable and can withstand washing steps, for example, detergents, freeze thawing, etc., step involved in assays and storage functions.

Copending applications 11/102,798 , 11/180,921, and 11/182,076 disclose methods and compositions for the treatment of CNPs and are incorporated by reference hererin. Commonly assigned patents 6,706,290 (Eradication of Nanobacteria) and 5,135,851 (Culture and Detection Methods for the Sterile Filterable autonomously replicating biological particles) are incorporated by reference herein.

BRIEF SUMMARY OF THE INVENTION Disclosed are methods and compositions for detecting, analyzing and assessing the significance of calcifying nano-particles. The disclosed methods and compositions generally involve detecting one or more proteins present on a calcifying nano-particle. It has been discovered that particular proteins become associated with calcifying nano- particles. This association provides a means for detecting, classifying, analyzing, categorizing, and assessing calcifying nano-particles. Detecting particular proteins while associated with a calcifying nano-particle can be used to indicate the presence and type of calcifying nano-particle, which can be used to indicate the presence of, or disposition to, diseases or conditions. Multiple proteins on a calcifying particle can be detected. The presence or absence of particular proteins and the pattern of the presence and absence of particular proteins can be used to indicate the presence and type of calcifying nano- particle.

The disclosed method can involve detecting calcifying particles by detecting one or more proteins on the calcifying particle. The method generally can involve detecting at least one protein on the calcifying particle by binding at least one compound to the protein and detecting the bound compound. Binding a compound to the protein can involve, for example, an antibody. The antibody can be the compound and also can be the means of specific binding of the compound to the protein. As another example, a compound can be associated with an antibody with the antibody mediating binding of the compound to the protein. Detecting the bound compound can be accomplished by, for example, detecting the compound directly or indirectly. For example, the compound can be detected using, for example, a microarray, coded beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination. It should be understood that myriad compositions and methods are known for the detection of analytes and such can be used in and with the disclosed compositions and methods for the detection of calcifying nano-particles and proteins on calcifying nano- particles. Some such compositions and methods are described herein and others are known to those of skill in the art. It has also been discovered that particular proteins and other components are found on calcifying nano-particles and that detection of such proteins and components can serve to detect, classify, analyze, categorize, and assess calcifying nano-particles. For example, the detection of two or more particular proteins in association (in the same location or on the same particle, for example) is indicative and/or characteristic of calcifying nano- particles. As another example, the detection of a particular protein on a calcifying nano- particle is indicative and/or characteristic of calcifying nano-particles. The presence of the protein on the calcifying nano-particle and/or the identity of combinations of particular proteins serve as identifying characteristics of calcifying nano-particles.

Said proteins can undergo a conformational change as result of being associated with calcifying nano-particles. For example, calcium binding proteins will bind to the mineral calcium or hydroxy apaptite coating that surrounds calcifying nano-particles in the circulatory sytem of a mammal. There may be primary or primary and secondary changes that occur to the calcium binding protein. Secondary conformational changes involve crosslink formation between peptides or modification of amino acids in peptides by enzymes, oxidation, and chemical reactions. The conformational changes may result in neoepitopes which are specific to these conformationally changed proteins. This speficity of conformational changed proteins on the surface of the calcifying nano-particles provides for the specific discovery, detection, classification, analysis, categorization, and assessment of calcifying nano-particles as described herein is useful for diagnosing, assessing, and/or monitoring diseases associated with calcification and calcifying nano- particles, the progress of such diseases, and the progress of treatment of such diseases.

Calcifying nano-particles are implicated in and represent a risk factor for disease. For example, as described in Example 1, calcifying nano-particles can stimulate a novel blood coagulation mechanism. This mechanism can explain why thrombosis occurs in diseases associated with calcification and calcifying nano-particles. Because of this discovery, detection, classification, analysis, categorization, and assessment of calcifying nano-particles as described herein is useful for diagnosing, assessing, and/or monitoring diseases associated with calcification and calcifying nano-particles, the progress of such diseases, and the progress of treatment of such diseases.

Disclosed is a method for detecting calcifying nano-particles, where the method comprises detecting calcifying nano-particles by detecting one or more proteins on the calcifying nano-particles.

Also disclosed is a method for detecting one or more proteins, where the method comprises detecting one or more proteins on a calcifying nano-particle.

Also disclosed is a method of characterizing a calcifying nano-particle, where the method comprises identifying one or more proteins on a calcifying nano-particle. Also disclosed is a method of charactering a calcifying nano-particle, where the method comprises identifying one or more protein on a calcifying nano-partilce where said identification forms a pattern.

Also disclosed is a method using said pattern to diagnose a disease or condition.

Also disclosed is a method of diagnosing a disease or condition, where the method comprises identifying one or more proteins on a calcifying nano-particle from a subject.

The identified proteins identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated.

Also disclosed is a method of assessing the prognosis of a disease or condition, where the method comprises identifying one or more proteins on a calcifying nano-particle from a subject. The identified proteins identify calcifying nano-particles that are related to or associated with the prognosis of the disease or condition.

Also disclosed is a method of identifying a subject at risk of a disease or condition, where the method comprises identifying one or more proteins on a calcifying nano-particle from a subject. The identified proteins identify calcifying nano-particles that are related to or associated with a risk of developing a disease or condition.

Also disclosed is an isolated calcifying nano-particle, where the calcifying nano- particle comprises one or more of the proteins selected from the group consisting of proteins with a Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor XfXa, CDl 4, Prothrombin, Factor DC, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Larninin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. Additionally, proteins that bind to calcium binding proteins may bind to said calcium binding protein/calcifying nano-particles complex including but not limited to Fetuin binding proteins, Thrombin binding proteins, Troponin binding proteins, Tropomyosin binding proteins, GLA Matric binding proteins, Fibrin binding proteins, Kallikrein binding proteins, Factor binding proteins, Matrix metalloprotinease binding proteins, Platelet glycol binding proteins, NF Kappa B binding protein, Factor X binding protein. Table 9 shows representative proteins.

Also disclosed is a composition comprising a calcifying nano-particle and one or more compounds bound to one or more proteins on the calcifying nano-particle. Also disclosed is a composition of a calcifying nano-particle comprising a hydroxy apatite (mineral calcium phosphate) coating.

Also disclosed is a composition of a calcifying nano-particle comprising said calcifying nanoparticle and a mineral calcium hydroxy apatite coating containing bound proteins that may be conformationally changed. Also disclosed is a method of determining the progress of treatment of a subj ect having calcifying nano-particles, where the method comprises detecting one or more proteins on calcifying nano-particles in a sample from the subject, and repeating the detection in another sample from the subject following treatment. A change in the level, amount, concentration, or a combination of calcifying nano-particles in the subject indicates the progress of the treatment of the subject.

Also disclosed are compositions comprising apatite and a coating material, where, for example, the coating material limits exposure of the blood of a subject when the composition is in a subject. The present applications may provide for testing of implants of other devices for the detection of CNPs, for example, stents, prosthetics, articificial valves, etc. Artificial devices are commonly covered with calcific biofilms.

Also disclosed is a method of testing biocompatibility comprising testing blood coagulation in the absence of anticoagulants. Also disclosed is a method of testing materials that will be exposed to circulating blood for formation of calcific biofilm formation.

For purposes of explanation, the term "protein" is meant to include both proteins in there natural state or proteins that have undergone a conformational change, be it primary or primary and secondary hereafter. Calcifying nano-particles can be detected by detecting one or more of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A₅ Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kapρa B, Osteopontin, Factor X/Xa, CD 14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin- 1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFFon the calcifying nano-particle. Additionally, proteins that bind to calcium binding proteins may bind to said calcium binding protein/calcifying nano-particles complex including but not limited to Fetuin binding proteins, Thrombin binding proteins, Troponin binding proteins, Tropomyosin binding proteins, GLA Matric binding proteins, Fibrin binding proteins, Kallikrein binding proteins, Factor binding proteins, Matrix metalloprotinease binding proteins, Platelet glycol binding proteins, NF Kappa B binding protein, Factor X binding protein. Table 9 shows representative proteins. Calcifying nano-particles can be detected by detecting two or more proteins on the calcifying nano-particles. Calcifying nano-particles can be detected by detecting one or more proteins with a GLA-containing domain. Calcifying nano-particles can be detected by detecting one or more proteins with a calcium binding domain. Calcifying nano-particles can be captured, identified, or both prior to, simultaneous with, or following detection of one or more of the proteins. Capture or identification of the calcifying nano- particle can indicate that the detected proteins are on the calcifying nano-particles. Calcifying nano-particles can be captured by binding at least one compound to one or more of the proteins, wherein the compound is or becomes immobilized. Calcifying nano- particles can be identified by binding at least one compound to one or more of the proteins, wherein the calcifying nano-particles are separated based on the compound. Calcifying nano-particles can be separated by fluorescence activated sorting.

One or more of the proteins can be detected by binding at least one compound to the protein and detecting the bound compound. Detection of two or more bound compounds can indicate that the proteins to which the compounds are bound are on the calcifying nano-particle. The two or more compounds can be detected in the same location or at the same time. The compounds can be an antibody, where the antibody is specific for the protein. The calcifying nano-particles can comprise calcium phosphate and one or more of the proteins. The proteins can be detected by detecting any combination of 100 or fewer of the proteins selected from the group consisting of proteins with a Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CD14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. The proteins can be detected by detecting any combination of 75 or fewer of the proteins. The proteins can be detected by detecting any combination of 50 or fewer of the proteins. The proteins can be detected by detecting any combination of 25 or fewer of the proteins. The proteins can be detected by detecting any combination of 10 or fewer of the proteins. The proteins can be detected by detecting any combination of 7 or fewer of the proteins. The proteins can be detected by detecting any combination of 3 or fewer of the proteins. The combination of proteins can be detected in the same assay. The combination of proteins can be detected simultaneously. The combination of proteins can be detected on the same calcifying nano-particle. The combination of proteins can be detected on or within the same device. The combination of proteins detected can constitute a pattern of proteins. The pattern can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The pattern can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern can identify the type of calcifying nano-particles detected. The proteins can be detected by detecting the presence or absence of any combination of 100 or fewer of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kaρρa B, Osteopontin, Factor XZXa, CD 14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain,

Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano- particle. The pattern of the presence or absence of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The pattern of the presence or absence of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern of the presence or absence of the proteins can identify the type of calcifying nano- particles detected. The presence of one or more of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The presence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The presence of one or more of the proteins can identify the type of calcifying nano-particles detected. The absence of one or more of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The absence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The absence of one or more of the proteins can identify the type of calcifying nano-particles detected. The proteins can be detected using any suitable composition, apparatus, or technique, for example, a microarray, coded beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination.

The proteins on the calcifying nano-particle can be detected by (a) capturing the calcifying nano-particle, (b) binding a detection compound to one or more of the proteins, and (c) detecting the detection compound. The proteins on the calcifying nano-particle can be detected by (a) binding a detection compound to one or more of the proteins, (b) capturing the calcifying nano-particle, and (c) detecting the detection compound. The calcifying nano-particle can be captured by binding a capture compound to one or more of the proteins, where the capture compound is or becomes immobilized. The proteins to which capture compounds bind can mediate capture, where the detection compound can be bound to one of the proteins, where the calcifying nano-particle can be characterized by determining which proteins mediate capture of the calcifying nano-particle to which the detected detection compound is bound. The capture compound can be bound to one of the proteins, where the detection compounds detected can indicate which of the proteins is present on the calcifying nano-particle, where the calcifying nano-particle can be characterized by which proteins are present on the calcifying nano-particle. The identified proteins can identify the type of calcifying nano-particle. The identified type of calcifying nano-particle can be related to or associated with a disease or condition. The identified proteins can identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated. The identified proteins can identify a disease or condition that is caused by calcifying nano- particles having the identified proteins. The identified proteins can identify a disease or condition in which calcifying nano-particles having the identified proteins are produced.

Subjects in which pathological thrombosis can occur via apatite-mediated clotting are useful targets for the disclosed methods. Such subjects can include (1) Patients with vulnerable plaque rupture exposing atheroma calcification; (2) Patients undergoing angioplasty or heart-lung machine perfusion; (3) Patients with massive bone fractures or dislocated implants releasing potentially apatite particles; (4) Patients with implants, catheters, wires or stents subject to calcium encrustation; (5) Cancer patients with soft tissue calcification; and (6) Healthy or sick people with CNPs in their blood or positive calcification scores in arteries. The composition can comprise a calcifying nano-particle and one or more compounds bound to two or more proteins on the calcifying nano-particle. The compound can comprise an antibody, where the antibody is specific for the protein. The compound can block the calcifying nano-particle.

Additional advantages of the disclosed method and compositions will be set forth in part in the description which follows, and in part will be understood from the description, or may be learned by practice of the disclosed method and compositions. The advantages of the disclosed method and compositions will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate several embodiments of the disclosed method and compositions and together with the description, serve to explain the principles of the disclosed method and compositions.

Figures IA- IE are diagrams showing an example of Surface Antigen Pattern Immunoassay (SAPIA). CNP refers to calcifying nano-particles.

Figures 2A and 2B are graphs of levels of signal generated for various proteins in SAPIA performed on positive (Figure 2A) and negative (Figure 2B) serum and plasma samples showing same levels in serum and plasma.

Figure 3 is a scatterplot of SAPIA results for clotting matrix GLA proteins, fibrinogen and tissue factor, and CNP capture ELISA results.

Figure 4 is a graph of levels of signal generated for various proteins in SAPIA showing the presence of pro-thrombin fragments and oesteocalcin in CNPsas measured by sepia.

Figures 5 A and 5B are graphs of prothrombin activation on apatite using bovine (Figure 5A) and human (Figure 5B) prothrombin.

Figure 6 is a graph of whole blood clotting times for various materials using glass slide test. Figure 7 is a diagram of apatite-mediated clotting pathway.

Figure 8 is a diagram of a model for conformational changes caused by apatite/blood calcium binding as exemplified by prothrombin.

Figure 9 is a diagram of formation of fibrin in response to thrombotic event due to CNPs how thrombin bound to apatite surface activates formation of fibrin. Figures 1OA shows boxplots of individual disease states.

Figures 1OB shows boxplots of individual proteins correlating with disease.

Figure 1OC shows protein stip plots.

Figure 11 is a graph of clinomics samples for 15 diseases associated with CNPs. Marker values can be obtained from the disease. Figure 12 is a graph depicting urine expression showing physiological differentiations of various CNP isolates ^99mTc.

Figure 13 is a graph of CNP antigen (U/niL) for Pacreatitis, Rheumatoid Arthritis and Cholecystitis. Figure 14 is a boxplot of biomarkers for negative endometrioid adenocarcinoma. Figure 15 is a boxplot for biomarkers for positive endometrioid adenocarcinoma. Figure 16 is scatterplot of markers for aortic data. Figure 17 is a scatterplot of markers for arthritis data. Figure 18 is a scatterplot of markers for cholecystitis data.

Figure 19 is a scatterplot of markers for endometrioid data. Figure 20 is a- scatterplot of markers for kidney stones data. Figure 21 is a scatterplot of markers for Parkinson's data. Figure 22 is a scatterplot of markers for prostate data. Figure 23 is a scatterplot of markers for prostatitis data.

DETAILED DESCRIPTION OF THE INVENTION The disclosed method and compositions may be understood more readily by reference to the following detailed description of particular embodiments and the Example included therein and to the Figures and their previous and following description. Disclosed are methods and compositions for detecting, analyzing and assessing the significance of calcifying nano-particles. The disclosed methods and compositions generally involve detecting one or more proteins present on a calcifying nano-particle. It has been discovered that particular proteins become associated with calcifying nano- particles. This association provides a means for detecting, classifying, analyzing, categorizing, and assessing calcifying nano-particles. Detecting particular proteins while associated with a calcifying nano-particle can be used to indicate the presence and type of calcifying nano-particle, which can be used to indicate the presence of, or disposition to, diseases or conditions. Multiple proteins on a calcifying particle can be detected. Proteins may experience a conformational change resultant from association and/or binding to the califying nano-particle. Proteins associated with calcifying nano-particles may undergo secondary conformational changes. Proteins may bind to proteins associated to calcifying nanoparticles. The presence or absence of particular proteins and the pattern of the presence and absence of particular proteins can be used to indicate the presence and type of calcifying nano-particle. The disclosed method can involve detecting calcifying particles by detecting one or more proteins on the calcifying particle. The method generally can involve detecting at least one protein on the calcifying particle by binding at least one compound to the protein and detecting the bound compound. Binding a compound to the protein can involve, for example, an antibody. The antibody can be the compound and also can be the means of specific binding of the compound to the protein. As another example, a compound can be associated with an antibody with the antibody mediating binding of the compound to the protein. Detecting the bound compound can be accomplished by, for example, detecting the compound directly or indirectly. For example, the compound can be detected using, for example, a microarray, coded beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination. It should be understood that myriad compositions and methods are known for the detection of analytes and such can be used in and with the disclosed compositions and methods for the detection of calcifying nano-particles and proteins on calcifying nano- particles. Some such compositions and methods are described herein and others are known to those of skill in the art.

It has been discovered that particular proteins and other components are found on calcifying nano-particles and that detection of such proteins and components can serve to detect, classify, analyze, categorize, and assess calcifying nano-particles. For example, the detection of two or more particular proteins in association (in the same location or on the same particle, for example) is indicative and/or characteristic of calcifying nano-particles. As another example, the detection of a particular protein on a calcifying nano-particle is indicative and/or characteristic of calcifying nano-particles. The presence of the protein on the calcifying nano-particle and/or the identity of combinations of particular proteins serve as identifying characteristics of calcifying nano-particles.

Detection of two or more proteins associated with calcifying nanoparticles enables the generation of a patterns that are useful for diagnosing, assessing, and/or monitoring diseases. The origin and activity of said detected proteins is usefull in the determination of a potential or active disease state in the host.

Calcifying nano-particles are implicated in and represent a risk factor for disease. For example, as described in the Example, calcifying nano-particles can stimulate a novel blood coagulation mechanism. This mechanism can explain why thrombosis occurs in diseases associated with calcification and calcifying nano-particles. Because of this discovery, detection, classification, analysis, categorization, and assessment of calcifying nano-particles as described herein is useful for diagnosing, assessing, and/or monitoring diseases associated with calcification and calcifying nano-particles, the progress of such diseases, and the progress of treatment of such diseases. It is to be understood that the disclosed method and compositions are not limited to specific synthetic methods, specific analytical techniques, or to particular reagents unless otherwise specified, and, as such, may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

Materials

Disclosed are materials, compositions, and components that can be used for, can be used in conjunction with, can be used in preparation for, or are products of the disclosed method and compositions. These and other materials are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these materials are disclosed that while specific reference of each various individual and collective combinations and permutation of these compounds may not be explicitly disclosed, each is specifically contemplated and described herein. For example, if a protein is disclosed and discussed and a number of modifications that can be made to a number of molecules including the protein are discussed, each and every combination and permutation of the protein and the modifications that are possible are specifically contemplated unless specifically indicated to the contrary. Thus, if a class of molecules A, B, and C are disclosed as well as a class of molecules D, E, and F and an example of a combination molecule, A-D is disclosed, then even if each is not individually recited, each is individually and collectively contemplated. Thus, in this example, each of the combinations A-E, A-F, B-D, B-E, B-F, C-D, C-E, and C-F are specifically contemplated and should be considered disclosed from disclosure of A, B, and C; D, E, and F; and the example combination A-D. Likewise, any subset or combination of these is also specifically contemplated and disclosed. Thus, for example, the sub-group of A-E, B-F, and C-E are specifically contemplated and should be considered disclosed from disclosure of A, B, and C; D, E, and F; and the example combination A-D. This concept applies to all aspects of this application including, but not limited to, steps in methods of making and using the disclosed compositions. Thus, if there are a variety of additional steps that can be performed it is understood that each of these additional steps can be performed with any specific embodiment or combination of embodiments of the disclosed methods, and that each such combination is specifically contemplated and should be considered disclosed. Disclosed is an isolated calcifying nano-particle, where the calcifying nano-particle comprises one or more of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kapρa B, Osteopontin, Factor XIXa, CDU, Prothrombin, Factor JX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin- 1₅ B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin,

Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. In addition, binding proteins to the aforementioned protein list can bind to the associated proteins. Proteins may or may not undergo a primary and/or secondary conformational change.

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that collects said calcium binding proteins. Also disclosed is a compositon comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that has calcium binding proteins associated thereon and proteins that bind to said calcium binding proteins.

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that has calcium binding proteins associated thereon wherein said calcium binding proteins undergo a primary conformation change as a result of said association Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating containing bound calcium binding binding proteins that may experience conformational changes and wherein secondary bound proteins thereon experience conformational changes.

Also disclosed is a composition comprising a calcifying nano-particle and one or more compounds bound to one or more proteins on the calcifying nano-particle.

Also disclosed are compositions comprising apatite and a coating material, where, for example, the coating material limits exposure of the blood of a subject when the composition is in a subj ect.

The composition can comprise a calcifying nano-particle and one or more compounds bound to two or more proteins on the calcifying nano-particle. The compound can comprise an antibody, where the antibody is specific for the protein. The compound can block the calcifying nano-particle. A. Compounds

The disclosed method can make use of compounds that can bind to calcifying nano-particles, such as compounds that can bind proteins on calcifying nano-particles. Detection compounds and capture compounds are examples of such compounds. Compounds for use in the disclosed methods can be any compound, molecule, material or substance that can bind to a calcifying nano-particle and/or a protein on a calcifying nano- particle. It is preferred that the compound bind specifically to the calcifying nano-particle or protein. Such specificity allows detection and identification of calcifying nano-particles and proteins. Useful compounds include antibodies and molecules that can bind to proteins on calcifying nano-particles such as ligands, substrates, proteins, cofactors, coenzymes.

Useful compounds include compounds, such as antibodies, that can bind to proteins with a Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor XJXa, CD 14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF. The disclosed compounds can be used for detection and capture of calcifying nano-particles and/or proteins on calcifying nano-particles. Although not limited to such uses, detecting compounds can be used for detection and capture compounds can be used for capture of calcifying nano-particles and/or proteins on calcifying nano-particles. Detection and identification of calcifying nano-particles and proteins on calcifying nano-particles can be facilitated by including labels on the disclosed compounds. Useful labels and their use are described elsewhere herein. Detection of compounds bound to calcifying nano-particles and/or proteins on calcifying nano-particles indicates the presence of the bound calcifying nano-particles and/or proteins on calcifying nano-particles. The disclosed compounds can be detected, for example, via labels on the compounds, by direct detection of the compounds (via an intrinsic feature of the compounds, for example), or by binding a secondary compound to the primary compound and detecting the secondary compound. For this purpose, the secondary compound can include a label. B. Labels

To aid in detection, identification, and/or quantitation of calcifying nano-particles and proteins on calcifying nano-particles, labels can be used. For example, labels can be incorporated into, coupled to, or associated with, compounds, detection compound, capture compound (such as compounds to be bound to proteins). A label can include, for example, a fluorescent dye, a member of binding pair, such as biotin/streptavidin, a metal (e.g., gold), or an epitope tag that can specifically interact with a molecule that can be detected, such as by producing a colored substrate or fluorescence. Many other types of labels and signals, and many other principals of signal detection and known and can also be used, some of which are described herein. For example, labels (and other compounds and components) can be detected using nuclear magnetic resonance, electron paramagnetic resonance, surface enhanced raman scattering, surface plasmon resonance, fluorescence, phosphorescence, chemiluminescence, resonance raman, microwave, photometry, mass spectrometry, or a combination.

Substances suitable for detectably labeling proteins include, for example, fluorescent dyes (also known herein as fluorochromes and fluorophores), chromophores, and enzymes that react with colorometric substrates (e.g., horseradish peroxidase). The use of fluorescent dyes is useful as they can be detected at very low amounts. Furthermore, in the case where multiple proteins are to be detected in a single assay, array, and/or system, each protein can be associated with a distinct label compound for simultaneous and/or multiplex detection. Labels can be detected using a detection device or apparatus suitable for the label to be detected, such as a fluorimeter, spectrophotomer, or mass spectrometer, the presence of a signal indicating the presence of the corresponding protein.

Fluorophores are compounds or molecules that luminesce. Typically fluorophores absorb electromagnetic energy at one wavelength and emit electromagnetic energy at a second wavelength. Representative fluorophores include, but are not limited to, 1,5 IAEDANS; 1,8-ANS; 4- Methylumbelliferone; 5-carboxy-2,7-dichlorofluorescein; 5- Carboxyfluorescein (5-FAM); 5-Carboxynapthofluorescein; 5- Carboxytetramethylrhodamine (5-TAMRA); 5 -Hydroxy Tryptamine (5-HAT); 5-ROX (carboxy-X-rhodamine); 6-Carboxyrhodamine 6G; 6-CR 6G; 6- JOE; 7-Amino-4- methylcoumarin; 7-Aminoactmomycm D (7 -AAD); 7-Hydroxy-4- 1 methylcoumariii; 9- Amino-6-chloro-2-methoxyacridine (ACMA); ABQ; Acid Fuchsin; Acridine Orange; Acridine Red; Acridine Yellow; Acriflavin; Acriflavin Feulgen SITSA; Aequorin (Photoprotein); AFPs - AutoFluorescent Protein - (Quantum Biotechnologies) see sgGFP, sgBFP; Alexa Fluor 350™; Alexa Fluor 430™; Alexa Fluor 488™; Alexa Fluor 532™; Alexa Fluor 546™; Alexa Fluor 568™; Alexa Fluor 594™; Alexa Fluor 633™; Alexa Fluor 647™; Alexa Fluor 660™; Alexa Fluor 680™; Alizarin Complexon; Alizarin Red; Allophycocyanin (APC); AMC, AMCA-S; Ammomethylcoumarin (AMCA); AMCA-X; Aminoactinomycin D; Ammocoumarin; Anilin Blue; Anthrocyl stearate; APC-Cy7; APTRA-BTC; APTS; Astrazon Brilliant Red 4G; Astrazon Orange R; Astrazon Red 6B; Astrazon Yellow 7 GLL; Atabrine; ATTO- TAG™ CBQCA; ATTO-TAG™ FQ; Auramine; Aurophosphine G; Aurophosphine; BAO 9 (Bisaminophenyloxadiazole); BCECF (high pH); BCECF (low pH); Berberine Sulphate; Beta Lactamase; BFP blue shifted GFP (Y66H); Blue Fluorescent Protein; BFP/GFP FRET; Bimane; Bisbenzemide; Bisbenzimide (Hoechst); bis- BTC; Blancophor FFG; Blancophor SV; BOBO™ -1; BOBO™-3; Bodipy492/515; Bodipy493/503; Bodipy500/510; Bodipy; 505/515; Bodipy 530/550; Bodipy 542/563; Bodipy 558/568; Bodipy 564/570; Bodipy 576/589; Bodipy 581/591 ; Bodipy 630/650-X; Bodipy 650/665-X; Bodipy 665/676; Bodipy Fl; Bodipy FL ATP; Bodipy Fl-Ceramide; Bodipy R6G SE; Bodipy TMR; Bodipy TMR-X conjugate; Bodipy TMR-X₅ SE; Bodipy TR; Bodipy TR ATP; Bodipy TR-X SE; BO-PRO™ -1; BO- PRO™ -3; Brilliant Sulphoflavin FF; BTC; BTC-5N; Calcein; Calcein Blue; Calcium Crimson - ; Calcium Green; Calcium Green- 1 Ca²⁺ Dye; Calcium Green-2 Ca²⁺; Calcium Green-5N Ca²⁺; Calcium Green-C18 Ca²⁺; Calcium Orange; Calcofluor White; Carboxy- X-rhodamine (5-ROX); Cascade Blue™; Cascade Yellow; Catecholamine; CCF2 (GeneBlazer); CFDA; CFP (Cyan Fluorescent Protein); CFP/YFP FRET; Chlorophyll; Chromomycin A; Chromomycin A; CL-NERF; CMFDA; Coelenterazine; Coelenterazine cp; Coelenterazine f; Coelenterazine fcp; Coelenterazine h; Coelenterazine hep; Coelenterazine ip; Coelenterazine n; Coelenterazine O; Coumarin Phalloidin; C- phycocyanine; CPM I Methylcoumarin; CTC; CTC Formazan; Cy2™; Cy3.1 8; Cy3.5™; Cy3™; Cy5.1 8; Cy5.5™; Cy5™; Cy7™; Cyan GFP; cyclic AMP Fluorosensor (FiCRhR); Dabcyl; Dansyl; Dansyl Amine; Dansyl Cadaverine; Dansyl Chloride; Dansyl DHPE; Dansyl fluoride; DAPI; Dapoxyl; Dapoxyl 2; Dapoxyl 3¹DCFDA; DCFH (Dichlorodihydrofluorescein Diacetate); DDAO; DHR (Dihydorhodamine 123); Di-4- ANEPPS; Di-8-ANEPPS (non-ratio); DiA (4-Di 16-ASP); Dichlorodihydrofluorescein Diacetate (DCFH); DiD- Lipophilic Tracer; DiD (DilC18(5)); DE)S; Dihydorhodamine 123 (DHR); DiI (DiICl 8(3)); I Dinitrophenol; DiO (DiOC18(3)); DiR; DiR (DilC18(7)); DM-NERF (highpH); DNP; Dopamine; DsRed; DTAF; DY-630-NHS; DY-635-NHS; EBFP; ECFP; EGFP; ELF 97; Eosin; Erytihrosin; Erythrosin ITC; Ethidium Bromide;

Ethidium homodimer-1 (EthD-1); Euchrysin; EukoLight; Europium (111) chloride; EYFP; Fast Blue; FDA; Feulgen (Pararosaniline); FIF (Formaldehyd Induced Fluorescence); FITC; Flazo Orange; Fluo-3; Fluo-4; Fluorescein (FITC); Fluorescein Diacetate; Fluoro- Emerald; Fluoro-Gold (Hydroxystilbamidine); Fluor-Ruby; FluorX; FM 1-43™; FM 4-46; Fura Red™ (high pH); Fura Red™/Fluo-3 ; Fura-2; Fura-2/BCECF; Genacryl Brilliant Red B; Genacryl Brilliant Yellow 10GF; Genacryl Pink 3G; Genacryl Yellow 5GF; GeneBlazer; (CCF2); GFP (S65T); GFP red shifted (rsGFP); GFP wild type' non-UV excitation (wtGFP); GFP wild type, UV excitation (wtGFP); GFPuv; Gloxalic Acid; Granular blue; Haematopoφhyrin; Hoechst 33258; Hoechst 33342; Hoechst 34580; HPTS; Hydroxycoumarin; Hydroxystilbamidine (FluoroGold); Hydroxytryptamine; Indo- 1, high calcium; Indo-1 low calcium; hidodicarbocyanine (DiD); Indotricarbocyanine (DiR); Intrawhite Cf; JC-I; JO JO-I; JO-PRO-I; LaserPro; Laurodan; LDS 751 (DNA); LDS 751 (RNA); Leucophor PAF; Leucophor SF; Leucophor WS; Lissamine Rhodamine; Lissamine Rhodamine B; Calcein/Ethidium homodimer; LOLO-I; LO-PRO-I; ; Lucifer Yellow; Lyso Tracker Blue; Lyso Tracker Blue- White; Lyso Tracker Green; Lyso Tracker Red; Lyso Tracker Yellow; LysoSensor Blue; LysoSensor Green; LysoSensor Yellow/Blue; Mag Green; Magdala Red (Phloxin B); Mag-Fura Red; Mag-Fura-2; Mag- Fura-5; Mag-lndo-1 ; Magnesium Green; Magnesium Orange; Malachite Green; Marina Blue; I Maxilon Brilliant Flavin 10 GFF; Maxilon Brilliant Flavin 8 GFF; Merocyanin; Methoxycoumarin; Mitotracker Green FM; Mitotracker Orange; Mitotracker Red; Mitramycin; Monobromobimane; Monobromobimane (niBBr-GSH); Monochlorobimane; MPS (Methyl Green Pyronine Stilbene); NBD; NBD Amine; Nile Red; Nitrobenzoxedidole; Noradrenaline; Nuclear Fast Red; i Nuclear Yellow; Nylosan

Brilliant lavin E8G; Oregon Green™; Oregon Green™ 488; Oregon Green™ 500; Oregon Green™ 514; Pacific Blue; Pararosaniline (Feulgen); PBFI; PE-Cy5; PE-Cy7; PerCP; PerCP-Cy5.5; PE-TexasRed (Red 613); Phloxin B (Magdala Red); Phorwite AR; Phorwite BKL; Phorwite Rev; Phorwite RPA; Phosphine 3R; PhotoResist; Phycoerythrin B [PE]; Phycoerythrin R [PE] ; PKH26 (Sigma); PKH67; PMIA; Pontochrome Blue Black; POPO- 1; POPO-3; PO-PRO-I; PO- 1 PRO-3; Primuline; Procion Yellow; Propidium lodid (Pl); PyMPO; Pyrene; Pyronine; Pyronine B; Pyrozal Brilliant Flavin 7GF; QSY 7; Quinacrine Mustard; Resorufin; RH 414; Rhod-2; Rhodamine; Rhodamine 110; Rhodamine 123; Rhodamine 5 GLD; Rhodamine 6G; Rhodamine B; Rhodamine B 200; Rhodamine B extra; Rhodamine BB; Rhodamine BG; Rhodamine Green; Rhodamine Phallicidine; Rhodamine: Phalloidine; Rhodamine Red; Rhodamine WT; Rose Bengal; R- phycocyanine; R-phycoerythrin (PE); rsGFP; S65A; S65C; S65L; S65T; Sapphire GFP; SBFI; Serotonin; Sevron Brilliant Red 2B; Sevron Brilliant Red 4G; Sevron I Brilliant Red B; Sevron Orange; Sevron Yellow L; sgBFP™ (super glow BFP); sgGFP™ (super glow GFP); SITS (Primuline; Stilbene Isothiosulphonic Acid); SNAFL calcein; SNAFL-I ; SNAFL-2; SNARF calcein; SNARFl; Sodium Green; SpectrumAqua; SpectrumGreen; SpectrumOrange; Spectrum Red; SPQ (6-methoxy- N-(3 sulfopropyl) quinolinium); Stilbene; Sulphorhodamine B and C; Sulphorhodamine Extra; SYTO 11; SYTO 12; SYTO 13; SYTO 14; SYTO 15; SYTO 16; SYTO 17; SYTO 18; SYTO 20; SYTO 21; SYTO 22; SYTO 23; SYTO 24; SYTO 25; SYTO 40; SYTO 41; SYTO 42; SYTO 43; SYTO 44; SYTO 45; SYTO 59; SYTO 60; SYTO 61; SYTO 62; SYTO 63; SYTO 64; SYTO 80; SYTO 81; SYTO 82; SYTO 83; SYTO 84; SYTO 85; SYTOX Blue; SYTOX Green; SYTOX Orange; Tetracycline; Tetramethylrhodamine (TRITC); Texas Red™; Texas Red- X™ conjugate; Thiadicarbocyanine (DiSC3); Thiazine Red R; Thiazole Orange; Thioflavin 5; Thioflavin S; Thioflavin TON; Thiolyte; Thiozole Orange; Tinopol CBS (Calcofhior White); TIER; TO-PRO-I; TO-PRO-3; TO-PRO-5; TOTO-I; TOTO-3; Tricolor (PE-Cy5); TRITC TetramethylRodaminelsoThioCyanate; True Blue; Tru Red; Ultralite; Uranine B; Uvitex SFC; wt GFP; WW 781 ; X-Rhodamine; XRITC; Xylene Orange; Y66F; Y66H; Y66W; Yellow GFP; YFP; YO-PRO-I; YO- PRO 3; YOYO- l;Y0Y0-3; Sybr Green; Thiazole orange (interchelating dyes); semiconductor nanoparticles such as quantum dots; or caged fluorophore (which can be activated with light or other electromagnetic energy source), or a combination thereof. Other labels include molecular or metal barcodes, mass labels, and labels detectable by nuclear magnetic resonance, electron paramagnetic resonance, surface enhanced raman scattering, surface plasmon resonance, fluorescence, phosphorescence, chemiluminescence, resonance raman, microwave, photometry, mass spectrometry, or a combination. Mass labels are compounds or moieties that have, or which give the labeled component, a distinctive mass signature in mass spectroscopy. Mass labels are useful when mass spectroscopy is used for detection. Preferred mass labels are peptide nucleic acids and carbohydrates. Combinations of labels can also be useful. For example, color- encoded microbeads having, for example, 256 unique combinations of labels, are useful for distinguishing numerous components. For example, 256 different ligator-detectors can be uniquely labeled and detected allowing multiplexing and automation of the disclosed method.

Examples of useful labels are described in de Haas et al., "Platinum porphyrins as phosphorescent label for time-resolved microscopy," J. Histochem. Cytochem. 45(9):1279-92 (1997); Karger and Gesteland, "Digital chemiluminescence imaging of DNA sequencing blots using a charge-coupled device camera," Nucleic Acids Res.

20(24):6657-65 (1992); Keyes et al., "Overall and internal dynamics of DNA as monitored by five-atom-tethered spin labels," Biophys. J. 72(l):282-90 (1997); Kirschstein et al., "Detection of the DeltaF5O8 mutation in the CFTR gene by means of time- resolved fluorescence methods," Bioelectrochem. Bioenerg. 48(2):415-21 (1999); Kricka, "Selected strategies for improving sensitivity and reliability of immunoassays," Clin. Chem. 40(3):347-57 (1994); Kricka, "Chemiluminescent and bioluminescent techniques," CHn. Chem. 37(9):1472-81 (1991); Kumke et al., "Temperature and quenching studies of fluorescence polarization detection of DNA hybridization," Anal. Chem. 69(3):500-6

(1997); McCreery, "Digoxigenin labeling," MoI. Biotechnol. 7(2):121-4 (1997); Mansfield et al., "Nucleic acid detection using non-radioactive labeling methods," MoI. Cell Probes 9(3): 145-56 (1995); Nurmi et al., "A new label technology for the detection of specific polymerase chain reaction products in a closed tube," Nucleic Acids Res. 28(8):28 (2000); Oetting et al. "Multiplexed short tandem repeat polymorphisms of the Weber 8 A set of markers using tailed primers and infrared fluorescence detection," Electrophoresis 19(18):3079-83(1998); Roda et al., "Chemiluminescent imaging of enzyme-labeled probes using an optical microscope-videocamera luminograph," Anal. Biochem. 257(l):53-62 (1998); Siddiqi et al., "Evaluation of electrochemiluminescence- and bioluminescence- based assays for quantitating specific DNA," J. Clin. Lab. Anal. 10(6):423-31 (1996); Stevenson et al., "Synchronous luminescence: a new detection technique for multiple fluorescent probes used for DNA sequencing," Biotechniques 16(6): 1104-11 (1994); Vo- Dinh et al., "Surface-enhanced Raman gene probes," Anal. Chem. 66(20):3379-83 (1994); Volkers et al., "Microwave label detection technique for DNA in situ hybridization," Eur. J Morphol. 29(l):59-62 (1991).

Metal barcodes, a form of molecular barcode, can be, for example, 30-300 nm diameter by 400-4000 nm multilayer multi metal rods. These rods can be constructed by electrodeposition into an alumina mold, then the alumina is removed leaving these small multilayer objects behind. The system can have multiple zones encoded using multiple different metals where the metals have different reflectivity and thus appear lighter or darker in an optical microscope depending on the metal. For example, up to 12 zones can be encoded in up to 7 different metals. This allows practically unlimited identification codes. The metal bars can be coated with glass or other material, which can facilitate attachment of the bars to compounds to be labeled. The bars can be identified from the light dark pattern of the barcode.

Epitopes can be used as labels. Epitopes (that is, a portion of a molecule to which an antibody binds) can be composed of sugars, lipids or amino acids. Epitope tags are useful for the labeling and detection of proteins when an antibody to the protein is not available. Due to their small size, they are unlikely to affect the tagged protein's biochemical properties. Epitope tags generally range from 10 to 15 amino acids long and are designed to create a molecular handle for the protein. An epitope tag can be placed anywhere within the protein, but typically they are placed on either the amino or carboxyl terminus to minimize any potential disruption in tertiary structure and thus function of the protein. Any short stretch of amino acids known to bind an antibody could become an epitope tag. Useful epitope tags include c-myc (a 10 amino acid segment of the human protooncogene myc), haemoglutinin (HA) protein, Hisβ, Green flourescent protein (GFP), digoxigenin (DIG), and biotin. Flourescent dyes, such as those described herein, can also be used as epitope tags. C. Samples

Calcifying nano-particles and proteins on calcifying nano-particles can be any from any source, such as an animal. In general, the disclosed method is performed using a sample that contains (or is suspected of containing) calcifying nano-particles. A sample can be any sample of interest. The source, identity, and preparation of many such samples are known. The sample can be, for example, a sample from one or more cells, tissue, or bodily fluids such as blood, urine, semen, lymphatic fluid, cerebrospinal fluid, or amniotic fluid, or other biological samples, such as tissue culture cells, buccal swabs, mouthwash, stool, tissues slices, and biopsy aspiration. Types of useful samples include blood samples, urine samples, semen samples, lymphatic fluid samples, cerebrospinal fluid samples, amniotic fluid samples, biopsy samples, needle aspiration biopsy samples, cancer samples, tumor samples, tissue samples, cell samples, cell lysate samples, and/or crude cell lysate samples.

The sample can be from any organism of interest that contains or is suspected of containing calcifying nano-particles. For example, the sample can be animal, non-human animals, vertebrate, non-human vertebrate, invertebrate, insect, amphibian, avian, reptilian, fish, mammalian, non-human mammalian, rodent, farm animal, domesticated animal, bovine, porcine, murine, feline, canine, or human. The term subject can refer to any animal or any member of any subgroup or classification of animal, including those listed above and elsewhere herein. The term patient can refer to any animal under care or treatment, such as a veterinary patient or human patient. D. Solid Supports

Solid supports are solid-state substrates or supports with which molecules, such as analytes and analyte binding molecules, can be associated. Analytes, such as calcifying nano-particles and proteins, can be associated with solid supports directly or indirectly. For example, analytes can be directly immobilized on solid supports. Analyte capture agents, such a capture compounds, can also be immobilized on solid supports. A preferred form of solid support is an array. Another form of solid support is an array detector. An array detector is a solid support to which multiple different capture compounds or detection compounds have been coupled in an array, grid, or other organized pattern. Solid-state substrates for use in solid supports can include any solid material to which molecules can be coupled. This includes materials such as acrylamide, agarose, cellulose, nitrocellulose, glass, polystyrene, polyethylene vinyl acetate, polypropylene, polymethacrylate, polyethylene, polyethylene oxide, polysilicates, polycarbonates, teflon, fluorocarbons, nylon, silicon rubber, polyanhydrides, polyglycolic acid, polylactic acid, polyorthoesters, polypropylfumerate, collagen, glycosaminoglycans, and polyamino acids. Solid-state substrates can have any useful form including thin film, membrane, bottles, dishes, fibers, woven fibers, shaped polymers, particles, beads, microparticles, or a combination. Solid-state substrates and solid supports can be porous or non-porous. A preferred form for a solid-state substrate is a microtiter dish, such as a standard 96-well type. In preferred embodiments, a multiwell glass slide can be employed that normally contain one array per well. This feature allows for greater control of assay reproducibility, increased throughput and sample handling, and ease of automation.

Different compounds can be used together as a set. The set can be used as a mixture of all or subsets of the compounds used separately in separate reactions, or immobilized in an array. Compounds used separately or as mixtures can be physically separable through, for example, association with or immobilization on a solid support. An array can include a plurality of compounds immobilized at identified or predefined locations on the array. Each predefined location on the array generally can have one type of component (that is, all the components at that location are the same). Each location will have multiple copies of the component. The spatial separation of different components in the array allows separate detection and identification of calcifying nano-particles and proteins. Although preferred, it is not required that a given array be a single unit or structure. The set of compounds may be distributed over any number of solid supports. For example, at one extreme, each compound may be immobilized in a separate reaction tube or container, or on separate beads or microparticles. Different modes of the disclosed method can be performed with different components (for example, different compounds specific for different proteins) immobilized on a solid support.

Some solid supports can have capture compounds, such as antibodies, attached to a solid-state substrate. Such capture compounds can be specific for calcifying nano- particles or a protein on calcifying nano-particles. Captured calcifying nano-particles or proteins can then be detected by binding of a second, detection compound, such as an antibody. The detection compound can be specific for the same or a different protein on the calcifying nano-particle.

Methods for immobilizing antibodies (and other proteins) to solid-state substrates are well established. Immobilization can be accomplished by attachment, for example, to aminated surfaces, carboxylated surfaces or hydroxylated surfaces using standard immobilization chemistries. Examples of attachment agents are cyanogen bromide, succinimide, aldehydes, tosyl chloride, avidin-biotin, photocrosslinkable agents, epoxides and maleimides. A preferred attachment agent is the heterobifimctional cross-linker N-[γ- Maleimidobutyryloxy] succinimide ester (GMBS). These and other attachment agents, as well as methods for their use in attachment, are described in Protein immobilization: fundamentals and applications, Richard F. Taylor, ed. (M. Dekker, New York, 1991), Johnstone and Thorpe, Immunochemistry In Practice (Blackwell Scientific Publications, Oxford, England, 1987) pages 209-216 and 241-242, and Immobilized Affinity Ligands, Craig T. Hermanson et al., eds. (Academic Press, New York, 1992). Antibodies can be attached to a substrate by chemically cross-linking a free amino group on the antibody to reactive side groups present within the solid-state substrate. For example, antibodies may be chemically cross-linked to a substrate that contains free amino, carboxyl, or sulfur groups using glutaraldehyde, carbodiimides, or GMBS, respectively, as cross-linker agents. In this method, aqueous solutions containing free antibodies are incubated with the solid-state substrate in the presence of glutaraldehyde or carbodiimide.

A preferred method for attaching antibodies or other proteins to a solid-state substrate is to functionalize the substrate with an amino- or thiol-silane, and then to activate the functionalized substrate with a homobifunctional cross-linker agent such as (Bis-sulfo-succinimidyl suberate (BS³) or a heterobifunctional cross-linker agent such as GMBS. For cross-linking with GMBS, glass substrates are chemically fimctionalized by immersing in a solution of mercaptopropyltrimethoxysilane (1% vol/vol in 95% ethanol pH 5.5) for 1 hour, rinsing in 95% ethanol and heating at 120 ⁰C for 4 hrs. Thiol- derivatized slides are activated by immersing in a 0.5 mg/ml solution of GMBS in 1% dimethylformamide, 99% ethanol for 1 hour at room temperature. Antibodies or proteins are added directly to the activated substrate, which are then blocked with solutions containing agents such as 2% bovine serum albumin, and air-dried. Other standard immobilization chemistries are known by those of skill in the art. Each of the components (compounds, for example) immobilized on the solid support preferably is located in a different predefined region of the solid support. Each of the different predefined regions can be physically separated from each other of the different regions. The distance between the different predefined regions of the solid support can be either fixed or variable. For example, in an array, each of the components can be arranged at fixed distances from each other, while components associated with beads will not be in a fixed spatial relationship. In particular, the use of multiple solid support units (for example, multiple beads) will result in variable distances.

Components can be associated or immobilized on a solid support at any density. Components preferably are immobilized to the solid support at a density exceeding 400 different components per cubic centimeter. Arrays of components can have any number of components. For example, an array can have at least 1,000 different components immobilized on the solid support, at least 10,000 different components immobilized on the solid support, at least 100,000 different components immobilized on the solid support, or at least 1,000,000 different components immobilized on the solid support. E. Kits

The materials described above as well as other materials can be packaged together in any suitable combination as a kit useful for performing, or aiding in the performance of, the disclosed method. It is useful if the kit components in a given kit are designed and adapted for use together in the disclosed method. For example disclosed are kits for detecting calcifying nano-particles, the kit comprising one or more detection compounds, one or more capture compounds, and one or more solid supports. The kits also can contain one or more buffers. F. Mixtures

Disclosed are mixtures formed by performing or preparing to perform the disclosed method. For example, disclosed are mixtures comprising a calcifying nano-particle, a detection compound, and a capture compound. Whenever the method involves mixing or bringing into contact compositions or components or reagents, performing the method creates a number of different mixtures. For example, if the method includes 3 mixing steps, after each one of these steps a unique mixture is formed if the steps are performed separately. In addition, a mixture is formed at the completion of all of the steps regardless of how the steps were performed. The present disclosure contemplates these mixtures, obtained by the performance of the disclosed methods as well as mixtures containing any disclosed reagent, composition, or component, for example, disclosed herein.

G. Systems

Disclosed are systems useful for performing, or aiding in the performance of, the disclosed method. Systems generally comprise combinations of articles of manufacture such as structures, machines, devices, and the like, and compositions, compounds, materials, and the like. Such combinations that are disclosed or that are apparent from the disclosure are contemplated. For example, disclosed and contemplated are systems comprising a calcifying nano-particle, a detection compound, and a solid support. . H. Data Structures and Computer Control

Disclosed are data structures used in, generated by, or generated from, the disclosed method. Data structures generally are any form of data, information, and/or objects collected, organized, stored, and/or embodied in a composition or medium. A pattern of proteins present on a calcifying nano-particle stored in electronic form, such as in RAM or on a storage disk, is a type of data structure.

The disclosed method, or any part thereof or preparation therefor, can be controlled, managed, or otherwise assisted by computer control. Such computer control can be accomplished by a computer controlled process or method, can use and/or generate data structures, and can use a computer program. These include such techniques as neural network that may quickly analyze and interpret data for clinical diagnosis and interpreations to indicated a disease state. Such computer control, computer controlled processes, data structures, and computer programs are contemplated and should be understood to be disclosed herein. Uses

The disclosed methods and compositions are applicable to numerous areas including, but not limited to, detecting, analyzing and assessing the significance of calcifying nano-particles. Other uses include, for example, detecting one or more proteins on a calcifying nano-particle, characterizing a calcifying nano-particle, diagnosing a disease or condition, assessing the prognosis of a disease or condition, identifying a subject at risk of a disease or condition, determining the progress of treatment of a subject having calcifying nano-particles, testing biocompatibility comprising testing blood coagulation in the absence of anticoagulants, and testing materials that will be exposed to circulating blood for formation of calcific biofilm formation. Other uses are disclosed, apparent from the disclosure, and/or will be understood by those in the art.

Method

Disclosed are methods for detecting, analyzing and assessing the significance of calcifying nano-particles. The disclosed methods generally involve detecting one or more proteins present on a calcifying nano-particle. It has been discovered that particular proteins become associated with calcifying nano-particles. This association provides a means for detecting, classifying, analyzing, categorizing, and assessing calcifying nano- particles. Detecting particular proteins while associated with a calcifying nano-particle can be used to indicate the presence and type of calcifying nano-particle, which can be used to indicate the presence of, or disposition to, diseases or conditions. Multiple proteins on a calcifying particle can be detected. The presence or absence of particular proteins and the pattern of the presence and absence of particular proteins can be used to indicate the presence and type of calcifying nano-particle.

The disclosed method can involve detecting calcifying particles by detecting one or more proteins on the calcifying particle. The method generally can involve detecting at least one protein on the calcifying particle by binding at least one compound to the protein and detecting the bound compound. Binding a compound to the protein can involve, for example, an antibody. The antibody can be the compound and also can be the means of specific binding of the compound to the protein. As another example, a compound can be associated with an antibody with the antibody mediating binding of the compound to the protein. Detecting the bound compound can be accomplished by, for example, detecting the compound directly or indirectly. For example, the compound can be detected using, for example, a microarray, coded beads, coated beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination.

Detection and identification of calcifying nano-particles and proteins on calcifying nano-particles can be facilitated by including labels on the disclosed compounds. Useful labels and their use are described elsewhere herein. Detection of compounds bound to calcifying nano-particles and/or proteins on calcifying nano-particles indicates the presence of the bound calcifying nano-particles and/or proteins on calcifying nano- particles. The disclosed compounds can be detected, for example, via labels on the compounds, by direct detection of the compounds (via an intrinsic feature of the compounds, for example), or by binding a secondary compound to the primary compound and detecting the secondary compound. For this purpose, the secondary compound can include a label.

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that collects said calcium binding proteins.

Also disclosed is a compositon comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that has calcium binding proteins associated thereon and proteins that bind to said calcium binding proteins.

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that has calcium binding proteins associated thereon wherein said calcium binding proteins undergo a primary conformation change as a result of said association

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating containing bound calcium binding binding proteins that may experience conformational changes and s secondary bound proteins thereon that experience conformational changes.

Also disclosed is a method for detecting one or more proteins, where the method comprises detecting one or more proteins on a calcifying nano-particle. Also disclosed is a method of characterizing a calcifying nano-particle, where the method comprises identifying one or more proteins on a calcifying nano-particle.

Also disclosed is a method of diagnosing a disease or condition, where the method comprises identifying one or more proteins on a calcifying nano-particle from a subject. The identified proteins identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated.

Also disclosed is a method of identifying a subject at risk of a disease or condition, where the method comprises identifying one or more proteins on a calcifying nano-particle from a subject. The identified proteins identify calcifying nano-particles that are related to or associated with a risk of developing a disease or condition. Also disclosed is a method of determining the progress of treatment of a subj ect having calcifying nano-particles, where the method comprises detecting one or more proteins on calcifying nano-particles in a sample from the subject, and repeating the detection in another sample from the subject following treatment. A change in the level, amount, concentration, or a combination of calcifying nano-particles in the subject indicates the progress of the treatment of the subj ect.

Also disclosed is a method of testing biocompatibility comprising testing blood coagulation in the absence of anticoagulants.

Also disclosed is a method of testing materials that will be exposed to circulating blood for formation of calcific biofilm formation. Calcifying nano-particles can be detected by detecting one or more of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kapρa B, Osteopontin, Factor X/Xa, CD 14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin- 1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl , Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. Additionally, proteins that bind to the aforementioned protein list may also become associated with the calcifying nanoparticles. Said proteins may or may not undergo conformational changes.

Calcifying nano-particles can be detected by detecting two or more proteins on the calcifying nano-particles. Calcifying nano-particles can be detected by detecting one or more proteins with a GLA-containing domain. Calcifying nano-particles can be detected by detecting one or more proteins with a calcium binding domain. Calcifying nano- particles can be captured, identified, or both prior to, simultaneous with, or following detection of one or more of the proteins. Capture or identification of the calcifying nano- particle can indicate that the detected proteins are on the calcifying nano-particles. Calcifying nano-particles can be captured by binding at least one compound to one or more of the proteins, wherein the compound is or becomes immobilized. Calcifying nano- particles can be identified by binding at least one compound to one or more of the proteins, wherein the calcifying nano-particles are separated based on the compound. Calcifying nano-particles can be separated by fluorescence activated sorting.

One or more of the proteins can be detected by binding at least one compound to the protein and detecting the bound compound. Detection of two or more bound compounds can indicate that the proteins to which the compounds are bound are on the calcifying nano-particle. The two or more compounds can be detected in the same location or at the same time. The compounds can be an antibody, where the antibody is specific for the protein. The calcifying nano-particles can comprise calcium phosphate and one or more of the proteins.

The proteins can be detected by detecting any combination of 10 or fewer of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappaB, Osteopontin, Factor X/Xa, CD 14, Prothrombin, Factor FX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1 , BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein,

Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. Additionally, proteins that bind to the aforementioned protein list may also become associated with the calcifying nanoparticles. Said proteins may or may not undergo conformational changes. The proteins can be detected by detecting any combination of 7 or fewer of the proteins. The proteins can be detected by detecting any combination of 5 or fewer of the proteins. The proteins can be detected by detecting any combination of 3 or fewer of the proteins. The combination of proteins can be detected in the same assay. The combination of proteins can be detected simultaneously. The combination of proteins can be detected on the same calcifying nano-particle. The combination of proteins can be detected on or within the same device. The combination of proteins detected can constitute a pattern of proteins. The pattern can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The pattern can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern can identify the type of calcifying nano-particles detected. Disease associated with patholical clarification include, but are not limited to for example, heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Scleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve

Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Intercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia;

Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofϊlms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease.

The proteins can be detected by detecting the presence or absence of any combination of 10 or fewer of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CDU, Prothrombin, Factor FX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra- 1 , Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano- particle. Additionally, proteins that bind to calcium binding proteins may bind to said calcium binding protein/calcifying nano-particles complex including but not limited to Fetuin binding proteins, Thrombin binding proteins, Troponin binding proteins, Tropomyosin binding proteins, GLA Matric binding proteins, Fibrin binding proteins, Kallikrein binding proteins, Factor binding proteins, Matrix metalloprotinease binding proteins, Platelet glycol binding proteins, NF Kappa B binding protein, Factor X binding protein. Table 9 shows representative proteins. Said proteins may or may not undergo conformational changes.

The pattern of the presence or absence of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The pattern of the presence or absence of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern of the presence or absence of the proteins can identify the type of calcifying nano- particles detected. The presence of one or more of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The presence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The presence of one or more of the proteins can identify the type of calcifying nano-particles detected. The absence of one or more of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The absence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The absence of one or more of the proteins can identify the type of calcifying nano-particles detected.

Diseases associated with CNPs and pathological calcification include, but are not limimted to, for example, heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental

Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Schleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile

Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and

Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Intercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofilms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease.

The proteins can be detected using any suitable composition, apparatus, or technique, for example, a microarray, coded beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination.

Specifically, the disclosed method can use an immunassy detecting approximagtely 100 or fewer difrrerent antigens on the same particles using only one tracer antibody for all of said detected target antigens or epitopes. Thereby utilitizing only one standard curve to provide quantitation of the target antigens and/or epitopes (focused on the use of the antibody). The disclosed method is especially suitable for biogenic particles, such as CNPs, due to stable surface structure due to crosslinking of proteins and binding to the HA. However, the disclosed method is not limited to CNPs. The disclosed method can be utilitzed with viruses, spores, bacteria with stable capsules or similar stable substrate, microparticles in blood, plasma, and the like. Noteably, the particles may be captured using antibodies from any source or based on chemical regions from any source.

The proteins on the calcifying nano-particle can be detected by (a) capturing the calcifying nano-particle, (b) binding a detection compound to one or more of the proteins, and (c) detecting the detection compound. The proteins on the calcifying nano-particle can be detected by (a) binding a detection compound to one or more of the proteins, (b) capturing the calcifying nano-particle, and (c) detecting the detection compound. The calcifying nano-particle can be captured by binding a capture compound to one or more of the proteins, where the capture compound is or becomes immobilized. The proteins to which capture compounds bind can mediate capture, where the detection compound can be bound to one of the proteins, where the calcifying nano-particle can be characterized by determining which proteins mediate capture of the calcifying nano-particle to which the detected detection compound is bound. The capture compound can be bound to one of the proteins, where the detection compounds detected can indicate which of the proteins is present on the calcifying nano-particle, where the calcifying nano-particle can be characterized by which proteins are present on the calcifying nano-particle.

The identified proteins can identify the type of calcifying nano-particle. The identified type of calcifying nano-particle can be related to or associated with a disease or condition. The identified proteins can identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated. The identified proteins can identify a disease or condition that is caused by calcifying nano- particles having the identified proteins. The identified proteins can identify a disease or condition in which calcifying nano-particles having the identified proteins are produced. Subjects in which pathological thrombosis can occur via apatite-mediated clotting are useful targets for the disclosed methods. Such subjects can include (1) Patients with vulnerable plaque rupture exposing atheroma calcification; (2) Patients undergoing angioplasty or heart-lung machine perfusion; (3) Patients with massive bone fractures or dislocated implants releasing potentially apatite particles; (4) Patients with implants, catheters, wires or stents subject to calcium encrustation; (5) Cancer patients with soft tissue calcification; and (6) Healthy or sick people with CNPs in their blood or positive calcification scores in arteries. A. Protein Detection and Identification

Some forms of the disclosed methods involve detection and/or identification of calcifying nano-particles and/or proteins on calcifying nano-particles. Molecules of interest— including calcifying nano-particles, proteins, and/or proteins in or on a calcifying nano-particle— can be detected using any suitable technique. Molecules of interest to be detected can be in any sample, any composition or any other context. Detection and identification of calcifying nano-particles and proteins on calcifying nano-particles can be facilitated by including labels on the disclosed compounds. Useful labels and their use are described elsewhere herein. Detection of compounds bound to calcifying nano-particles and/or proteins on calcifying nano-particles indicates the presence of the bound calcifying nano-particles and/or proteins on calcifying nano-particles. The disclosed compounds can be detected, for example, via labels on the compounds, by direct detection of the compounds (via an intrinsic feature of the compounds, for example), or by binding a secondary compound to the primary compound and detecting the secondary compound. For this purpose, the secondary compound can include a label. Molecules that interact with or bind to the disclosed calcifying nano-particles and proteins, such as antibodies to a protein, can be detected using known techniques. Many suitable techniques—such as techniques generally known for the detection of proteins, peptides and other analytes and antigens— are known, some of which are described herein. These techniques can involve, for example, direct imaging (for example, microscopy), immunoassays, or functional determination. By "functional determination" is meant that a given protein such as a protein that has a function can be detected by the detection of the function. For example, an enzyme can be detected by evaluating its activity on its substrate. Labeling of proteins and calcifying nano-particles can be either direct or indirect.

In direct labeling, the detecting molecule (the compound that binds the protein of interest such as a detecting compound or capture compound) can include a label. Calcifying nano- particles and/or proteins can be contacted with the labeled molecules (such as detection compounds and capture compounds) under conditions effective and for a period of time sufficient to allow the formation of complexes. The complexes can then be generally washed to remove any non-specifically bound labeled molecules, and the remaining label in the complexes can then be detected. Detection of the label indicates the presence of the detecting molecule which in turn indicates the presence of the protein of interest or other analyte. In indirect labeling, an additional molecule or moiety is brought into contact with, or generated at the site of, the complex of the protein of interest and the detecting molecule. For example, a signal-generating molecule or moiety such as an enzyme can be attached to or associated with the detecting molecule. The signal-generating molecule can then generate a detectable signal at the site of the immunocomplex. For example, an enzyme, when supplied with suitable substrate, can produce a visible or detectable product at the site of the immunocomplex. ELISAs use this type of indirect labeling.

As another example of indirect labeling, an additional molecule (which can be referred to as a binding agent) that can bind to the protein of interest can be contacted with the protein complex. The additional molecule can have a label or signal-generating molecule or moiety. The additional molecule can be termed a secondary molecule or compound. If the secondary molecule is an antibody it can be termed a secondary antibody. The complexes can be contacted with the labeled molecules under conditions effective and for a period of time sufficient to allow the formation of secondary complexes. The secondary complexes can then be generally washed to remove any non- specifically bound labeled secondary molecules, and the remaining label in the secondary complexes can then be detected. The additional molecule can also be or include one of a pair of molecules or moieties that can bind to each other, such as the biotin/avidin pair. In this mode, the detecting molecule can include the other member of the pair. Other modes of indirect labeling include the detection of primary complexes by a two step approach. For example, a molecule (which can be referred to as a first binding agent), such as an antibody, that has binding affinity for the protein of interest can be used to form secondary complexes, as described above. After washing, the secondary complexes can be contacted with another molecule (which can be referred to as a second binding agent) that has binding affinity for the first binding agent, again under conditions effective and for a period of time sufficient to allow the formation of complexes (thus forming tertiary complexes). The second binding agent can be linked to a detectable label or signal-generating molecule or moiety, allowing detection of the tertiary complexes thus formed. This system can provide for signal amplification. Methods for detecting and measuring signals generated by labels are known. For example, radioactive isotopes can be detected by scintillation counting or direct visualization; fluorescent molecules can be detected with fluorescent spectrophotometers; phosphorescent molecules can be detected with a spectrophotometer or directly visualized with a camera; enzymes can be detected by measurement or visualization of the product of a reaction catalyzed by the enzyme; antibodies can be detected by detecting a secondary detection label coupled to the antibody. Such methods can be used directly in the disclosed methods. As used herein, detection molecules are molecules which interact with a molecule of interest (such as a calcifying nano-particle and/or proteins) and to which one or more detection labels are coupled. In another form of detection, labels can be distinguished temporally via different fluorescent, phosphorescent, or chemiluminescent emission lifetimes. Multiplexed time-dependent detection is described in Squire et al., J. Microscopy 197(2):136-149 (2000), and WO 00/08443.

Quantitative measurement of the amount or intensity of a label can be used. For example, quantitation can be used to determine if a given label, and thus the labeled component, is present at a threshold level or amount. A threshold level or amount is any desired level or amount of signal and can be chosen to suit the needs of the particular form of the method being performed. Methods that involve the detection of a substance, such as a protein or an antibody to a specific protein, include label-free assays, protein separation methods (i.e., electrophoresis), solid support capture assays, or in vivo detection. Label-free assays are generally diagnostic means of determining the presence or absence of a specific protein, or an antibody to a specific protein, in a sample. Protein separation methods are additionally useful for evaluating physical properties of the protein, such as size or net charge. Capture assays are generally more useful for quantitatively evaluating the concentration of a specific protein, or antibody to a specific protein, in a sample. Finally, in vivo detection is useful for evaluating the spatial expression patterns of the substance, i.e., where the substance can be found in a subject, tissue or cell.

Assay and detection techniques described herein use various terms, such as antigen, substance, molecule, analyte, etc., to refer molecules of interest that are to be bound or detected. Use of particular terms is not intended to be limiting. Unless the context clearly indicates otherwise, the assays and detection techniques described herein can be used to assay and detect calcifying nano-particles and proteins, such as proteins on calcifying nano-particles and/or proteins on or associated with the proteins on the calcifying nano-particles. As such, the calcifying nano-particles and proteins can be considered the antigen, substance, molecule, analyte, etc. that is bound and/or detected in the assay or detection technique. Assay and detection techniques described herein refer, at various times, to the use of antibodies, such as antibodies that bind to or are specific for antigens, proteins, molecules, etc. Although many forms of the described assays and detection techniques are typically performed using antibodies, the assays and techniques for use in the disclosed methods is not intended to be limiting. Unless the context clearly indicates otherwise, the assays and detection techniques described herein that are described as using (or that commonly used) antibodies can be used with any suitable compound that can bind to the disclosed calcifying nano-particles and proteins. 1. SAPIA

Surface Antigen Pattern Immunoassay (SAPIA) can be used to detect and/or identify stable particles from biological sources and/or components associated thereof. Said components can include, but are not limited to, proteins, peptides, isopeptide bonds, carbohydrates, lipids (fatty acids, phospholipids), endotoxin, heparin sulfate, calcium phosphate, and or nucleic acids (nucleic acid binding proteins associated with HA, amyloid protein P, etc. as associated on the particles.). Examples of stable particles include spores, virus, certain bateria, any colloidal size mineral, metal biological or synthetic material particles (capable of binding antigens to its surface) and calcifying nanoparticles. For example, SAPIA calcifying nano-particles and/or components on calcifying nano-particles. SAPIA allows detection of the presence of multiple proteins on CNPs (Figures 1 A-IE). An example and demonstration of SAPIA is described in the Example 1. In SAPIA, capture compounds, such as antibodies specific for one or more proteins on calcifying nano-particles, are immobilized on a solid support. In some forms, capture compounds specific for multiple proteins on calcifying nano-particles can be situated on a single solid support and/or in an array. SAPIA generally involves capture of calcifying nano-particles on a solid support via binding of one or more proteins on the calcifying nano-particles to capture compounds on the solid support. The captured calcifying nano-particles can then be detected and/or identified by binding a detection compound to the calcifying nano-particles and/or one or more proteins on the calcifying nano-particles and/or one or more of proteins bound to said proteins. In preferred forms of SAPIA, an array of capture compounds specific for different proteins on calcifying nano-particles is used, thus capturing calcifying nano- particles at each array location where a capture compound is present that can bind a protein on the calcifying nano-particles. Because calcifying nano-particles contain a number of proteins, each type of calcifying nano-particle can bind to multiple locations where multiple different capture compounds are present in the array, hi this way detection of the presence of calcifying nano-particles at a given array location can identify a protein on the calcifying nano-particle. Such detection can be accomplished with detection compounds that bind to a single type of protein on calcifying nano-particles because only the presence of calcifying nano-particles needs to be detected. In other forms of SAPIA, capture of calcifying nano-particles can be via a single type of protein on calcifying nano- particles and detection can be via multiple types of proteins on calcifying nano-particles or capture and detection can each be via multiple types of proteins on calcifying nano- particles.

2. Immunoassays Immunodetection methods can be used for detecting, binding, purifying, removing and quantifying various molecules including the disclosed proteins. Further, antibodies and ligands to the disclosed calcifying nano-particles and proteins can be detected. For example, the disclosed proteins can be employed to detect antibodies having reactivity therewith. This is useful, for example, to detect whether a subject has been exposed to or has developed antibodies against a protein. Standard immunological techniques are described, e.g., in Hertzenberg, et al., Weir's Handbook of Experimental Immunology, vols. 1-4 (1996); Coligan, Current Protocols in Immunology (1991); Methods in Enzymology, vols. 70, 73, 74, 84, 92, 93, 108, 116, 121, 132, 150, 162, and 163; and Paul, Fundamental Immunology (3d ed. 1993) each incorporated herein by reference in its entirety and specifically for its teaching regarding immunodetection methods.

The steps of various useful immunodetection methods have been described in the scientific literature, such as, e.g., Maggio et al., Enzyme-Immunoassay, (1987) and Nakamura, et al., Enzyme Immunoassays: Heterogeneous and Homogeneous Systems, Handbook of Experimental Immunology, Vol. 1 : Immunochemistry, 27.1-27.20 (1986) each incorporated herein by reference in its entirety and specifically for its teaching regarding immunodetection methods. Immunoassays, in their most simple and direct sense, are binding assays involving binding between antibodies and antigen. Many types and formats of immunoassays are known and all are suitable for detecting the disclosed proteins. Examples of immunoassays are enzyme linked immunosorbent assays (ELISAs), radioimmunoassays (RIA), radioimmune precipitation assays (RIPA), immunobead capture assays, Western blotting, dot blotting, gel-shift assays, Flow cytometry, protein arrays, multiplexed bead arrays, magnetic capture, in vivo imaging, fluorescence resonance energy transfer (FRET), and fluorescence recovery/localization after photobleaching (FRAP/ FLAP).

In general, immunoassays involve contacting a sample suspected of containing a molecule of interest (such as the disclosed calcifying nano-particles and proteins) with an antibody to the molecule of interest or contacting an antibody to a molecule of interest (such as antibodies to the disclosed proteins) with a molecule that can be bound by the antibody, as the case may be, under conditions effective to allow the formation of immunocomplexes. Contacting a sample with the antibody to the molecule of interest or with the molecule that can be bound by an antibody to the molecule of interest under conditions effective and for a period of time sufficient to allow the formation of immune complexes (primary immune complexes) is generally a matter of simply bringing into contact the molecule or antibody and the sample and incubating the mixture for a period of time long enough for the antibodies to form immune complexes with, i.e., to bind to, any molecules (e.g. antigens) present to which the antibodies can bind, hi many forms of immunoassay, the sample-antibody composition, such as a tissue section, ELISA plate, dot blot or Western blot, can then be washed to remove any non-specifically bound antibody species, allowing only those antibodies specifically bound within the primary immune complexes to be detected. The sample used can be any sample that is suspected of containing a molecule of interest (or an antibody to a molecule of interest). The sample can be, for example, one or more cells, tissue, or bodily fluids such as blood, urine, semen, lymphatic fluid, cerebrospinal fluid, or amniotic fluid, or other biological samples, such as tissue culture cells, buccal swabs, mouthwash, stool, tissue slices, tissue sections, homogenized tissue extract, cell membrane preparation, biopsy aspiration, archeological samples such as bone or mummified tissue, infection samples, nosocomial infection samples, production samples, drug preparation samples, biological molecule production samples, protein preparation samples, lipid preparation samples, and/or carbohydrate preparation samples, and separated or purified forms of any of the above. Such samples can come from subjects or patients.

Immunoassays can include methods for detecting or quantifying the amount of a molecule of interest (such as the disclosed proteins or their antibodies) in a sample, which methods generally involve the detection or quantitation of any immune complexes formed during the binding process. In general, the detection of immunocomplex formation is well known in the art and can be achieved through the application of numerous approaches. These methods are generally based upon the detection of a label or marker, such as any radioactive, fluorescent, biological or enzymatic tags or any other known label. See, for example, U.S. Patents 3,817,837; 3,850,752; 3,939,350; 3,996,345; 4,277,437; 4,275,149 and 4,366,241, each incorporated herein by reference in its entirety and specifically for its teaching regarding immunodetection methods and labels.

Immunoassays that involve the detection of a substance, such as a protein or an antibody to a specific protein, include label-free assays, protein separation methods (i.e., electrophoresis), solid support capture assays, or in vivo detection. Label-free assays are generally diagnostic means of determining the presence or absence of a specific protein, or an antibody to a specific protein, in a sample. Protein separation methods are additionally useful for evaluating physical properties of the protein, such as size or net charge. Capture assays are generally more useful for quantitatively evaluating the concentration of a specific protein, or antibody to a specific protein, in a sample. Finally, in vivo detection is useful for evaluating the spatial expression patterns of the substance, i.e., where the substance can be found in a subject, tissue or cell.

3. Label-free Assays

Provided that the concentrations are sufficient, the molecular complexes can be visible to the naked eye, but smaller amounts may also be detected and measured due to their ability to scatter a beam of light. The formation of complexes indicates that both reactants are present, and in immunoprecipitation assays a constant concentration of a reagent antibody can be used to measure specific antigen and reagent antigens can be used to detect specific antibody. If the reagent species is previously coated onto cells (as in hemagglutination assay) or very small particles (as in latex agglutination assay),

"clumping" of the coated particles is visible at much lower concentrations. A variety of assays based on these elementary principles are in common use, including Ouchterlony immunodiffusion assay, rocket Immunoelectrophoresis, and immunoturbidometric and nephelometric assays. The main limitations of such assays are restricted sensitivity (lower detection limits) in comparison to assays employing labels and, in some cases, the fact that very high concentrations of analyte can actually inhibit complex formation, necessitating safeguards that make the procedures more complex. A variety of instruments can directly detect molecular interactions (binding, for example). Many are based on an evanescent wave on a sensor surface with immobilized ligand, which allows continuous monitoring of binding.

4. Protein Separation

Detection of calcifying nano-particles and/or proteins can involve the separation of the calcifying nano-particles and/or proteins by electophoresis. In two-dimensional electrophoresis, proteins are fractionated first on the basis of one physical property, and, in a second step, on the basis of another. For example, isoelectric focusing can be used for the first dimension, conveniently carried out in a tube gel, and SDS electrophoresis in a slab gel can be used for the second dimension. One example of a procedure is that of O'Farrell, P.H., High Resolution Two-dimensional Electrophoresis of Proteins, J. Biol. Chem. 250:4007-4021 (1975), herein incorporated by reference in its entirety for its teaching regarding two-dimensional electrophoresis methods. Other examples include but are not limited to, those found in Anderson, L and Anderson, NG, High resolution two- dimensional electrophoresis of human plasma proteins, Proc. Natl. Acad. Sci. 74:5421- 5425 (1977), Ornstein, L., Disc electrophoresis, L. Ann. N.Y. Acad. Sci. 121:321349 (1964), each herein incorporated by reference in its entirety for its teaching regarding electrophoresis methods. 5. Western Blot

One example of an immunoassay that uses electrophoresis is Western Blot analysis. Western blotting or immunoblotting allows the determination of the molecular mass of a protein and the measurement of relative amounts of the protein present in different samples. Detection methods include chemiluminescence and chromagenic detection. Standard methods for Western Blot analysis can be found in, for example, D.M. Bollag et al., Protein Methods (2d edition 1996) and E. Harlow & D. Lane, Antibodies, a Laboratory Manual (1988), U.S. Patent 4,452,901, each herein incorporated by reference in their entirety for their teaching regarding Western Blot methods. Generally, proteins are separated by gel electrophoresis, usually SDS-PAGE. The proteins are transferred to a sheet of special blotting paper, e.g., nitrocellulose, though other types of paper, or membranes, can be used. The proteins retain the same pattern of separation they had on the gel. The blot is incubated with a generic protein (such as milk proteins) to bind to any remaining sticky places on the nitrocellulose. An antibody is then added to the solution which is able to bind to its specific protein

The attachment of specific antibodies to specific immobilized antigens can be readily visualized by indirect enzyme immunoassay techniques, usually using a chromogem^'c substrate (e.g. alkaline phosphatase or horseradish peroxidase) or chemiluminescent substrates. Other possibilities for probing include the use of fluorescent or radioisotope labels (e.g., fluorescein, T). Probes for the detection of antibody binding can be conjugated anti-immunoglobulins, conjugated staphylococcal Protein A (binds IgG), or probes to biotinylated primary antibodies (e.g., conjugated avidin/ streptavidin). The power of the technique lies in the simultaneous detection of a specific protein by means of its antigenicity, and its molecular mass: proteins are first separated by mass in the SDS-PAGE, then specifically detected in the immunoassay step. Thus, protein standards (ladders) can be run simultaneously in order to approximate molecular mass of the protein of interest in a heterogeneous sample. 6. Capture Assays

Calcifying nano-particles and proteins can be detecting when captured or bound to a solid support (e.g., tube, well, bead, or cell). Examples of such capture assays include Radioimmunoassay (RIA), Enzyme-Linked Immunosorbent Assay (ELISA), Flow cytometry, protein array, multiplexed bead assay, and magnetic capture. i. Radioimmunoassay (RIA)

Radioimmunoassay (RIA) is a quantitative assay for detection of binding complexes using a radioactively labeled substance (radioligand), either directly or indirectly, to measure the binding of the unlabeled substance to a specific antibody or other compound that can bind to the substance. RIA involves mixing a radioactive substance (because of the ease with which iodine atoms can be introduced into tyrosine residues in a protein, the radioactive isotopes ¹²⁵I or ¹³¹I are often used) with antibody or other compound that can bind to the substance. The antibody or other compound is generally linked to a solid support, such as the tube or beads. Unlabeled or "cold" substance is then adding in known quantities and the amount of labeled substance displaced is measured. Initially, the radioactive substance is bound. When cold substance is added, the two compete for binding sites - and at higher concentrations of cold substance, more binds to the antibody or compound, displacing the radioactive variant. The bound substance is separated from the unbound in solution and the radioactivity of each used to plot a binding curve. The technique is both extremely sensitive, and specific. ii. ELISAs Enzyme-Linked Immunosorbent Assay (ELISA), or more generically termed EIA (Enzyme ImmunoAssay), is an immunoassay that can detect an antibody specific for a protein. In such an assay, a detectable label bound to either an antibody-binding or antigen-binding reagent is an enzyme. When exposed to its substrate, this enzyme reacts in such a manner as to produce a chemical moiety which can be detected, for example, by spectrophotometric, fluorometric or visual means. Enzymes which can be used to detectably label reagents useful for detection include, but are not limited to, horseradish peroxidase, alkaline phosphatase, glucose oxidase, /3-galactosidase, ribonuclease, urease, catalase, malate dehydrogenase, staphylococcal nuclease, asparaginase, yeast alcohol dehydrogenase, alpha.-glycerophosphate dehydrogenase, triose phosphate isomerase, glucose-6-phosphate dehydrogenase, glucoamylase and acetylcholinesterase. For descriptions of ELISA procedures, see Voller, A. et al.. J. Clin. Pathol. 31:507-520 (1978); Butler, J. E., Meth. Enzymol. 73:482-523 (1981); Maggio, E. (ed.), Enzyme Immunoassay, CRC Press, Boca Raton, 1980; Butler, J. E., In: Structure of Antigens, Vol. 1 (Van Regenmortel, M., CRC Press, Boca Raton, 1992, pp. 209-259; Butler, J. E., In: van Oss, C. J. et al., (eds), Immunochemistry, Marcel Dekker, Inc., New York, 1994, pp. 759- 803; Butler, J. E. (ed), Immunochemistry of Solid-Phase Immunoassay, CRC Press, Boca Raton, 1991); Crowther, "ELISA: Theory and Practice," In: Methods in Molecule Biology, Vol. 42, Humana Press; New Jersey, 1995. ;U.S. Patent 4,376,110, each incorporated herein by reference in its entirety and specifically for its teaching regarding ELISA methods. ELISA techniques can also be adapted to use compounds, other than antibodies, that bind to molecules of interest.

Variations of ELISA techniques are know to those of skill in the art. In one variation, antibodies that can bind to proteins can be immobilized onto a selected surface exhibiting protein affinity, such as a well in a polystyrene microtiter plate. Then, a test composition suspected of containing a marker antigen can be added to the wells. After binding and washing to remove non-specifically bound immunocomplexes, the bound antigen can be detected. Detection can be achieved by the addition of a second antibody specific for the target protein, which is linked to a detectable label. This type of ELISA is a simple "sandwich ELISA." Detection also can be achieved by the addition of a second antibody, followed by the addition of a third antibody that has binding affinity for the second antibody, with the third antibody being linked to a detectable label.

Another variation is a competition ELISA. In competition ELISA' s, test samples compete for binding with known amounts of labeled antigens or antibodies. The amount of reactive species in the sample can be determined by mixing the sample with the known labeled species before or during incubation with coated wells. The presence of reactive species in the sample acts to reduce the amount of labeled species available for binding to the well and thus reduces the ultimate signal.

Irrespective of the format employed, ELISAs have certain features in common, such as coating, incubating or binding, washing to remove non-specifically bound species, and detecting the bound immunecomplexes. Antigen or antibodies can be linked to a solid support, such as in the form of plate, beads, dipstick, membrane or column matrix, and the sample to be analyzed applied to the immobilized antigen or antibody. In coating a plate with either antigen or antibody, one will generally incubate the wells of the plate with a solution of the antigen or antibody, either overnight or for a specified period of hours. The wells of the plate can then be washed to remove incompletely adsorbed material. Any remaining available surfaces of the wells can then be "coated" with a nonspecific protein that is antigenically neutral with regard to the test antisera. These include bovine serum albumin (BSA), casein and solutions of milk powder. The coating allows for blocking of nonspecific adsorption sites on the immobilizing surface and thus reduces the background caused by nonspecific binding of antisera onto the surface. Such coating and blocking can be used with other capture assays and with other forms of the disclosed methods involving capture and/or solid supports.

In ELISAs, a secondary or tertiary detection means rather than a direct procedure can also be used. Thus, after binding of a protein or antibody to the well, coating with a non-reactive material to reduce background, and washing to remove unbound material, the immobilizing surface is contacted with the control sample to be tested under conditions effective to allow immunecomplex (antigen/antibody) formation. Detection of the immunecomplex then requires a labeled secondary binding agent, or a secondary binding agent in conjunction with a labeled third binding agent.

"Under conditions effective to allow immunecomplex (antigen/antibody) formation" means that the conditions include diluting the antigens and antibodies with solutions such as BSA, bovine gamma globulin (BGG) and phosphate buffered saline (PBS)/Tween. These added agents can also assist in the reduction of nonspecific background.

The "suitable" conditions also mean that the incubation is at a temperature and for a period of time sufficient to allow effective binding. Incubation steps can typically be from about 1 minute to twelve hours, at temperatures of about 20° to 30° C, or can be incubated overnight at about 0° C to about 10° C.

Following all incubation steps in an ELISA, the contacted surface can be washed so as to remove non-complexed material. A washing procedure can include washing with a solution such as PBS/Tween, or borate buffer. Following the formation of specific immunecomplexes between the test sample and the originally bound material, and subsequent washing, the occurrence of even minute amounts of immunecomplexes can be determined.

To provide a detecting means, the second or third antibody can have an associated label to allow detection, as described elsewhere herein. This can be an enzyme that can generate color development upon incubating with an appropriate chromogenic substrate. Thus, for example, one can contact and incubate the first or second immunecomplex with a labeled antibody for a period of time and under conditions that favor the development of further immunecomplex formation (e.g., incubation for 2 hours at room temperature in a PBS-containing solution such as PBS-Tween).

After incubation with the labeled antibody, and subsequent to washing to remove unbound material, the amount of label can be quantified, e.g., by incubation with a chromogenic substrate such as urea and bromocresol purple or 2,2'-azido-di-(3-ethyl- benzthiazoline-6-sulfonic acid [ABTS] and H₂O₂, in the case of peroxidase as the enzyme label. Quantitation can then be achieved by measuring the degree of color generation, e.g., using a visible spectra spectrophotometer. iii. Flow Cytometry Flow cytometry, fluorescent activated cell sorting (FACS), fluorescence activated sorting, and flow microfluorometry provide a means of scanning individual cells or particles for the presence of a molecule of interest. Although commonly used for analysis of cells, these techniques can be used in the disclosed method to detect, analyze and identify calcifying nano-particles and/or proteins on calcifying nano-particles. Flow Cytometry is the characterization of single cells or particles as they pass at high speed through a laser beam. While a hematologist can count 200 cells in less than a minute by hand (hemocytometer) on a stage microscope, a flow cytometer can discriminate cells at speeds up to 50,000 cells/second. The Flow component is a fluidics system that precisely delivers the cells at the intersection of the laser beam and light gathering lens by hydrodynamic focusing (a single stream of cells is injected and confined within an outer stream at greater pressure). The laser acting as a light source develops parameters of light scatter as well as exciting the fluorescent molecules used to label the cell. Cells are characterized individually by their physical and/or chemical properties (Kohler, G. and Milstein, C. (1975) Continuous Cultures of Fused Cells Secreting Antibody of Predefined Specificity. Nature 256: p. 495-49) which provide analytical parameters capable of accurate quantitation of the number of molecules/cell through Quantitative Flow Cytometry (QFCM). The physical (morphological) profile of a cell or particle can be observed by combining forward light scatter (FS) and orthogonal or side light scatter (SSC). In forward light scatter the laser beam is interrupted by the cell or particle and the light that passes around the cell or particle is measured. Comparable to casting shadow puppets on a wall with a flashlight. This measurement is an indication of the cell's or particle's unique refractive index. Side scatter is the light that is reflected 90° to the laser beam (all fluorescence is emitted and therefore collected at this angle) and is an indication of density or surface granularity.

A short list of some of the information that can be discerned by multiparameter (multi-color) Flow Cytometry includes; Apoptosis (programmed cell death), Cell Type, DNA Content, Enzyme Activity, Intracellular Proteins, Cell Surface Antigens,

Cytoplasmic Granularity, Surface Membrane Integrity, Intracellular [Ca++]-Signal Transduction, DNA Synthesis-Proliferation, Cell Surface Receptors, Intracellular Cytokines, Oxidative Metabolism, Intracellular pH, RNA Content, and Cell Size.

Antibodies can provide a useful tool for the analysis and quantitation of markers of individual cells. Such flow cytometric analyses are described in Melamed, et al., Flow Cytometry and Sorting (1990); Shapiro, Practical Flow Cytometry (1988); and Robinson, et al., Handbook of Flow Cytometry Methods (1993), each herein incorporated by reference in its entirety for their teaching regarding FACS. Generally, proteins are detected with antibodies that have been conjugated to fluorescent molecules such as FITC, PE, Texas Red, APC, etc. Molecules on the cell or particle surface can be detected.

By tagging antibodies with a colored fluorochrome, it is easy to distinguish the presence and quantity of antigens on particles or cells. Employing dichroic splitting mirrors, band pass filters and compensation, the colors can be resolved where each color is associated with a single antibody. As each cell or particle, tagged with a fluorescently labeled antibody, enters the laser light outer orbital electrons in the fluorochrome are excited at a specific excitation wavelength (e.g., 494 nm for FITC). As it transitions the width of the laser beam maximum peak fluorescence is achieved within approximately 10 nsec as the excited outer orbital electrons return to their more stable ground state and emit a photon of light at a longer wavelength (e.g., 520 nm for FITC) than that at which they were excited. Photomultiplier tubes (PMT's) detect these faint fluorescent signals and their sole role is to change discrete packets of light called photons (hv) into electrons and amplify them by producing as much as 10 million electrons for every photon captured.

Fluorescence-activated cell sorting (FACS) and fluorescence-activated sorting are types of flow cytometry. FACS is a method for sorting a suspension of biologic cells into two or more containers, one cell at a time. FACS can also be performed on particles such as calcifying nano-particles (in which case it can be referred to as fluorescence-activated sorting). Fluorescence-activated cell sorting is based upon specific light scattering and fluorescence characteristics of each cell or particle. In FACS, the cell or particle suspension is entrained in the center of a narrow, rapidly flowing stream of liquid. The flow is arranged so that there is a large separation between cells and particles relative to their diameter. A vibrating mechanism causes the stream of cells and particles to break into individual droplets. The system is adjusted so that there is a low probability of more than one cell or particle being in a droplet. Just before the stream breaks into droplets the flow passes through a fluorescence measuring station where the fluorescence character of interest of each cell or particle is measured. An electrical charging ring is placed just at the point where the stream breaks into droplets. A charge is placed on the ring based on the immediately prior fluorescence intensity measurement and the opposite charge is trapped on the droplet as it breaks from the stream. The charged droplets then fall through an electrostatic deflection system that diverts droplets into containers based upon their charge. iv. Protein Arrays

Protein arrays are solid-phase ligand binding assay systems using immobilised proteins on surfaces which include glass, membranes, microtiter wells, mass spectrometer plates, and beads or other particles. The assays are highly parallel (multiplexed) and often miniaturised (microarrays, protein chips). Their advantages include being rapid and automatable, capable of high sensitivity, economical on reagents, and giving an abundance of data for a single experiment. Bioinformatics support is important; the data handling demands sophisticated software and data comparison analysis. However, the software can be adapted from that used for DNA arrays, as can much of the hardware and detection systems. Such systems and techniques of protein arrays can be used to detect calcifying nano-particles and/or proteins on calcifying nano-particles.

One of the chief formats is the capture array, in which ligand-binding reagents, which are usually antibodies but can also be alternative protein scaffolds, peptides or nucleic acid aptamers, are used to detect target molecules in mixtures such as plasma or tissue extracts. In diagnostics, capture arrays can be used to carry out multiple immunoassays in parallel, both testing for several analytes in individual sera for example and testing many serum samples simultaneously. In proteomics, capture arrays are used to quantitate and compare the levels of proteins in different samples in health and disease, i.e. protein expression profiling. Proteins other than specific ligand binders are used in the array format for in vitro functional interaction screens such as protein-protein, protein- DNA, protein-drug, receptor-ligand, enzyme-substrate, etc. They may also be used to correlate the polymorphic changes resulting from SNPs with protein function. The capture reagents themselves are selected and screened against many proteins, which can also be done in a multiplex array format against multiple protein targets. Analysis of multiple proteins on calcifying nano-particles can be performed using such techniques. For construction of arrays, sources of proteins include cell-based expression systems for recombinant proteins, purification from natural sources, production in vitro by cell-free translation systems, and synthetic methods for peptides. Many of these methods can be automated for high throughput production. For capture arrays and protein function analysis, it is important that proteins should be correctly folded and functional; this is not always the case, e.g. where recombinant proteins are extracted from bacteria under denaturing conditions. Nevertheless, arrays of denatured proteins are useful in screening antibodies for cross-reactivity, identifying autoantibodies and selecting ligand binding proteins.

Protein arrays have been designed as a miniaturisation of familiar immunoassay methods such as ELISA and dot blotting, often utilizing fluorescent readout, and facilitated by robotics and high throughput detection systems to enable multiple assays to be carried out in parallel. Commonly used physical supports include glass slides, silicon, microwells, nitrocellulose or PVDF membranes, and magnetic and other microbeads. While microdrops of protein delivered onto planar surfaces are the most familiar format, alternative architectures include CD centrifugation devices based on developments in microfluidics [Gyros] and specialised chip designs, such as engineered microchannels in a plate [The Living Chip™, Biotrove] and tiny 3D posts on a silicon surface [Zyomyx]. Particles in suspension can also be used as the basis of arrays, providing they are coded for identification; systems include color coding for microbeads [Luminex, Bio-Rad] and semiconductor nanocrystals [QDots™, Quantum Dots], and barcoding for beads [UltraPlex™, Smartbeads] and multimetal microrods [Nanobarcodes™ particles, Nanoplex Technologies]. Beads can also be assembled into planar arrays on semiconductor chips [LEAPS technology, Bio Array Solutions].

Immobilization of proteins involves both the coupling reagent and the nature of the surface being coupled to. A good protein array support surface is chemically stable before and after the coupling procedures, allows good spot morphology, displays minimal nonspecific binding, does not contribute a background in detection systems, and is compatible with different detection systems. The immobilization method used are reproducible, applicable to proteins of different properties (size, hydrophilic, hydrophobic), amenable to high throughput and automation, and compatible with retention of fully functional protein activity. Orientation of the surface-bound protein is recognized as an important factor in presenting it to ligand or substrate in an active state; for capture arrays the most efficient binding results are obtained with orientated capture reagents, which generally require site-specific labeling of the protein.

Both covalent and noncovalent methods of protein immobilization are used and have various pros and cons. Passive adsorption to surfaces is methodologically simple, but allows little quantitative or orientational control; it may or may not alter the functional properties of the protein, and reproducibility and efficiency are variable. Covalent coupling methods provide a stable linkage, can be applied to a range of proteins and have good reproducibility; however, orientation may be variable, chemical derivatization may alter the function of the protein and requires a stable interactive surface. Biological capture methods utilizing a tag on the protein provide a stable linkage and bind the protein specifically and in reproducible orientation, but the biological reagent must first be immobilized adequately and the array may require special handling and have variable stability.

Several immobilization chemistries and tags have been described for fabrication of protein arrays. Substrates for covalent attachment include glass slides coated with amino- or aldehyde-containing silane reagents. In the Versalinx™ system [Prolinx], reversible covalent coupling is achieved by interaction between the protein derivatised with phenyldiboronic acid, and salicylhydroxamic acid immobilized on the support surface. This also has low background binding and low intrinsic fluorescence and allows the immobilized proteins to retain function. Noncovalent binding of unmodified protein occurs within porous structures such as HydroGel™ [PerkinElmer], based on a 3- dimensional polyacrylamide gel; this substrate is reported to give a particularly low background on glass microarrays, with a high capacity and retention of protein function. Widely used biological coupling methods are through biotin/streptavidin or hexahistidine/Ni interactions, having modified the protein appropriately. Biotin may be conjugated to a poly-lysine backbone immobilised on a surface such as titanium dioxide [Zyomyx] or tantalum pentoxide [Zeptosens].

Array fabrication methods include robotic contact printing, ink-jetting, piezoelectric spotting and photolithography. A number of commercial arrayers are available [e.g. Packard Biosience] as well as manual equipment [V & P Scientific]. Bacterial colonies can be robotically gridded onto PVDF membranes for induction of protein expression in situ.

At the limit of spot size and density are nanoarrays, with spots on the nanometer spatial scale, enabling thousands of reactions to be performed on a single chip less than lmm square. BioForce Laboratories have developed nanoarrays with 1521 protein spots in 85 sq microns, equivalent to 25 million spots per sq cm, at the limit for optical detection; their readout methods are fluorescence and atomic force microscopy (AFM).

Fluorescence labeling and detection methods are widely used. The same instrumentation as used for reading DNA microarrays is applicable to protein arrays. For differential display, capture (e.g. antibody) arrays can be probed with fluorescently labeled proteins from two different cell states, in which cell lysates are directly conjugated with different fluorophores (e.g. Cy-3, Cy-5) and mixed, such that the color acts as a readout for changes in target abundance. Fluorescent readout sensitivity can be amplified 10-100 fold by tyramide signal amplification (TSA) [PerkinElmer Lifesciences]. Planar waveguide technology [Zeptosens] enables ultrasensitive fluorescence detection, with the additional advantage of no intervening washing procedures. High sensitivity can also be achieved with suspension beads and particles, using phycoerythrin as label [Luminex] or the properties of semiconductor nanocrystals [Quantum Dot]. A number of novel alternative readouts have been developed, especially in the commercial biotech arena. These include adaptations of surface plasmon resonance [HTS Biosystems, Intrinsic Bioprobes], rolling circle DNA amplification [Molecular Staging], mass spectrometry [Ciphergen, Intrinsic Bioprobes], resonance light scattering [Genicon Sciences] and atomic force microscopy [BioForce Laboratories]. Capture arrays form the basis of diagnostic chips and arrays for expression profiling. They employ high affinity capture reagents, such as conventional antibodies, single domains, engineered scaffolds, peptides or nucleic acid aptamers, to bind and detect specific target ligands in high throughput manner.

Antibody arrays have the required properties of specificity and acceptable background, and some are available commercially [BD Biosciences Clontech, BioRad, Sigma]. Antibodies for capture arrays are made either by conventional immunisation (polyclonal sera and hybridomas), or as recombinant fragments, usually expressed in E. coli, after selection from phage or ribosome display libraries [Cambridge Antibody Technology, Biolnvent, Affϊtech, Biosite]. In addition to the conventional antibodies, Fab and scFv fragments, single V-domains from camelids or engineered human equivalents [Domantis] may also be useful in arrays.

The term 'scaffold' refers to ligand-binding domains of proteins, which are engineered into multiple variants capable of binding diverse target molecules with antibody-like properties of specificity and affinity. The variants can be produced in a genetic library format and selected against individual targets by phage, bacterial or ribosome display. Such ligand-binding scaffolds or frameworks include 'Affibodies' based on Staph, aureus protein A [Affibody], 'Trinectins' based on fibronectins [Phylos] and 'Anticalins' based on the lipocalin structure [Pieris]. These can be used on capture arrays in a similar fashion to antibodies and may have advantages of robustness and ease of production.

Non-protein capture molecules, notably the single-stranded nucleic acid aptamers which bind protein ligands with high specificity and affinity, are also used in arrays [SomaLogic]. Aptamers are selected from libraries of oligonucleotides by the Selex™ procedure and their interaction with protein can be enhanced by covalent attachment, through incorporation of brominated deoxyuridine and UV-activated crosslinking (photoaptamers). Photocrosslinking to ligand reduces the crossreactivity of aptamers due to the specific steric requirements. Aptamers have the advantages of ease of production by automated oligonucleotide synthesis and the stability and robustness of DNA; on photoaptamer arrays, universal fluorescent protein stains can be used to detect binding.

Protein analytes binding to antibody arrays may be detected directly or via a secondary antibody in a sandwich assay. Direct labeling is used for comparison of different samples with different colors. Where pairs of antibodies directed at the same protein ligand are available, sandwich immunoassays provide high specificity and sensitivity and are therefore the method of choice for low abundance proteins such as cytokines; they also give the possibility of detection of protein modifications. Label- free detection methods, including mass spectrometry, surface plasmon resonance and atomic force microscopy, avoid alteration of ligand. An alternative to an array of capture molecules is one made through 'molecular imprinting' technology, in which peptides (e.g. from the C-terminal regions of proteins) are used as templates to generate structurally complementary, sequence-specific cavities in a polymerisable matrix; the cavities can then specifically capture (denatured) proteins which have the appropriate primary amino acid sequence [ProteinPrint™, Aspira Biosystems].

Another methodology which can be used diagnostically and in expression profiling is the ProteinChip® array [Ciphergen], in which solid phase chromatographic surfaces bind proteins with similar characteristics of charge or hydrophobicity from mixtures such as plasma or tumour extracts, and SELDI-TOF mass spectrometry is used to detection the retained proteins. This technology differs from the protein arrays under discussion here since, in general, it does not involve immobilization of individual proteins for detection of specific ligand interactions. For detecting protein-protein interactions, protein arrays can be in vitro alternatives to the cell-based yeast two-hybrid system and may be useful where the latter is deficient, such as interactions involving secreted proteins or proteins with disulphide bridges. High- throughput analysis of biochemical activities on arrays has been described for yeast protein kinases and for various functions (protein-protein and protein-lipid interactions) of the yeast proteome, where a large proportion of all yeast open-reading frames was expressed and immobilised on a microarray. v. Multiplexed Bead Assay

A multiplexed bead assay, such as for example the BD™ Cytometric Bead Array, is a series of spectrally discrete particles that can be used to capture and quantitate soluble analytes. The analyte is then measured by detection of a fluorescence-based emission and flow cytometric analysis. Multiplexed bead assay generates data that is comparable to ELISA based assays, but in a "multiplexed" or simultaneous fashion. Concentration of unknowns is calculated for the cytometric bead array as with any sandwich format assay, i.e. through the use of known standards and plotting unknowns against a standard curve. Further, multiplexed bead assay allows quantification of soluble analytes in samples never previously considered due to sample volume limitations, hi addition to the quantitative data, powerful visual images can be generated revealing unique profiles or signatures that provide the user with additional information at a glance. vi. Magnetic Capture Antibody-coated magnetic particles can be used to capture and selectively separate analytes, such as calcifying nano-particles, from solution. In the technique, target-specific antibody is bound to a magnetic particle (often termed an immunobead). After reaction time to allow binding of immunobead and target, a strong magnetic field is applied to selectively separate the captured target-particle complexes from the milieu. 7. Imunocytochemistry/ immunohistochemistry

Also provided are methods of detecting a substance of interest such as a protein in vivo or in situ using antibody conjugates. Imunocytochemistry and immunohistochemistry are techniques for identifying cellular or tissue constituents, respectively, by means of antigen-antibody interactions. The methods generally involve administering to an animal or subject an imaging-effective amount of a detectably-labeled protein-specific antibody or fragment thereof, and then detecting the location of the labeled antibody in the sample cell or tissue. An "imaging effective amount" is an amount of a detectably-labeled antibody, or fragment thereof, that when administered is sufficient to enable later detection of binding of the antibody or fragment in the specific cell or tissue. The effective amount of the antibody-marker conjugate is allowed sufficient time to come into contact with reactive antigens that are present within the tissues of the subject, and the subject is then exposed to a detection device to identify the detectable marker.

Antibody conjugates or constructs for imaging thus have the ability to provide an image of the tissue, for example, through fluorescence microscopy, laser scanning confocal microscopy (LSCM), magnetic resonance imaging (MRT), SEM, TEM, x-ray imaging, computerized emission tomography and the like. Fluorescence microscopy and laser scanning confocal microscopy (LSCM) involve the detection of fluorochrome labels, such as those provided herein. Wide-field fluorescence microscopy is a very widely used technique to obtain both topographical and dynamic information. It relies on the simultaneous illumination of the whole sample. The source of light is usually a mercury lamp, giving out pure white light. Optical filters are then used in order to select the wavelength of excitation light (the excitation filter).

Excitation light is directed to the sample via a dichroic mirror (i.e., a mirror that reflects some wavelengths but is transparent to others) and fluorescent light detected by a camera (usually a CCD camera). Thus both the illumination and detection of light covering the whole visual field of the chosen microscope objective is achieved simultaneously. LSCM differs from wide-field fluorescence microscopy in a number of ways. The light source in LSCM is one or more laser(s). This has two consequences. Firstly, the excitation light bandwidth is determined by the source, not the excitation filter and thus is much narrower than in fluorescence microscopy (2-3 nm rather than 20 - 30 nm). Secondly, in order to illuminate the whole visual field, the laser beam has to be rapidly scanned across the area in a series of lines, much like a TV image is generated. The fluorescence detected at each point is measured in a photomultiplier tube (PMT) and an image built up. The major difference between fluorescence microscopy and LSCM, however, is the pinhole, which is a device that removes unwanted, out-of-focus fluorescence, giving an optical slice of a 3-dimensional image. This "optical slicing" allows the observer to see inside the object of interest and gives clearer images, with more fine detail observable. This method of illumination also has advantages in that it is possible to illuminate selected regions of the visual field allowing complex photobleaching protocols to be carried out to investigate the rates of lateral travel of fluorophores, etc. and for the excitation of different fluorophores in different regions of the same cell. In addition, by altering the focus of the microscope, images can be obtained at different depths. Each image is called a z-section, and can be used to reconstruct an image of the 3- dimensional object. Multi-Photon LSCM is a variation of LSCM that involves the generation of high energy fluorescence using low energy incident light. This is achieved by delivering multiple photons of excitation light to the same point in space in a sufficiently short time that the energy effectively is summed and so acts as a higher energy single photon. The lasers required for this technique are very specialized and very expensive; however, there are a number of advantages of using multiphoton LSCM over conventional techniques. Firstly, high intensity red light scatters less than low intensity blue light, so objects of interest can be imaged in thicker sections of tissue than in conventional LSCM. Thicker slices are likely to be healthier, and the cells being observed are less likely to have been damaged in the preparation of the sample. Secondly, the lower overall energy of the excitation light means that less phototoxic damage is caused during viewing and less photobleaching is seen, extending the time that cells can be observed. Thirdly, multiphoton LSCM is innately confocal, i.e., no pinhole is required. Excitation of the fluorophore can only occur where the two photons can interact. Given the quadratic nature of the probability of two photons interacting with the fluorophore in the necessary timescale, excitation only occurs in the focal plane of the objective lens, which provides cleaner images.

Elements particularly useful in MPJ include the nuclear magnetic spin-resonance isotopes ¹⁵⁷Gd, ⁵⁵Mn, ¹⁶²Dy, ⁵²Cr, and ⁵⁶Fe, with gadolinium often being preferred. Radioactive substances, such as technicium⁹⁹"¹ or indium ^π, that can be detected using a gamma scintillation camera or detector, also can be used. Further examples of metallic ions suitable for use in the current methods are ¹²³1, ¹³¹I, ⁹⁷Ru, ⁶⁷Cu, ⁶⁷Ga, 1251, ⁶⁸Ga, ⁷²As, ⁸⁹Zr, and ²⁰¹Tl. A radionuclide can be bound to an antibody either directly or indirectly by using an intermediary functional group. Intermediary functional groups which are often used to bind radioisotopes which exist as metallic ions to antibody are diethylenetriaminepentaacetic acid (DTPA) and ethylene diaminetetracetic acid (EDTA). Administration of the antibodies can be done as disclosed herein. Nucleic acid approaches for antibody delivery also exist. Antibodies and antibody fragments can also be administered to patients or subjects as a nucleic acid preparation (e.g., DNA or RNA) that encodes the antibody or antibody fragment, such that the patient's or subject's own cells take up the nucleic acid and produce and secrete the encoded antibody or antibody fragment. The delivery of the nucleic acid can be by any means, as disclosed herein, for example. Administration of the antibody can be local or systemic and accomplished intravenously, intra-arterially, via the spinal fluid or the like. Administration also can be intradermal or intracavitary, depending upon the body site under examination. After a sufficient time has lapsed for the labeled antibody or fragment to bind to the diseased tissue, for example 30 minutes to 48 hours, the area of the subject under investigation can then be examined by an imaging technique, such as those described herein.

The distribution of the bound radioactive isotope and its increase or decrease with time can be monitored and recorded. By comparing the results with data obtained from studies of clinically normal individuals, the presence and extent of the diseased tissue can be determined. The exact imaging protocol will necessarily vary depending upon factors specific to the subject, and depending upon the body site under examination, method of administration, type of label used and the like. One of ordinary skill in the art will be able to determine which imaging protocol to use based on these factors. Effective dosages and schedules for administering the compositions can be determined empirically, and making such determinations is within the skill in the art. The dosage ranges for the administration of the compositions are those large enough to produce the desired effect in which the symptoms of the disorder are affected. The dosage should not be so large as to cause adverse side effects, such as unwanted cross-reactions, anaphylactic reactions, and the like. Generally, the dosage will vary with the age, condition, sex and extent of the disease in the patient, route of administration, or whether other drugs are included in the regimen, and can be determined by one of skill in the art. The dosage can be adjusted by the individual physician in the event of any counterindications. Dosage can vary, and can be administered in one or more dose administrations daily, for one or several days. Guidance can be found in the literature for appropriate dosages for given classes of pharmaceutical products. For example, guidance in selecting appropriate doses for antibodies can be found in the literature on therapeutic uses of antibodies, e.g., Ferrone et al., Handbook of Monoclonal Antibodies, (1985) ch. 22 and pp. 303-357; Haber et al., Antibodies in Human Diagnosis and Therapy, (1977) pp. 365-389. A typical daily dosage of the antibody used alone might range from about 1 μg/kg to up to 100 mg/kg of body weight or more per day, depending on the factors mentioned above.

As used herein, "FRET" relates to the phenomenon known as "fluorescence resonance energy transfer". The principle of FRET has been described for example in J.R. Lakowicz, "Principles of Fluorescence Spectroscopy", 2 (nd) Ed. Plenum Press, New York, 1999. Briefly, FRET can occur if the emission spectrum of a first chromophore (donor chromophore or FRET-donor) overlaps with the absorption spectrum of a second chromophore (acceptor chromophore or FRET-acceptor), so that excitation by lower- wavelength light of the donor chromophore is followed by transfer of the excitation energy to the acceptor chromophore. A prerequisite for this phenomenon is the very close proximity of both chromophores. A result of FRET is the decrease/loss of emission by the donor chromophore while at the same time emission by the acceptor chromophore is observed. A further result of FRET is shortening of the duration of the donor excited state as detected by a reduction in the fluorescence lifetime. A pair of 2 chromophores which can interact in the above described manner is called a "donor-acceptor-pair" for FRET.

In FRET, the energy stored in the excited state of a fluorophore (the donor) upon absorption of a photon, is transferred non-radiatively to a second fluorophore (or chromophore), the acceptor. This transfer is due to dipole-dipole interactions between the emission dipole of the donor and the absorption dipole of the acceptor and depends on the separation distance, the orientation between the dipoles, and the extent of overlapping energy levels (the overlap integral). The inverse sixth order dependence of FRET on separation distance produces an extremely steep decline of the FRET efficiency over a couple of nanometers. Furthermore, the typical distance for most pairs at which 50% of the molecules engage in FRET (the Foerster or RO distance) lies in the order of magnitude of average protein diameter (4-6 nm), giving rise to detectable FRET at a maximum distance of about 10 nm.

For the latter reason, FRET is a very popular method to assess (fluorescently labeled) protein-protein interactions and protein conformational changes. Thus, FRET can be used to detect calcifying nano-particles and/or proteins on calcifying nano-particles.

A number of techniques are available at present to detect and quantify the occurrence of FRET. These fall into two categories: 1) Spectral, i.e. fluorescence emission intensity-based methods that are based on the loss of donor emission and concomitant gain of acceptor emission. These are: sensitized acceptor emission, ratio imaging, acceptor photobleaching-induced donor unquenching, and anisotropy microscopy. 2) Fluorescence decay kinetics-based methods that are based on the reduced donor photobleaching phenomenon and reduced donor fluorescence lifetime (or duration of the excited state) in the presence of FRET. These are: donor photobleaching kinetics and fluorescence lifetime imaging microscopy (FLEVl). The latter technique is especially useful for FRET as the fluorescence lifetime is relatively independent of trivial non-FRET related events and is furthermore independent of fluorophore concentration and light path, both of which are difficult to control in a microscope. Different, functionally equivalent implementations of FLBVI exist (Szmacinski et al. (1994) "Fluorescence lifetime imaging microscopy: homodyne technique using high- speed gated image intensifier." Methods

Enzymol, 240:723-48; Wang et al. (1992) Crit Rev Anal Chem, 23 (5): 369-395; Clegg et al. (2003) Methods Enzymol, 360:509-42; Theodoras et al (1993) Biophys. Chem. Volume 48, Issue 2, Dec.1993, pp. 221-239. )

FRAP (Reits andNeefjes (2001) Nat Cell Biol,Jwi;3(6) :E145-7) is a technique that reports on diffusion of fluorescently labeled biomolecules in living cells. In this technique, a high-power laser beam is used to photodestruct labeled biomolecules in a defined area of the cell. Diffusion (and transport) of molecules from neighboring non- illuminated areas can then repopulate the illuminated area, leading to a time-dependent recovery of fluorescence in this area. For the recovery kinetics, the diffusional recovery can be determined. In another implementation called fluorescence loss in photobleaching (FLIP), the high-power laser illuminates the same area in the cell for a longer period. Diffusionally connected areas in the cell, outside of the illuminated area will loose total fluorescence intensity due to continuous delivery and photodestruction in the illuminated area. FRAP and FLIP can be used to detect and follow the movements of calcifying nano- particles.

A recent implementation of FRAP called fluorescence localization after photobleaching (FLAP) (Dunn et al. (2002) J Microsc, Jan;205(Pt 1): 109-12) uses two spectrally separated fluorescently labeled forms of the same biomolecule where only one of the fluorescent species is photodestructed, either in the short-term FRAP or long-term FLIP mode. The non-destructed fluorescent species now acts as reference and diffusion/transport of the biomolecule can be assessed by simple division of the two fluorescent emission bands. The loss of the photodestructed species leads to a detectable change in the image ratio and provides, in addition to diffusional velocity parameters, information on the directionality of the diffusion/transport process. The same effect can be achieved when using photoconvertible or photoactivatable fluorescent protein tags (Zhang et al. (2002) Nat Rev MoI Cell Biol, Dec;3(12):906-18). This technique is particularly suited to detection of calcifying nano-particles. Specific Embodiments

Disclosed is a method for detecting calcifying nano-particles, the method comprising detecting calcifying nano-particles by detecting one or more proteins on the calcifying nano-particles.

Also disclosed is a method for detecting one or more proteins, the method comprising detecting one or more proteins on a calcifying nano-particle.

Also disclosed is a method of characterizing a calcifying nano-particle, the method comprising identifying one or more proteins on a calcifying nano-particle.

Also disclosed is a method of diagnosing a disease or condition, the method comprising identifying one or more proteins on a calcifying nano-particle from a subject, wherein the identified proteins identify a disease or condition with which calcifying nano- particles having the identified proteins are related or associated.

Also disclosed is a method of assessing the prognosis of a disease or condition, the method comprising identifying one or more proteins on a calcifying nano-particle from a subject, wherein the identified proteins identify calcifying nano-particles that are related to or associated with the prognosis of the disease or condition.

Also disclosed is a method of identifying a subject at risk of a disease or condition, the method comprising identifying one or more proteins on a calcifying nano-particle from a subject, wherein the identified proteins identify calcifying nano-particles that are related to or associated with a risk of developing a disease or condition.

Also disclosed is an isolated calcifying nano-particle, wherein the calcifying nano- particle comprises one or more of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CD14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CPvP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra- 1 , Jun B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I₅ Antithrombin, Protein S, BAFF on the calcifying nano- particle. In addition, binding proteins to the aforementioned protoein list can bind to the associated proteins. Proteins may or may not undergo a primary and/or secondary conformational change.

Also disclosed is a compositon comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating that has calcium binding proteins associated thereon and proteins that bind to said calcium binding proteins .

Also disclosed is a composition comprising a calcifying nano-particle where the calcifying nano-particle is covered in a hydroxy apatite (calcium phosphate mineral) coating containing bound calcium binding binding proteins that may experience conformational changes and wherein secondary bound proteins thereon experience conformational changes.

Also disclosed is a composition comprising a calcifying nano-particle and one or more compounds bound to one or more proteins on the calcifying nano-particle. Also disclosed is a method of determining the progress of treatment of a subj ect having calcifying nano-particles, the method comprising detecting one or more proteins on calcifying nano-particles in a sample from the subject, and repeating the detection in another sample from the subject following treatment, wherein a change in the level, amount, concentration, or a combination of calcifying nano-particles in the subject indicates the progress of the treatment of the subject.

Also disclosed herein are compositions comprising apatite and a coating material, where, for example, the coating material limits exposure of the blood of a subject when the composition is in a subject.

Also disclosed herein is a method of testing biocompatibility comprising testing blood coagulation in the absence of anticoagulants and a method of testing materials that will be exposed to circulating blood for formation of calcific biofilm formation.

The calcifying nano-particles can be detected by detecting one or more of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CD 14, Prothrombin, Factor IX, Fetuin B, CD40,

Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VTIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particles.

The calcifying nano-particles can be detected by detecting two or more proteins on the calcifying nano-particles. The calcifying nano-particles can be detected by detecting one or more proteins with a GLA-containing domain. The calcifying nano-particles can be detected by detecting one or more proteins with a calcium binding domain. The calcifying nano-particles can be captured, identified, or both prior to, simultaneous with, or following detection of one or more of the proteins. Capture or identification of the calcifying nano-particle can indicate that the detected proteins are on the calcifying nano- particles. The calcifying nano-particles can be captured by binding at least one compound to one or more of the proteins, wherein the compound is or becomes immobilized. The calcifying nano-particles can be identified by binding at least one compound to one or more of the proteins, wherein the calcifying nano-particles are separated based on the compound. The calcifying nano-particles can be separated by fluorescence activated sorting. One or more of the proteins can be detected by binding at least one compound to the protein and detecting the bound compound. Detection of two or more bound compounds can indicate that the proteins to which the compounds are bound are on the calcifying nano-particle. The two or more compounds can be detected in the same location or at the same time. At least one of the compounds can be an antibody, wherein the antibody is specific for the protein. The calcifying nano-particles can comprise calcium phosphate and one or more of the proteins.

The proteins can be detected by detecting any combination of 10 or fewer of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CD14, Prothrombin, Factor IX, Fetuin B, CD40,

Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin- 1, B2 microglobulin, CD 18, Laminin, Antitrypsin, Notch- 1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer, Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl , Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano-particle. The proteins can be detected by detecting any combination of 100 or fewer of the proteins. The proteins can be detected by detecting any combination of 5 or fewer of the proteins. The proteins can be detected by detecting any combination of 3 or fewer of the proteins. The combination of proteins can be detected in the same assay. The combination of proteins can be detected simultaneously. The combination of proteins can be detected on the same calcifying nano-particle. The combination of proteins can be detected on or within the same device.

The combination of proteins detected can constitute a pattern of proteins. The pattern can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination including but not limited to for example, heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque,

Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic

Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Schleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular

Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian

Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Mercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofilms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease. The pattern can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern can identify the type of calcifying nano-particles detected.

The proteins can be detected by detecting the presence or absence of any combination of 10 or fewer of the proteins selected from the group consisting of proteins Bovine CaBP-HA complex, Fetuin A, Calmodulin, Tissue Transglutaminase II, MMP-9, MMP-3, CD 42b, NF-kappa B, Osteopontin, Factor X/Xa, CD14, Prothrombin, Factor IX, Fetuin B, CD40, Myeloperoxidase, Fibronectin, Factor VII, Tissue factor, Human complement 5b-9, Human CRP, Matrix GLA protein, CD61, Kappa Light Chain, Macrophage Ll Protein, Factor XIIIA, hsp 60, Fibrillin-1, B2 microglobulin, CD 18,

Laminin, Antitrypsin, Notch-1, BSA, LBP, PTX3, Complement C5, Fibrinogen, D-Dimer Factor V, gamma-Gla residues, TF-VIIa, Complement 3c3, Complement C4, Antichymotrypsin, Annexin V, Lipid A, Isopeptide bond, Vitronectin, Thrombin, Osteocalcin, Troponin T, Vimentin, Tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, Kallikrein 6, Prothrombin Fl, Antithrombin III, Thrombin, Factor VIII, Heparan Sulphate, Factor XI, c-jun, Fra-2, Fra-1, Jim B, P-c- Jun, TGase3, alpha fetoprotein, Prostate Specific Antigen, erbB2, VEGF, alpha synuclein, Mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Tgase 2, Ubiquitin, TLR 4, Cathepsin D, GFAP, RAGE, CD 9, Prostate Acid Phosphatase, Smith Antigen, PRGP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C Macrophage Scavenger Receptor Type I, Antithrombin, Protein S, BAFF on the calcifying nano- particle. The pattern of the presence or absence of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The pattern of the presence or absence of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The pattern of the presence or absence of the proteins can identify the type of calcifying nano- particles detected. The presence of one or more of the proteins can indicate or identify a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The presence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The presence of one or more of the proteins can identify the type of calcifying nano-particles detected. The absence of one or more of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination. The absence of one or more of the proteins can indicate or identify a treatment to inhibit, remove or prevent the calcifying nano-particles. The absence of one or more of the proteins can identify the type of calcifying nano-particles detected.

The proteins can be detected using a microarray, coded beads, coated beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination.

The identified proteins can identify the type of calcifying nano-particle. The identified type of calcifying nano-particle can be related to or associated with a disease or condition. The identified proteins can identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated. The identified proteins can identify a disease or condition that is caused by calcifying nano- particles having the identified proteins. The identified proteins can identify a disease or condition in which calcifying nano-particles having the identified proteins are produced. Subjects in which pathological thrombosis can occur via apatite-mediated clotting are useful targets for the disclosed methods. Such subjects can include (1) Patients with vulnerable plaque rupture exposing atheroma calcification; (2) Patients undergoing angioplasty or heart-lung machine perfusion; (3) Patients with massive bone fractures or dislocated implants releasing potentially apatite particles; (4) Patients with implants, catheters, wires or stents subject to calcium encrustation; (5) Cancer patients with soft tissue calcification; and (6) Healthy or sick people with CNPs in their blood or positive calcification scores in arteries. Such people in the last category can be identified using the disclosed compositions and methods.

The composition can comprise a calcifying nano-particle and one or more compounds bound to two or more proteins on the calcifying nano-particle. The compound can comprise an antibody, wherein the antibody is specific for the protein. The compound can block the calcifying nano-particle.

Examples A. Example 1 In this example evidence is presented of host molecules involving two families of calcium binding Gla-proteins, calcification-defense system and clotting Gla-proteins, simultaneously binding to apatite surfaces and calcifying nano-particles. Thus, it was discovered that both Gla-systems participate in the body's calcification-defense by spatially blocking apatite surfaces. It was also realized that this creates a novel clotting mechanism. Thrombosis (the clotting of blood within an artery or vein) is a major cause of death and serious illness. Patients with circulatory, autoimmune and renal diseases, diabetes and cancers have abnormal ongoing coagulation often leading to thrombosis. However the principle clotting pathways, intrinsic and extrinsic, do not fully explain how or why thrombosis blocks blood vessels. It has been discovered that exposed calcium phosphate mineral surfaces (such as on calcifying nano-particles) simultaneously bind clotting and mineral-defense proteins creating a clotting mechanism that combines both intrinsic and extrinsic factors to the common factor X (FX) and prothrombin activation. This is the first direct proof of a link between calcification, which is widespread in disease, and pathological clotting. It was discovered that this novel physiological clotting mechanism can be activated when apatite is injected intravenously in vivo. A clotting test was developed to measure effects of various surfaces, including apatite and calcifying nano-particles (CNPs), on blood clotting in vitro. A multiplex surface antigen pattern test was also developed to demonstrate the pattern of clotting factors and their activators on the surface of CNPs isolated from human plasma and serum. This multiplex surface antigen pattern test is an example of the disclosed method for detecting calcifying nano- particles. The significance of this novel calcium mediated clotting mechanism is far- reaching since many diseases have a thrombotic component which may cause death. Clinical experience in cardiovascular medicine suggested that contact of blood with exposed calcified surface leads to thrombi (Halloran and Bekavac, Neuroimaging. 2004 Oct;14(4):385-7; Demer, Int. J. Epidemiol. 31, 737 (2002); Bini et al., Arterioscler. Tromb. Vase. Biol. 19, 1852 (1999); Lahey and Horton, Am J Kidney Dis. 40, 416 (2002)). Recent coronary artery calcification (CAC) scoring data supports that view, because positive CAC scores are a biomarker to predict future atherosclerotic thrombotic events, such as myocardial infarcts and strokes (Demer, Int. J. Epidemiol. 31, 737 (2002)). Many studies have also shown that patients with calcification-associated diseases such as atherosclerosis, kidney and autoimmune diseases, diabetes and cancer often have abnormal ongoing blood coagulation and thrombosis (Doherty et al., Endocrine Reviews 25, 629 (2004); Caine et al., Neoplasia 4, 465 (2002); Chambers and Laurent, Biochem.

Soc. Transact. 30, 194 (2002)). Yet, prior to the present discoveries, there was an absence of experimental studies that link calcification directly to thrombus formation. Current theories on blood clotting involve the binding of tissue factor to factor Vila to provide for an enzymatically active complex which then activates factors IX and X, leading to thrombin generation and clot formation (Banner et al., Nature 380, 41 (1996)). Injury that exposes tissue factor under the endothelium is the key activator resulting in production of factor Xa. Vitamin- K-dependent, gamma-carboxyglutamic acid (Gla)-containing domains of clotting proteins in this family are homologous and are responsible for phospholipid membrane association considered to be the substratum for clotting activation cascades (Nelsestuen, Trends Cardiovasc. Med. 9, 162 (1999)). Normal hemostasis results in platelet activation, aggregation and more thrombin generation (Dumas et al., Science 301, 222 (2003)) leading to a clot covering the damaged area. Clot growth is stopped by anticoagulation cascades activating inhibitors of clotting. Furthermore, factor Xa and thrombin are assumed to diffuse through the developing clot, filled with their specific inhibitors, to the surface of the growing clot. Formation of a large thrombus blocking a blood vessel is difficult to explain with this hypothesis, and has been experimentally shown to be insufficient (Hathcock and Nemerson, Blood 104, 123

(2004)). Therefore, other explanations have been sought, e.g. the existence of a small pool of circulating tissue factor, factor X, or thrombin, as microvesicles, has been proposed (Del Conde et al., Blood 106, 1604 (2005)).

Four clotting factors (Factor II, Factor VII, Factor IX, Factor X) acting as proteolytic executors of the clotting cascade are calcium-binding proteins also known to bind to apatite/calcium phosphate via their calcium binding GIa domains. The classical models imply that the Gla-domains undergo calcium dependent conformation changes before or concomitant with binding to phospholipid membrane. It was discovered that calcium phosphate surfaces serve the dual function as a suitable substratum (replacing phospholipid membrane) and as activators in normal and pathological blood clotting. The significance of this for human (patho)physiology is high because there are many situations where calcium phosphate minerals can have contact with blood/clotting factors: (1) Acutely during bone fracture, bone surgery, and dental surgery; (2) Artificially with the introduction of uncoated implants, fillers and apatite adjuvants; (3) Chronically with the growth of calcium phosphate deposits in atherosclerotic vessels, catastrophically with rupture of vulnerable plaque, and via cell death, exposing pathological calcification (e.g. Randall's plaque) and stones; (4) Hematologically with calcium phosphate macromolecular complexes with matrix Gla-protein and fetuin that were detected by Price in blood of animals suffering massive bone degradation (Price et al., J. Biol. Chem. 278, 22153 (2003))--Price (Price et al., J. Biol. Chem. 279, 1594 (2004)) showed that blood calcium phosphate macromolecular complexes lead to rapid arterial calcification in vivo; and (5) Systemically with calcifying nano-particles (CNPs), known until now as nanobacteria. CNPs have been found circulating in blood and implicated in pathological calcification (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. U S A. 95, 8274 (1998)). Although CNPs are controversial in their content and genetic characterization, critics and proponents alike agree that CNPs have a calcium phosphate mineral surface (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. U S A. 95, 8274 (1998); Cisar et al., Proc. Natl. Acad. Sci. U S A. 97, 11511 (2000); VaIi et al, Geochim. Cosmochim. Acta 65, 63 (2001); Miller et al., Am. J. Physiol. Heart Circ. Physiol. 287, Hl 115 (2004); Ciftcioglu et al., Kidney Int. 67, 483 (2005)). 1. Materials and Methods

L Preparation of Apatite and CNPs Hydroxyapatite was prepared according to Poser and Price (Poser and Price, J.

Biol. Chem. 254, 43 (1979)) using sterile solutions. Calcifying nano-particles (CNPs) were isolated from fetal bovine serum (FBS) obtained from several manufacturers (Seralab, UK; Gibco, Paisley, Scotland; HyClone, Logan, UT and Biological Industries, Israel) using methods described earlier (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. USA 95, 8274 (1998)). ii. Acute toxicity

Colloidal solutions of synthetic apatite (Poser and Price, J. Biol. Chem. 254, 43 (1979)) or CNPs in sterile phosphate buffered saline (PBS; 0.14M NaCl, 2.7 mM KCl, 8 mM Na₂HPO₄, 1.5 mM KH₂HPO₄, pH 7.4) were injected (at a dose of 0-50 μ\ wet pellet) into tail vein of Wistar rats. Rats were euthanized with phenobarbital 48 hours later and tissue samples were excised and placed to a fixative, 4 % paraformaldehyde, within 2 minutes from start of anesthesia. Tissues were processed to paraffin blocks, sectioned, deparaffmized and stained with H&E and with TUNEL assay for apoptotic changes with In situ Cell Death Detection Kit, AP (Roche) according to the manufacturer's instructions. Tissues were pretreated for TUNEL staining with 20 μg/ml proteinase K (Sigma, molecular biology grade) in 10 mM Tris/HCl, pH 7.4 for 15 min at room temperature. Apoptotic changes were evaluated with light microscopy. The method used detected apoptosis based on labeling of DNA strand-breaks using modified nucleotide labeling by terminal deoxynucleotidyl transferase visualized with enzymic reaction using Fast Red substrate (Roche). No changes were observed in control rats exposed to sterile PBS. The study was approved by the Ethics Committee of the University of Kuopio. iii. Thrombosis detection after i.v. injection of ^99mTc-labeled apatite or CNPs in rabbits

Biodistribution study data on ^99mTc-radiolabeled CNPs and apatite by Akerman et al. (Akerman et al., Proc. SPIE Int. Soc. Opt. Eng. 3111, 436 (1997)) was re-evaluated to detect thrombotic changes after i.v. injection. Dynamic imaging data (1 frame/minute) revealed thrombosis associated with radiolabeled material. Thrombus formation was observed in pulmonary artery on first pass through pulmonary circulation, and was Verified at autopsy at 48 hours. iv. Whole blood clotting slide test

Clotting induced by apatite was detected initially by using standard whole blood clotting time tube tests, with added glass beads, incubated at +37°C water bath with or without apatite. The clotting times were of the order of 2 minutes and did not allow precise evaluation of subtle changes by extraneous materials on clotting time due to need of sample preparation time, such as mixing the extraneous minerals. This could not be amended by using anti-coagulated blood samples (citrate or EDTA), reconstituted with 25 to 50 mM CaCl₂ at start of the test, because such samples clotted poorly indicating irreversible interference by the anticoagulant to some important player(s) in clotting.

A novel test platform was developed using glass slides (Menzel-Glaser, Braunschweig, Germany) incubated at room temperature. The method allows for measuring changes in the clotting time induced by contact with foreign surfaces, i.e. plain glass or coated glass, and for studying the effects of drugs on the clotting induced by foreign surface. Glass slides were coated with synthetic apatite (Poser and Price, J. Biol. Chem. 254, 43 (1979)) and controlled by TEM and EDX analysis (Kajander and giftcioglu, Proc. Natl. Acad. Sci. USA 95, 8274 (1998)). 250 μ\ of apatite colloidal suspension (10% pellet containing suspension) was pipetted to each slide, and slides were dried +37°C overnight. Commercial heat-fixed CNP-coated slides were obtained from Nanobac Oy, Kuopio, Finland. Plain glass slides without further processing were used as a foreign surface. Effect of Calcium EDTA, disodium EDTA, and clodronate on blood clotting time was investigated by adding 10 μl solution to a plain glass slide immediately before addition of blood. Calcium EDTA and disodium EDTA were from Fluka. Clodronate was a gift from Professor Jouko Vepsalainen (University of Kuopio).

Venous blood was collected with venipuncture from 19 random volunteers participating in CNP epidemiological study (Ethical Committee Approval, Kuopio University). Volunteers signed an informed consent. Blood was collected with venipuncture in siliconized glass serum tubes, EDTA plasma tubes or citrate plasma tubes (Terumo), and was tested immediately after collection for whole blood clotting time on different test platforms.

200 μl of freshly drawn blood was added to pre-coated or plain glass slides which were put on a tilting shaker 15 tilts/minute at room temperature until formation of a solid clot was observed as "frozen droplet". Experiments were carried out usually in triplicate to determine reproducibility of tests. CV% for the triplicate tests were less than 6.81% (CNP-coated slide, n = 13), 8.79% (apatite-coated slide, n = 15) and 10.37% (non-treated control slide, n = 15). Clotting time results were analyzed by Bonferroni (Dunn) t Test (Table 1). v. Proteomics on proteins bound to apatite particles Protein-free apatite particles in DMEM (Gibco) without any additives were suspended into 10% FBS-DMEM and were immediately centrifuged at 14 000 rpm, 30 rain at +4°C. The pellet was washed two times by suspending with sterile PBS followed by centrifugation at 13,200 rpm, 20 min at room temperature. Pellet was frozen prior to analysis. Proteomics analysis was provided by Protana, Montreal, Canada. The SDS- boiled samples were subjected to ID SDS-PAGE under reducing conditions. Protein bands were detected by Coomassie staining, excised and processed following standard procedures including: 1. The proteins in the gel plug were reduced with DTT.

2. The free cysteine residues were alkylated with iodoacetamide.

3. The proteins were digested with the endoprotease trypsin.

4. The peptides produced were extracted in neutral, acidic and basic conditions. vi. Mass Spectrometry Analysis The peptide mixtures were separated by C 18 reverse phase chromatography into a

Thermo-Finnigan LTQ-FT ion trap/FTICR hybrid mass spectrometer coupled with a nano- spray interface. The mass spectrometer was operated in data-dependent mode to obtain tandem (ms/ms) spectra of each peptide above an intensity threshold as it emerged from the chromatography column. The raw data files were processed using LCQ-DTA to generate peak lists of the tandem spectra. The processed data was searched with Mascot (Matrix Sciences, London UK) using the NCBI non-redundant database. The Mascot results were curated by mass spectrometry scientists to correlate the results with the raw data (Table 2). vii. Nanocapture and SAPIA ELISA Methods

Presence of CNPs was first detected with commercially available Nanocapture ELISA kit (Nanobac Oy). The test measures presence of CNPs in human serum or plasma, with a measurement range from 0 to 640 units (Pretorius et al., HIV Med. 5, 391 (2004)). The capture kit uses separate step-wise capture and detection reactions involving two monoclonal antibodies targeted on different surface epitopes on the CNPs.

Surface Antigen Pattern Immunoassay (SAPIA) test was developed to detect presence of multiple proteins on CNPs (Figures 1 A-IE). The SAPIA test here used specific commercial antibodies against designated targets (Table 3), in this case against clotting and anti-calcification Gla-proteins (Figure IA). SAPIA method was first tested using plasma and serum samples from 8 persons. Human plasma and serum samples were first tested to determine if they are comparable samples (Figure 2). Note that the results of positive sample shown are exceptionally high for clotting factors (Figure 2A). Based on the results obtained with these 8 samples, both serum and plasma samples could be used to test the specified parameters. Thereafter, a random panel (n = 16, each sample was combined from 1-5 human serum samples of similar CNP unit values to make up the necessary volume needed to run many tests, done in duplicate) with Nanocapture results ranging from 0-640 Units was selected for the SAPIA test.

SAPIA plates were made by coating high binding polystyrene ELISA plates (Coming, USA) with antibodies against anti-calcification proteins and GIa clotting factors and control antibodies. SAPIA was controlled by using antibodies against human serum albumin, D-Dimer, NF-κB and fibronectin as these proteins were not expected to be specifically bound on particle surface (Figure IA). Monoclonal antibodies were diluted at a final concentration of 1 μg/ml with IX PBS, pH 7.4, 100 μl/well to ELISA plates and incubated at +4°C overnight. Polyclonal antibodies were diluted to a concentration of 10 μg/ml and plates were coated as above. After coating procedure, plates were washed once with TBS-Tween 20 and blocked by adding TBS-Tween 20 300 μl/well and incubated 2 hours at room temperature. Thereafter, blocking solution was removed and storage solution 0.05% NaN₃-TBS was added 200 μl/well, and the plates were stored sealed with tape in a refrigerator.

Before use, storage solution was removed and plates were washed once with TBS- Tween. 50 μl/well of Assay Buffer (0.05 M Tris, 0.15 M NaCl, 0,05% Proclin 300, pH 7.5 with 1% mouse serum) was added in duplicates and 50 μl/well serum sample was added (Figure IB). Plate was sealed with tape and incubated 1 hour at room temperature with moderate shaking (Figure 1C). Plates were washed four times using TBS-T ween and detection antibody HRP-8D10 (Nanobac Oy) was added 100 μl/well. Plates were incubated 1 hour at room temperature with moderate shaking (Figure ID). Plates were washed four times using TBS-T ween and TMB substrate (Moss Inc., Pasadena, MD

21123) was added 100 μl/well. Plates were sealed and protected from light with foil and incubated 20 min at room temperature with moderate shaking (Figure IE). Absorbance at 630 nm was read with microplate reader (Biohit BP 808). Blank values were subtracted and unit values were calculated from standard curve of Nanocapture ELISA test using TableCurve 2D program (Systat, Point Richmond, CA). Pearson Correlation Coefficients (N=I 6, Prob > |r| under HO: Rho=0) were calculated (Tables 4 and 5). Anti-calcification proteins and coagulation GIa factors were found to be present in CNPs (Figures 3 and 4). viii. Activation of prothrombin by apatite in vitro Human prothrombin >95 % pure (Calbiochem) and two samples of bovine prothrombin >98 % pure (ICN, Aurora, OH and American Diagnostica, Stamford, CT) were diluted to a concentration of 10 μg/ml, 1 μg/ml and 0.1 μg/ml in 25 niM Tris, 150 mM NaCl and 5 mM CaCl₂, pH 7.4 (which is the substrate buffer for thrombin). 20 μl of prothrombin solution was mixed with 20 μl apatite (Poser and Price, J. Biol. Chem. 254, 43 (1979)) and incubated 30 minutes with moderate shaking at room temperature. As control reactions, prothrombins at above mentioned concentrations were incubated with buffer only. Thereafter, thrombin substrate Sar-Pro-Arg-pNA (Bachem, Bubendorf, Switzerland) 0.5 mg/ml (in substrate buffer solution, first solubilized in acetone) was added (100 μl) to all wells and plate was transferred to +37°C. Reaction was monitored with Elisa reader at 405 nm. Control absorbances were subtracted to produce data shown in Figure 5. No thrombin generation was found to take place in prothrombin wells without hydroxyapatite addition. ix. Thrombin and FXa activity measurements from SAPIA tests

Serum and plasma samples from 6 healthy volunteers were used for measurement of thrombin and FXa activity in particles captured with SAPIA using plates coated with antibodies against CNPs, thrombin and Factor XJXa. 50 μl of serum or plasma samples were pipetted onto plates and 50 μl of Assay Buffer (0.05 M Tris, 0.15 M NaCl, 0,05% Proclin 300, pH 7.5 with 1% mouse serum) was added. Plates were incubated 1 hour at room temperature with moderate shaking. Plates were washed 4 times, before 100 μl specific substrate was added. Three substrates were used for thrombin: Bx-Phe-Val-Arg- pNA HCl (Bachem), Sar-Pro-Arg-pNA (Bachem) and /33-Ala-Gly-Arg-pNA-acetate (Sigma, St. Louis, MI). One substrate was used for Factor Xa, CH₃ -D-CHA-GIy- Arg- pNA-AcOH (Sigma). Thrombin substrates Bx-Phe-Val-Arg-pNA HCl (0.136 mg/ml) and Sar-Pro-Arg-pNA (0.25 mg/ml) were in 25 mM Tris, 150 mM NaCl, 5 mM CaCI2, pH 7.4; and /3-Ala-Gly-Arg-pNA-acetate (1 mM) in 50 mM Tris, 100 mM NaCl, 5 mM CaCl₂, pH 7.4. Factor Xa substrate was CH₃ -D-CHA-Gly-Arg-pNA-AcOH (0.5 mM) in 50 mM Tris, 100 mM NaCl, 5 mM CaCl₂, pH 7.4. Plates were sealed with tape and parafϊlm to avoid evaporation and incubated at +37°C. Absorbance was measured at 405 nm using Microplate Reader (BP-808, Biohit). Measured sample values were compared to a standard curve made using thrombin from Terumo. Only thrombin substrate Sar-Pro- Arg-pNA gave weak positive results with serum samples after 18 hours incubation. The results did not correlate with the presence of CNPs, based upon Capture ELISA results.

Thrombin substrates Bx-Phe-Val-Arg-pNA HCl and /3-Ala-Gly-Arg-pNA-acetate failed to give positive signals. Factor Xa substrate CH₃ -D-CHA-GIy- Arg-pNA- AcOH gave weak positive results for serum samples after 18 hours incubation. Results did not correlate with the presence of CNPs. Thus, the results indicate only non-specific binding of thrombin and Factor Xa activity to ELISA plate which was present only in serum samples.

Therefore, the CNP-bound antigens must have been in an inactive form, as is expected in blood samples of healthy people. x. Immunohistochemical staining for antigen pattern analysis Paraffin-embedded arterial tissue blocks representing various forms of severe atherosclerotic lesions were obtained from commercial sources (Clinomics BioSciences, Inc., Pittsfield MA 01201. Tissue samples were collected from New York area and processed under Institutional Review Board permit). Thin sections were cut using standard techniques. Sections were deparaffinized without decalcification and stained with monoclonal antibodies for antigen pattern analysis mapping calcification defense proteins, clotting factors and CNPs. The staining protocol was tailored for each antibody,

TM see Table 3. Power Vision+ PoIy-HRP IHC kit (Irnrnuno Vision Technologies, Brisbane CA 94005) was used according to manufacturer's instructions. Color was developed using 3,3'-diaminobenzidine substrate. Sections were counterstained using Mayer's

Hematoxylin (Reagena, Siiilinjarvi, Finland), mounted and staining results were evaluated with light microscopy. Calcium deposits were stained with von Kossa staining. Dehydrated slides were immersed into 5% silver nitrate (BDH) solution for 1 hour under IOOW lamp. Slides were rinsed shortly with distilled water and further immersed into 5% sodium thiosulphate (Merck) for 2 minutes. Slides were washed three times with distilled water before staining with Kernetchrot solution (Reagena) for 5 minutes. Slides were rinsed with distilled water, dehydrated and mounted with Depex (BDH). Samples were microscoped with Nikon FXA microscope. Antigen patterns in soft plaque and hard plaque were compared. A specific pattern was observed that involved strongest intensity of staining in calcifications, followed by focal necrotic areas, and individual areas in media and intima layers. The pattern was comparable for all studied GIa protein antigens and CNPs. Patterns of Factor XIIIA and tissue factor showed a more universal presence, albeit also indicated accumulations of these antigens in the atherosclerotic lesions. Stainings carried out omitting primary antibody were negative. Calcification staining with von Kossa method matched with large macroscopic calcifications and some of the microscopic areas where CNP and GIa protein stainings revealed positivity. This can be interpreted to mean that although the tissue staining pattern was comparable, the sensitivity of von Kossa staining is inferior to immunostainings in detecting CNPs and nanoscopic calcifications. 2. Results

This example various forms of apatite were studied, including inorganic synthetic (Poser and Price, J. Biol. Chem. 254, 43 (1979)) and organic form built on calcifying nano-particles, referred to previously as nanobacteria (Kajander and Ciftcioglu, Proc. Natl. Acad. Sci. USA 95, 8274 (1998)). Hydroxyapatite formation includes several metastable calcium phosphate intermediate phases (NancoUas, Pure & Appl. Chem,l 1, 1673 (1992)). Brushite (dicalcium phosphate dihydrate) and octacalcium phosphate are considered initial phases that are transformed to hydroxyapatite, which is the most insoluble calcium phosphate mineral phase forming under neutral or basic conditions (Johnsson and Nancollas, Crit. Rev. Oral, Biol. Med. 3, 61 (1992)). Basic calcium phosphate (BCP) is a term that includes various calcium phosphate minerals, i.e. hydroxyapatite, carbonate- apatite, octacalcium phosphate and brushite. hi this example the general name apatite is used for the calcium phosphate mineral. Synthetic colloidal apatite was used as a control while performing acute toxicity studies for calcifying nano-particles (CNPs). Surprisingly, it was found that both iv injected apatite and CNPs caused ischemia-type tissue damage in the kidneys of rats. The pathognomic feature in ischemia-reperfusion kidney damage is that glomeruli are saved whereas tubuli die (Park et al., Am. J. Physiol. Renal Physiol. 282, F352 (2002)). The kidney damage was dose-dependent, and did not occur when two microliter or less apatite was injected. Control animals receiving only phosphate buffered saline (PBS) did not show histological changes in kidneys. There were also signs of thrombotic events in large blood vessels and cardiac chamber walls.

99m

To verify thrombotic events after iv injection, bio-distribution of Tc-labeled colloidal apatite and CNPs was reexamined by using Single Photon Emission Computed Tomography (SPECT) after iv-injection in rabbits (Akerman et al., Proc SPIE Int Soc Opt Eng 3111, 436 (1997)). Thrombosis was observed in left pulmonary artery starting within one minute of the injection and was stable and could still be detected 48 h after injection. i. How was thrombosis activated? Standard blood coagulation tests (e.g., activated partial thromboplastin time, prothrombin time) were inappropriate to measure calcium phosphate mineral surface- mediated clotting because those tests require use of anticoagulants, which would interact with an apatite surface. Counteracting the anticoagulants with high calcium chloride concentrations, as is required in the tests, creates non-physiological competition for binding between free calcium (tens of times higher than the physiological) and calcium phosphate surface. Furthermore, the apatite surface would be modified by a solution high in calcium, forming other forms of calcium minerals on the surface (e.g., octacalcium phosphate) (Boskey, J. Phys. Chem. 93, 1628 (1989)). Apatite is stable under physiological calcium and phosphate concentrations. Therefore, to study the effects of apatite on clotting, a whole blood clotting slide test was developed. In this test, plain objective glass, or objective glass coated with various forms of apatite, or test drugs, were used as test platforms. 200 μL of freshly collected human blood was applied on the slides, which were tilted ±30°, 15 tilts per minute, at room temperature. Clotting time was established at the time when droplet contents stopped moving. The test indicated that clotting was two times faster on apatite coating compared to the control slide. CNP coating also decreased clotting time significantly (Figure 6; Table 1). The method was controlled by using EDTA or citrate plasma samples, which never clotted, even when exposed to apatite coated test platforms. Calcium EDTA and a small concentration of the calcium binding drug etidronate did not affect the clotting time. Therefore the test appropriately measured clotting triggered by a foreign surface, glass. It was surprising that the apatite surface was superior at inducing clotting over the untreated glass, the traditionally used foreign surface in clotting tests. ii. How does apatite cause clotting?

Calcium is a major player throughout the clotting process. The extrinsic clotting pathway is activated by tissue factor, which is a 40 kD membrane-spanning protein expressed normally by almost all cells, except the endothelium. Endothelial damage exposes tissue factor, which binds and allosterically activates a serine protease, factor Vila (FVIIa), in the presence of calcium. This complex then proteolytically activates two serine protease zymogens, factor IX (FIX) and factor X (FX) (Banner et al, Nature 380, 41 (1996)), again in the presence of calcium, resulting in formation of factor Xa (FXa), which splits prothrombin to thrombin, again in the presence of calcium, which is the final coagulation executor proteolytically insolublizing fibrinogen as fibrin. The clot is further stabilized by cross-linking by factor XIIIa (FXIIIa) (activated by thrombin in the presence of calcium). The intrinsic pathway commences upon exposure to a foreign negatively charged surface, activating calcium-dependent conformational changes of clotting factors resulting in binding to a platelet or other phospholipid membrane, and leading to an activation-amplification cascade which eventually activates FX resulting in thrombin release.

Proteomics analysis revealed prothrombinase complex on apatite surface together with players of complement, antibodies and protease inhibitors. Although the use of serum to test clotting factors is not preferred, this proved the ability of apatite surface to bind clotting factors and provided information about what proteins can bind in biological situations, for instance on CNPs.

The same proteomics method was not preferred for CNPs because 1-D or 2 -D electrophoresis can not be run without extracting proteins from the particles, which is difficult. Difficulty in extracting proteins form CNPs indicates that the proteins on CNPs are cross-linked. Therefore, the surface protein patterns of CNPs were mapped using Surface Antigen Pattern Immuno- Assay (SAPIA; Figure 1), which is an example of a specific embodiment of the disclosed method of detecting proteins on calcifying nano- particles. In this technique specific antibodies directed against clotting and anti- mineralization proteins were used (the 5/2 capture antibody from the Nanocapture Elisa kit can be used to form the standard curve for any of the assays. The results can be used for calculation of algorithims for specificy disease diagnosis). SAPIA profiles of CNPs using plasma and serum samples were practically identical (Figure 3). These results indicated that serum samples can be used for the test. The results also indicated that particles with this specific antigen surface pattern can be isolated from human blood without any culturing steps. SAPIA results were stable after freeze-thawing, detergent (Tween20), EDTA or citrate application. Evidence was found that the detected proteins are cross- linked (very little protein released by SDS boiling). The stability of CNPs makes them amenable to surface antigen mapping with SAPIA technique which involves extended step-wise incubations separated by numerous washings before the detection. This feature of CNPs also allows the use of harsh treatments, when useful or desired, in other assays and detection methods.

SAPIA indicated that clotting factors V, VII, IX, X, tissue factor-FVIIa complex, fibrin, fibrinogen, FXIIIa, fragments of factor II, thrombin and prothrombin Fragment 1, but not prothrombin Fragment 2 are on CNPs (Tables 2 and 3; Figure 2). Both matrix

GLA-protein and osteocalcin were present on CNPs as well. The pattern of these factors was positively correlated with results using the Nanocapture kit with a high confidence level, indicating that the particles are composed of these surface antigens. SAPIA did not give positive results with capture antibodies specific for fibronectin (Figure 3) nor for human serum albumin, D-Dimer or NF-kB. The results prove that the particle surface contains players of the intrinsic and the extrinsic pathway (Table 2). Much of the CNP prothrombin has been activated to release thrombin and prothrombin Fragment 1. Prothrombin fragment 1 has 10 GIa residues whereas fragment 2 has none, which can explain why fragment 2 is released. However, it was surprising that the thrombin is retained in the particle. There may be mechanism(s) to retain it, such as crosslinking, or complex formation. For example, thrombin is known to make a complex with FXIII and fibrin (Aliens et al., Blood 100, 743 (2002)), which were also found on the particle. It was discovered that apatite binds clotting factors and their activators, concentrating them in close proximity, thus providing the necessary players for clotting on a suitable substratum (Figures 7-9). GIa residues in the GIa domain are known to bind to apatite. Free blood calcium completes the activation by binding to the rest of Gla-residues (Figure 8). Interaction of prothrombin with hydroxyapatite mineral has been shown by Romberg (Romberg et al., Arterioscler. Thromb. Vase. Biol. 18, 33 (1998)) to be comparable to anti-mineralization Gla-proteins. The clotting cascade has Gla-containing factors II, VII, IX, and X, and their levels have been linked to hypercoagulability and as risk factors for atherosclerosis and its thrombotic complications (Xu et al., Arterioscler. Thromb. Vase. Biol. 18, 33 (1998); Carlsson et al., Eur. J. Biochem 270, 2576 (2003)). Calcium phosphate, the key element in apatite, is a normal body constituent, therefore cannot be regarded as foreign surface that activates the intrinsic pathway of clotting. The key player in the extrinsic pathway, tissue factor, is not a calcium binding protein but might act as a player on the apatite after complex with FVIIa (Table 2; Figure 7). To find out whether particle-bound thrombin was active, chromogenic thrombin substrate incubations were made after capture of the CNPs. Very slight conversion of thrombin substrate was observed after 3 hours incubation at 20°C in the most positive samples, but this could have been due to other proteolytic activity on CNPs. Therefore, most if not all of particle immunologically detected thrombin must have been inactive, as was expected, because active thrombin would otherwise lead to dire consequences. The body has an efficient anti-thrombin system to inactivate the thrombin. SAPIA for detecting Anti-thrombin III gave only 2/16 high positive results (for the samples with the highest Nanocapture results). The test may have failed to detect less positive cases due to the use of an antibody that binds to an epitope known to block the thrombin-anti-thrombin complex formation, which means that its epitope was inside the inactive complex. Factor Xa activity chromogenic substrate test revealed no activity. This factor is also inactivated by anti-thrombin.

It was also tested whether non-enzymatic activation of thrombin could take place on apatite. The results presented in this example indicate that a tiny amount of thrombin activity, measurable with the chromogenic substrate, was generated on the apatite but not on the ELISA plate surface exposed with purified human or bovine prothrombin.

Using SAPIA, matrix Gla-protein and osteocalcin were identified on the CNPs. The presence of calcification-defense GIa proteins and blood clotting factors of the extrinsic and intrinsic pathways were identified on the same particle. To def ermine if the two classes of GIa proteins could be associated with calcification in atherosclerotic lesions in humans, immunohistochemical stainings on human atherosclerotic lesions were made. Immunohistochemical staining showed CNPs were concentrated in both soft plaque and overt calcifications or hard plaque areas. The same type of localization was found for several members of both GIa protein families. It is noteworthy that von Kossa staining could detect only large calcific areas whereas the CNPs were found as almost nanoscopic calcifications. 3. Discussion The results in this example show that apatite surfaces lead to rapid activation of the clotting cascade. Among other implications, this provides support for long-established clinical evidence suggesting that calcified lesions participate in formation of atherothrombi. It was proven that apatite surfaces simultaneously bind multiple GIa proteins, some of which are clotting proteins. This creates a platform for a clotting mechanism that combines both intrinsic and extrinsic factors to the common FX and prothrombin activation. This clotting mechanism is shown in Figures 7-9. The diagram depicts a novel platform, formation of complexes and activation of a clotting cascade on apatite surfaces. It was also shown that apatite itself can contribute to conformational changes leading to activation of prothrombin on apatite surfaces to release active thrombin. This non-enzymatic activation was much less rapid without the added clotting cascade players, yet proves the essential role that apatite plays. Prothrombin activation involves initial reactions with calcium, followed by a membrane prothrombinase complex formation leading to a thrombin release (Borowski et al, J. Biol. Chem. 261, 14969 (1986)). The players in this complex and their activators were shown in this example to be bound on apatite surfaces. It was also shown that the apatite-mediated clotting was twice as fast as clotting mediated by contact with a foreign surface, in this case glass, activating the intrinsic pathway.

The apatite-mediated clotting cascade, as with other clotting cascades, would have to be meticulously controlled by anti-thrombin, Protein S and C, heparin and other anti- clotting mechanisms and fibrinolytic systems to maintain a fine balance between activation and inhibition. Tissue factor found on CNPs shows that apatite particles can activate clotting using extrinsic pathway players. This process could be controlled by inhibitors, for example, by tissue factor inhibitor pathway (TFIP), which is likely since CNPs were not more active than apatite, which lacked the presence of the tissue factor. However, for the reasons shown above, processes required to control apatite-mediated clotting break down, leading to massive thrombosis.

This example shows for two forms of apatite that sudden circulatory exposure leads to thrombotic events, indicating that exposure of blood to apatite can have catastrophic results. Thrombosis was found when blood in a vessel was suddenly exposed to apatite pellet (colloidal) volume in excess of two microliters. Apatite exposure of this magnitude could take place as a consequence of, for example, bone fracture, rapture of vulnerable plaque revealing pathological vascular calcification, or in any situation where circulatory apatite particle counts would become locally high, for example, after rapture of a cyst filled with them.

Apatite-mediated clotting can have an important physiological function in bone physiology. Large bones have cancellous surface compartments with a diameter larger than largest blood vessels. Thus bone fracture often leads to clots up to 10 centimeters in diameter that must be made relatively rapidly to prevent the victim from bleeding to death. Exposed apatite could serve as the platform, providing booster power for clotting, since the hollow bone cannot reduce its diameter as damaged blood vessels do via vasoconstriction, and the bone has few tissue factor sources. Bone trabeculae are covered with only a monocellular layer, endostium, and the cortical bone has very low cell density (no subendothelial cells available with cell tissue factor carrying membranes as present in other tissues). It had not been clear how tissue factor-mediated clotting could take place in bone, but based on the results in this example it can be seen that the exposed bone could allow apatite-mediated clotting. Intriguingly, bone contains significant amounts of clotting GIa proteins. Those proteins are present at 1 - 2 % level of the non-collagen proteins in bone They could act with the bone Gla-protein osteocalcin, which was also found on CNPs, to control bone mineralization and/or provide protection against bleeding after bone fracture, where large areas of calcified surface are exposed. Gla-proteins are also found in kidney stones, suggesting a role in stone formation via both mineralization and thrombin production via thrombotic events or other mechanisms. Prothrombin Fl is the most common protein associated with kidney stones, and thrombin has been detected in urine in kidney diseases. Thrombogenic mechanisms have been proposed for kidney stone formation (Stoller et al., J. Urol. 171, 1920 (2004)). There is a very high incidence of calcifying nano-particles in disease processes known to be associated with calcification/thrombosis, for example, 97.5% associated with carotid stenosis, whereas only 10% association in Crohn's disease. Furthermore, the faster whole blood clotting time observed with calcium phosphate (bio)films supports the hypothesis from cardiology that rupture of unstable plaque endothelium exposing calcific plaque can cause clotting and lead to thrombosis and myocardial infarction or stroke. CNPs were shown to be present in atherosclerotic calcification and in soft plaque as nanoscopic calcific particles. This is consistent with a pathological role for any sized calcification in the vasculature. Calcification can be the driving force for atherothrombosis. The connection between apatite particles in the wrong part(s) of the body and inflammation and immunological activation has been shown (Morgan et al., Arthritis Rheum. 50, 1642 (2004); Nadra et al., Circ. Res. 96, 1248 (2005)).

Immunohistochemical stainings revealed the accumulation of clotting and anti- mineralization Gla-proteins on the CNPs. This evidence directly shows that GIa proteins have particular accumulations in atherosclerotic lesions associated with calcifications of all sizes. Thus, calcification is linked to both clotting factors and anti-mineralization Gla- proteins. Both clotting factors and anti-mineralization Gla-proteins have been separately shown to co-localize with calcification in atheromas and similar types of lesions (Bini et al., Arterioscler. Tromb. Vase. Biol. 19, 1852 (1999); Mullins et al., FASEB J. 14, 835 (2000); McKee Nature, but not in the same lesions prior to the results in this example.

Since CNPs are detectable just below the endothelium, they can contribute to thrombotic clotting together with the circulating CNPs when the endothelium lining is damaged. The results in this example indicate a role for an apatite-mediated clotting system in thrombotic events. Studies on thrombogenicity of biomaterials have examined heparin stabilized apatite, or heparinized animals. Since heparin is an anticoagulant, such studies do not reveal thrombotic potential adequately. Thus, biocompatible materials may not be hemocompatible. Apatite coated implants are widely used due to their bone biocompatibility. Many new medical applications for apatite have been proposed including drug delivery systems to blood, lung airways, or tissue; as a vaccine adjuvant; a vehicle for DNA transfer; and even as stent material for blood vessels. However, the effects of implants or injected apatite outside of bone and teeth have not been widely studied. Biocompatibility studies for calcium phosphate mineral particles or surfaces do nox seem to nave reported thrombotic events. Aoki et al reported vascular collapse as the cause of death in rats injected i.v. with colloidal apatite. Although Aoki reported severe hypoxia and elevation of infarct enzymes, above a threshold dose, the intravenous administration to humans was suggested to be feasible while using dosage less than LD50 for rats (Aoki et al., J. Mater. Sci. Mater. Med. 11, 67 (2000)). However, thrombi in rats injected with apatite i.v. were observed as descrubed in this example. Therefore, the biocompatibility of apatite, when exposed to circulation, is now seriously in question. This does not suggest that apatite use in implants should be discontinued, but rather that it must be separated from the blood in biocompatible ways with, for example resilient coatings, just as the body separates natural bone from blood via endostium. Thus, disclosed herein are compositions comprising apatite and a coating material, where, for example, the coating material limits exposure of the blood of a subject when the composition is in a subject.

The contrast between results in this example and apatite biocompatibility published earlier may be due to the ISO 10993-4. It requires the use of citrate or hirudin blood, or plasma and allows their application on implant materials while performing hemocompatibility testing (Seyfert et al., Biomolecular Engineering 19, 91 (2002)). The results in this example indicate that ISO 10993-4 required conditions cannot be used to detect blood clotting on apatite. The following improvements in biomaterial testing were devised: (1) Complementing ISO 10993-4 with tests for whole blood clotting in the absence of anticoagulants; and (2) Stents, catheters and materials exposed to circulation should repel calcific biofϊlm formation, because calcifying particles have been found to bind and coat such surfaces (Kajander et al., NASA/CP-2002-210786, 51 (2002)). Thus, disclosed herein is a method of testing biocompatibility comprising testing blood coagulation in the absence of anticoagulants and a method of testing materials that will be exposed to circulating blood for formation of calcific biofilm formation. Subjects in which pathological thrombosis can occur via apatite-mediated clotting are useful targets for these and other method disclosed herein. Such subject include (1) Patients with vulnerable plaque rupture exposing atheroma calcification; (2) Patients undergoing angioplasty or heart-lung machine perfusion; (3) Patients with massive bone fractures or dislocated implants releasing potentially apatite particles; (4) Patients with implants, catheters, wires or stents subject to calcium encrustation; (5) Cancer patients with soft tissue calcification; and (6) Healthy or sick people with CNPs in their blood or positive calcification scores in arteries. Such people in the last category can be identified using the disclosed compositions and methods.

This example describes a newly discovered pathophysiological mechanism linking pathological calcification to thrombosis. Blood anti-calcification Gla-proteins and GIa- clotting factor proteins were shown to bind to calcium phosphate surfaces creating a novel clotting mechanism capable of causing thrombosis where blood is in contact with apatite or CNPs. This was shown by detecting thrombosis after IV injections of apatite and CNPs in vivo in rats and rabbits, leading to thrombotic events, including ischemia- reperfusion damage. A whole blood coagulation slide test was developed to measure effects of various surfaces, including apatite and CNP, on blood clotting in vitro. Avid binding of Gla-clotting factors to apatite was detected by proteomics. A novel SAPIA test was developed to demonstrate the pattern of clotting factors and their activators on the surface of CNPs isolated from human plasma or serum. The apatite prothrombin interaction resulted in a small amount of thrombin activity detected by chromogenic substrate, despite the absence of other clotting factors. B. Example 2

The SAPIA method described in Example 1 was utilized to detect CNP components in 16 serum samples. Tables 11 and 12 illustrate the results of SAPIA testing. Table 11 shows raw absorbance data in the upper half of the table for 97 proteins and components measured in 16 human serum pools. The lower half illustrates units per ml. The pools were obtained by mixing the serum from 1-5 donors for each pool, pooled according to capture ELISA results that showed similar antigen levels.

The results show, with few exceptions, that each protein or component was detected on CNPs. Significant patterns are realized via intpretation of the data. Observations showed that certain proteins and/or components exhibit high and low values. Trends were realized and, for example in Table 11, different patterns are shown by anti- thrombin and anti-osteocalcin. At least 6-12 patterns are able to be visualized (qualitatively) by those skilled in the art.

Table 12 shows the statistical analysis as generated from the raw data of Table 11. The table shows correlation between the markers (100x100). Correlation coefficients greater than 0.5 indicate positive correlation (with low p values) and those values approaching 0.0 indicate a negative correlation. Therefore, statistical review via the generation of, for example, of box plots or scatter plots enables one skilled in the art to visualize data patterns that may be useful in the assessment, diagnosis, and therapeutic selection for certain diseases and/or conditions. Various algorithmic methods may be applied, for example, by multiplying, dividing, addition, or subtraction for various antigen values. These algorithms may be used in the diagnosis of diseases and/or conditions. Data may be further analyzed via more sophisticated techniques, for instance, cluster analysis, neural network, or multivariate loigistic regression techniques.

Cluster analysis is a multivariate statistical technique which assesses the similarities between units or assemblages, based on the occurrence or non-occurrence of specific artifact types or other components within them. Neural networks are a well-established technology for solving prediction and classification problems, using training and testing data to build a model. The data involves historical data sets containing input variables, or data fields, which correspond to an output. The network uses the training data to "learn" the solution to the problem by example. Since the network learns in this way, no complex models need to be created. Also, it is not necessary for your data to be complete or show a clear trend - neural networks can still converge to a solution under these conditions.

Logistic regression is part of a category of statistical models called generalized linear models. This broad class of models includes ordinary regression and ANOVA, as well as multivariate statistics such as ANCOVA and loglinear regression. An excellent treatment of generalized linear models is presented in Agresti (1996).

Logistic regression allows one to predict a discrete outcome, such as group membership, from a set of variables that maybe continuous, discrete, dichotomous, or a mix of any of these. Generally, the dependent or response variable is dichotomous, such as presence/absence or success/failure. Discriminant analysis is also used to predict group membership with only two groups. However, discriminant analysis can only be used with continuous independent variables. Thus, in instances where the independent variables are a categorical, or a mix of continuous and categorical, logistic regression is preferred.

These selected markers (biomarkers) are well known in the art to be indicative of or risk factors for disease. C. Example 3

Disease specific sera was obtained from Clinomics Bioscience Inc. for 15 diseases, n=40 per disease. Nano capture results are shown in Figures 11 and 13. The data indicated that CNPs were detectable in each disease, however at quite different percentages and levels. To understand the meaning of the biomarkers present in said CNPs, 10 samples showing the highest values for CNPs were selected for further analysis of biomarkers on the CNPs.

The data show clearly evident disease patterns easily recognized to the trained eyes of those skilled in the art. Especially prominent patterns were seen in prostatitis and prostate cancer. The establishment of these ratios and scatter graphs (see Figures 11 and 13 respectively) offer substantial improvements to the diagnosing of these diseases.

In prostate cancer and prostatitis, the most important biomarkers are the presence or absence or MHC-I, Macrophage Scavenger Receptor, Osteocalcin, PGRP-I, PSA₅ Aquaporin-4. The results may be better analyzed by comparison of specific marker values to the capture results. In prostate cancer, the ratio of marker Macrophage 1:1.5 to (or and approximate 30 fold difference) capture, whereas in prostatitis the ratio is 1:0.5.

Similarly, the ratio result (prostate cancer) MHC-I to capture is about 5% whereas the ratio in Prostatitis is almost 1.0 or a 20 fold difference. Significantly, Osteocalcin shows importance as either a presence and absence value as it is not present in Cancer.

For PGRP-I, the difference is approximately 0.15 in Prostate Cancer and 0.8 in prostatitis, meaning approximately 5.5 fold.

PSA shows a value of approximately 0.076 in Prostatitis and 0.03 in prostate cancer, or approximately 2 fold differences. This is a very small factor in favor of prostate cancer. In TG2 (labvision) the difference is .0009 in Prostatitis and approximately 0.15 in prostate cancer, a difference of approximately 166 fold.

For Aquaporin, values show 0.8 in Prostatitis and 0.05 in prostate cancer, approximately a 20 fold increase in prostatitis.

Therefore, levels of these different markers are very important in the diagnosis of disease. For example, analysis via custer analysis that may involved sophisticated methods such as multivariate logistic regression.

In Psammoma Endometrioid adenocarecenoma, the most important biomarkers that are present or absent are MHC-I, Cystatin A, osteocalcin, PGRP-I Beeta, PSA, Labvisoin TG-2, Aquaporin-4. Psammoma Endometrioid adenocarecenoma had 8 groups with extremely high calcification that may be, for instance, easily separated by the correlation of the presence or absence MSR and PGRP-I Beeta and Aquaporin-4. Notable is that some normal positive high value had high PSA. Therefore, disease specific marker tests results indicate that since the measurements were made using human blood samples different patterns of antigens on CNP may be explained only by assuming that those markers were bound on the surface of the CNP at the specific location of the pathological process. Therefore, these markers as associated with the CNP may be used to diagnose pathological processes, diseases, and ongoing processes leading to pathological problems (risk analysis and therapy follow up). This is due to the fact that different tissue and cells contain different (and the same) types of specific markers. It is well known that markers for diseases can be present YEARS before the onset of disease. Therefore these biomarkers can detectable prior to clinical diagnosis of disease and may be used as risk factor analysis or early detection of diseases including, but are not limited to, for example, heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Schleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1

Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Intercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofilms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease. D. Example 4

Evidence of various type of CNP

Biomarker patterns found indicate that various types of CNPs exist in the body of animal. The presence of different "types" has been verified by testing biodistribution in rats. Test results showed very different bio-distributions for the CNPs. It was determined that CNPs vary depending upon where they are harvested.

For example, CNPs taken from hosts and passage several times in various growth media, then injected into the tails of rats still showed specific characteristics depending upon original location of harvesting. Figure 12 shows the excretion in urine from a RAT. The excretion kinetics in the urine were very different. The most pronounced differentiation was shown with the Kindey stone isolate.

Table 8 is a list of some proteins that can be on CNPs. Table 9 is a list of proteins and compounds that can be associated with CNPs and proteins on CNPs. Table 10 shows calculated unit per ml data from 8 diseases using 14 markers and 10 patient samples for each disease. Table 11 shows the use of SAPIA technique to map Proteins associated with CNPS (Raw Data plus units per ml data). Table 12 shows a table on correlation on SAPIA results for various proteins and antigens on CNPs (coefficients and significances). Table 1. Bonferroni (Dunn) t Tests for Clotting Time

Difference Type Between Simultaneous 95% Comparison Means Confidence Limits

Clodrona- CaIEDTA 3.00 -134.38 140.38 Clodrona - Nontreat 38.68 -81.34 158.69 Clodrona - Nanobact 171.68 51.66 291.69 ***

Clodrona - Hydroxya 283.31 163.30 403.33 ***

CaIEDTA - Clodrona -3.00 -140.38 134.38 CaIEDTA - Nontreat 35.68 -84.34 155.69 CaIEDTA - Nanobact 168.68 48.66 288.69 ***

CaIEDTA - Hydroxya 280.31 160.30 400.33 ***

Nontreat - Clodrona -38.68 -158.69 81.34 Nontreat - CaIEDTA -35.68 -155.69 84.34 Nontreat - Nanobact 133.00 33.33 232.67 ***

Nontreat - Hydroxya 244.63 144.96 344.30 Nanobact - Clodrona -171.68 -291.69 -51.66 φ*φ

Nanobact - CaIEDTA -168.68 -288.69 -48.66 ***

Nanobact - Nontreat -133.00 -232.67 -33.33 H=**

Nanobact - Hydroxya 111.63 11.96 211.30 ***

Hydroxya - Clodrona -283.31 -403.33 -163.30 ***

Hydroxya - CaIEDTA -280.31 -400.33 -160.30 ***

Hydroxya - Nontreat -244.63 -344.30 -144.96 ***

Hydroxya - Nanobact -111.63 -211.30 -11.96 ***

Comparisons significant at the 0.05 level are indicated by ***. Table 2. Proteomic analysis of proteins on apatite particles briefly exposed to fetal bovine serum.

Protein name in the database %AA coverage Distinct Summed MS/MS Distinct

Search Score peptides

Serum albumin precursor 72 912.08 52

Apolipoprotein A-I precursor 52 321.51 18

Alpha- 1-antiproteinase precursor 39 261.59 14

IgGl heavy chain constant region 62 251.72 15

Alpha-2-HS-glycoprotein precursor 47 234.91 13

Vitamin K-dependent protein S precursor 22 221.73 13

Coagulation factor II 14 144.06 9

Endopin 1 27 131.14 8

Serotransferrin precursor 13 128.21 8

Anti-testosterone antibody 30 92.71 5

Hemoglobin alpha chain 22 78.07 5

Immunoglobulin light chain variable region 60 74.94 5

Hemoglobin beta fetal chain 30 73.16 4

Alpha-macroglobulin precursor 3 65.05 4

Ceruloplasmin 5 59.91 4

Inter-alpha-trypsin inhibitor H4 precursor 3 54.06 3

Beta-2-glycoprotein I 13 48.78 3

Immunoglobulin heavy chain constant region 10 48.58 3

C4b-binding protein alpha chain precursor 6 47.06 3

Vitronectin precursor 3 43.03 2

Ig lambda chain C region 18 33.32 2

Complement C3 precursor 1 32.27 2

IgG3 heavy chain constant region 5 28.10 2

Complement 9 2 21.00 1

Apolipoprotein A-II (antimicrobial peptide 21 21.00 1

BAMP-I)

Complement component C3 4 20.75 1

Coagulation factor V 0 19.47 1

RIKEN CDNA 2210010C04 4 19.14 1

Vitronectin precursor 2 16.83 1

Complement component 3 10 15.33 1

Alpha- 1-antichymotrypsin isoform pHHK12 3 14.65 1

Lipoprotein CIII 20 14.33 1

Adiponectin 6 13.71 1

Alpha-2-antiplasmin precursor 2 13.28 1 Table 3. List of antibodies used in the SAPIA test and immunohistochemical staining (IHS).

Antibody Supplier Clone Specificity Cross-reactivity ms Ref

Dilution α-prothrombin Biodesign 2A Human Not known 1:100 prothrombin, prethrombin 1 and fragment 2 α-prothrombin Cedarlane Affinity Fragment 1 region ND fragment 1 purified of human sheep prothrombin polyclonal α-thrombin Biodesign BDI905 Human thrombin Not known 1:100 α-Factor V American V237 Epitope on the Bovine factor V ND (20) Diagnostica light chain of and Va. human factor V. Binds to both factor V and factor Va. α-Factor VII USBiological 8.H.3 Human Factor VII, ND VHa, BFPRck Factor Vila α-Factor IX Biodesign 9D Human Factor IX Not known. 1:500 α-Factor X/Xa R&D Systems 156106 Human Factor X 1:100 and Xa. α-Factor XIIIA Labvision AC-IAl Human Factor Not known 1:100

XIΠA α-TF Calbiochem TF9- Human TF epitope 1:1000 (21) 10H10 locus I.

Recognized native, non-reduced and reduced human TF. α-TF-Vϋa American TF8-5G9 Human non- Not known ND (21).

Diagnostica reduced native TF and TF-VIIa complex. α-Fibrin(ogen) American Fl 3 Human fibrinogen No reactivity ND Diagnostica fragments D & for human DD, α, β, γ chains, fibrinogen early plasmin fragment E digestion fragments of fibrinogen α-chain α-Matrix GIa Alexis 52.1C5D Human Rat l:500^a (22)

Biochemicals carboxylated and carboxylated non-carboxylated and non- matrix GIa protein carboxylated matrix GIa protein α-Osteocalcin Biodesign OCl Human/bovine Not known 1:51 (23) osteocalcin α-Fibronectin Labvision TV-I Human Pig, mouse and ND fibronectin. rat fibronectin. α-Human Biodesign 15C7 Human serum Not known. ND serum albumin albumin.

α-D-Dimer American DD- Human D-Dimer No cross ND Diagnostica 3B6/22 and cross-linked reactivity with fibrin derivatives human (DD-E). fibrinogen or fibrinogen degradation products.

CC-NF-KB ρ65 Labvision Rabbit Human Internal Rat and rabbit ND polyclonal domain of NF-κB Internal domain p65 of NF-KB p65 α-CNPs Nanobac Oy 8D10 Human CNPs Bovine CNPs 1:2° (2)

ND = not done ^a = pretreated by heating in microwave in 0.2% citric acid pH 6.0 for 15 minutes. Cooled at room temperature 15 minutes followed by washing three times with PBS. ^b = pretreated by heating in microwave in 0.01 M citric acid pH 6.0 for 20 minutes. Cooled at room temperature 1 h.

⁰ = culture supernatant

ATTORNEY DOCKET NO. 14151.0001P1

Table 4. Correlation between SAPIA and Nanocapture Elisa results. Pearson Correlation Coefficients (N = 16 Prob > |r| under HO: Rho=0) indicate presence of all clotting Gla-proteins and matrix-Gla protein in CNPs. Correlation coefficients are given,/? values in italics.

Capture a-FX/Xa a-FIX a-FVII a-mGLA p. a-FXIIIa a-fibrinogen a-FV a-TF-VIIa

Capture 1 0,62185 0,57671 0,67705 0,88105 0,61302 0,69009 0,59148 0,88746

0,0101 0,0194 0,0040 <,0001 0,0116 0,0031 0,0158 <,0001 a-FX/Xa 0,62185 1,00000 0,99729 0,98883 0,60706 0,97139 0,96756 0,99848 0,83422

0,0101 <,0001 <,0001 0,0126 <,0001 <,0001 <,0001 <,0001

a-FIX 0,57671 0,99729 1,00000 0,98139 0,58712 0,97522 0,96202 0,99792 0,81505

0,0194 <,0001 <,0001 0,0168 <,0001 <,0001 <,0001 0,0001 a-FVII 0,67705 0,98883 0,98139 1,00000 0,65116 0,97890 0,98065 0,98502 0,86068

0,0040 <,0001 <,0001 0,0063 <,0001 <,0001 <,0001 <,0001 a-mGLA p. 0,88105 0,60706 0,58712 0,65116 1,00000 0,64331 0,67566 0,57268 0,92621

<,0001 0,0126 0,0168 0,0063 0,0072 0,0041 0,0204 <,0001 a-FXIIIa 0,61302 0,97139 0,97522 0,97890 0,64331 1,00000 0,98412 0,97309 0,84151

0,0116 <,0001 <,0001 <,0001 0,0072 <,0001 <,0001 <,0001

a-fϊbrinogen 0,69009 0,96756 0,96202 0,98065 0,67566 0,98412 1,00000 0,96519 0,87082

0,0031 <,0001 <,0001 <,0001 0,0041 <,0001 <,0001 <,0001

a-FV 0,59148 0,99848 0,99792 0,98502 0,57268 0,97309 0,96519 1,00000 0,81100

0,0158 <,0001 <,0001 <,0001 0,0204 <,0001 <,0001 0,0001

a-TF-VIIa 0,88746 0,83422 0,81505 0,86068 96 0,92621 0,84151 0,87082 0,81100 1,00000

<,0001 <,0001 0,0001 <,0001 <,0001 <,0001 <,0001 0,0001

ATTORIsIEY DOCKET NO. 14151.0001P1

Table 5. Correlation for prothrombin fragments and osteocalcin in SAPIA and Nanocapture Elisa results. Pearson Correlation Coefficients (N = 16, Prob > |r[ under HO: Rho=0) indicate presence of prothrombin fragments, including thrombin, and osteocalcin in CNPs. Correlation coefficients are given,/? values in italics.

Capture a-Thrombin a-Prothr. Frag.l a-Prothr. Frag.2 a-Osteocalcin

i. Capture 1,00000 0,94414 0,66731 0,70832 0,72244 <,0001 0,0047 0,0021 0,0016

a-Thrombin 0,94414 1,00000 0,58615 0,74985 0,56848 <,0001 0,0170 0,0008 0,0216

a-Prothr. Frag.l 0,66731 0,58615 1,00000 0,38848 0,66931 0,0047 0,0170 0,1370 0,0046 a-Prothr. Frag.2 0,70832 0,74985 0,38848 1,00000 0,51525 0,0021 0,0008 0,1370 0,0411 a-Osteocalcin 0,72244 0,56848 0,66931 0,51525 1,00000 0,0016 0,0216 0,0046 0,0411

ATTORNEYDOCKETNO.14151.0001P1

Table 6. List of Antibodies.

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ATTORNEYDOCKETNO.14151.0001P1

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Table 7. Marker-Disease Correlations

Ill

Testican-3 precursor (SPARC/osteonectin, CWCV, and Kazal-like domains

TIC3 HUMAN (Q9BQ16) proteoglycan 3). {GENE: Name=SPOCK3; Synonyms=TICN3; ORFNames=UNQ409/PRO771} - Homo sapiens (Human)

Thrombomodulin precursor (TM) (Fetomodulin) (CD141 antigen). {GENE:

TRBM HUMAN (P07204) Name=THBD; Synonyms=THRM} - Homo sapiens (Human)

Uromodulin precursor (Tamm-Horsfall urinary glycoprotein) (THP). {GENE:

UROM HUMAN (P07911) Name=UMOD} - Homo sapiens (Human)

Visinin-like protein 1 (VILIP) (Hippocalcin-like protein 3) (HLP3). {GENE:

VISL1 HUMAN (P62760) Name=VSNL1 ; Synonyms=VISL1} - Homo sapiens (Human)

Table 9: Proteins that bind to Calcium Binding Proteins (CaBP-BP 's)

Myeloperoxidase

FIBRONECTIN

BSA

LBP

COMPLEMENT C5

Human gamma GIa

Annexin

gamma-carboxy glutamate

ATTORNEYDOCKETNO.14151.0001P1

90 Table 10

O O Cholecystitis

H U

O O r-- o

O O

O

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90 IΛ rr

O O rs Cholecystitis

U

O O

(-- (--

O O

O

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Kidney Stones

O O o

O O

O

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ft

O O Kidney Stones hi U

O O

O l~-

O O

O

ATTORNEY DOCKET NO. 14151.0001P1

90

5 Psommoma Endometrioid adenocarcinoma

O O

CΛ Macrophage Abeam

U scavenger Kallikrein Alpha- Troponin Transglutaminase

Capture MHC-I receptor Cystatin A 6 synuclein Osteonectin Osteocalcin C 2

Nan-04-289 511.902 640.000 39.515 26.824 1.954 45.569 0.808 3.206 1.211 0.093

Nan-04-290 482.080 640.000 49.795 24.256 2.880 43.601 1.459 3.842 1.490 0.187

Nan-04-291 477.375 640.000 46.383 23.139 2.880 39.601 1.273 3.842 1.304 0.466

Nan-04-292 394.152 640.000 44.134 23.913 2.418 37.551 0.994 3.630 1.211 0.093

Nan-04-293 470.192 640.000 45.208 25.456 2.880 43.601 2.387 3.206 1.490 0.839

Nan-04-294 343.062 640.000 40.458 25.798 1.954 43.247 1.087 3.206 1.118 1.118

Nan-04-295 482.237 640.000 76.910 28.189 1.304 46.656 1.459 3.630 0.653 0.373

Nan-04-296 413.482 640.000 48.215 29.382 0.932 42.018 0.901 2.352 0.932 0.093

Nan-04-315 14.989 0.200 11.784 5.908 0.653 14.396 0.435 0.191 0.093 0.093

Nan-04-316 14.936 0.107 13.005 2.973 0.093 10.908 0.342 0.000 0.000 0.000

Mean 360.441 512.031 41.541 21.584 1.795 36.715 1.114 2.710 0.950 0.336

SD 188.930 269.783 18.596 9.260 1.009 12.979 0.586 1.446 0.537 0.373

O Median 441.837 640.000 44.671 24.856 1.954 42.633 1.040 3.206 1.165 0.140 O

O O

O

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ft

O O

hi

U

Psommoma Endometrioid adenocarcinoma

Labvision Aquaporin-

Capture PGRP-1 Beeta PSA Tgase 2 4

Nan-04-289 511.902 640.000 46.261 0.000 640.000

Nan-04-290 482.080 640.000 42.206 4.921 640.000

Nan-04-291 477.375 640.000 41.984 2.806

Nan-04-292 394.152 640.000 40.658 0.871 640.000

Nan-04-293 470.192 640.000 43.546 0.871 640.000

Nan-04-294 343.062 640.000 43.434 8.645 640.000

Nan-04-295 482.237 640.000 44.898 7.209

Nan-04-296 413.482 640.000 41.984 0.218 640.000

Nan-04-315 14.989 1.950 0.036 4.712 0.000

Nan-04-316 14.936 0.000 0.036 2.593 0.000

O O

O l~-

O O Mean 360.441 512.195 34.504 3.285 480.000

O SD 188.930 269.437 18.236 3.007 296.262

Median 441.837 640.000 42.095 2.700 640.000

ATTORNEYDOCKETNO.14151.0001P1

90

Prostate cancer

O O

U

O O

O

O O

O

ATTORNEYDOCKETNO.14151.0001P1

90 IΛ rr

O O rs

U

Prostate cancer

o

O

(--

O O

O

ATTORNEY DOCKET NO. 14151.0001P1

90

5 Prostatitis

O O

CΛ

U

O O

O O

O

ATTORNEY DOCKET NO. 14151.0001P1

90

O O

U a.

Prostatitis

O O

O

ATTORNEYDOCKETNO.14151.0001P1

so

Rheumatoid

1*1

S3

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O

ATTORNEYDOCKETNO.14151.0001P1

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O O

U a. Rheumatoid arthritis

O O

O

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Aortic valve stenosis

O O r--

o

O O

O

ATTORNEYDOCKET NO. 14151.0001P1

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O

Aortic valve stenosis

H u eh

O O r-- o

O O

O

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Parkinsons

O

O t~

O r-- o

O

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90

SM Parkinsons

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Table 11. Use of SAPIA Technique to map proteins assocatied with CNPs (raw data plus units per ml data)

Capture Time DATA: Summary table of Data by MARKERS

Variable Label

Capture varl anti-Fetuin A var2 anti-calmodulin var3 anti-Tgase II var4 anti-MMP-9 var5 anti-MMP-3 var6 anti-CD 42b var7 NF-kappa B var8 anti-osteopontin var9 anti-Factor X/Xa varlO anti CD14 varll anti-prothrombin varl2 anti-Factor IX varl3 anti-Fetuin B varl4 anti-CD40 varl5 anti-myeloperoxidase varl6 vanti-Fibronectin varl7 anti-Factor VII varl8 anti-tissue factor varl9 anti-human complement 5b-9 var20 anti-human CRP var21 anti-matrix GLA var22 anti-CD61 var23 anti-Kappa Light Chain var24 anti-Macrophage var25 anti-factor XIIIA var26 anti-hsp 60 var27 anti-fibrillin-1 var28 anti-B2 microgl var29 anti-CD 18 var30 anti-laminin var31 anti-antitrypsin var32 anti-Notch-1 var33 anti-BSA var34 anti-LBP var35 anti-PTX3 var36 anti-complement C5 var37 anti-fibrinogen var38 anti-D-Dimer var39 anti-factor V var40 anti-human gamma-Gla var41 anti-TF-VIIa var42 anti-complement C3c var43 anti-Complement C4 var44 anti-antichymotrypsin var45 anti-Annexin V var46 anti-Lipid A var47 anti-isopeptide bond var48 anti-vitronectin var49 anti-thrombin var50 anti-osteocalcin var51 anti-Troponin T var52 anti-vimentin var53 a-tropomyosin var54 anti-HSA var55 Troponin I cardiac var56 anti-Apo Al var57 MHC class I var58 Amyloid P protein var59 anti-sCD40 L var60 anti-kallikrein var61 Anti-Prothr Fl var62 goat-ATIII var63 anti-Thrombin var64 anti-Factor VIII var65 anti-heparan Sulph var6S anti-Factor XI var67 anti-c-jun var68 anti-Fra-2 var69 anti-Fra-1 var70 anti-Jun B var71 anti-P-c-Jun var72 anti-TGase3 var73 anti-alpha fetoprotein var74 anti-PSA var75 anti-erbB2 var76 anti-VEGF var77 anti-alpha synuclein var78 anti-mucin-1 var79 anti-Cystatin A var80 anti-Cystatin S var81 Prostein var82 Aquaporin 4 var83 Trypsin var84 Osteonectin var85 RAGE var86 PGRP-I Beeta var87 PGRP-S var88 Gram positive bacteria var89 Troponin C Cardiac var90 Protein C var91 Macrophage Scavenger Receptor Type I var92 anti-anti-Thrombin var93 Protein S var94 BAFP

(Continued)

(Continued)

_ - - - Var52 16.00 4.06 0.00 34.41 0.00 0.00 4.08

Var53 IS. OO 1.04 0.00 9.61 0.00 0.00 0.00

Var54 16.00 0.54 0.00 5.03 0.00 0.00 0.00

VarS5 16.00 0.21 0.00 1.22 0.00 0.00 0.00

Var5S 16.00 14.45 0.00 125.7 0.00 0.00 0.S7

Var5₇ 16.00|202.7 0.58 640.0 17.66 115.5 319.7

VarΞ8 16.00 4.28 0.10 8. SS 1.96 3.52 7.22

VarS9 16.00 23.01 0.12 110.2 1.33 6.61 32.00

Var6 16.00 65.25 1.03 156.5|l8.50 66.58 108.7

Var60 16.00 14.93 0.00 125.7 0.04 0.59 3.32

Varδl 16.00 10.00 0.00 80.84 0.00 0.49 7.68

Var62 16.00 10.27 0.00 49.02 1.19 3.33 11.75

(Continued)

values

Medi¬

N Mean Min Max Ql an Q3 markers

Var63 16.00 117.2 0.48 640.0 15.40 77.92 148.7

Var64 16.00 1.38 0.00 17.44 0.00 0.00 0.39

Var65 16.00|22.85 0.00 113.8 1.70 10.14 39.35

Var66 16.00 15.36 0.00 100.3 0.64 3.97 16.72

Var67 16.00 0.86 0.00 3.10 0.32 0.57 0.98

Var68 16.00 0.98 0.20 2.22 0.66 1.01 1.21

Var69 16.00 0.46 0.00 3.54 0.15 0.30 0.35

Var7 16.00 0.27 0.00 2.70 0.00 0.00 0.02

Var70 16.00 2.70 0.00 7.07 0.66 2.07 4.90

Var71 16.00 9.47 0.25 28.37 1.06 7.68 16.21

Var72 16.00 1.34 0.00 5.05 0.35 0.96 2.07

__ __ Var73 16.00 0.00 0.00 0.00 0.00 0.00 0.00

Var74 16.00 43.54 0.03|l03.9 12.06|40.71 76.21 _ _ __ Var75 16.00 3.80 0.00 11.18 0.96 3.09 5.60

Var76 16.00 5.63 0.00|l6.46 1.22 4.71 8.47

Var77 16.00 39.21 1.89 80.77 16.3l|38.95 64.15

Var78 16.00 0.79 0.00 4.47 0.06 0.11 0.76

Var79 16.00 10.32 0.00 34.51 2.40 10.54 16.56

Var8 16.00 0.93 0.00 3.56 0.00 0.68 1.54 Var80 16.00 9.41 0.00|22.97 1.98 8.50 15.98| I 1

(Continued) __ _ l values

__ _ _ _ _

Medi¬

N Mean Min Max Ql an Q3 markers

__ _ __ _ __ Var81 12.00 0.63 0.00 2.84 0.26 0.36 0.80

Var82 12.00 153.8 0.94 640.0 8.84 65.15 208.2

Var83 12.00 105.8 0.51 529.4 8.37 44.11 106.6

I

Var84 12.00 22.14 0.07 239.8 0.29 1.21 2.50

Var85 12.00 3.58 0.00 12.18 0.42 2.57 5.01

Var86 16.00 302.7 0.47 640.0 17.40 127.1 640.0

Var87 14.00 250.0 0.00 640.0 11.14 83.15 574.3

I

Var88 14.00 0.36 0.00 2.92 0.00 0.05 0.32

Var89 14.00 27.09 0.00|241.9 0.00 0.87 6.52

Var9 16.00 12.07 0.00 124.1 0.00 1.97 6.80

Var90 14.00 0.16 0.00 1.91 0.00 0.00 0.00

Var91 14.00 27.05 1.4B|l52.3 3.32 14.78 27.53

Var92 IS.00 7.81 0.00 50.66 0.00 1.49 7.46

Var93 16.00 1.47 0.00|20.10 0.00 0.00 0.40

Var94 16.00 0.00 0.00 0.00 0.00 0.00 0.00

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Capture 16 253.06400 217.10056 4049 0 640.00000 varl 16 42.39131 36.97189 678.26100 1.17000 130.51800 var2 16 2.87156 5.25100 45.94500 0.08500 21.84000 var3 16 6.87844 14.85900 110.05500 0.34200 60.35300 var4 16 5.62819 12.59201 90.05100 0 51.61700 var5 16 0.89450 1.04024 14.31200 0 3.13200 var6 16 65.25106 50.53021 1044 1.02700 156.47900 var7 16 0.26788 0.73790 4.28600 0 2.70200 var8 16 0.93481 1.12028 14.95700 0 3.56300 var9 16 12.06594 30.70712 193.05500 0 124.10700 varlO 16 4.57550 11.25589 ' 73.20800 0 45.74200 varll 16 0.91200 1.57184 14.59200 0 4.72800 varl2 16 11.52425 30.57534 184.38800 0 124.50100 varl3 16 57.37475 64.84223 917.99600 0.25600 253.52800 varl4 16 0.20106 0.58191 3.21700 0 2.32400 varl5 16 2.74681 2.10943 43.94900 0.32100 9.43600 varl6 16 7.23081 12.24811 115.69300 0.06400 48.90700 varl7 16 8.48956 14.43197 135.83300 0.83000 59.36700 varl8 16 6.82150 14.44434 109.14400 0 58.26500 varl9 16 0.69163 2.22119 11.06600 0 8.90200 var20 16 0.77719 2.28338 12.43500 0 8.51500 var21 16 126.07219 108.26025 2017 2.92400 342.73900 var22 16 4.26063 5.96719 68.17000 0 22.51500 var23 16 1.63538 1.71553 26.16600 O 6.59400 var24 IS 3.62650 4.37522 58.02400 0.06400 17.94700 var25 16 1.72625 3.28336 27.62000 O 13.38700 var26 16 1.54344 2.50923 24.69500 O 10.29700 var27 16 4.08681 8.85404 65.38900 0.07100 36.23900 var28 16 O .76188 1.09194 12.19000 O 2.82900 var29 16 1.86238 4.14488 29.79800 0.04600 16.69300 var30 16 0.68919 1.17260 11.02700 O 4.59700 var31 16 0.64381 0.87088 10.30100 O 3.49800 var32 16 5.45506 4.48899 87.28100 O 12.28800 var33 16 11.60594 25.43922 185.59500 0.29600 101.52500 var34 16 4.93469 13.56550 78.95500 O 52.46400 var35 16 0.01056 0.02338 0.16900 O 0.07000 var3S 16 0.36519 1.07551 5.84300 O 4.35900 var37 16 4.64031 7.83236 74.24500 O 31.41500 var38 16 O .11931 0.30392 1.90900 O 1.10900 var39 16 7.39944 19.88615 118.39100 O 80.24500 var40 16 0.74363 1.43253 11.89800 O 4.43100 var41 16 20.46100 21.12955 327.37600 O 80.53500 var42 16 0.34069 0.68747 5.45100 O 2.67800 var43 16 0.33200 0.99070 5.31200 O 3.88600 var45 16 0.32513 0.68749 5.20200 O 2.02500 var46 16 0.51231 0.72217 8.19700 O 2.92600 var47 16 0.41181 0.46771 6.58900 O 1.69300 var48 16 4.27238 3.81834 68.35800 0.21700 13.13000 var49 16 274.29412 260.86792 4389 1.88300 640.00000 var50 16 85.43369 197.39999 1367 O 602.03800 var51 16 6.01763 6.88874 96.28200 O 26.83800 var52 16 4.05869 8.84811 64.93900 O 34.40900 var53 16 1.03713 2.58091 16.59400 O 9.61100 var54 16 0.54319 1.45735 8.69100 O 5.02500 var55 16 0.20763 0.44867 3.32200 O 1.22200 var5S 16 14.45100 38.87846 231.21600 O 125.71300 var57 16 202.73894 238.71781 3244 0.58400 640.00000 var58 16 4.27713 2.96205 68.43400 0.09700 8.64500 var59 16 23.00694 34.06665 368.11100 0.12000 110.20800 var60 16 14.93225 38.02049 238.91600 O 125.74400 var61 16 10.00131 22.36333 160.02100 O 80.84200 var62 16 10.27450 14.95231 164.39200 O 49.02000 var63 16 117.18013 158.07018 1875 0.48100 640.00000 var64 16 1.38181 4.33492 22.10900 O 17.44400 var65 16 22.85213 30.42459 365.63400 O 113.78900 var66 16 15.36038 26.24358 245.76600 O 100.25900 var67 16 0.86044 0.91891 13.76700 O 3.09800 var68 16 0.98475 0.50500 15.75600 0.20200 2.22200 var69 16 0.46081 0.83284 7.37300 O 3.53500 var70 16 2.69563 2.28526 43.13000 O 7.07100 var71 16 9.46619 9.10550 151.45900 0.25300 28.36700 var72 ■ 16 1.34463 1.29190 21.51400 O 5.05100 var74 16 43.54356 34.96082 696.69700 0.02500 103.90400 var75 16 3.80356 3.51674 60.85700 O 11.17900 var76 16 5.63056 5.29653 90.08900 O 16.45900 var77 16 39.21356 27.55760 627.41700 1.89300 80.76600 var78 16 0.78650 1.32865 12.58400 O 4.46600 var79 16 10.31588 9.45851 165.05400 O 34.50600 var80 16 9.41475 8.02499 150.63600 O 22.97200 varδl 13 0.78431 0.90546 10.19600 O 2.84200 var82 13 191.17715 242.13190 2485 0.94300 640.00000 var83 13 146.36031 210.81152 1903 0.50900 633.40600 var84 13 38.64208 88.67047 502.34700 0.07300 239.77100 var85 13 4.07300 4.12665 52.94900 O 12.17500 var86 16 302.69400 307.07168 4843 0.46800 640.00000 var87 15 237.47640 265.70065 3562 O 640.00000 var88 15 0.33900 0.75763 5.08500 O 2.92300 var89 15 25.40413 66.59440 381.06200 O 241.92100 var90 15 0.18747 0.50593 2.81200 O 1.91100 var91 15 27.10693 38.25447 406.60400 1.47800 152.32500 var92 16 7.80681 14.72424 124.90900 O 50.65800 var93 16 1.47194 4.98897 23.55100 O 20.10300 Correlation Analysis Results:

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations

Capture varl var2 var3

Capture 1.00000 0.93991 0.63286 0.56886

<.0001 0.0085 0.0215

16 16 16 16 varl 0.93991 1.00000 0.76597 0.69788 anti-Fetuin A <.0001 0.0005 0.0026

16 16 16 16 var2 0.63286 0.76597 1.00000 0.98310 anti-calmodulin 0.0085 0.0005 <.0001

16 16 16 16 var3 0.56886 0.69788 0.98310 1.00000 anti-Tgase II 0.0215 0.0026 <.0001

16 16 16 16 var4 0.58481 0.72299 0.99419 0.99522 anti-MMP-9 0.0173 0.0016 <.0001 <.0001

16 16 16 16 var5 0.58183 0.63641 0.40855 0.31555 anti-MMP-3 0.0181 0.0080 0.1162 0.2338

16 16 16 IS var6 0.90051 0.93484 0.62866 0.55540 anti-CD 42b <.0001 <.0001 0.0091 0.0255

16 16 16 16 var₇ 0.17190 0.31429 0.49314 0.47198

NF-kappa B 0.5244 0.2358 0.0523 0.0649

16 16 16 16 var8 0.65029 0.72953 0.65846 0.61872 anti-osteopontin 0.0064 0.0013 0.0055 0.0106

16 16 16 16 var9 0.62185 0.74939 0.98142 0.97553 anti-Factor X/Xa 0.0101 0.0008 <.0001 <.0001

16 16 16 16 varlO 0.57969 0.71543 0.99201 0.99590 anti CD14 0.0186 0.0018 ■c.OOOl <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var4 var5 var6 var7

Capture 0.58481 0.58183 0.90051 0.17190

0.0173 0.0181 <.0001 0.5244

16 16 16 16 varl 0.72299 0.63641 0.93484 0.31429 anti-Fetuin A 0.0016 0.0080 <.0001 0.2358

16 16 16 16 var2 0.99419 0.40855 0.62866 0.49314 anti-calmodulin <.0001 0.1162 0.0091 0.0523 16 16 16 16 var3 0.99522 0.31555 0.55540 0.47198 anti-Tgase II <.0001 0.2338 0.0255 0.0649

16 16 16 16 var4 1.00000 0.34598 0.58010 0.48042 anti-MMP~9 0.1893 0.0185 0.0596

16 16 16 16 var5 0.34598 1.00000 0.59898 0.63782 anti-MMP-3 0.1893 0.0142 0.0079

16 16 16 16 var6 0.58010 0.59898 1.00000 0.23898 anti-CD 42b 0.0185 0.0142 0.3727

16 16 16 16 var₇ 0.48042 0.63782 0.23898 1.00000 NF-kappa B 0.0596 0.0079 0.3727

16 16 16 16 var8 0.62453 0.82557 0.69888 0.81215 anti-osteopontin 0.0097 <.0001 0.0026 0.0001

16 16 16 16 var9 0.98511 0.32463 0.56932 0.41401 anti-Factor X/Xa <.0001 0.2199 0.0213 0.1109

16 16 16 16 varlO 0.99928 0.33104 0.56695 0.48624 anti CD14 <.0001 0.2104 0.0220 0.0562

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var8 var9 varlO varll

Capture 0.65029 0.62185 0.57969 0.70832

0.0064 0.0101 0.0186 0.0021

16 16 16 16 varl 0.72953 0.74939 0.71543 0.63724 anti-Fetuin A 0.0013 0.0008 0.0018 0.0079

16 16 16 16 var2 0.65846 0.98142 0.99201 0.22354 anti-calmodulin 0.0055 <.0001 <.0001 0.4053

16 16 16 16 var3 0.61872 0.97553 0.99590 0.11153 anti-Tgase II 0.0106 <.0001 <.0001 0.6809

16 16 16 16 var4 0.62453 0.98511 0.99928 0.14631 anti-MMP-9 0.0097 <.0001 <.0001 0.5887

16 16 16 16 var5 0.82557 0.32463 0.33104 0.69878 anti-MMP-3 <.0001 0.2199 0.2104 0.0026

16 16 16 16 var6 0.69888 0.56932 0.56695 0.55757 anti-CD 42b 0.0026 0.0213 0.0220 0.0248

16 16 16 16 var7 0.81215 0.41401 0.48624 0.01608 NF-kappa B 0.0001 0.1109 ^' 0.0562 0.9529

16 16 16 16 var8 1.00000 0.56718 0.62165 0.42121 anti-osteopontin 0.0219 0.0101 0.1042

IS 16 16 16 var9 0.56718 1 .00000 0 -98625 0.20805 anti-Factor X/Xa 0.0219 <.0001 0.4394

16 16 16 16 varlO 0.62165 0 .98625 1 -00000 0.13315 anti CD14 0.0101 <.0001 0.6230

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varl2 varl3 varl4 varl5

Capture 0.57671 0.88442 0.05923 0.28195

0.0194 <.0001 0.8275 0.2901

16 16 16 16 varl 0.71641 0.96367 0.15111 0.34949 anti-Fetuin A 0.0018 <.0001 0.5764 0.1845

16 16 16 16 var2 0.98449 0.89303 0.23225 0.41062 anti-calmodulin <.0001 <.0001 0.3867 0.1141

16 16 16 16 var3 0.98157 0.84782 0.20211 0.35023 anti-Tgase II <.0001 <.0001 0.4529 0.1836

16 16 16 16 var4 0.99094 0.86772 0.20835 0.36891 anti-MMP-9 <.0001 <.0001 0.4387 0.1597

16 16 16 16 var5 0.29848 0.52688 0.63685 0.80332 anti-MMP-3 0.2615 0.0360 0.0080 0.0002

16 16 16 16 var6 0.54529 0.86044 0.13309 0.32601 anti-CD 42b 0.0289 <.0001 0.6232 0.2179

16 16 16 16 var7 0.42396 0.34154 0.94828 0.90119 NF-kappa B 0.1017 0.1954 <.0001 <.0001

16 16 16 16 var8 0.55314 0.68982 0.74645 0.81846 anti-osteopontin 0.0262 0.0031 0.0009 0.0001

16 16 16 16 var9 0.99729 0.89231 0.13080 0.29691 anti-Factor X/Xa <.0001 <.0001 0.6292 0.2641

16 16 16 16 varlO 0.99154 0.86294 0.21406 0.36585 anti CD14 <.0001 <.0001 0.4260 0.1635

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl6 varl7 varl8 varl9

Capture 0 .51899 0 .67705 0 .64129 0 .49770

0.0394 0.0040 0.0074 0.0498

16 16 16 16 varl 0 .61993 0 .79587 0 .76742 0 .65791 anti-Fetuin A 0.0104 0.0002 0.0005 0.0056

16 16 16 16 var2 0.92951 0.98452 0.98947 0.97407 anti-calmodulin <.0001 <.0001 <.0001 <.0001

16 16 16 16 var3 0.94957 0.97122 0.98767 0.95984 anti-Tgase II <.0001 <.0001 <.0001 <.0001

16 16 16 16 var4 0.94567 0.97960 0.99139 0.97578 anti-MMP-9 <.0001 <.0001 <.0001 <.0001

16 16 16 16 varΞ 0.30536 0.44636 0.38813 0.29682 anti-MMP-3 0.2501 0.0831 0.1374 0.2643

16 16 16 16 var6 0.47516 0.61878 0.61754 0.51326 anti-CD 42b 0.0629 0.0106 0.0108 0.0420

16 16 16 16 var7 0.47331 0.48916 0.42528 0.53231 NP-kappa B 0.0641 0.0545 0.1006 0.0338

16 16 16 16 var8 0.59266 0.66521 0.62493 0.59215 anti-osteopontin 0.0155 0.0049 0.0096 0.0157

16 16 16 16 var9 0.92467 0.98883 0.98468 0.96146 anti-Factor X/Xa <.0001 <.0001 <.0001 <.0001

16 16 16 16 varlO 0.94549 0.97991 0.98848 0.97778 anti CD14 ■c.OOOl <.0001 <-0001 <.0001

16 16 16 IS

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var20 var21 var22 var23

Capture 0.47936 0.88105 0.21537 0.41533

0.0603 <.0001 0.4231 0.1096

16 16 16 16 varl 0.60423 0.93081 0.25789 0.46120 anti-Fetuin A 0.0132 <.0001 0.3349 0.0722

16 16 16 16 var2 0.91784 0.67281 0.39993 0.52797 anti-calmodulin <.0001 0.0043 0.1248 0.0355

16 16 16 16 var3 0.96775 0.58348 0.37305 0.48608 anti-Tgase II <.0001 0.0177 0.1547 0.0563

16 16 16 16 var4 0.94614 0.61876 0.38151 0.49693 anti-MMP-9 <.0001 0.0106 0.1448 0.0502

16 16 15 16 var5 0.17637 0.61698 0.36635 0.74506 anti-MMP-3 0.5135 0.0109 0.1628 0.0009

16 16 16 16 vars 0.49394 0.98125 0.26629 0.40273 anti-CD 42b 0.0518 <.0001 0.3188 0.1220

16 16 16 16 var7 0.34426 0.23612 0.24225 0.90335 NF-kappa B 0.1917 0.3786 0.3660 <.0001 16 16 16 16 var8 0.51585 0.68745 0.25991 0.86217 anti-osteopontin^* 0.0408 0.0033 0.3310 <-0001

16 16 16 16 var9 0.91038 0.60706 0.35075 0.44674 anti-Factor X/Xa <.0001 0.0126 0.1829 0.0828

16 16 16 16 varlO 0.94551 0.60270 0.37088 0.50100 anti CD14 ■c.0001 0.0135 0.1573 0.0481

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var24 var25 var26 var27

Capture 0.46976 0.61302 0.66343 0.58715

0.0664 0.0116 0.0051 0.0168

16 16 16 16 varl 0.58079 0.74598 0.80077 0.72483 anti-Fetuin A 0.0183 0.0009 0.0002 0.0015

16 16 16 16 var2 0.89027 0.99224 0.99203 0.98986 anti-calmodulin <.0001 <.0001 <.0001 <.0001

16 16 16 16 var3 0.88540 0.99314 0.96453 0.99690 anti-Tgase II <.0001 <.0001 <.0001 <.0001

16 16 16 16 var4 0.89062 0.99360 0.97699 0.99862 anti-MMP-9 <.0001 <.0001 <.0001 <.0001

15 16 16 16 var5 0.34946 0.40201 0.49105 0.33755 anti-MMP-3 0.1846 0.1227 0.0534 0.2010

16 16 16 16 var6 0.47073 0.61145 0.66429 0.58375 anti-CD 42b 0.0657 0.0118 0.0050 0.0176

16 16 16 16 var7 0.41264 0.51384 0.53450 0.47275 NF-kappa B 0.1122 0.0417 0.0329 0.0644

16 16 16 16 var8 0.49953 0.68161 0.71667 0.62376 anti-osteopontin 0.0488 0.0036 0.0018 0.0098

16 16 16 16 var9 0.87154 0.97139 0.96222 0.98317 anti-Factor X/Xa <.0001 <.0001 <.0001 <.0001

16 16 16 16 varlO 0.88663 0.99240 0.97365 0.99802 anti CD14 <.0001 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var28 var29 var30 var31

Capture 0.54689 0.57128 0.29338 0.35605

0.0284 0.0208 0.2701 0.1759

16 16 16 16 varl 0.53057 0.49230 0.39162 0.43030 anti-Fetuin A 0.0345 0.0527 0.1336 0.0962

16 16 16 16 var2 0.21140 0.10049 0.46122 0.42276 anti-calmodulin 0.4319 0.7112 0.0722 0.1028

IS 16 16 16 var3 0.08364 0.04146 0.42606 0.38843 anti-Tgase II 0.7581 0.8788 0.0999 0.1371

16 16 16 16 var4 0.12816 0.05860 0.43513 0.39298 anti-MMP-9 0.6362 0.8293 0.0921 0.1321

16 16 16 16 var5 0.89012 0.55910 0.73362 0.79589 anti-MMP-3 <.0001 0.0243 0.0012 0.0002

16 16 16 16 var6 0.52671 0.30744 0.34039 0.39268 anti-CD 42b 0.0361 0.2467 0.1970 0.1324

16 16 16 16 var7 0.43907 0.01747 0.97764 0.93324 NF-kappa B 0.0889 0.9488 <.0001 <.0001

16 16 16 16 var8 0.67164 0.26612 0.87649 0.91061 anti-osteopontin 0.0044 0.3191 <.0001 <.0001

16 16 16 16 var9 0.12094 0.17435 0.37080 0.32715 anti-Factor X/Xa 0.6555 0.5184 0.1574 0.2161

16 16 16 16 varlO 0.11438 0.05671 0.43926 0.39483 anti CD14 0.6732 0.8348 0.0887 0.1302

16 16 16 16

Pearson Correlation Coefficients Prob > |r] under HO: RhO=O Number of Observations var32 var33 var34 var35

Capture -0.06698 0.65841 0.60363 0.07772

0.8053 0.0056 0.0133 0.7748

16 16 16 16 varl 0.06560 0.77003 0.70955 0.25857 anti-Fetuin A. 0.8093 0.0005 0.0021 0.3336

16 16 16 16 var2 -0.06241 0.96906 0.95087 0.57869 anti-calmodulin 0.8184 <-0001 <.0001 0.0188

16 16 16 16 var3 -0.16035 0.96654 0.92782 0.60340 anti-Tgase II 0.5530 <.0001 <.0001 0.0133

16 16 16 16 var4 -0.11793 0.97197 0.94046 0.61061 anti-MMP-9 0.6636 <.0001 <.0001 0.0120

16 16 . 16 16 var5 0.44092 0.36622 0.26377 -0.09396 anti-MMP-3 0.0874 0.1630 0.3236 0.7293

16 16 16 16 var6 0.05534 0.57620 0.59200 0.08403 anti-CD 42b 0.8387 0.0195 0.0157 0.7570

16 16 16 16 var7 0.30892 0.39922 0.36591 0.20732

NF-kappa B 0.2443 0.1256 0.1634 0.4410

16 16 16 16 var8 0.26533 0.58095 0.55675 0.12530 anti-osteopontin 0.3206 0.0183 0.0251 0.6438

16 16 16 16 var9 0.14116 0.99365 0.92864 0.62035 anti-Factor X/Xa 0.6021 <.0001 <.0001 0.0104

16 16 16 16 varlO 0.12839 0.97282 0.94101 0.61538 anti CD14 0.6356 <.0001 <.0001 0.0112

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39

Capture 0.50372 0.69009 0.37031 0.59148

0.0467 0.0031 0.1580 0.0158

16 16 16 16 varl 0.66261 0.79671 0.52970 0.71951 anti-Fetuin A 0.0052 0.0002 0.0348 0.0017

16 16 16 16 var2 0.97807 0.97580 0.49388 0.97935 anti-calπiodulin <-0001 <.0001 0.0519 <.0001

16 16 16 16 var3 0.96763 0.97655 0.41161 0.98118 anti-Tgase II <.0001 <.0001 0.1132 <.0001

16 16 16 16 var4 0.98091 0.97352 0.46439 0.98705 anti-MMP-9 <.0001 <.0001 0.0700 <.0001

16 16 16 16 var5 0.27642 0.41830 0.54893 0.29504 anti-MMP-3 0.3000 0.1069 0.0277 0.2673

16 16 16 16 var6 0.51641 0.64895 0.52695 0.53743 anti-CD 42b 0.0406 0.0065 0.0360 0.0318

16 16 16 16 var7 0.50034 0.41141 0.14459 0.42224 NF-kappa B 0.0484 0.1134 0.5932 0.1033

16 16 16 16 var8 0.57206 0.65306 0.35461 0.55581 anti-osteopontin 0.0206 0.0061 0.1778 0.0254

16 16 16 16 var9 0.96882 0.96756 0.44673 0.99848 anti-Factor X/Xa ■c.OOOl <.0001 0.0828 <.0001

16 16 16 16 varlO 0.98274 0.97110 0.43407 0.98936 anti CD14 <.0001 <.0001 0.0930 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var40 var41 var42 var43 Capture 0.71298 0.88746 0.47842 0.41587

0.0019 <.0001 0.0608 0.1091

16 16 16 16 varl 0.82790 0.97162 0.62818 0.56614 anti-Fetuin A <.0001 <.0001 0.0092 0.0222

16 16 16 16 var2 0.76182 0.85852 0.86629 0.91864 anti-calmodulin 0.0006 <.0001 <-0001 <.0001

16 16 16 16 var3 0.70055 0.80681 0.86555 0.92626 anti-Tgase II 0.0025 0.0002 <.0001 <.0001

16 16 16 16 var4 0.73614 0.82823 0.87736 0.93376 anti-MMP-9 0.0011 <.0001 <.0001 <.0001

16 16 IS 16 var5 0.60405 0.54333 0.20110 0.19627 anti-MMP-3 0.0132 0.0296 0.4552 0.4663

16 16 IS 16 var6 0.65865 0.92353 0.45404 0.42876 anti-CD 42b 0.005S <-0001 0.0773 0.0975

16 16 16 IS var7 0.24298 0.32507 0.35220 0.39611

NF-kappa B 0.3645 0.2193 0.1809 0.1288

16 16 16 16 var8 0.52423 0.70764 0.40104 0.43000 anti-osteopontin 0.0371 0.0022 0.1237 0.0964

16 16 16 16 var9 0.78834 0.83422 0.90526 0.92716 anti-Factor X/Xa 0.0003 <.0001 <.0001 <.0001

16 16 16 16 varlO 0.72223 0.82004 0.88148 0.93429 anti CD14 0.0016 0.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48

Capture 0.03495 0.21956 0.55360 0.79115

0.8977 0.4139 0.0261 0.0003

16 16 16 16 varl 0.15964 0.26315 0.67480 0.83565 anti-Fetuin A 0.5548 0.3248 0.0041 <.0001

16 16 16 16 var2 0.29020 0.23719 0.76636 0.41706 anti-calmodulin 0.2756 0.3764 0.0005 0.1080

16 16 16 IS var3 0.30545 0.19732 0.70764 0.31431 anti-Tgase II 0.2500 0.4639 0.0022 0.2358

16 16 16 16 var4 0.31538 0.20853 0.74546 0.35799 anti-MMP-9 0.2341 0.4383 0.0009 0.1734

16 16 16 16 var5 -0.14667 0.73822 0.43452 0.69951 anti-MMP-3 0.5878 0.0011 0.0926 0.0026

16 16 16 16 var6 0.10421 0.25282 0.57691 0.87166 anti-CD 42b 0.7009 0.3448 0.0193 <,0001

16 IS 16 16 var7 0.06172 0.86477 0.19175 0.09382

NF-kappa B 0.8204 <.O001 0.4768 0.7296

16 16 16 16 var8 0.03383 0.78915 0.44063 0.55368 anti-osteopontin 0.9010 0.0003 0.0876 0.0261

16 16 16 16 var9 0.32514 0.14419 0.75133 0.37987 anti-Factor X/Xa 0.2191 0.5942 0.0008 0.1467

16 16 16 16 varlO 0.31803 0.20798 0.72932 0.33594 anti CD14 0.2300 0.4396 0.0013 0.2033

16 16 16 IS

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var49 var50 var51 var52

Capture 0.94414 0.72244 0.57268 0.63099

<.0001 0.0016 0.0204 0.0088

16 16 16 16 varl 0.91683 0.75733 _ 0.64825 0.75103 anti-Fetuin A <.0001 0.0007 0.0066 0.0008

IS 16 16 16 var2 0.52135 0.75291 0.87832 0.96176 anti-calmodulin 0.0384 0.0008 <.0001 <.0001

16 16 16 16 var3 0.42238 0.73235 0.90882 0.97582 anti-Tgase II 0.1031 0.0013 <.0001 <.0001

16 IS 16 16 var4 0.46083 0.74009 0.89003 0.97125 anti-MMP-9 0.0724 0.0010 <.0001 ■=.0001

16 16 16 16 var5 0.60215 0.42892 0.46340 0.36698 anti-MMP-3 0.0136 0.0974 0.0706 0.1621

16 16 16 16 var6 0.93105 0.49309 0.50840 0.61073 anti-CD 42b <.0001 0.0523 0.0443 0.0120

16 16 16 16

^• var7 0.08564 0.28445 0.56279 0.37175 NF-kappa B 0.7525 0.2856 0.0232 0.1562

16 16 16 16 var8 0.57969 0.48975 0.68347 0.60284 anti-osteopontin 0.0186 0.0542 0.0035 0.0134

16 16 16 16 var9 0.49640 0.82780 0.86965 0.95951 anti-Factor X/Xa 0.0505 <.0001 <.0001 <.0001

16 16 16 16 varlO 0.44806 0.74625 0.89152 0.96673 anti CD14 0.0818 0.0009 <.0001 <-0001

16 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations var53 var54 var55 var56

Capture 0.43379 0.48395 0.64933 0.69446

0.0932 0.0575 0.0065 0.0028

16 16 16 16 varl 0.59600 0.36530 0.74974 0.75106 anti-Fetuin A 0.0148 0.1641 0.0008 0.0008

16 16 16 16 var2 0.92297 0.10316 0.62637 0.79709 anti-calmodulin <.0001 0.7038 0.0094 0.0002

16 16 16 16 var3 0.94925 0.15254 0.54707 0.77993 ant±-Tgase II <.0001 0.5728 0.0283 0.0004

IS 16 16 16 var4 0.93901 0.10624 0.59234 0.78983 anti-MMP-9 <.0001 0.6954 0.0156 0.0003

16 16 16 16 var5 0.39691 0.30313 0.63205 0.38871 anti-MMP-3 0.1280 0.2538 0.0086 0.1368

16 16 16 16 varβ 0.47832 0.21445 0.59726 0.48720 anti-CD 42b 0.0609 0.4251 0.0146 0.0556

16 16 16 16 var7 0.69094 -0.07686 0.16578 0.29890 NF-kappa B 0.0030 0.7772 0.5395 0.2608

16 16 16 16 var8 0.73244 0.23078 0.43852 0.47836 anti-osteopontin 0.0013 0.3898 0.0893 0.0609

16 16 16 16 var9 0.88444 0.17287 0.65086 0.87310 anti-Factor X/Xa <.0001 0.5220 0.0063 <.O001

16 16 16 16 varlO 0.94098 0.11055 0.57397 0.79596 anti CD14 <.0001 0.6836 0.0201 0.0002

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var57 var58 var59 var60

Capture 0.80940 0.87903 0.81297 0.70252

0.0001 <.0001 0.0001 0.0024

16 16 16 16 varl 0.81508 0.84176 0.85281 0.70978 anti-Fetuin A 0.0001 <.0001 <.0001 0.0021

16 16 16 16 var2 0.61271 0.58190 0.80618 0.63399 anti-calmodulin 0.0116 0.0180 0.0002 0.0084

16 16 16 16 var3 0.50427 0.50814 0.72366 0.61426 anti-Tgase II 0.0464 0.0445 0.0015 0.0114

16 16 16 16 var4 0.55305 0.53091 0.75251 0.62090 anti-MMP-9 0.0263 0.0343 0.0008 0.0103

16 16 16 16 var5 0.57313 0.76733 0.58350 0.41865 anti-MMP-3 0.0203 0.0005 0.0177 0.1065

16 16 16 16 var6 0.85634 0.86073 0.76827 0.43998 anti-CD 42b <.0001 <.0001 0.0005 0.0881

16 16 16 16 var7 0.15782 0.40620 0.31165 0.21638 NF-kappa B 0.5594 0.1185 0.2400 0.4209

16 16 16 16 var8 0.57779 0.77801 0.67238 0.42431 anti-osteopontin 0.0191 0.0004 0.0043 0.1014

16 16 16 16 var9 0.54194 0.51938 0.75615 0.72579 anti-Factor X/Xa 0.0301 0.0392 0.0007 0.0015

16 16 16 16 varlO 0.53467 0.51875 0.74441 0.62790 anti CD14 0.0329 0.0395 0.0009 0.0092

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varδl var62 var63 var64

Capture 0.66731 0.74555 0.78627 0.52532

0.0047 0.0009 0.0003 0.0367

16 16 16 16 varl 0.74929 0.82864 0.90029 0.66836 anti-Fetuin A 0.0008 <.O001 <.0001 0.0047

16 16 16 16 var2 0.89920 0.78790 0.95060 0.97252 anti-calmodulin <.0001 0.0003 <.0001 <.0001

16 16 16 16 var3 0.84440 0.69336 0.90188 0.98407 anti-Tgase Il <.0001 0.0029 <.0001 <.0001

16 16 16 16 var4 0.86675 0.73329 0.92769 0.98742 anti-MMP-9 <.0001 0.0012 <.0001 <.0001

16 16 15 16 var5 0.39770 0.53435 0.51241 0.22030 anti-MMP-3 0.1271 0.0330 0.0424 0.4123

16 16 16 16 varδ 0.63590 0.80429 0.80973 0.50244 anti-CD 42b 0.0081 0.0002 0.0001 0.0473

16 16 16 16 var7 0.41933 0.33497 0.38471 0.39449 NF-kappa B 0.1059 0.2047 0.1412 0.1305

16 16 16 16 var8 0.63326 0.65936 0.68114 0.50997 anti-osteopontin 0.0085 0.0055 0.0037 0.0436

16 16 16 16 var9 0.8S002 0.71780 0.92693 0.98805 anti-Factor X/Xa <.0001 0.0017 <.0001 <.0001

16 16 16 16 varlO 0.86704 0.72304 0.91901 0.98909 anti CD14 <-0001 0.0016 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 varS7 var68

Capture 0.7567S 0.71633 0.42853 0.53166

0.0007 0.0018 0.0977 0.0340

16 16 16 16 varl 0.80573 0.84745 0.41157 0.54156 anti-Fetuin A 0.0002 <.0001 0.1132 0.0303

16 16 16 16 var2 0.84106 0.91876 0.S9364 0.68922 anti-calmodulin <.0001 <.0001 0.0153 0.0031

16 16 16 16 var3 0.78745 0.84891 0.61915 0.65043 anti-Tgase II 0.0003 <.0001 0.0105 0.0064

16 16 16 16 var4 0.817S3 0.88468 0.61710 0.66543 anti-MMP-9 0.0001 <.0001 0.0109 0.0049

16 16 16 16 var5 0.39117 0.47963 0.00427 0.25592 anti-MMP-3 0.1341 0.0601 0.9875 0.3387

16 16 16 16 var6 0.75314 0.77155 0.37975 0.42827 anti-CD 42b 0.0008 0.0005 0.1468 0.0979

16 16 16 16 var7 0.33425 0.38685 0.13357 0.13663 NF-kappa B 0.2058 0.1388 0.6219 0.6139

16 16 16 16 var8 0.60958 0.65038 0.22358 0.28187 anti-osteopontin 0.0122 0.0064 0.40B2 0.2902

16 16 16 16 var9 0.82108 0.87679 0.61173 0.68536 anti-Factor X/Xa <.0001 <.0001 0.0118 0.0034

16 16 16 16 varlO 0.81349 0.87627 0.62043 0.66200 anti CD14 0.0001 <.0001 0.0103 0.0052

16 16 16 16

Pearson Correlation Coefficients Prob > |r] under HO: Rho=0 Number of Observations var69 var70 var71 var72

Capture 0.02274 0.92490 0.90084 0.83004

0.9334 <.0001 <.0001 <.0001

16 16 16 16 varl 0.05661 0.93068 0.92293 0.90725 anti-Fetuin A 0.8350 <.0001 <.0001 <.0001

16 16 16 16 var2 -0.00684 0.64023 0.66398 0.89004 anti-calmodulin 0.9799 0.0076 0.0050 <.0001

16 16 16 16 var3 0.00385 0.58421 0.58842 0.84504 anti-Tgase II 0.9887 0.0175 0.0165 <.0001

16 16 16 16 var4 0.00753 0.60531 0.62415 0.85751 anti-MMP-9 0.9779 0.0130 0.0098 <.0001

16 16 16 16 varS -0.11547 0.54221 0.55053 0.63843 anti-MMP-3 0.6702 0.0300 0.0271 0.0078 ie 16 16 16 var6 0.10750 0.95539 0.947J.1 0.79704 anti-CD 42b 0.6919 <.0001 ■=.0001 0.0002

16 16 16 16 var7 0.08661 0.18542 0.19951 0.39437

NF-kappa B 0.7498 0.4918 0.4588 0.1306

16 16 16 16 var8 0.02999 0.63683 0.62878 0.71910 anti-osteopontin 0.9122 0.0080 0.0091 0.0017

IS 16 16 iε var9 0.02069 0.61494 0.63529 0.86242 anti-Factor X/Xa 0.9394 0.0112 0.0082 <.0001

16 16 16 16 varlO 0.00619 0.59467 0.61156 0.84872 anti CD14 0.9819 0.0151 0.0118 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RIiO=O Number of Observations var74 var75 var76 var77

Capture 0.91067 0.93923 0.93867 0.80153

<.0001 <.0001 <.0001 0.0002

16 16 16 16 varl 0.91469 0.94447 0.94841 0.74495 anti-Fetuin A <.0001 ■c.OOOl <.0001 0.0009

16 16 16 16 var2 0.52639 0.61580 0.61244 0.50938 anti-calmodulin 0.0362 0.0111 0.0117 0.0439

16 16 16 16 var3 0.43266 0.53344 0.53225 0.47936 anti-Tgase II 0.0942 0.0333 0.0338 0.0603

16 16 16 16 var4 0.46552 0.56283 0.56005 0.48453 anti-MMP-9 0.0692 0.0232 0.0241 0.0572

16 16 16 16 var5 0.70436 0.73158 0.73956 0.59036 anti-MMP-3 0.0023 0.0013 0.0011 0.0161

16 16 16 16 varδ 0.96401 0.86383 0.87890 0.79045 anti-CD 42b <.0001 <.0001 <.0001 0.0003

16 16 16 16 var7 0.17992 0.22001 0.22946 0.31338 NF-kappa B 0.5049 0.4129 0.3926 0.2372

16 16 16 16 var8 0.66374 0.65906 0.66896 0.69043 anti-osteopontin 0.0051 0.0055 0.0046 0.0031

16 16 16 16 var9 0.47162 0.61180 0.60457 0.46893 anti-Factor X/Xa 0.0651 0.0118 0.0131 0.0669

16 16 16 16 varlO 0.44842 0.55131 0.54822 0.47549 anti CD14 0.0815 0.0269 0.0279 0.0627

16 16 16 16 Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var78 var79 var80 varδl

Capture 0.52692 0.77586 0.92726 0.40299

0.0360 0.0004 <.0001 0.1721

16 16 16 13 varl 0.62008 0.81681 0.94615 0.40855 anti-Fetuin A 0.0104 0.0001 <.0001 0.1657

16 16 16 13 var2 0.84333 0.41588 0.60073 0.69511 anti-calmodulin <.0001 0.1091 0.0139 0.0084

16 16 16 13 var3 0.88376 0.31976 0.51284 0.77714 anti-Tgase II <.0001 0.2273 0.0422 0.0018

16 16 16 13 var4 0.85582 0.35929 0.54530 0.72543 anti-MMP-9 <.0001 0.1717 0.0289 0.0050

16 16 16 13 varS 0.49980 0.72880 0.71339 0.18341 anti-MMP-3 0.0487 0.0014 0.0019 0.5487

16 16 16 13 varβ 0.52267 0.88030 0.95302 0.39801 anti-CD 42b 0.0378 <.0001 <.0001 0.1780

16 16 16 13 var7 0.68430 0.13304 0.20478 0.32499 NF-kappa B 0.0035 0.6233 0.4468 0.2786

16 16 16 13 var8 0.81845 0.58860 0.67966 0.52456 anti-osteopontin 0.0001 0.0165 0.0038 0.0657

16 16 16 13 var9 0.79248 0.36059 0.56088 0.64036 anti-Factor X/Xa 0.0003 0.1700 0.0238 0.0184

16 16 16 13 varlO 0.85780 0.33502 0.52908 0.72315 anti CD14 <.0001 0.2046 0.0351 0.0052

16 16 16 13

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var82 var83 var84 var85

Capture 0.68495 0.93635 0.83437 0.96109

0.0098 <.0001 0.0004 <.0001

13 13 13 13 varl 0.77161 0.93032 0.78479 0.93519 anti-Fetuin A 0.0020 <.0001 0.0015 <.0001

13 13 13 13 var2 0 .61683 0 .79740 0 .73270 0 .58442 anti-calmodulin 0 . 0247 0 . 0011 0. 0044 0. 0359

13 13 13 13 var3 0 .53139 0 .73836 0 .70511 0 .50913 anti-Tgase II 0. 0616 0 . 0039 0. 0071 0. 0756

13 13 13 13 var4 0 .58096 0 .76321 0 .71362 0 .53623 anti-MMP-9 0.0373 0.0024 0.0062 0.0589

13 13 13 13 var5 0.52732 0.62196 0.41579 0.73554 anti-MMP-3 0.0640 0.0232 0.1576 0.0042

13 13 13 13 varβ 0.80693 0.77498 0.54191 0.87345 anti-CD 42b 0.0009 0.0019 0.0557 <.0001

13 13 13 13 var7 0.18374 0.28352 0.23791 0.22248 NF-kappa B 0.5479 0.3479 0.4338 0.4650

13 13 13 13 var8 0.50253 0.61969 0.47941 0.63289 anti-osteopontin 0.0801 0.0239 0.0974 0.0203

13 13 13 13 var9 0.58738 0.82489 0.80677 0.59061 anti-Factor X/Xa 0.0348 0.0005 0.0009 0.0336

13 13 13 13 varlO 0.55925 0.75638 0.72029 0.52326 anti CD14 0.0469 0.0028 0.0055 0.0665

13 13 13 13

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var86 var87 var88 var89

Capture 0.83523 0.73230 0.20993 0.65948

<-0001 0.0019 0.4527 0.0075

16 15 15 15 varl 0.80522 0.81257 0.19853 0.75658 anti-Fetuin A 0.0002 0.0002 0.4781 0.0011

16 15 15 15 var2 0.38817 0.47010 0.29036 0.91093 anti-calmodulin 0.1374 0.0770 0.2938 <.0001

16 15 15 15 var3 0.29482 0.39007 0.41067 0.89759 anti-Tgase II 0.2677 0.1506 0.1284 <.0001

16 15 15 15 var4 0.33832 0.43573 0.33465 0.90955 anti-MMP-9 0.1999 0.1045 0.2228 <.0001

16 15 15 15 var5 0.44373 0.42901 0.02229 0.33604 anti-MMP-3 0.0851 0.1106 0.9372 0.2207

16 15 15 15 var6 0.86399 0.79661 0.20360 0.52020 anti-CD 42b ■=.0001 0.0004 0.4667 0.0468

16 15 15 15 var7 0.03687 0.04733 -0.02347 0.35640 NF-kappa B 0.8922 0.8670 0.9338 0.1923

16 15 15 15 var8 0.46995 0.38155 0.24761 0.51022 anti-osteopontin 0.0662 0.1605 0.3736 0.0520

16 15 15 15 var9 0.37861 0.49897 0.26989 0.96468 anti-Factor X/Xa 0.1482 0.0583 0.3306 ■=.0001

16 15 15 15 varlO 0.32913 0.42311 0.33066 0.91407 anti CD14 0.2132 0.1161 0.2287 <.0001 16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var90 var91 var92 var93

Capture 0.39089 0.7564₇ 0.75787 0.49591

0.149₇ 0.0011 0.0007 0.0508

15 15 16 16 varl 0.56636 0.84200 0.79912 0.65320 anti-Fetuin A 0.0277 <.0001 0.0002 0.0061

15 15 16 16 var2 0.92862 0.96143 0.82839 0.97719 anti-calmodulin <.0001 <.0001 <.0001 <.0001

15 15 16 16 var3 0.92091 0.91769 0.82862 0.97947 anti-Tgase II <.0001 <.0001 <.0001 <.0001

15 15 16 16 var4 0.93604 0.93836 0.82857 0.98817 anti-MMP-9 <.0001 <.0001 <.0001 <.0001

15 15 16 16 var5 0.33069 0.44561 0.39380 0.24174 anti-MMP-3 0.2286 0.0960 0.1312 0.3671

15 15 16 16 var6 0.41406 0.71031 0.57954 0.50233 anti-CD 42b 0.1249 0.0030 0.0186 0.0474

15 15 16 16 var7 0.65986 0.44826 0.29249 0.45812

NF-kappa B 0.0074 0.0938 0.2716 0.0743

15 15 16 16 var8 0.62900 0.68505 0.53943 0.54033 anti-osteopontin 0.0120 0.0048 0.0310 0.0307

15 15 16 16 var9 0.91107 0.94536 0.89165 0.97842 anti-Factor X/Xa <.0001 <.0001 <.0001 <.0001

15 15 16 16 varlO 0.93905 0.93775 0.83272 0.98963 anti CD14 <.0001 <.0001 <.0001 <.0001

15 15 16 16

Capture varl var2 var3 varll 0.70832 0.63724 0.22354 0.11153 anti-prothrombin 0.0021 0.0079 0.4053 0.6809

16 16 16 16 varl2 0.57671 0.71641 0.98449 0.98157 anti-Factor IX 0.0194 0.0018 <.0001 <.0001

16 16 16 16 varl3 0.88442 0.96367 0.89303 0.84782 anti-Fetuin B <.0001 <.0001 <.0001 <.0001

16 16 16 16 varl4 0.05923 0.15111 0.23225 0.20211 anti-CD40 0.8275 0.5764 0.3867 0.4529

16 16 16 16 varl5 0.28195 0.34949 0.41062 0.35023 anti-myeloperoxidase 0.2901 0.1845 0.1141 0.1836

16 16 16 16 varl6 0.51899 0.61993 0.92951 0.94957 vanti-Fibronectin 0.0394 0.0104 <.0001 <.0001

16 16 16 16 varl7 0.67705 0.79587 0.98452 0.97122 anti-Factor VII 0.0040 0.0002 ■c.OOOl <.0001

16 16 16 16 varl8 0.64129 0.76742 0.98947 0.98767 anti-tissue factor 0.0074 0.0005 <.0001 <.0001 ie 16 16 16 varl9 0.49770 0.65791 0.97407 0.95984 anti-human complement 5b-9 0.0498 0.0056 <.0001 <.0001

16 16 16 16 var20 0.47936 0.60423 0.91784 0.96775 anti-human CRP 0.0603 0.0132 <.0001 <.0001

16 16 16 16 var21 0.88105 0.93081 0.67281 0.58348 anti-rαatrix GLA <.0001 <.0001 0.0043 0.0177

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var4 var5 var6 var7 varll 0.14631 0.69878 0.55757 0.01608 anti-prothrombin 0.5887 0.0026 0.0248 0.9529

16 16 16 16 varl2 0.99094 0.29848 0.54529 0.42396 anti-Factor IX <.0001 0.2615 0.0289 0.1017

16 16 16 16 varl3 0.86772 0.52688 0.86044 0.34154 anti-Fetuin B <.0001 0.0360 <.0001 0.1954

16 16 16 16 varl4 0.20835 0.63685 0.13309 0.94828 anti-CD40 0.4387 0.0080 0.6232 <.0001

16 16 16 16 varlS 0.36891 0.80332 0.32601 0.90119 anti-myeloperoxidase 0.1597 0.0002 0.2179 <.0001

16 16 16 16 varlδ 0.94567 0.30536 0.47516 0.47331 vanti-Fibronectin <.0001 0.2501 0.0629 0.0641

16 16 16 16 varl7 0.97960 0.44636 0.61878 0.48916 anti-Factor VII <.0001 0.0831 0.0106 0.0545

16 16 16 16 varl8 0.99139 0.38813 0.61754 0.42528 anti-tissue factor <.0001 0.1374 0.0108 0.1006

16 16 16 16 varl9 0.97578 0.29682 0.51326 0.53231 anti-human complement 5b-9 <.0001 0.2643 0.0420 0.0338

16 16 16 16 var20 0.94614 0.17637 0.49394 0.34426 anti-human CRP <.0001 0.5135 0.0518 0.1917

16 16 16 16 var21 0.61876 0.61698 0.98125 0.23612 anti-matrix GLA 0.0106 0.0109 <-0001 0.3786 ie 16 ie 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var8 var9 varlO varll varll 0.42121 0.20805 0.13315 1.00000 anti-prothrombin 0.1042 0.4394 0.6230

16 16 16 16 varl2 0.5S314 0.99729 0.99154 0.15400 anti-Factor IX 0.0262 <.0001 <-0001 0.5691

16 16 16 16 varl3 0.68982 0.89231 0.86294 0.49017 anti-Fetuin B 0.0031 <.0001 <.0001 0.0539

16 16 16 16 varl4 0.74645 0.13080 0.21406 0.04468 anti-CD40 0.0009 0.6292 0.4260 0.8695

16 16 16 16 varl5 0.81846 0.29691 0.36585 0.26620 anti-myeloperoxidase 0.0001 0.2641 0.1635 0.3190

16 16 16 16 varl6 0.59266 0.92467 0.94549 0.10198 vanti-Fibronectin 0.0155 <.0001 <.0001 0.7070

16 16 16 16 varl7 0.66521 0.98883 0.97991 0.29676 anti-Factor VII 0.0049 <.0001 <.0001 0.2644

16 16 16 16 varl8 0.62493 0.98468 0.98848 0.24073 anti-tissue factor 0.0096 <.0001 <.0001 0.3691

16 16 16 16 varl9 0.59215 0.96146 0.97778 0.07752 anti-human complement 5b-9 0.0157 <-0001 <.0001 0.7754

16 16 16 16 var20 0.51585 0.91038 0.94551 -0.00345 anti-human CRP 0.0408 <.0001 <.0001 0.9899

16 16 16 16 var21 0.68745 0.60706 0.60270 0.60155 anti-matrix GLA 0.0033 0.0126 0.0135 0.0137

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl2 varl3 varl4 varl5 varll 0.15400 0.49017 0.04468 0.26620 anti-prothrombin 0.5691 0.0539 0.8695 0.3190

16 16 16 16 varl2 1.00000 0.86912 0.13767 0.29887 anti-Factor IX <.0001 0.6111 0.2608

16 16 16 16 varl3 0.86912 1.00000 0.11729 0.32196 anti-Fetuin B <-0001 0.6653 0.2240

16 16 16 16 varl4 0.13767 0.11729 1.00000 0.90962 anti-CD40 0.6111 0.6653 <.0001 16 16 16 16 varl5 0.29887 0.32196 0.90962 1.00000 anti-myeloperoxidase 0.2608 0.2240 <.0001

16 16 16 16 varl6 0.93094 0.78148 0.21579 0.36323 vanti-Fibronectin <.0001 0.0004 0.4222 0.1667

16 16 16 16 varl7 0.98139 0.91466 0.22709 0.40116 anti-Factor VII <.0001 <.0001 0.3977 0.1236

16 16 16 16 varl8 0.98447 0.89730 0.15507 0.34192 anti-tissue factor <.0001 <.0001 0.5663 0.1949

16 16 16 16 varl9 0.97340 0.81081 0.26937 0.39480 anti-human complement 5b~9 <.0001 0.0001 0.3130 0.1302

IS 16 16 16 var20 0.92313 0.76474 0.07706 0.20469 anti-human CRP <.0001 0.0006 0.7767 0.4470

IS IS IS IS var21 0.58712 0.86712 0.12158 0.34046 anti-matrix GLA 0.0168 <.0001 0.6538 0.1969

16 IS 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varl6 varl7 varl8 varl9 varll 0.10198 0.29676 0.24073 0.07752 anti-prothrombin 0.7070 0.2644 0.3691 0.7754

16 16 16 16 varl2 0.93094 0.98139 0.98447 0.97340 anti-Factor IX <.0001 <.0001 <.0001 <.0001

16 16 16 16 varl3 0.78148 0.91466 0.89730 0.81081 anti-Fetuin B 0.0004 <.0001 <.0001 0.0001

16 16 16 16 varl4 0.21579 0.22709 0.15507 0.26937 anti-CD40 0.4222 0.3977 0.5663 0.3130

16 16 16 16 varl5 0.36323 0.40116 0.34192 0.39480 anti-myeloperoxidase 0.1667 0.1236 0.1949 0.1302

16 16 16 16 varl6 1.00000 0.91890 0.93681 0.90876 vanti-Fibronectin <.0001 <.0001 <.0001

16 16 16 16 varl7 0.91890 1.00000 0.98544 0.94721 anti-Factor VII <.0001 <.0001 <.0001

16 16 16 16 varl8 0.93681 0.98544 1.00000 0.94518 anti-tissue factor <.0001 <.0001 <.0001

16 16 16 16 varl 9 0.90876 0.94721 0.94518 1.00000 anti-human complement 5b-9 <.0001 <.0001 <.0001

16 16 16 16 var20 0.91937 0.89281 0.94476 0.88332 ant i- human CRP <.0001 ■=.0001 <.0001 <.0001

16 16 16 16 var21 0.51007 0.65116 0.65549 0.56744 anti-matrix GLA 0.0435 0.0063 0.0058 0.0219

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var20 var21 var22 var23 varll 0.00345 0.60155 0.15682 0.26293 anti-prothrombin 0.9899 0.0137 0.5619 0.3252

16 16 16 16 varl2 0.92313 0.58712 0.36071 0.43977 anti-Factor IX <.0001 0.0168 0.1699 0.0883

16 16 16 16 varl3 0.76474 0.86712 0.31378 0.46081 anti-Fetuin B 0.0006 <.0001 0.2366 0.0724

16 16 16 16 varl4 0.07706 0.12158 0.16735 0.87312 anti-CD40 0.77S7 0.6538 0.5356 <.0001

16 16 16 16 varlδ 0.20469 0.34046 0.37312 0.91216 anti-myeloperoxidase 0.4470 0.1969 0.1546 <.0001

16 16 16 16 varl6 0.91937 0.51007 0.33273 0.45662 vanti-Fibronectin <.0001 0.0435 0.2079 0.0754

16 16 16 16 varl7 0.89281 0.65116 0.39401 0.54324 anti-Factor VII <.0001 0.0063 0.1310 0.0297

16 16 16 16 varl8 0.94476 0.65549 0.37584 0.46279 anti-tissue factor <.0001 0.0058 0.1514 0.0711

16 16 16 16 varl9 0.88332 0.56744 0.38078 0.52607 anti-human complement 5b-9 <.0001 0.0219 0.1457 0.0363

16 16 16 16 var20 1.00000 0.51003 0.30351 0.32727 anti-human CRP 0.0436 0.2531 0.2160

16 16 16 16 var21 0.51003 1.00000 0.29536 0.40286 anti-matrix GLA 0.0436 0.2667 0.1218

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var24 var25 var26 var27 varll 0.12901 0.18856 0.29769 0.13348 anti-prothrombin 0.6340 0.4843 0.2628 0.6221

16 16 16 16 varl2 0.88227 0.97522 0.96218 0.98860 anti-Factor IX <.0001 <.0001 <.0001 <.0001

16 16 16 16 varl3 0.73338 0.87530 0.90334 0.86957 anti-Fetuin B 0.0012 <.0001 <.0001 <.0001

16 16 16 16 varl4 0.17368 0.25680 0.29098 0.19812 anti-CD40 0.5200 0.3370 0.2742 0.4620

16 16 IS 16 varl5 0.37979 0.41191 0.46862 0.35540 anti-myeloperoxidase 0.1468 0.1129 0.0671 0.1767

16 16 16 16 varl6 0.79898 0.93930 0.90979 0.94775 vanti-Fibronectin 0.0002 •=.0001 <.0001 <.0001

16 16 16 16 varl₇ 0.87614 0.97890 0.98003 0.97691 anti-Factor VII <.O001 <.0001 <.0001 <.0001

16 16 16 16 var!8 0.88430 0.99054 0.97832 0.99207 anti-tissue factor <.0001 <.0001 <.0001 <.0001

16 16 16 16 varl9 0.87265 0.95941 0.95390 0.96645 anti-human complement 5b-9 <.0001 <.0001 <.0001 <.0001

16 16 16 16 var20 0.83034 0.94827 0.89075 0.95630 anti-human CRP <.0001 <.0001 <.0001 <.0001

16 16 16 16 var21 0.51509 0.64331 0.70702 0.61519 anti-matrix GLA 0.0412 0.0072 0.0022 0.0112

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var28 var29 var30 var31 varll 0.82693 0.79726 0.15830 0.26228 anti-prothrombin <.0001 0.0002 0.5582 0.3264

16 16 16 16 varl2 0.08805 0.10882 0.37052 0.31991 anti-Factor IX 0.7457 0.6883 0.1577 0.2271

16 16 16 16 varl3 0.37279 0.38861 0.37669 0.38391 anti-Fetuin B 0.1550 0.1369 0.1504 0.1421

16 16 16 16 varl4 0.52514 0.00164 0.95814 0.93780 anti-CD40 0.0367 0.9952 <.0001 <.0001

16 16 16 16 varlS 0.67260 0.13611 0.92988 0.92070 anti-myeloperoxidase 0.0043 0.6152 <.0001 <.0001

16 16 16 16 varl6 0.07964 0.06183 0.42521 0.37951 vanti-Fibronectin 0.7694 0.8200 0.1006 0.1471

16 16 16 16 varl7 0.23914 0.24512 0.46595 0.43651 anti-Factor VII 0.3724 0.3602 0.0689 0.0909

16 16 16 16 varl8 0.17162 0.15208 0.39338 0.36798 anti-tissue factor 0.5251 0.5739 0.1317 0.1608

16 16 16 16 varl9 0.12142 -0.03540 0.46982 0.40176 anti-human complement 5b-9 0.6542 0.8964 0.0663 0.1229

16 16 16 16 var20 -0.07436 -0.07019 0.28790 0.26105 anti-human CRP 0.7843 0.7962 0.2796 0.3288 16 16 16 16 var21 0.5B061 0.28654 0.33086 0.37979 anti-matrix GLA 0.0184 0.2819 0.2107 0.1468

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 varll 0.32157 0.27248 0.22301 -0.13829 anti-prothrombin 0.2245 0.3073 0.4064 0.6095

16 IS 16 16 varl2 -0.13910 0.98495 0.93321 0.63897 anti-Factor IX 0.6074 ■=.0001 <.0001 0.0077

16 16 16 16 varl3 -0.07111 0.90296 0.83381 0.39639 anti-Fetuin B 0.7936 <.0001 <.0001 0.1285

16 16 16 16 varl4 0.40537 0.12098 0.13351 -0.00392 anti-CD40 0.1193 0.6554 0.6220 0.9885

16 16 16 16 varl5 0.34295 0.29782 0.29197 0.00390 anti-myeloperoxidase 0.1935 0.2626 0.2725 0.9886

16 16 16 16 varl6 -0.23721 0.91899 0.86813 0.53005 vanti-Fibronectin 0.3764 <.0001 <.0001 0.0347

16 16 16 16 varl7 -0.08381 0.99141 0.91958 0.56212 anti-Factor VII 0.7576 <.0001 <.0001 0.0234

16 16 16 16 varl8 -0.11789 0.98356 0.92746 0.57768 anti-tissue factor 0.6637 <.0001 <.0001 0.0191

16 16 16 16 varl9 -0.05027 0.92935 0.95168 0.65004 anti-human complement 5b-9 0.8533 <.0001 <.0001 0.0064

16 16 16 16 var20 -0.24971 0.90342 0.86670 0.58044 anti-human CRP 0.3510 <.0001 <.0001 0.0184

16 .16 16 16 var21 0.14430 0.60755 0.65640 0.14383 anti-matrix GLA 0.5939 0.0125 0.0057 0.5951

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39 varll 0.07474 0.30097 0.42187 0.16455 anti-prothrombin 0.7833 0.2573 0.1036 0.5425

16 16 16 16 varl2 0.98050 0.96202 0.45428 0.99792 anti-Factor IX <.0001 <.0001 0.0771 <.0001

16 16 16 16 varl3 0.81799 0.90874 0.52545 0.87162 anti-Fetuin B 0.0001 <.0001 0.0366 <.0001

16 16 16 16 varl4 0.23153 0.15683 0.00683 0.13734 anti-CD40 0.3882 0.5619 0.9800 0.6120

16 16 16 16 varl5 0.36299 0.34273 0.27770 0.29281 anti-myeloperoxidase 0.1S70 0.1938 0.2977 0.2711

16 16 16 16 varl6 0.91241 0.92033 0.39490 0.93118 vanti-Fibronectin <.0001 <.0001 0.1301 <.0001

16 16 16 16 varl7 0.95236 0.98065 0.45461 0.98502 anti-Factor VII ■=.0001 <-0001 0.0769 <.0001

16 16 16 16 varlδ 0.95380 0.99114 0.51036 0.98262 anti-tissue factor <.0001 <.0001 0.0434 <,0001

16 16 16 16 varl9 0.99820 0.91303 0.41354 0.96490 anti-human complement 5b-9 <.0001 <.0001 0.1113 <.0001

16 16 16 16 var20 0.89933 0.93873 0.37579 0.92196 anti-human CRP <.0001 <.0001 0.1514 <.0001

16 16 16 16 var21 0.56697 0.67566 0.62267 0.57268 anti-matrix GLA 0.0220 0.0041 0.0100 0.0204

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var40 var41 var42 var43 varll 0.60398 0.48652 0.08540 -0.01204 anti-prothrombin 0.0132 0.0560 0.7532 0.9647

16 16 IS 16 varl2 0.76375 0.81505 0.90646 0.94230 anti-Factor IX 0.0006 0.0001 <.0001 <.0001

16 16 16 16 varl3 0.85893 0.98466 0.77665 0.74645 anti-Fetuin B <.0001 <.0O01 0.0004 0.0009

16 16 16 16 varl4 0.02003 0.12320 0.07917 0.11691 anti-CD40 0.9413 0.6494 0.7707 0.6663

16 16 16 16 varl5 0.27707 0.33588 0.20781 0.27490 anti-myeloperoxidase 0.2989 0.2034 0.4399 0.3028

16 16 16 16 varl6 0.66993 0.73280 0.79247 0.86661 vanti-Fibronectin 0.0045 0.0012 0.0003 <.0001

16 16 16 16 varl7 0.80773 0.86068 0.88242 0.90233 anti-Factor VII 0.0002 <.0001 <.0001 <.0001

16 16 16 16 varl8 0.79686 0.85753 0.86085 0.90742 anti-tissue factor 0.0002 <.0001 <.0001 <.0001

16 16 16 16 varl9 0.66042 0.76957 0.88585 0.94065 anti-human complement 5b-9 0.0054 0.0005 <.0001 <.0001

16 16 16 16 var20 0.61439 0.73685 0.78852 0.87232 anti-human CRP 0.0113 0.0011 0.0003 <-0001 16 IS 16 16 var21 0. 70797 0.92621 0. 47473 0.46987 anti-matrix GLA 0.0021 <.0001 0.0632 0.0663 16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 varll -0.16726 0.22172 0.43601 0.75698 anti-prothrombin 0.5358 0.4092 0.0914 0.0007

16 16 16 16 varl2 0.33641 0.138S3 0.75109 0.34627 anti-Factor IX 0.2027 0.6086 0.0008 0.1889

16 16 16 16 varl3 0.22438 0.20930 0.74007 0.71016 anti-Fetuin B 0.4035 0.4366 0.0010 0.0021

16 16 16 16 varl4 -0.06278 0.91176 -0.00820 0.03253 anti-CD40 0.8173 <.0001 0.9759 0.9048

16 16 16 16 varl5 -0.21443 0.87709 0.25678 0.23233 anti-myeloperoxidase 0.4252 <.0001 0.3370 0.3866

16 16 16 16 varl6 0.23453 0.30727 0.63315 0.26150 vanti-Fibronectin 0.3819 0.2470 0.0085 0.3279

16 16 16 16 varl7 0.27476 0.24720 0.74875 0.43840 anti-Factor VII 0.3031 0.3560 0.0008 0.0894

16 16 16 16 varl8 0.28198 0.18215 0.77357 0.42833 anti-tissue factor 0.2900 0.4996 0.0004 0.0979

16 16 16 16 varl9 0.35948 0.22513 0.72003 0.28133 anti-human complement 5b-9 0.1715 0.4018 0.0017 0.2912

16 16 16 16 var20 0.30347 0.07759 0.64043 0.23912 anti-human CRP 0.2532 0.7752 0.0075 0.3724

16 16 16 16 var21 0.14157 0.24338 0.67953 0.89086 anti-matrix GIA 0.6010 0.3637 0.0038 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var49 var50 varSl var52 varll 0.74985 0.51525 0.16622 0.22668 anti-prothrombin 0.0008 0.0411 0.5384 0.3985

16 16 16 16 varl2 0.45538 0.78830 0.86583 0.95919 anti-Factor IX 0.0763 0.0003 <.0001 <.0001

16 16 16 16 varl3 0.81796 0.82512 0.77849 0.87891 anti-Fetuin B 0.0001 <.0001 0.0004 <.0001

IS 16 16 16 varl4 0.00259 0.06330 0.33714 0.10145 anti-CD40 0.9924 0.8158 0.2016 0.7085

16 16 16 16 varl5 0.23144 0.21895 0.49767 0.28965 anti-myeloperoxidase 0.3884 0.4152 0.0498 0.2765

16 16 16 16 varlS 0.36389 0.69980 0.89864 0.92978 vanti-Fibronectin 0.1659 0.0025 <.0001 <.0001

16 16 16 16 varl7 0.54486 0.84959 0.90391 0.95897 anti-Factor VII 0.0291 <.O001 <.0001 ■c.OOOl

16 16 16 16 varl8 0.51891 0.78341 0.89368 0.98978 anti-tissue factor 0.0394 0.0003 <.0001 <.0001

16 16 16 16 varl9 0.39417 0.68151 0.82222 0.89904 anti-human complement 5b-9 0.1309 0.0036 <.0001 <.0001

16 16 16 16 var20 0.32529 0.62551 0.86467 0.96273 anti-human CRP 0.2189 0.0096 <.0001 <.0001

16 16 16 16 var21 0.93764 0.49789 0.49407 0.64028 anti-matrix GIA <.0001 0.0497 0.0517 0.0075

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var53 var54 var55 var56 varll -0.00729 0.51270 0.66477 0.44546 anti-prothrombin 0.9786 0.0423 0.0050 0.0838

16 16 16 16 varl2 0.89977 0.11732 0.62440 0.83955 anti-Factor IX <.0001 0.6652 0.0097 <.0001

16 16 16 16 varl3 0.73528 0.31116 0.75163 0.84071 anti-Fetuin B 0.0012 0.2408 0.0008 <.0001

16 16 16 16 varl4 0.45892 -0.10351 -0.02055 0.05527 anti-CD40 0.0738 0.7028 0.9398 0.8389

16 16 16 16 varlS 0.53804 -0.03914 0.25511 0.21003 anti-myeloperoxidase 0.0316 0.8856 0.3403 0.4349

16 16 16 16 varl6 0.91169 0.16219 0.52854 0.74659 vanti-Fibronectin <.0001 0.5484 0.0353 0.0009

16 16 16 16 varl7 0.89930 0.23649 0.67429 0.88291 anti-Factor VII <.0001 0.3779 0.0042 <.0001

16 16 16 16 varlδ 0.91148 0.20430 0.66347 0.82448 anti-tissue factor <.0001 0.4479 0.0051 <.0001

16 16 16 16 varl9 0.91950 -0.06604 0.51565 0.74048 anti-human complement 5b-9 <.0001 0.8080 0.0409 0.0010 is 16 16 IS var20 0.91554 0.18158 0.45481 0.67681 anti-human CRP <.0001 0.5009 0.0767 0.0040

IS 16 16 16 var21 0.49335 0.13307 0.65958 0.49753 anti-matrix GLA 0.0521 0.6232 0.0054 0.0499

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var57 var58 var59 var60 varll 0.62708 0.61759 0.67062 0.55119 anti-prothrombin 0.0093 0.0108 0.0045 0.0269

16 16 16 16 varl2 0.52562 0.48868 0.73594 0.67821 anti-Factor IX 0.0365 0.0548 0.0012 0.0039

16 16 16 16 varl3 0.76332 0.77498 0.85378 0.75491 anti-Fetuin B O.OOOS 0.0004 <.0001 0.0007

16 16 16 16 varl4 0.06398 0.32614 0.17704 0.02053 anti-CD40 0.8139 0.2177 0.5119 0.9399

16 16 16 16 varl5 0.34104 0.56383 0.40781 0.16203 anti-myeloperoxidase 0.1961 0.0229 0.1169 0.5488

16 16 16 16 variε 0.45311 0.47465 0.66951 0.59197 vanti-Fibronectin 0.0780 0.0632 0.0046 0.0157

16 16 16 16 varl7 0.57520 0.59516 0.80243 0.75149 anti-Factor VII 0.0197 0.0150 0.0002 0.0008

16 16 16 16 varl8 0.58563 0.57377 0.78448 0.67462 anti-tissue factor 0.0171 0.0201 0.0003 0.0041

16 16 16 16 varl9 0.52259 0.44263 0.73373 0.55135 anti-human complement 5b-9 0.0378 0.0860 0.0012 0.0268

16 16 16 16 var20 0.41117 0.40976 0.61897 0.50703 anti-human CRP 0.1136 0.1150 0.0106 0.0450

16 16 16 16 var21 0.93372 0.84607 0.84044 0.43133 anti-matrix GIiA <.0001 <.0001 <-0001 0.0953

16 16 16 16

Pearson Correlation Coefficients Prob > |r] under HO: Rho=0 Number of Observations var61 var62 var63 var64 varll 0.38848 0.55262 0.41270 0.07530 anti-prothrombin 0.1370 0.0264 0.1121 0.7817

16 16 16 16 varl2 0.85565 0.70974 0.91899 0.99501 anti-Factor IX <.0001 0.0021 <.0001 <.0001

16 16 16 16 varl3 0.825S5 0.82780 0.96728 0.83476 anti-Fetuin B <-0001 <.0001 <.0001 <.0001

16 16 16 16 varl4 0.23724 0.20422 0.14700 0.10338 anti-CD40 0.37S3 0.4481 0.5870 0.7032

16 16 16 16 varl5 0.40091 0.41789 0.37340 0.24730 anti-myeloperoxidase 0.1238 0.1072 0.1543 0.3558

16 16 16 IS varl6 0.78682 0.64443 0.83962 0.93208 vanti-Fibronectin 0.0003 0.0070 <.0001 <.0001

16 16 16 16 varl7 0.87694 0.75035 0.93913 0.96279 anti-Factor VII <.0001 0.0008 <.0001 <.0001

16 16 16 16 varl8 0.85881 0.74488 0.94442 0.97633 anti-tissue factor <.0001 0.0009 <.0001 <.0001

16 IS 16 16 varl9 0.89284 0.74650 0.88991 0.96930 anti-human complement 5b- <.0001 0.0009 <.0001 <.0001

16 16 16 16 var20 0.74284 0.59106 0.82516 0.94536 anti-human CRP 0.0010 0.0159 <.0001 <.0001

16 16 16 16 var21 0.70785 0.87662 0.85304 0.54132 anti-matrix GLA 0.0022 <.0001 <.0001 0.0303

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 var67 var68 varll 0.32148 0.41788 -0.12295 0.28796 anti-prothrombin 0.2247 0.1073 0.6501 0.2795

16 16 16 16 varl2 0.81185 0.87477 0.61679 0.68076 anti-Factor IX 0.0001 <.0001 0.0109 0.0037

16 16 16 16 varl3 0.86723 0.90574 0.54280 0.63080 anti-Fetuin B <.0001 <.0001 0.0298 0.0088

16 16 16 16 varl4 0.13009 0.17852 -0.07247 -0.04889 anti-CD40 0.6311 0.5083 0.7897 0.8573

16 16 16 16 varl5 0.28841 0.39021 0.13983 0.25971 anti-myeloperoxidase 0.2787 0.1351 0.6055 0.3314

16 16 16 16 varl6 0.72328 0.78802 0.53706 0.512S0 vanti-Fibronectin 0.0015 0.0003 0.0319 0.0423

16 16 16 16 varl7 0.82242 0.88724 0.57283 0.68478 anti-Factor VII <.0001 <-0001 0.0204 0.0034

16 16 16 16 varl8 0.81097 0.88911 0.59441 0.68035 anti-tissue factor 0.0001 <.0001 0.0152 0.0037

16 16 16 16 varl9 0.81231 0.88985 0.57943 0.63805 anti-human complement 5b-9 0.0001 <.0001 0.0187 0.0078

16 16 16 16 var20 0.S9255 0.75683 0.59244 0.56903 anti-human CRP 0.0029 0.0007 0.0156 0.0214

16 16 16 16 var21 0.80335 0.83926 0.36744 0.47412 anti-matrix GlA 0.0002 <.0001 0.1615 0.0635

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var69 var70 var71 var72 varll -0.14467 0.52735 0.53343 0.56131 anti-prothrombin 0.5929 0.0358 0.0333 0.0237

16 16 16 16 varl2 0.02136 0.58554 0.60999 0.84298 anti-Factor IX 0.9374 0.0172 0.0121 <.0001

16 16 16 16 varl3 0.05276 0.88222 0.88359 0.93997 anti-Fetuin B 0.8461 <.0001 <.0001 <.0001

16 16 16 16 varl4 -0.12048 0.04499 0.05231 0.19567 anti-CD40 0.6567 0.8686 0.8474 0.4677

16 16 16 16 varl5 -0.30785 0.27441 0.28576 0.44217 anti-myeloperoxidase 0.2461 0.3037 0.2833 0.0864

16 16 16 16 varlδ -0.04334 0.50985 0.52495 0.77323 vanti-Fibroneσtin 0.8734 0.0436 0.0368 0.0004

16 16 16 16 varl7 -0.00357 0.64988 0.66178 0.91075 anti-Factor VII 0.9895 0.0064 0.0052 <.0001

16 16 16 16 varlδ -0.01090 0.64786 0.65806 0.89750 anti-tissue factor 0.9680 0.0067 0.0056 <.0001

16 16 16 16 varl9 0.02177 0.51604 0.56163 0.78679 anti-human complement 5b-9 0.9362 0.0407 0.0236 0.0003

16 16 16 16 var20 0.02165 0.52308 0.50688 0.76413 anti-human CRP 0.9366 0.0376 0.0451 0.0006

16 16 16 16 var21 0.10728 0.92718 0.95053 0.81840 anti-matrix GLA 0.6925 <.0001 <.0001 0.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var74 var75 var76 var77 varll 0.73061 0.80934 0.79478 0.42272 anti-prothrombin 0.0013 0.0001 0.0002 0.1028

16 16 16 16 varl2 0.43762 0.56604 0.55961 0.44101 anti-Factor IX 0.0900 0.0223 0.0242 0.0873 is 16 16 16 varl3 0.80426 0.87246 0-87311 0.69810 anti-Fetuin B 0.0002 <.0001 <-0001 0.0026

16 16 16 16 varl4 0.11001 0.10048 0.11127 0.22494 anti-CD40 0.6851 0.7112 0.6816 0.4023

16 16 16 16 varl5 0.34622 0.34367 0.35154 0.36223 anti-myeloperoxidase 0.1890 0.1925 0.1818 0.1680

16 16 16 16 varlδ 0.36799 0.48110 0.47763 0.43650 vanti-Fibronectin 0.1608 0.0592 0.0613 0.0909

16 16 16 16 varl7 0.53769 0.67662 0.67179 0.52593 anti-Factor VII 0.0317 0.0040 0.0044 0.0364

16 16 16 16 varl8 0.52524 0.63523 0.63172 0.51696 anti-tissue factor 0.0367 0.0082 0.0087 0.0403

16 16 16 16 varl9 0.38440 0.47099 0.46544 0.38149 anti-human complement 5b-9 0.1415 0.0656 0.0692 0.1448

16 16 16 16 var20 0.35149 0.42577 0.42849 0.42877 anti-human CRP 0.1819 0.1001 0.0977 0.0975

16 16 16 16 var21 0.95978 0.86533 0.87340 0.75787 anti-matrix GIA <.0001 <.0001 <.0001 0.0007

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 var81 varll 0.11622 0.71412 0.73756 -0.06200 anti-prothrombin 0.6682 0.0019 0.0011 0.8405

16 16 16 13 varl2 0.79527 0.33210 0.52599 0.65660 anti-Factor IX 0.0002 0.2089 0.0364 0.0148

16 16 16 13 varl3 0.71497 0.69272 0.85821 0.52857 anti-Fetuin B 0.0019 0.0029 <.0001 0.0633

16 16 16 13 varl4 0.50326 0.07602 0.10254 0.15805 anti-CD40 0.0469 0.7796 0.7055 0.6061

16 16 16 13 varl5 0.59035 0.30459 0.35054 0.29365 anti-myeloperoxidase 0.0161 0.2514 0.1831 0.3302

16 16 16 13 varl6 0.85528 0.27119 0.44790 0.79691 vanti-Fibronectin <.0001 0.3096 0.0819 0.0011

16 16 16 13 varl7 0.84006 0.42274 0.62217 0.65764 anti-Factor VII <.0001 0.1028 0.0101 0.0146

16 16 16 13 varl8 0.85031 0.42984 0.60672 0.73338 anti-tissue factor <.0001 0.0966 0.0127 0.0043

16 16 16 13 varl9 0.78820 0.2S669 0.46019 0.61900 anti-human complement 5b-9 0.0003 0.3181 0.0729 0.0241

16 16 16 13 var20 0.867S2 0.26034 0.42630 0.86955 anti-human CRP <.0001 0.3301 0.0996 0.0001

16 16 16 13 var21 0.50976 0.89180 0.95676 0.38922 anti-matrix GLA 0.0437 <-0001 <.0001 0.1887

16 16 16 13

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var82 var83 var84 var85 varll 0.48047 0.74094 0.62320 0.84541 anti-prothrombin 0.0965 0.0038 0.0229 0.0003

13 13 13 13 varl2 0.58147 0.78973 0.76447 0.54763 anti-Factor IX 0.0371 0.0013 0.0023 0.0527

13 13 13 13 varl3 0.74321 0.93526 0.83087 0.85037 anti-Petuin B 0.0036 <.0001 0.0004 0.0002

13 13 13 13 varl4 0.01497 0.06883 0.02500 0.08346 anti-CD40 0.9613 0.8232 0.9354 0.7863

13 13 13 13 varl5 0.18582 0.31994 0.20383 0.32036 anti-myeloperoxidase 0.5433 0.2866 0.5042 0.2859

13 13 13 13 varlδ 0.47235 0.69515 0.67323 0.46406 vanti-Fibronectin 0.1031 0.0083 0.0117 0.1102

13 13 13 13 varl7 0.59570 0.86010 0.82954 0.65197 anti-Factor VII 0.0317 0.0002 0.0005 0.0157

13 13 13 13 varl8 0.61132 0.82209 0.75999 0.61289 anti-tissue factor 0.0264 0.0006 0.0026 0.0259

13 13 13 13 varl9 0.54441 0.68372 0.65436 0.43053 anti-human complement 5b-9 0.0544 0.0100 0.0152 0.1420

13 13 13 13 var20 0.47022 0.63508 0.59523 0.41630 anti-human CRP 0.1049 0.0197 0.0319 0.1571

13 13 13 13 var21 0.88600 0.81126 0.55610 0.87178 anti-matrix GLA <.0001 0.0008 0.0484 0.0001

13 13 13 13

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var86 var87 var88 var89 varll 0 .56056 0 .44995 -0 .04510 0 .30534 anti-prothrombin 0.0239 0.0924 0.8732 0.2684

16 15 15 15 varl2 0 .34180 0 .46955 0 .27249 0 .94643 anti-Factor Ix 0.1951 0.0774 0.3258 <.0001

16 15 15 15 varl3 0.70S10 0.76052 0.24316 0.88401 anti-Fetuin B 0.0022 0.0010 0.3825 <.0001

16 15 15 15 varl4 0.03169 -0.11296 -0.10412 0.07838 anti-CD40 0.9073 0.6885 0.7119 0.7813

16 15 15 15 varl5 0.10780 0.05410 -0.06559 0.24146 anti-myeloperoxidase 0.6911 0.8481 0.8163 0.3860

16 15 15 15 varl6 0.23497 0.32721 0.38832 0.85475 vanti-Fibronectin 0.3810 0.2339 0.1526 <.0001

16 15 15 15 varl₇ 0.40447 0.50226 0.28902 0.95925 anti-Factor VII 0.1202 0.0564 0.2961 <.0001

16 15 15 15 varl8 0.37087 0.48021 0.38347 0.92392 anti-tissue factor 0.1573 0.0700 0.1583 <.0001

16 15 15 15 varl9 0.30424 0.37976 0.16249 0.87793 anti-human complement 5b-9 0.2519 0.1627 0.5629 <.0001

16 15 15 15 var20 0.19825 0.31319 0.58513 0.80639 anti-human CRP 0.4617 0.2557 0.0219 0.0003

16 15 15 15 var21 0.85636 0.77212 0.14609 0.54597 anti-matrix GLA <.0001 0.0007 0.6034 0.0352

16 15 15 15

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var90 var91 var92 var93 varll -0.01375 0.35659 0.40558 0.04830 anti-prothrombin 0.9612 0.1920 0.1191 0.8590

15 15 16 16 varl2 0.92726 0.93549 0.85985 0.99001 anti-Factor IX <.0001 <.0001 <.0001 <.0001

15 15 16 16 varl3 0.72997 0.93149 0.88703 0.81880 anti-Fetuin B 0.0020 <.0001 <.0001 0.0001

15 15 16 16 varl4 0.40661 0.21533 0.04224 0.17569 anti-CD40 0.1326 0.4409 0.8766 0.5151

15 15 16 16 varl5 0.49882 0.39060 0.20077 0.30888 anti-myeloperoxidase 0.0584 0.1500 0.4559 0.2444

15 15 16 16 varl6 0.92471 0.86142 0.78859 0.92812 vanti-Fibronectin <.0001 <.0001 0.0003 ■c.OOOl

15 15 16 16 varl7 0.90355 0.95866 0.90290 0.95522 anti-Factor VII <.0001 <.0001 <.0001 <.0001

15 15 16 16 varl8 0.89337 0.93764 0.86536 0.96613 anti-tissue factor <.0001 <.0001 <.0001 <.0001 15 15 16 16 varl9 0.96844 0.92907 0.74990 0.98995 anti-human complement 5b-9 <.0001 <.0001 0.0008 <.0001

15 15 16 16 var20 0.83621 0.81715 0.75626 0.92874 anti-human CRP 0.0001 0.0002 0.0007 <.0001

IS 15 16 16 var21 0.46146 0.75722 0.57468 0.54815 anti-matrix GIA 0.0834 0.0011 0.0199 0.0279

15 15 16 16

Capture varl var2 var3 var22 0.21537 0.25789 0.39993 0.37305 anti-CD61 0.4231 0.3349 0.1248 0.1547

16 16 16 16 var23 0.41533 0.46120 0.52797 0.48608 anti-Kappa Light Chain 0.1096 0.0722 0.0355 0.0563

16 16 16 16 var24 0.46976 0.58079 0.89027 0.88540 anti-Macrophage 0.0664 0.0183 <.0001 <.0001

16 16 16 16 var25 0.61302 0.74698 0.99224 0.99314 anti-factor XIIIA 0.0116 0.0009 <.0001 <.0001

16 16 16 16 var26 0.66343 0.80077 0.99203 0.96453 anti-hsp 60 0.0051 0.0002 <.0001 <.0001

16 16 16 16 var27 0.58715 0.72483 0.98986 0.99690 anti-fibrillin-1 0.0168 0.0015 <.0001 <.0001

16 16 16 16 var28 0.54689 0.53057 0.21140 0.08364 anti-B2 microgl 0.0284 0.0345 0.4319 0.7581

16 16 16 16 var29 0.57128 0.49230 0.10049 0.04146 anti-CD 18 0.0208 0.0527 0.7112 0.8788

16 16 16 16 var30 0.29338 0.39162 0.46122 0.42606 anti-1aminin 0.2701 0.1336 0.0722 0.0999

16 16 16 16 var31 0.35605 0.43030 0.42276 0.38843 anti-antitrypsin 0.1759 0.0962 0.1028 0.1371

16 16 16 16 var32 -0.06698 0.06560 -0.06241 -0.16035 anti-Notch-1 0.8053 0.8093 0.8184 0.5530

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var4 var5 var6 var7 var22 0.38151 0.36635 0.26629 0.24225 anti-CD61 0.1448 0.1628 0.3188 0.36S0

16 16 16 16 var23 0.49693 0.74506 0.40273 0.90335 anti-Kappa Light Chain 0.0502 0.0009 0.1220 <.0001

16 16 16 16 var24 0.89062 0.34946 0.47073 0.41264 anti-Macrophage <.0001 0.1846 0.0657 0.1122

16 16 16 16 var25 0.99360 0.40201 0.61145 0.51384 anti-factor XIIIA <.0001 0.1227 0.0118 0.0417

16 16 16 16 var26 0.97699 0.49105 0.66429 0.53450 anti-hsp 60 ■c.OOOl 0.0534 0.0050 0.0329

16 16 16 16 var27 0.99862 0.33755 0.58375 0.47275 anti-fibrillin-1 <.0001 0.2010 0.0176 0.0644

16 16 16 16 var28 0.12816 0.89012 0.52671 0.43907 anti-B2 microgl 0.6362 <.0001 0.0361 0.0889

16 16 16 16 var29 0.05860 0.55910 0.30744 0.01747 anti-CD 18 0.8293 0.0243 0.2467 0.9488

16 16 16 16 var30 0.43513 0.73362 0.34039 0.97764 anti-laminin 0.0921 0.0012 0.1970 <.0001

16 16 16 16 var31 0.39298 0.79589 0.39268 0.93324 anti-antitrypsin 0.1321 0.0002 0.1324 <.0001

16 16 16 16 var32 0.11793 0.44092 0.05534 0.30892 anti-Notch-1 0.6636 0.0874 0.8387 0.2443

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var8 var9 varlO varll var22 0.25991 0.35075 0.37088 0.15682 anti-CD61 0.3310 0.1829 0.1573 0.5619

16 16 16 16 var23 0.86217 0.44674 0.50100 0.26293 anti-Kappa Light Chain <.0001 0.0828 0.0481 0.3252

16 16 16 16 var24 0.49953 0.87154 0.88663 0.12901 anti-Macrophage 0.0488 <.0001 <.0001 0.6340

16 16 16 16 var25 0.68161 0.97139 0.99240 0.18856 anti-factor XIIIA 0.0036 <.0001 <.0001 0.4843

16 16 16 16 var26 0.71667 0.96222 0.97365 0.29769 anti-hsp 60 0.0018 <.0001 <.0001 0.2628

16 16 16 16 var27 0.62376 0.98317 0.99802 0.13348 anti-fibrillin-1 0.0098 <.0001 <.0001 0.6221

16 16 16 16 var28 0.67164 0.12094 0.11438 0.82693 anti-B2 microgl 0.0044 0.6555 0.6732 •=.0001

16 16 16 16 var29 0.26612 0.17435 0.05671 0.79726 anti-CD 18 0.3191 0.5184 0.8348 0.0002

16 16 16 IS var30 0 .87649 0 .37080 0 .43926 0 .15830 anti-laminin <.0001 0.1574 0.0887 0.5582

16 16 16 16 var31 0 .91061 0 .32715 0 .39483 0 .26228 anti-antitrypsin <.0001 0.2161 0.1302 0.3264

16 16 16 16 var32 0 .26533 -0 .14116 -0 .12839 0 .32157 anti-Notch-1 0.3206 0.6021 0.6356 0.2245

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl2 varl3 varl4 varlδ var22 0.36071 0.31378 0.16735 0.37312 anti-CD61 0.1699 0.2366 0.5356 0.1546

16 16 16 16 var23 0.43977 0.46081 0.87312 0.91216 anti-Kappa Light Chain 0.0883 0.0724 <.0001 <.0001

16 16 16 16 var24 0.88227 0.73338 0.17368 0.37979 anti-Macrophage <.0001 0.0012 0.5200 0.1468

16 16 16 16 var25 0.97522 0.87530 0.25680 0.41191 anti-factor XIIIA <.0001 <.0001 0.3370 0.1129

16 16 16 16 var26 0.96218 0.90334 0.29098 0.46862 anti-hsp 60 <.0001 <-0001 0.2742 0.0671

16 16 16 16 var27 0.98860 0.86957 0.19812 0.35540 anti-fibrillin-1 <.0001 <.0001 0.4620 0.1767

16 16 16 16 var28 0.08805 0.37279 0.52514 0.67260 anti-B2 microgl 0.7457 0.1550 0.0367 0.0043

16 16 16 16 var29 0.10882 0.38861 0.00164 0.13611 anti-CD 18 0.6883 0.1369 0.9952 0.6152

16 16 16 16 var30 0.37052 0.37669 0.95814 0.92988 anti-laminin 0.1577 0.1504 <.0001 <.0001

16 16 16 16 var31 0.31991 0.38391 0.93780 0.92070 anti-antitrypsin 0.2271 0.1421 <.0001 <.0001

16 16 16 16 var32 -0.13910 -0.07111 0.40537 0.34295 anti-Notch-1 0.6074 0.7936 0.1193 0.1935

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varlS varl7 varlδ varl9 var22 0.33273 0.39401 0.37584 0.38078 anti-CD61 0.2079 0.1310 0.1514 0.1457

16 16 16 16 var23 0.45662 0.54324 0.46279 0.52607 anti-Kappa Light Chain 0.0754 0.0297 0.0711 0.0363

16 16 16 16 var24 0.79898 0.87614 0.88430 0.87265 anti-Macrophage 0.0002 ■=.0001 <.0001 <.0001

16 16 16 16 var25 0.93930 0.97890 0.99054 0.95941 anti-factor XIIIA <.0001 <.0001 <.0001 <.0001

16 16 16 16 var26 0.90979 0.98003 0.97832 0.95390 anti-hsp 60 <.0001 <.0001 <.0001 <.0001

16 16 16 16 var27 0.94775 0.97691 0.99207 0.96645 anti-fibrillin-1 <.0001 <-0001 ■ς.0001 <.0001

16 16 16 16 var28 0.07964 0.23914 0.17162 0.12142 anti-B2 microgl 0.7694 0.3724 0.5251 0.6542

16 16 16 16 var29 0.06183 0.24512 0.15208 -0.03540 anti-CD 18 0.8200 0.3602 0.5739 0.8964

16 16 16 16 var30 0.42521 0.46595 0.39338 0.46982 anti-laminin 0.1006 0.0689 0.1317 0.0663

16 16 16 16 var31 0.37951 0.43651 0.36798 0.40176 anti-antitrypsin 0.1471 0.0909 0.1608 0.1229

16 16 16 16 var32 0.23721 -0.08381 -0.11789 -0.05027 anti-Notch-1 0.3764 0.7576 0.6637 0.8533

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var20 var21 var22 var23 var22 0.30351 0.29536 1.00000 0.41255 anti-CD61 0.2531 0.2667 0.1123

16 16 16 16 var23 0.32727 0.40286 0.41255 1.00000 anti-Kappa Light Chain 0.2160 0.1218 0.1123

16 16 16 16 var24 0.83034 0.51509 0.66760 0.51163 anti-Macrophage <.0001 0.0412 0.0047 0.0428

16 16 16 16 var25 0.94827 0.64331 0.37370 0.53359 anti-factor XIIIA <.0001 0.0072 0.1539 0.0333

16 16 16 16 var26 0.89075 0.70702 0.39789 0.56801 anti-hsp 60 <.0001 . 0.0022 0.1269 0.0217

16 16 16 16 var27 0.95630 0.61519 0.35949 0.48217 anti-fibrillin-1 <.0001 0.0112 0.1715 0.0586

16 16 16 16 var28 -0.07436 0.58061 0.24475 0.62876 anti-B2 microgl 0.7843 0.0184 0.3609 0.0091

16 16 16 16 var29 0.07019 0.28654 -0.01121 0.17911 anti-CD 18 0.7962 0.2819 0.9671 0.5069

IS 16 16 16 var30 0.28790 0.33086 0.24651 0.94210 anti-laminin 0.2796 0.2107 0.3574 ■c.OOOl

16 16 16 16 var31 0.26105 0.37979 0.22491 0.93636 anti-antitrypsin 0.3288 0.1468 0.4023 <.0001

16 16 16 16 var32 0.24971 0.14430 -0.08537 0.23586 anti-Notch-1 0.3510 0.5939 0.7533 0.3792

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var24 var25 var26 var27 var22 0.66760 0.37370 0.39789 0.35949 anti-CD61 0.0047 0.1539 0.1269 0.1715

16 16 16 16 var23 0.51163 0.53359 0.56801 0.48217 anti-Kappa Light Chain 0.0428 0.0333 0.0217 0.0586

16 16 16 16 var24 1.00000 0.87973 0.86309 0.88120 anti-Macrophage <.0001 <.0001 <.0001

16 16 16 16 var25 0.87973 1.00000 0.98636 0.99368 anti-factor XIIIA <.0001 <.0001 <.0001

16 16 16 16 var26 0.86309 0.98636 1.00000 0.97210 anti-hsp 60 <.0001 <.0001 <-0001

16 16 16 16 var27 0.88120 0.99368 0.97210 1.00000 anti-fibrillin-1 <.0001 <.0001 <.0001

16 16 16 16 var28 0.14267 0.18091 0.29753 0.10606 anti-B2 microgl 0.5981 0.5025 0.2631 0.6959

16 16 16 16 var29 0.01606 0.08426 0.15491 0.06273 anti-CD 18 0.9529 0.7564 0.5668 0.8175

16 16 16 16 var30 0.36284 0.48089 0.51630 0.42673 anti-laminin 0.1672 0.0593 0.0406 0.0993

16 16 16 16 var31 0.31905 0.44961 0.48647 0.38661 anti-antitrypsin 0.2284 0.0806 0.0560 0.1391

16 16 16 16 var32 -0.19289 -0.08228 0.01862 -0.14179 anti-Notch-1 0.4741 0.7620 0.9454 0.6004

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var28 var29 var30 var31 var22 0.24475 -0.01121 ^■0.24651 0.22491 anti-CD61 0.3609 0.9671 0.3574 0.4023

16 16 16 16 var23 0.62876 0.17911 0.94210 0.93636 anti-Kappa Light Chain 0.0091 0.5069 <.0001 <.0001

16 16 16 16 var24 0.14267 0.01606 0.36284 0.31905 anti-Macrophage 0.5981 0.9529 0.1672 0.2284

16 16 16 16 var25 0.18091 0.08426 0.48089 0.44961 anti-factor XIIIA 0.5025 0.7564 0.0593 0.0806

16 16 16 IS var26 0.29753 0.15491 0.51630 0.48647 anti-hsp 60 0.2631 0.5668 0.0406 0.0560

16 16 16 16 var27 0.10606 0.06273 0.42673 0.38661 anti-fibrillin-1 0.6959 0.8175 0.0993 0.1391

16 16 16 16 var28 1.00000 0.53483 0.57063 0.65267 anti-B2 microgl 0.0328 0.0210 0.0061

16 16 16 16 var29 0.53483 1.00000 0.12037 0.19633 anti-CD 18 0.0328 0.6570 0.4662

16 16 16 16 var30 0.57063 0.12037 1.00000 0.98338 anti-laminin 0.0210 0.6570 <.0001

16 16 16 16 var31 0.65267 0.19633 0.98338 1.00000 anti-antitrypsin 0.00S1 0.4662 <.0001

16 16 16 16 var32 0.55190 0.09054 0.36006 0.39789 anti-Notch-1 0.0267 0.7388 0.1707 0.1269

16 16 16 16

Pearson Correlation Coefficients Prob :> I r I under HO : RhO=O Number of Observations var32 var33 var34 var35 var22 -0.08537 0.34704 0.39055 0.082S4 anti-CD61 0.7533 0.1879 0.1348 0.7612

16 16 16 16 var23 0.23586 0.44914 0.44007 0.14353 anti-Kappa Light Chain 0.3792 0.0809 0.0880 0.5959

16 16 16 16 var24 -0.19289 0.86026 0.84110 0.43600 anti-Macrophage 0.4741 <.0001 <.0001 0.0914

16 16 16 16 var25 -0.08228 0.96413 0.93306 0.57323 anti-factor XIIIA 0.7620 <.0001 <.0001 0.0203

16 16 16 16 var26 0.01862 0.95517 0.93686 0.54811 anti-hsp 60 0.9454 <.0001 <.0001 0.0279

16 16 16 16 var27 -0.14179 0.97225 0.92755 0.60544 anti-fibrillin-1 0.6004 <.0001 <.0001 0.0129

16 16 16 16 var28 0.55190 0.15417 0.18694 -0.18905 anti-B2 microgl 0.0267 0.5686 0.4882 0.4832

16 16 16 16 var29 0.09054 0.26345 -0.01452 -0.14470 anti-CD 18 0.7388 0.3242 0.9574 0.5929

16 16 16 16 var30 0.36006 0.36737 0.34083 0.11391 anti-laminin 0.1707 0.1616 0.1964 0.6745

16 16 16 16 var31 0.39789 0.33736 0.30279 0.05073 anti-antitrypsin 0.1269 0.2013 0.2543 0.8520

IS 16 16 16 var32 1.00000 -0.15118 -0.05345 0.06710 anti-Notch-1 0.5762 0.8441 0.8050

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39 var22 0.38364 0.38385 0.27271 0.34896 anti-CD61 0.1424 0.1422 0.3068 0.1853

16 16 16 16 var23 0.49407 0.47127 0.15488 0.44512 anti-Kappa Light Chain 0.0518 0.0654 0.5668 0.0840

16 16 16 16 var24 0.87830 0.86531 0.45692 0.87408 anti-Macrophage <.0001 <.0001 0.0752 <.0001

16 16 16 16 var25 0.96503 0.98412 0.45509 0.97309 anti-factor XIIIA <.0001 <.0001 0.0765 <.0001

16 16 16 16 var26 0.95738 0.97468 0.50708 0.95756 anti-hsp 60 <.0001 <.0001 0.0450 <.0001

16 16 16 16 var27 0.97301 0.97556 0.46042 0.98571 anti-fibril1in-1 <-0001 <.0001 0.0727 <.0001

16 16 16 16 var28 0.09271 0.20770 0.43198 0.08346 anti-B2 microgl 0.7327 0.4402 0.0947 0.7586

16 16 16 16 var29 -0.03140 0.20438 0.20193 0.14173 anti-CD 18 0.9081 0.4477 0.4533 0.6006

16 16 16 16 var30 0.43686 0.39787 0.13902 0.37286 anti-laminin 0.0907 0.1270 0.6076 0.1549

16 16 16 16 var31 0 .36980 0.38696 0.16325 0.32490 anti-antitrypsin 0.1586 0.1387 0.5458 0.2195

16 16 16 16 var32 -0 .07404 -0.11429 0.25820 -0.15869 anti-Notch-1 0.7852 0.6734 0.3343 0.5572

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var40 var41 var42 var43 var22 0.27382 0.32330 0.51333 0.58487 anti-CD61 0.3048 0.2219 0.0420 0.0173

16 16 16 16 var23 0.31802 0.44440 0.39253 0.41908 anti-Kappa Light Chain 0.2300 0.0846 0.1326 0.1062

16 16 16 16 var24 0.65172 0.69826 0.83966 0.93812 anti-Macrophage 0.0062 0.0026 <.0001 <.0001

16 16 16 16 var25 0.73285 0.84151 0.84762 0.90312 anti-factor XIIIA 0.0012 ■=.0001 ■c.OOOl <.0001

16 16 16 16 var26 0.77735 0.87401 0.83824 0.87982 anti-hsp 60 0.0004 <.0001 ς.OOOl <.0001

16 16 16 16 var27 0.73723 0.83100 0.87163 0.92579 anti-fibrillin-1 0.0011 ■=.0001 ς.OOOl <.0001

16 16 16 16 var28 0.42984 0.40174 -0.00173 -0.02820 anti-B2 microgl 0.0966 0.1230 0.9949 0.9174

16 16 16 16 var29 0.58575 0.31503 0.10311 -0.06297 anti-CD 18 0.0171 0.2347 0.7039 0.8168

16 16 16 16 var30 0.25350 0.36940 0.28943 0.31844 anti-laminin 0.3435 0.1591 0.2769 0.2294

16 16 16 16 var31 0.27059 0.38484 0.21567 0.24384 anti-antitrypsin 0.3108 0.1410 0.4224 0.3628

16 16 16 16 var32 0.05325 -0.04759 -0.20127 -0.21857 anti-Notch-1 0.8447 0.8S11 0.4548 0.4161

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 var22 -0.02318 0.12040 0.37343 0.22206 anti-CD61 0.9321 0.6569 0.1542 0.4085

16 16 16 16 var23 0.03432 0.81032 0.31643 0.26387 anti-Kappa Light Chain 0.8996 0.0001 0.2325 0.3234

16 16 16 16 var24 0.18753 0.10917 0.73097 0.29990 anti-Macrophage 0.4868 0.6873 0.0013 0.2591

16 16 16 16 var25 0.29354 0.25829 0.72439 0.38558 anti-factor XIIIA 0.2698 0.3341 0.0015 0.1402

16 16 16 16 var26 0.26701 0.30156 0.75436 0.46756 anti-hsp 60 0.3175 0.2564 0.0007 0.0678

16 16 16 16 var27 0.30991 0.20321 0.73183 0.35658 anti-fibrillin-1 0.2428 0.4503 0.0013 0.1752 16 16 16 16 var28 0.16207 0.62380 0.37651 0.67969 anti-B2 microgl 0.5487 0.0098 0.1505 0.0038

16 16 16 16 var29 0.15529 0.19585 0.18601 0.53903 anti-CD 18 0.5658 0.4673 0.4904 0.0312

16 16 16 16 var30 0.03930 0.91040 0.17721 0.20989 anti-1aminin 0.8851 <-0001 0.5115 0.4353

16 16 16 16 var31 0.00522 0.91505 0.19549 0.29548 anti-antitrypsin 0.9847 <.000l 0.4681 0.2665

16 16 16 16 var32 0.21549 0.327S2 0.09473 0.26500 anti-Notch-1 0.4228 0.2156 0.7271 0.3213

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var49 varSO var51 var52 var22 0.17383 0.21688 0.52676 0.33094 anti-CD61 0.5197 0.4198 0.0360 0.2106

16 16 16 16 var23 0.31423 0.39226 0.61892 0.40017 anti-Kappa Light Chain 0.2359 0.1329 0.0106 0.1246

16 16 16 16 var24 0.35097 0.62911 0.86729 0.85371 anti-Macrophage 0.1826 0.0090 <.0001 <.0001

16 16 16 16 var25 0.48041 0.74082 0.90336 0.97463 anti-factor XIIIA 0.0596 0.0010 <.0001 <.0001

16 16 16 16 var26 0.55695 0.76214 0.87233 0.94907 anti-hsp 60 0.0250 0.0006 <.0001 <.0001

16 16 16 16 var27 0.45813 0.74109 0.89602 0.97795 anti-fibrillin-1 0.0743 0.0010 •=.0001 <.0001

16 16 16 16 var28 0.62362 0.27241 0.16820 0.12842 anti-B2 microgl 0.0098 0.3074 0.5335 0.6355

16 16 16 16 var29 0.53210 0.66159 0.20016 0.15670 anti-CD 18 0.0339 0.0053 0.4573 0.5622

16 16 16 16 var30 0.21456 0.29931 0.53798 0.34163 anti-laminin 0.4249 0.2601 0.0316 0.1953

16 16 16 16 var31 0.28601 0.29635 0.51459 0.33011 anti-antitrypsin 0.2829 0.2651 0.0414 0.2118

16 16 16 16 var32 0.10982 -0.11374 -0.29282 -0.15691 anti-Notch-1 0.6856 0.6749 0.2711 0.5617

16 16 16 16

Pearson Correlation Coefficients Prob > | r| under HO : RhO=O Number of Observations var53 var54 var55 var5β var22 0.34213 -0.09464 0.24944 0.22494 anti-CDSl 0.1946 0.7274 0.3515 0.4023

16 16 16 16 var23 0.63373 0.04480 0.25135 0.38417 anti-Kappa Light Chain 0.0084 0.8691 0.3477 0.1418

16 16 16 16 var24 0.82281 0.02942 0.54073 0.67551 anti-Macrophage <.0001 0.9139 0.0306 0.0041

16 16 16 16 var25 0.95139 0.15948 0.58716 0.78264 anti-factor XIIIA <.0001 0.5552 0.0168 0.0003

16 16 16 16 var2S 0.91751 0.14194 0.64760 0.79702 anti-hsp 60 <.0001 0.6000 0.0067 0.0002

16 16 16 16 var27 0.94240 0.13294 0.59109 0.79080 anti-fibrillin-1 <.0001 0.6236 0.0159 0.0003

16 16 16 16 var28 0.12246 0.17927 0.49238 0.21602 anti-B2 microgl 0.6514 0.5065 0.0527 0.4217

16 16 16 16 var29 -0.06106 0.76639 0.64050 0.59164 anti-CD 18 0.8223 0.0005 0.0075 0.0158

16 16 16 16 var30 0.63377 0.01292 0.18810 0.29522 anti-1aminin 0.0084 0.9621 0.4854 0.2670

16 16 16 16 var31 0.58898 0.11505 0.21661 0.27810 anti-antitrypsin 0.0164 0.6714 0.4204 0.2970

16 16 16 16 var32 -0.05715 -0.20487 0.13109 -0.14091 anti-Notch-1 0.8335 0.4466 0.6284 0.6027

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var57 var58 var59 var60 var22 0.29462 0.21692 0.40463 0.14342 anti-CD61 0.2680 0.4197 0.1200 0.5962

16 16 16 16 var23 0.37058 0.60158 0.50236 0.33199 anti-Kappa Light Chain 0.1577 0.0137 0.0474 0.2090

16 16 16 16 var24 0.48215 0.44511 0.67769 0.51345 anti-Macrophage 0.0586 0.0840 0.0039 0.0419

16 16 16 16 var25 0.55904 0.56862 0.77415 0.62279 anti-factor XIIIA 0.0244 0.0215 0.0004 0.0100

16 16 16 16 var26 0.63228 0.62135 0.83905 0.64657 anti-hsp 60 0.0086 0.0102 <.0001 0.0068

16 16 16 16 var27 0.53890 0.53531 0.73388 0.62478 anti-fibrillin-1 0.0312 0.0326 0.0012 0.0097

16 16 16 16 var28 0.62S45 0.66042 0.61188 0.27318 anti-B2 microgl 0.0094 0.0054 0.0118 0.3060

16 16 16 16 var29 0.24026 0.47712 0.32020 0.76254 anti-CD 18 0.3701 0.0617 0.2266 0.0006

16 16 16 16 var30 0.25531 0.52320 0.37758 0.24385 anti-laminin 0.3399 0.0376 0.1494 0.3628

16 16 16 16 var31 0.30454 0.58180 0.40682 0.25247 anti-antitrypsin 0.2515 0.0181 0.1179 0.3455

16 16 16 16 var32 0.19535 0.06370 0.17611 -0.12495 anti-Notch-1 0.4684 0.8147 0.5141 0.6447

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var61 var62 var63 var64 var22 0.40634 0.40248 0.38460 0.33089 anti-CD61 0.1183 0.1222 0.1413 0.2106

16 16 16 16 var23 0.53714 0.47376 0.47851 0.39220 anti-Kappa Light Chain 0.0319 0.0638 0.0608 0.1330

16 16 16 16 var24 0.77604 0.65030 0.81767 0.87107 anti-Macrophage 0.0004 0.0064 0.0001 <.0001

16 16 16 16 var25 0.87119 0.74619 0.92749 0.96934 anti-factor XIIIA <.0001 0.0009 <.0001 <.0001

16 16 16 16 var26 0.90743 0.81597 0.95255 0.94312 anti-hsp 60 <.0001 0.0001 <.0001 <-0001

16 16 16 16 var27 0.84650 0.71363 0.92365 0.98718 anti-fibrillin-1 <.0001 0.0019 <.0001 <.0001

16 16 16 16 var28 0.38825 0.56782 0.36179 0.00400 anti-B2 microgl 0.1373 0.0218 0.1685 0.9883

16 16 16 16 var29 0.09001 0.14421 0.22794 0.03748 anti-CD 18 0.7403 0.5942 0.3959 0.8904

16 16 16 16 var30 0.42825 0.38008 0.39461 0.32971 anti-laminin 0.0979 0.1465 0.1304 0.2124

16 16 16 16 var31 0.40472 0.38601 0.38756 0.27582 anti-antitrypsin 0.1200 0.1397 0.1380 0.3011

16 16 16 16 var32 0.08377 0.17657 -0.01028 -0.17696 anti-Notch-1 0.7577 0.5130 0.9698 0.5121

16 16 16 16 Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 varS6 var67 varδβ var22 0.28951 0.40822 0.28597 0.47689 anti-CD61 0.2768 0.1165 0.2829 0.0618

16 IS 16 16 var23 0.4757S 0.47283 0.25046 0.32901 anti-Kappa Light Chain 0.0625 0.0644 0.3495 0.2134

IS 16 -16 16 var24 0.69820 0.78845 0.58568 0.72257 anti-Macrophage 0.0026 0.0003 0.0171 0.0016

16 16 16 16 var25 0.80563 0.88287 0.57325 0.64678 anti-factor XIIIA 0.0002 <.0001 0.0203 0.0068

16 16 16 16 var26 0.82757 0.92672 0.52746 0.67135 anti-hsp εo <.0001 ■c.OOOl 0.0358 0.0044

16 16 16 16 var27 0.80614 0.87102 0.62351 0.65394 anti-fibrillin-1 0.0002 <.0001 0.0099 0.0060

16 16 16 16 var28 0.32674 0.40956 -0.17081 0.16420 anti-B2 microgl 0.2168 0.1152 0.5271 0.5434

16 16 16 16 var29 0.13972 0.12485 -0.08778 0.16111 anti-CD 18 0.6058 0.6450 0.7465 0.5511

16 16 16 16 var30 0.37485 0.38881 0.11340 0.13694 anti-laminin 0.1526 0.1367 0.6758 0.6131

16 16 16 16 var31 0.37037 0.36939 0.07338 0.11746 anti-antitrypsin 0.1579 0.1591 0.7871 0.6648

16 16 16 16 var32 0.05781 0.07932 -0.40034 -0.09636 anti-Notch-1 0.8316 0.7703 0.1244 0.7226

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var69 var70 var71 var72 var22 -0.04982 0.20565 0.21673 0.50831 anti-CD61 0.8546 0.4448 0.4201 0.0444

16 16 16 16 var23 -0.07514 0.36143 0.37019 0.54559 anti-Kappa Light Chain 0.7821 0.1690 0.1581 0.0288

16 16 16 16 var24 -0.01632 0.47125 0.49907 0.80477 anti-Macrophage 0.9522 0.0654 0.0491 0.0002

16 16 16 16 var25 -0.00277 0.62094 0.62795 0.88124 anti-factor XIIIA 0.9919 0.0103 0.0092 <.0001

16 16 16 16 var26 -0.02433 0.S5707 0.67456 0.91710 anti-hsp 60 0.9287 0.0057 0.0042 <.0001

16 16 16 16 var27 0.00476 0.61487 0.62615 0.85460 anti-fibrillin-1 0.9860 0.0113 0.0095 <.0001

16 16 16 16 var28 0.11775 0.43094 0.47471 0.47191 anti-B2 microgl 0.6641 0.0956 0.0632 0.0650

16 16 16 16 var29 0.07612 0.38816 0.35087 0.40126 anti-CD 18 0.7793 0.1374 0.1827 0.1235

16 16 16 16 var30 0.05449 0.27936 0.28579 0.43645 anti-1aminin 0.8411 0.2947 0.2833 0.0910

16 16 16 16 var31 0.03480 0.32948 0.32729 0.45442 anti-antitrypsin 0.8982 0.2127 0.2159 0.0770

16 16 16 16 var32 0.19049 -0.07057 0.00714 0.00418 anti-Notch-1 0.4798 0.7951 0.9791 0.9878

16 • 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var74 var75 var76 var77 var22 0.27408 0.25279 0.28089 0.12496 anti-CD61 0.3043 0.3449 0.2920 0.6447

16 16 16 16 var23 0.38757 0.42549 0.42965 0.49909 anti-Kappa Light Chain 0.1380 0.1004 0.0967 0.0491

16 16 16 16 var24 0.39007 0.47632 0.47975 0.38345 anti-Macrophage 0.1353 0.0622 0.0600 0.1426

16 16 16 16 var25 0.49981 0.59027 0.58972 0.51624 anti-factor XIIIA 0.0487 0.0161 0.0162 0.0406

16 16 16 16 var26 0.57436 0.66022 0.65849 0.52604 anti-hsp 60 0.0200 0.0054 0.0055 0.0363

16 16 16 16 var27 0.46607 0.56387 0.56222 0.49485 anti-fibrillin-1 0.0688 0.0229 0.0234 0.0513

16 16 16 16 var28 0.67016 0.65566 0.64894 0.46085 anti-B2 microgl 0.0045 0.0058 0.0065 0.0724

16 16 16 16 var29 0.48158 0.70844 0.69568 0.36963 anti-CD 18 0.0589 0.0021 0.0028 0.1588

16 16 16 16 var30 0.30589 0.32558 0.33665 0.43507 anti-laminin 0.2492 0.2185 0.2023 0.0921

16 16 16 16 var31 0.38207 0.39411 0.40391 0.50848 anti-antitrypsin 0.1442 0.1309 0.1208 0.0443

16 16 16 16 var32 0.13563 0.08541 0.08062 0.02011 anti-Notch-1 0.6165 0.7531 0.7666 0.9411

16 16 16 16 Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var78 var79 var80 varδl var22 0.31054 0.203S3 0.28317 0.30684 anti-CD61 0.2418 0.4496 0.2879 0.3079

16 16 16 13 var23 0.68348 0.28704 0.40430 0.32168 anti-Kappa Light Chain 0.0035 0.2811 0.1204 0.2838

16 16 16 13 var24 0.73429 0.30063 0.45887 0.64069 anti-Macrophage 0.0012 0.2579 0.0738 0.0183

16 16 16 13 var25 0.89379 0.39160 0.57354 0.75980 anti-factor XIIIA <.0001 0.1336 0.0202 0.0026

16 16 16 13 var26 0.85524 0.46587 0.64315 0.69004 anti-hsp 60 <.0001 0.0690 0.0072 0.0090

16 16 16 13 var27 0.86565 0.36281 0.54586 0.74362 anti-fibrillin-1 <.0001 0.1672 0.0287 0.0036

16 16 16 13 var28 0.22928 0.67326 0.65255 -0.08034 anti-B2 microgl 0.3930 0.0043 0.0061 0.7942

16 16 16 13 var29 0.06561 0.48866 0.52424 -0.16507 anti-CD 18 0.8092 0.0548 0.0371 0.5900

16 16 16 13 var30 0.67583 0.24523 0.31718 0.30240 anti-laminin 0.0041 0.3600 0.2313 0.3153

16 16 16 13 var31 0.67640 0.33280 0.39030 0.30984 anti-antitrypsin 0.0040 0.2078 0.1350 0.3029

16 16 16 13 var32 0.07247 0.22819 0.12247 -0.35933 anti-Notch-1 0.7897 0.3953 0.6514 0.2279

16 16 16 13

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var82 var83 var84 var85 var22 0.22772 0.26621 0.19408 0.22301 anti-CD61 0.4543 0.3793 0.5252 0.4640

13 13 13 13 var23 0.25043 0.42017 0.37841 0.36884 anti-Kappa Light Chain 0.4092 0.1529 0.2023 0.2149

13 13 13 13 var24 0.50640 0.65650 0.59977 0.44385 anti-Macrophage 0.0774 0.0148 0.0303 0.1287

13 13 13 13 var25 0.57854 0.77360 0.71544 0.56577 anti-factor XIIIA 0.0383 0.0019 0.0060 0.0439

13 13 13 13 var26 0.63416 0.82640 0.74754 0.63719 an.ti-b.sp 60 0.0199 0.0005 0.0033 0.0192

13 13 13 13 var27 0.57667 0.76547 0.71446 •0.54498 anti-fibrillin-1 0.0391 0.0023 0.0061 0.0541

13 13 13 13 var28 0.47768 0.52272 0.32356 0.65713 anti-B2 microgl 0.0988 0.0668 0.2809 0.0147

13 13 13 13 var29 0.24791 0.64874 0.67284 0.73526 anti-CD 18 0.4141 0.0165 0.0117 0.0042

13 13 13 13 var30 0.22648 0.32738 0.26638 0.31167 anti-laminin 0.4568 0.2749 0.3790 0.2999

13 13 13 13 var31 0.25167 0.34773 0.26635 0.36828 anti-antitrypsia 0.4068 0.2443 0.3791 0.2157

13 13 13 13 var32 0.30626 0.01168 -0.13013 0.08622 anti-Notch-1 0.3088 0.9698 0.6718 0.7794

13 13 13 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var86 var87 var88 var89 var22 0.05963 0.07123 -0.01943 0.28179 anti-CD61 0.8264 0.8009 0.9452 0.3089

16 15 15 15 var23 0.23780 0.10912 -0.04305 0.40914 anti-Kappa Light Chain 0.3751 0.6987 0.8789 0.1299

16 15 15 15 var24 0.21783 0.31953 0.23308 0.79133 anti-Macrophage 0.4177 0.2457 0.4031 0.0004

16 15 15 15 var25 0.34017 0.42678 0.38751 0.89479 anti-factor XIIIA 0.1973 0.1126 0.1536 <.0001

16 15 15 15 var26 0.40451 0.48423 0.29364 0.89956 anti-hsp 60 0.1202 0.0674 0.2881 <.0001

16 15 15 15 var27 0.33571 0.44580 0.36860 0.90855 anti-fibrillin-1 0.2037 0.0958 0.1764 <.0001

16 15 15 15 var28 0.48755 0.29018 -0.20129 0.13548 anti-B2 microgl 0.0554 0.2941 0.4719 0.6302

16 15 15 15 var29 0.40572 0.48447 -0.03521 0.38106 anti-CD 18 0.1190 0.0672 0.9009 0.1611

16 15 15 15 var30 0.15923 0.09587 -0.01090 0.32655 anti-laminin 0.5558 0.7340 0.9692 0.2349

16 15 15 15 var31 0.21697 0.10963 0.06935 0.28539 anti-antitrypsin 0.4196 0.6973 0.8060 0.3025 16 15 15 15 var32 0.09605 0.00141 -0.26377 -0.13603 anti-Notch-1 0.7235 0.9960 0.3422 0.6288

16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var90 var91 var92 var93 var22 0.34787 0.35555 0.21047 0.35786 anti-CD61 0.2039 0.1934 0.4340 0.1735

15 15 16 16 var23 0.59281 0.55086 0.38958 0.44471 anti-Kappa Light Chain 0.0199 0.0333 0.1358 0.0844

15 15 16 16 var24 0.81509 0.81524 0.69475 0.88083 anti-Macrophage 0.0002 0.0002 0.0028 <.0001

15 15 16 16 var25 0.92104 0.93846 0.82751 0.96984 anti-factor XIIIA <.0001 <.0001 <.0001 <.0001

15 15 16 16 var26 0.91406 0.96348 0.82293 0.94976 anti-hsp 60 <.0001 <.0001 <.0001 <.0001

15 15 16 16 var27 0.92859 0.92813 0.83603 0.98437 anti-fibrillin-1 <.0001 <.0001 <.0001 <.0001

15 15 16 16 var28 0.10430 0.32557 0.18775 0.03568 anti-B2 microgl 0.7114 0.2364 0.4862 0.8956

15 15 16 16 var29 -0.05699 0.20112 0.53809 -0.02353 anti-CD 18 0.8401 0.4723 0.0315 0.9311

15 15 16 16 var30 0.58160 0.45893 0.30412 0.38924 anti-laminin 0.0230 0.0853 0.2521 0.1362

15 15 16 16 var31 0.49631 0.43517 0.30531 0.32536 anti-antitrypsin 0.0599 0.1050 0.2502 0.2188

15 15 16 16 var32 -0.03387 0.03050 -0.18950 -0.12895 anti-Notch-1 0.9046 0.9141 0.4821 0.6341

15 15 16 16

Capture varl var2 var3 var33 0.65841 0.77003 0.96906 0.96654 anti-BSA 0.0056 0.0005 <.0001 <.0001

16 16 16 16 var34 0.60363 0.70955 0.95087 0.92782 anti-LBP 0.0133 0.0021 <.0001 <.0001

16 16 16 16 var35 0.07772 0.25857 0.57869 0.60340 anti-PTX3 0.7748 0.3336 0.0188 0.0133

16 16 16 16 var3S 0.50372 0.66261 0.97807 0.96763 anti-complement C5 0.0467 0.0052 <.0001 <.0001

16 16 16 16 var37 0.69009 0.79671 0.97580 0.97655 anti-fibrinogen 0.0031 0.0002 <.0001 <.0001

16 16 16 16 var38 0.37031 0.52970 0.49388 0.41161 anti-D-Dimer 0.1580 0.0348 0.0519 0.1132

16 16 16 16 var39 0.59148 0.71951 0.97935 0.98118 anti-factor V 0.0158 0.0017 <.0001 <.0001

16 16 16 16 var40 0.71298 0.82790 0.75182 0.70055 anti-human gamma-Gla 0.0019 <.0001 0.0006 0.0025

16 16 16 16 var41 0.88746 0.97162 0.85852 0.80681 anti-TF-VIIa <.0001 <.0001 <.0001 0.0002

16 16 16 16 var42 0.47842 0.62818 0.86629 0.86555 anti-complement C3c 0.0608 0.0092 <.0001 <.0001

16 16 IS 16 var43 0.41587 0.56614 0.91864 0.92626 anti-Complement C4 0.1091 0.0222 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var4 var5 var6 var7 var33 0.97197 0.36622 0.57620 0.39922 anti-BSA <.0001 0.1S30 0.0195 0.1256

16 16 16 16 var34 0.94046 0.26377 0.59200 0.36591 anti-LBP <.0001 0.3236 0.0157 0.1634

16 16 16 16 var35 0.61061 -0.0939S 0.08403 0.20732 anti-PTX3 0.0120 0.7293 0.7570 0.4410

16 16 16 16 var36 0.98091 0.27642 0.51641 0.50034 anti-complement C5 <.0001 0.3000 0.0406 0.0484

16 16 16 16 var37 0.97352 0.41830 0.64895 0.41141 anti-fibrinogen <.0001 0.1069 0.0065 0.1134

16 16 16 16 var38 0.46439 0.54893 0.52695 0.14459 anti-D-Dimer 0.0700 0.0277 0.0360 0.5932

16 16 16 16 var39 0.98705 0.29504 0.53743 0.42224 anti-factor V <.0001 0.2673 0.0318 0.1033

16 16 16 16 var40 0.73614 0.60405 0.65865 0.24298 anti-human gamma-Gla 0.0011 0.0132 0.0055 0.3645

16 16 16 16 var41 0.82823 0.54333 0.92353 0.32507 anti-TF-VIIa <.0001 0.0296 <.0001 0.2193

16 16 16 16 var42 0.87736 0.20110 0.45404 0.35220 anti-complement C3c <.0001 0.4552 0.0773 0.1809

16 16 16 16 var43 0.9337S 0.19627 0.42876 0.39611 anti-Complement C4 <.0001 0.4663 0.0975 0.1288

16 16 16 ie

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var8 var9 varlO varll var33 0.58095 0.99365 0.97282 0.27248 anti-BSA 0.0183 <.0001 <-0001 0.3073

16 16 16 16 var34 0.55675 0.92864 0.94101 0.22301 anti-LBP 0.0251 <.0001 <.0001 0.4064

16 16 16 16 var35 0.12530 0.62035 0.61538 -0.13829 anti-PTX3 0.6438 0.0104 0.0112 0.6095

16 16 16 16 var36 0.57206 0.96882 0.98274 0.07474 anti-complement CS 0.0206 <.O001 <.0001 0.7833

16 16 16 16 var37 0.65306 0.96756 0.97110 0.30097 anti-fibrinogen 0.0061 <.0001 <.0001 0.2573

16 16 16 16 var38 0.35461 0.44673 0.43407 0.42187 anti-D-Dimer 0.1778 0.0828 0.0930 0.1036

16 16 16 16 var39 0.55581 0.99848 0.98936 0.16455 anti-factor V 0.0254 <.0001 <.0001 0.5425

16 16 16 16 var40 0.52423 0.78834 0.72223 0.60398 anti-human gamma-Gla 0.0371 0.0003 0.0016 0.0132

16 16 16 16 var41 0.70764 0.83422 0.82004 0.48652 anti-TF-VIIa 0.0022 <.0001 0.0001 0.0560

16 16 16 16 var42 0.40104 0.90526 0.88148 0.08540 anti-complement C3c 0.1237 <.0001 <.0001 0.7532

16 16 16 16 var43 0.43000 0.92716 0.93429 -0.01204 anti-Complement C4 0.0964 <.0001 <.O001 0.9647

16 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations varl2 varl3 varl4 varl5 var33 0.98495 0.90296 0.12098 0.29782 anti-BSA <.0001 <.0001 0.6554 0.2626

16 16 16 16 var34 0.93321 0.83381 0.13351 0.29197 anti-LBP <.0001 <.0001 0.6220 0.2725

16 16 16 16 var35 0.63897 0.39639 -0.00392 0.00390 anti-PTX3 0.0077 0.1285 0.9885 0.9886 16 16 16 16 var36 0.98050 0.81799 0.23153 0.36299 anti-complement C5 ■c.OOOl 0.0001 0.3882 0.1670

16 16 16 16 var37 0.96202 0.90874 0.15683 0.34273 anti-fibrinogen <.0001 ■c.OOOl 0.5619 0.1938

16 16 16 16 var38 0.45428 0.52545 0.00683 0.27770 anti-D-Dimer 0.0771 0.0366 0.9800 0.2977

16 16 16 16 var39 0.99792 0.87162 0.13734 0.29281 anti-factor V <.0001 <.0001 0.6120 0.2711

16 16 IS 16 var40 0.76375 0.85893 0.02003 0.27707 anti-human gamma-Gla 0.0006 <.0001 0.9413 0.2989

16 16 16 16 var41 0.81505 0.98466 0.12320 0.33588 anti-TF-VIIa 0.0001 <.0001 0.6494 0.2034

16 16 16 16 var42 0.90646 0.77S65 0.07917 0.20781 anti-complement C3c <.0O01 0.0004 0.7707 0.4399

16 16 16 16 var43 0.94230 0.74645 0.11691 0.27490 anti-Complement C4 <.0001 0.0009 0.6663 0.3028

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varl6 varl7 varl8 varl9 var33 0.91899 0.99141 0.98356 0.92935 anti-BSA ^■e.OOOl ■=.0001 <.0001 <.0001

16 16 16 16 var34 0.86813 0.91958 0.92746 0.95168 anti-LBP <.0001 <-0001 <.0001 <-0001

16 16 16 16 var35 0.53005 0.56212 0.57768 0.65004 anti-PTX3 0.0347 0.0234 0.0191 0.0064

16 16 16 16 var36 0.91241 0.95236 0.95380 0.99820 anti-complement C5 <.0001 <.0001 <.0001 <.0001

16 16 16 16 var37 0.92033 0.98065 0.99114 0.91303 anti-fibrinogen <.0001 <.0001 <.0001 <.0001

16 16 16 16 var38 0.39490 0.45461 0.51036 0.41354 anti-D-Dimer 0.1301 0.0769 0.0434 0.1113

16 16 16 16 var39 0.93118 0.98502 0.98262 0.96490 anti-factor V <.0001 <.0001 ^.0001 <.0001

16 16 16 16 var40 0.66993 0.80773 0.79686 0.66042 anti-human gamma-Gla 0.0045 0.0002 0.0002 0.0054

16 16 16 16 var41 0.73280 0.86068 0.85753 0.76957 anti-TF-VIIa 0.0012 <.0001 <.0001 0.0005

16 16 16 16 var42 0.79247 0.88242 0.86085 0.88585 anti-complement C3c 0.0003 <.0001 <-0001 <-0001

16 IS 16 16 var43 0.86S61 0.90233 0.90742 0.94065 anti-Complement C4 <.0001 <.0001 <-0001 <.0001

IS 16 16 16

Pearson Correlation Coefficients Prob > ]r| under HO: Rho=0 Number of Observations var20 var21 var22 var23 var33 0.90342 0.60755 0.34704 0.44914 anti-BSA <.0001 0.0125 0.1879 0.0809

16 16 16 16 var34 0.8S670 0.65640 0.39055 0.44007 anti-LBP <.0001 0.0057 0.1348 0.0880

16 16 16 16 var35 0.58044 0.14383 0.08254 0.14353 anti-PTX3 0.0184 0.5951 0.7612 0.5959

16 16 16 16 var36 0.89933 0.56697 0.38364 0.49407 anti-complement C5 <.0001 0.0220 0.1424 0.0518

16 16 16 16 var37 0.93873 0.67566 0.38385 0.47127 anti-fibrinogen <.0001 0.0041 0.1422 0.0654

16 16 16 16 var38 0.37579 0.62267 0.27271 0.15488 anti-D-Dimer 0.1514 0.0100 0.3068 0.5668

16 16 16 16 var39 0.92196 0.57268 0.34896 0.44512 anti-factor V <.0001 0.0204 0.1853 0.0840

16 16 16 16 var40 0.61439 0.70797 0.27382 0.31802 anti-human gamma-Gla 0.0113 0.0021 0.3048 0.2300

16 16 16 16 var41 0.73685 0.92621 0.32330 0.44440 anti-TF-VIIa 0.0011 <.0001 0.2219 0.0846

16 16 16 16 var42 0.78852 0.47473 0.51333 0.39253 anti-complement C3c 0.0003 0.0632 0.0420 0.1326

16 16 16 16 var43 0.87232 0.46987 0.58487 0.41908 anti-Complement C4 ■c.OOOl 0.0663 0.0173 0.1062

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var24 var25 var26 var27 var33 0 .8602S 0 .96413 0 .95517 0 .97225 anti-BSA <.0001 <.0001 <-0001 <.0001

16 16 16 16 var34 0 .84110 0 .93306 0 .93686 0 .92755 anti-LBP <.0001 <.0001 <-0001 <.0001

16 16 16 16 var35 0 .43600 0 .57323 0 .54811 0 .60544 anti-PTX3 0.0914 0.0203 0.0279 0.0129

16 16 16 16 var3S 0.87830 0.96503 0.95738 0.97301 anti-complement C5 <.0001 <.0001 <.0001 <.0001

IS 16 16 16 var37 0.86531 0.98412 0.97468 0.97556 anti- fibrinogen <.0001 <.0001 <.0001 <.0001

16 16 16 16 var38 0.45692 0.45509 0.50708 0.46042 anti-D-Dimer 0.0752 0.0765 0.0450 0.0727

16 16 16 16 var39 0.87408 0.97309 0.95756 0.98571 anti-factor V <.0001 <.0001 <.0001 <.0001

16 16 16 16 var40 0.65172 0.73285 0.77735 0.73723 anti-human gamma-Gla 0.0062 0.0012 0.0004 0.0011

16 16 16 16 var41 0.69826 0.84151 0.87401 0.83100 anti-TF-VIIa 0.0026 <.0001 <.0001 <.0001

16 16 16 16 var42 0.83966 0.84762 0.83824 0.87163 anti-complement C3c <.0001 <.0001 <-0001 <.0001

16 16 16 16 var43 0.93812 0.90312 0.87982 0.92579 anti-Complement C4 <.0001 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var28 var29 var30 var31 var33 0.15417 0.26345 0.36737 0.33736 anti-BSA 0.5686 0.3242 0.1616 0.2013

16 16 16 16 var34 0.18694 -0.01452 0.34083 0.30279 anti-LBP 0.4882 0.9574 0.1964 0.2543

16 16 16 16 var35 -0.18905 -0.14470 0.11391 0.05073 anti-PTX3 0.4832 0.5929 0.6745 0.8520

16 16 ^' 16 16 var36 0.09271 -0.03140 0.43686 0.36980 anti-complement C5 0.7327 0.9081 0.0907 0.1586

16 16 16 16 var37 0.20770 0.20438 0.39787 0.38696 anti-fibrinogen 0.4402 0.4477 0.1270 0.1387

16 16 16 16 var38 0.43198 0.20193 0.13902 0.16325 anti-D-Dimer 0.0947 0.4533 0.6076 0.5458

16 16 16 16 var39 0.08346 0.14173 0.37286 0.32490 anti-factor V 0.7586 0.6006 0.1549 0.2195

16 16 16 16 var40 0.42984 0.58575 0.25350 0.27059 anti-human gamma-Gla 0.0966 0.0171 0.3435 0.3108

16 16 16 16 var41 0.40174 0.31503 0.36940 0.38484 anti-TF-VIIa 0.1230 0.2347 0.1591 0.1410 16 16 IS 16 var42 0.00173 0.10311 0 .28943 0.21567 anti-complement C3c 0.9949 0.7039 0.2769 0.4224

16 16 16 16 var43 0.02820 -0.06297 0 .31844 0.24384 anti-Complement C4 0.9174 0.8168 0.2294 0.3628

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 var33 -0.15118 1.00000 0.90263 0.58931 anti-BSA 0.5762 <.0001 0.0163

16 16 16 16 var34 -0.05345 0.90263 1.00000 0.59678 anti-LBP 0.8441 <.0001 0.0147

16 16 IS 16 var35 0.06710 0.58931 0.59678 1.00000 anti-PTX3 0.8050 0.0163 0.0147

16 16 16 16 var36 -0.07404 0.93879 0.95493 0.65301 anti-complement C5 0.7852 <.0001 <.0001 0.0061

16 IS 16 16 var37 -0.11429 0.97600 0.91889 0.53575 anti-fibrinogen 0.6734 <.0001 <.0001 0.0324

16 16 16 16 var38 0.25820 0.44657 0.37895 0.23044 anti-D-Dimer 0.3343 0.0829 0.1478 0.3905

16 16 16 16 var39 -0.15869 0.99072 0.92735 0.63144 anti-factor V 0.5572 <.0001 <-0001 0.0087

16 16 16 16 var40 0.05325 0.82049 0.63486 0.37297 anti-human gamma-Gla 0.8447 <.0001 0.0082 0.1548

16 16 16 16 var41 -0.04759 0.83869 0.80805 0.34345 anti-TF-VIla 0.8611 <.0001 0.0002 0.1928

16 16 16 16 var42 -0.20127 0.88805 0.83457 0.71507 anti-complement C3c 0.4548 <.0001 <.0001 0.0018

16 16 16 16 var43 -0.21857 0.90006 0.88567 0.S2157 anti-Complement C4 0.4161 <.0001 <.0001 0.0102

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39 var33 0.93879 0.97600 0.44657 0.99072 anti-BSA <.0001 <.0001 0.0829 <.0001

16 16 16 16 var34 0.95493 0.91889 0.37895 0.92735 anti-LBP <.0001 <.0001 0.1478 <.0001

16 16 16 16 var35 0.65301 0.53575 0.23044 0.63144 anti-PTX3 0.0061 0.0324 0.3905 0.0087

16 16 16 16 var3S 1.00000 0.92501 0.40936 0.97279 anti-complement C5 <.0001 0.1154 <.0001

16 16 16 16 var37 0.92501 1.00000 0.46319 0.96519 anti-fibrinogen <.0001 0.0708 <.0001

16 16 16 16 var38 0.40936 0.46319 1.00000 0.41347 anti-D-Dimer 0.1154 0.0708 0.1114

16 16 16 16 var39 0.97279 0.96519 0.41347 1.00000 anti-factor V <.0001 <.0001 0.1114

16 16 16 16 var40 0.66664 0.78659 0.76874 0.75882 anti-human gamma-Gla 0.0048 0.0003 0.0005 0.0007

16 16 16 16 var41 0.77644 0.87082 0.56678 0.81100 anti-TF-VIIa 0.0004 <.0001 0.0221 0.0001

16 16 16 16 var42 0.89334 0.83816 0.32588 0.90737 anti-complement C3c <.0001 <.0001 0.2180 <.0001

16 16 16 16 var43 0.94822 0.87484 0.38901 0.93446 anti-Complement C4 <.0001 <.0001 0.1364 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var40 var41 var42 var43 var33 0.82049 0.83869 0.88805 0.90006 anti-BSA <.0001 <.0001 <.0001 <.0001

16 16 16 16 var34 0.63486 0.80805 0.83457 0.88567 anti-LBP 0.0082 0.0002 <.0001 <.0001

IS 16 16 16 var35 0.37297 0.34345 0.71507 0.62157 anti-PTX3 0.1548 0.1928 0.0018 0.0102

16 16 16 16 var36 0.66664 0.77644 0.89334 0.94822 anti-complement C5 0.0048 0.0004 <.0001 <.0001

16 16 16 16 var37 0.78659 0.87082 0.83816 0.87484 anti-fibrinogen 0.0003 <.0001 <.0001 <.0001

16 16 16 16 var38 0.76874 0.56678 0.32588 0.38901 anti-D-Dimer 0.0005 0.0221 0.2180 0.1364

16 16 16 16 var39 0.75882 0.81100 0.90737 0.93446 anti-factor V 0.0007 0.0001 <.0001 <.0001

16 16 16 16 var40 1.00000 0.81907 0.66389 0.62722 anti-human gamma-Gla 0.0001 0.0050 0.0093

16 16 16 16 var41 0.81907 1.00000 0.71902 0.70038 anti-TF-VIIa 0.0001 0.0017 0.0025

16 16 16 16 var42 0.66389 0.71902 1.00000 0.93856 anti-complement C3c 0.0050 0.0017 <.0001

16 16 16 16 var43 0.62722 0.70038 0.93856 1.00000 anti-Complement C4 0.0093 0.0025 <-0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 var33 0.29072 0.15395 0.74772 0.40864 anti-BSA 0.2747 0.5692 0.0009 0.1161

16 16 16 16 var34 0.33018 0.11132 0.74813 0.35477 anti-LBP 0.2117 0.6815 0.0009 0.1775

16 16 16 16 var35 0.64927 -0.13045 0.47584 -0.04070 anti-PTX3 0.0065 0.6301 0.0625 0.8810

16 16 16 16 var36 0.35092 0.18793 0.72153 0.27949 anti-complement C5 0.1826 0.4858 0.0016 0.2945

16 16 16 16 var37 0.25301 0.19027 0.74263 0.45342 anti-fibrinogen 0.3444 0.4803 0.0010 0.0777

16 16 16 16 var38 0.05855 0.13297 0.78013 0.69611 anti-D-Dimer 0.8295 0.6235 0.0004 0.0027

16 16 16 16 var39 0.33041 0.14029 0.72774 0.33326 anti-factor V 0.2113 0.6043 0.0014 0.2072

16 16 16 16 var40 0.14194 0.16294 0.81138 0.73448 anti-human gamma-Gla 0.6000 0.5466 0.0001 0.0012

16 16 16 16 var41 0.18511 0.21452 0.73364 0.75968 anti-TF-VIIa 0.4925 0.4250 0.0012 0.0006

16 16 16 16 var42 0.45420 0.02325 0.60691 0.26575 anti-complement C3c 0.0772 0.9319 0.0127 0.3198

16 16 16 16 var43 0.33075 0.06114 0.68956 0.21478 anti-Complement C4 0.2108 0.8220 0.0031 0.4244

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var49 var50 var51 var52 var33 0.51992 0.87200 0.88837 0.96626 anti-BSA 0.0390 <.0001 <.0001 <.0001

16 16 16 16 var34 0.50441 0.67004 0.76379 0.88412 anti-LBP 0.0463 0.0045 0.0006 <.0001

16 16 16 16 var35 0.02163 0.41198 0.37998 0.55529 anti-PTX3 0.9366 0.1128 0.1466 0.0256

16 16 16 16 var36 0.3945S 0.69268 0.83013 0.91143 anti-complement C5 0.1305 0.0029 <.0001 <.0001

16 16 16 16 var37 0.55054 0.80532 0.90522 0.98500 anti-fibrinogen 0.0271 0.0002 < .0001 <.0001

16 16 16 16 var38 0.52600 0.27626 0.31320 0.52780 anti-D-Dimer 0.0364 0.3003 0.2375 0.0356

16 16 16 16 var39 0.45470 0.81565 0.87686 0.95830 anti-factor V 0.0768 0.0001 <.0001 <.0001

16 16 16 16 var40 0.70812 0.82143 0.65610 0.79740 anti-human gamma-Gla 0.0021 <.0001 0.0058 0.0002

16 16 16 16 var41 0.85142 0.72116 0.73042 0.84353 anti-TF-VIIa <.0001 0.0016 0.0013 <.0001

16 16 16 16 var42 0.35818 0.74354 0.79008 0.81693 anti-complement C3c 0.1731 0.0010 0.0003 0.0001

16 16 16 16 var43 0.29904 0.65150 0.84862 0.86974 anti-Complement C4 0.2605 0.0063 <-0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var53 var54 var55 var56 var33 0.86924 0.27755 0.68824 0.90785 anti-BSA <.0001 0.2980 0.0032 <.0001

16 16 16 16 var34 0.83244 -0.00919 0.49047 0.71342 anti-LBP <.0001 0.9731 0.0537 0.0019

16 16 16 16 var35 0.54976 -0.13650 0.27710 0.46757 anti-PTX3 0.0274 0.6142 0.2988 0.0678

16 16 16 16 var36 0.91756 -0.04132 0.51887 0.75117 anti-complement C5 <.0001 0.8792 0.0395 0.0008

16 16 16 16 var37 0.89672 0.29448 0.64850 0.83431 anti-fibrinogen <.0001 0.2682 0.0066 <.0001

16 16 16 16 var38 0.35954 -0.06781 0.82753 0.30705 anti-D-Dimer 0.1714 0.8030 <.0001 0.2474

16 16 16 16 var39 0.89666 0.16567 0.61518 0.86289 anti-factor V <.0001 0.5398 0.0112 <.0001

16 16 16 16 var40 0.57876 0.37474 0.97648 0.83307 anti-human gamma-Gla 0.0188 0.1527 <.0001 < .0001 IS 16 16 16 var41 0.70S35 0.24541 0.71788 0. 73718 anti-TF-VIIa 0.0022 0.359S 0.0017 0.0011 16 16 16 16 var42 0.76970 0.05806 0.53149 0. 79380 anti-complement C3c 0.0005 0.8309 0.0341 0.0002 16 16 16 16 var43 0.85358 -0.05149 0.48969 0. 71406 anti-Complement C4 <.0001 0.8498 0.0542 0.0019 16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var57 var58 var59 var60 var33 0.53527 0.55006 0.76222 0.78201 anti-BSA 0.0326 0.0273 0.0006 0.0003

16 16 16 16 var34 0.63251 0.46316 0.85748 0.53727 anti-LBP 0.0086 0.0708 <.0001 0.0319

16 16 IS 16 var35 0.14443 0.00484 0.33119 0.32035 anti-PTX3 0.5936 0.9858 0.2102 0.2264

16 16 16 16 var36 0.51398 0.43449 0.73186 0.56303 anti-complement C5 0.0417 0.0926 0.0013 0.0232

16 16 16 16 var37 0.58502 0.59883 0.81129 0.70232 anti-fibrinogen 0.0173 0.0142 0.0001 0.0024

16 16 16 16 var38 0.67649 0.52808 0.50116 0.22336 anti-D-Dimer 0.0040 0.0355 0.0480 0.4057

16 16 16 16 var39 0.50527 0.49004 0.73235 0.71110 anti-factor V 0.0459 0.0540 0.0013 0.0020

16 16 16 16 var40 0.66543 0.67605 0.72507 0.78878 anti-human gamma-Gla 0.0049 0.0040 0.0015 0.0003

16 16 16 16 var41 0.81656 0.80244 0.85369 0.64375 anti-TF-VIIa 0.0001 0.0002 <.O001 0.0071

16 16 16 16 var42 0.38580 0.34488 0.62033 0.64691 anti-complement C3c 0.1400 0.1908 0.0104 0.0068

16 16 16 16 var43 0.41863 0.33310 0.62800 0.52844 anti-Complement C4 0.1066 0.2074 0.0092 0.0353

16 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : RhO=O Number of Observations var61 var62 var63 var64 var33 0.83940 0.69824 0.92123 0.97208 anti-BSA <.0001 0.0026 <.0001 <.0001

16 16 16 16 var34 0.96884 0.85277 0.90374 0.92853 anti-LBP <.0001 <.0001 <.0001 •=.0001

IS 16 16 16 var35 0.50614 0.32331 0.47699 0.66418 anti-PTX3 0.0455 0.2219 0.0617 0.0050

16 16 16 16 var36 0.88936 0.74073 0.89294 0.97863 anti-complement C5 <.0001 0.0010 < .0001 <.0001

16 16 16 16 var37 0.86365 0.75267 0.93591 0.95190 anti-fibrinogen <.0001 0.0008 <.0001 <.0001

16 16 16 16 var38 0.35988 0.54910 0.63356 0.41726 anti-D-Dimer 0.1710 0.0276 0.0084 0.1078

16 16 16 16 var39 0.85172 0.69290 0.90927 0.99274 anti-factor V <.0001 0.0029 <.0001 <.0001

16 16 16 16 var40 0.6227S 0.66267 0.85403 0.71603 anti-human gamma-Gla 0.0100 0.0052 <.O001 0.0018

16 16 16 16 var41 0.80547 0.86123 0.96038 0.78161 anti-TF-VIIa 0.0002 <.0001 <.0001 0.0003

16 16 16 16 var42 0.76154 0.60829 0.80195 0.89754 anti-complement C3c 0.0006 0.0124 0.0002 <.0001

16 16 16 16 var43 0.79138 0.63190 0.82545 0.94416 anti-Complement C4 0.0003 0.0086 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 var67 var68 var33 0.80125 0.85449 0.59336 0.68759 anti-BSA 0.0002 <.0001 0.0154 0.0032

16 16 16 16 var34 0.84070 0.93263 0.53830 0.67100 anti-LBP <.0O01 <.0001 0.0315 0.0044

16 16 16 16 var35 0.39887 0.48178 0.46208 0.49240 anti-PTX3 0.1259 0.0588 0.0715 0.0527

16 16 16 16 var36 0.80627 0.88826 0.58688 0.65348 anti-complement C5 0.0002 <.0001 0.0169 0.0060

16 16 16 16 var37 0.79624 0.87719 0.55732 0.67599 anti-fibrinogen 0.0002 <.0001 0.0249 0.0040

16 16 16 16 var38 0.45336 0.60729 0.22510 0.38560 anti-D-Dimer 0.0778 0.0126 0.4019 0.1402

16 16 16 16 var39 0.80551 0.85819 0.61853 0.67970 anti-factor V 0.0002 <.0001 0.0106 0.0038

16 16 16 16 var40 0.67051 0.77183 0.37484 0.57783 anti-human garama-Gla 0.0045 0.0005 0.1526 0.0191

16 16 16 16 var41 0.84864 0.91304 0.52505 0.60023 anti-TF-VIIa <.0001 <.0001 0.0368 0.0140

16 16 16 16 var42 0.67643 0.77315 0.61100 0.66437 anti-complement C3c 0.0040 0.0004 0.0119 0.0050

16 16 16 16 var43 0.72399 0.80300 0.64056 0.68247 anti-Complement C4 0.0015 0.0002 0.0075 0.0036

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var69 var70 var71 var72 var33 0.00431 0.63168 0.63974 0.88551 anti-BSA 0.9874 0.0087 0.0076 <.0001

16 16 16 16 var34 0.00817 0.56866 0.60927 0.82439 anti-LBP 0.9760 0.0215 0.0122 <.0001

16 16 16 16 var35 -0.01213 0.16099 0.15738 0.40197 anti-PTX3 0.9644 0.5514 0.5605 0.1227

16 16 16 16 var36 0.01906 0.52190 0.56091 0.79553 anti-complement C5 0.9441 0.0381 0.0238 0.0002

16 16 16 16 var37 -0.01488 0.66884 0.66114 0.92486 anti-fibrinogen 0.9564 0.0046 0.0053 <.0001

16 16 16 16 var38 -0.06376 0.52937 0.60600 0.55741 anti-D-Dimer 0.8145 0.0350 0.0128 0.0249

16 16 16 16 var39 0.01856 0.58468 0.60159 0.84468 anti-factor V 0.9456 0.0174 0.0137 <.0001

16 16 16 16 var40 -0.03795 0.71784 0.74462 0.84932 anti-human gamma-Gla 0.8890 0.0017 0.0009 <.0001

16 16 16 16 var41 0.03180 0.92170 0.92003 0.92626 anti-TF-VIIa 0.9069 •s.OOOl <.0001 <.0001

16 16 16 16 var42 0.00912 0.49813 0.49451 0.77917 anti-complement C3c 0.9732 0.0496 0.0515 0.0004

16 16 16 16 var43 0.03521 0.45243 0.48240 0.75966 anti-Complement C4 0.8970 0.0785 0.0584 0.0006

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var74 var75 var76 var77 var33 0.49700 0.65905 0.65121 0.49786 anti-BSA 0.0502 0.0055 0.0063 0.0497 16 16 16 16 var34 0.47641 0.53106 0.52236 0.39315 anti-LBP 0.0621 0.0343 0.0379 0.1319

16 16 16 16 var35 0.00462 0.10186 0.08856 -0.03366 anti-PTX3 0.9864 0.7074 0.7443 0.9015

16 16 16 16 var36 0.38484 0.47475 0.46956 0.37564 anti-complement C5 0.1411 0.0631 0.0665 0.1516

16 16 16 16 var37 0.56197 0.67289 0.67125 0.54232 anti-fibrinogen 0.0235 0.0043 0.0044 0.0300

16 16 16 16 var38 0.59716 0.57319 0.56879 0.38141 anti-D-Dimer 0.0146 0.0203 0.0215 0.1449

16 16 16 16 var39 0.43122 0.57358 0.56694 0.44786 anti-factor V 0.0954 0.0202 0.0220 0.0819

16 16 16 16 var40 0.70504 0.85909 0.84900 0.54431 anti-human gamma-Gla 0.0023 <.0001 <.0001 0.0293

16 16 16 16 var41 0.86168 0.86838 0.87437 0.71124 anti-TF-VIIa <.0001 <.0001 <.0001 0.0020

16 16 16 16 var42 0.35303 0.47794 0.48662 0.27216 anti-complement C3c 0.1798 0.0611 0.0559 0.3079

16 16 16 16 var43 0.30614 0.40103 0.40507 0.29781 anti-Complement C4 0.2488 0.1237 0.1196 0.2626

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 varδl var33 0.80448 0.38975 0.58989 0.65310 anti-BSA 0.0002 0.1356 0.0162 0.0155

16 16 16 13 var34 0.73783 0.32359 0.53765 0.66785 anti-LBP 0.0011 0.2215 0.0317 0.0126

16 16 16 13 var35 0.39892 -0.06996 0.06518 0.29302 anti-PTX3 0.1259 0.7968 0.8105 0.3313

16 16 16 13 var36 0.78821 0.26490 0.46234 0.63759 anti-complement C5 0.0003 0.3214 0.0714 0.0191

16 16 16 13 var37 0.86844 0.45077 0.63870 0.76235 anti- fibrinogen <.0001 0.0797 0.0077 0.0024

16 16 16 13 var38 0.28150 0.74801 0.63416 0.19901 anti-D-Dimer 0.2909 0.0009 0.0083 0.5145

16 16 16 13 var39 0.80386 0.31572 0.52141 0.66136 anti- factor V 0.0002 0.2336 0.0383 0.0138

16 16 16 13 var40 0.53796 0.72491 0.78562 0.34493 anti-human gamma-Gla 0.0316 0.0015 0.0003 0.2484

16 16 16 13 var41 0.69320 0.75803 0.89735 0.53899 anti-TF-VIIa 0.0029 0.0007 <.0001 0.0573

16 16 16 13 var42 0.S3578 0.22022 0.42259 0.48653 anti-complement C3c 0.0081 0.4125 0.1030 0.0918

16 16 16 13 var43 0.71350 0.19494 0.38563 0.62413 anti-Complement C4 0.0019 0.4694 0.1402 0.0226

16 16 16 13

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var82 var83 var84 var85 var33 0.58045 0.86594 0.85353 0.64343 anti-BSA 0.0375 0.0001 0.0002 0.0177

13 13 13 13 var34 0.55573 0.71543 0.69032 0.45952 anti-LBP 0.0486 0.0060 0.0090 0.1142

13 13 13 13 var35 0.19015 0.32627 0.37546 0.07151 antl-PTX3 0.5338 0.2766 0.2062 0.8164

13 13 13 13 var36 0.54224 0.69328 0.66693 0.44041 anti-complement C5 0.0556 0.0086 0.0128 0.1320

13 13 13 13 var37 0.58882 0.83978 0.78811 0.64893 anti-fibrinogen 0.0342 0.0003 0.0014 0.0164

13 13 13 13 var38 0.78195 0.57381 0.24142 0.59641 anti-D-Dxmer 0.0016 0.0403 0.4268 0.0314

13 13 13 13 var39 0.55451 0.79934 0.79374 0.55462 anti-factor V 0.0492 0.0010 0.0012 0.0492

13 13 13 13 var40 0.77606 0.96451 0.81173 0.89335 anti-human gamma-Gla 0.0018 <.0001 0.0008 <.0001

13 13 13 13 var41 0.76995 0.89006 0.73386 0.84841 anti-TF-VIIa 0.0021 <.0001 0.0043 0.0002

13 13 13 13 var42 0.44387 0.69609 0.71876 0.47375 anti-complement C3c 0.1287 0.0082 0.0056 0.1020

13 13 13 13 var43 0.48573 0.63333 0.61974 0.38410 anti-Complement C4 0.0924 0.0201 0.0239 0.1951

13 13 13 13

Pearson Correlation Coefficients Prob > J 271 under HO: Rho=0 Number of Observations var86 var87 var88 var89 var33 0.38276 0.50955 0.31852 0.97706 anti-BSA 0.1434 0.0524 0.2473 <.0001

16 15 15 15 var34 0.38397 0.35263 0.21694 0.83898 anti-LBP 0.1420 0.1974 0.4374 <.0001

16 15 15 15 var35 0.04561 0.08464 0.09773 0.56450 anti-PTX3 0.8668 0.7642 0.7290 0.0284

16 15 15 IS var36 0.29887 0.38895 0.19603 0.88780 anti-complement C5 0.2608 0.1519 0.4838 <.0001

16 15 15 15 var3₇ 0.38401 0.47218 0.44464 0.91610 anti-fibrinogen 0.1420 0.0755 0.0968 <.0001

16 15 15 15 var38 0.40341 0.58521 0.05425 0.37059 anti-D-Dimer 0.1213 0.0219 0.8477 0.1739

16 15 15 15 var39 0.33880 0.46107 0.28806 0.95906 anti-factor V 0.1993 0.0837 0.2978 <.0001

16 15 15 15 var40 0.54724 0.75446 0.15603 0.82665 anti-human gamma-Gla 0.0282 0.0012 0.5787 0.0001

16 15 15 15 var41 0.74193 0.77645 0.25603 0.79502 anti-TF-VIIa 0.0010 0.0007 0.3570 0.0004

16 15 15 15 var42 0.26176 0.43135 0.08840 0.88031 anti-complement C3c 0.3274 0.1084 0.7541 <.0001

16 15 15 15 var43 0.21049 0.34784 0.18804 0.84804 anti-Complement C4 0.4339 0.2039 0.5022 <.0001

16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var90 var91 var92 var93 var33 0.87849 0.93609 0.92807 0.95257 anti-BSA <.0001 <.0001 <.0001 <.0001

15 15 16 16 var34 0.86538 0.94676 0.72969 0.94057 anti-LBP <.0001 <.0001 0.0013 <.0001

15 15 16 16 var35 0.60007 0.49530 0.43441 0.66225 anti-PTX3 0.0180 0.0605 0.0927 0.0052

15 15 16 16 var36 0.96074 0.92961 0.76278 0.99433 anti-complement C5 <.0001 <.0001 0.0006 <.0001

15 15 16 16 var37 0.85235 0.93565 0.87988 0.93529 ant i - f ibr inogen <.0001 <.0001 <-0001 <.0001

15 15 16 16 var38 0.37928 0.42820 0.33103 0.42358 anti-D-Dimer 0.1632 0.1113 0.2104 0.1021

15 15 16 16 var39 0.91863 0.93554 0.88277 0.98343 anti- factor V ■=.0001 <.0001 <.0001 <.0001 15 15 ie 16 var40 0.S0794 0.75267 0.83115 0.68543 anti-human gamma-Gla 0.0152 0.0012 <.0001 0.0034

15 15 16 16 var41 0.68118 0.89318 0.79922 0.77315 anti-TF-VIIa 0.0052 <.0001 0.0002 0.0004

15 15 IS 16 var42 0.83233 0.81371 0.77212 0.89769 anti-complement C3c 0.0001 0.0002 0.0005 <.0001

15 15 16 16 var43 0.89750 0.84086 0.72378 0.95311 anti-Complement C4 <.0001 <.0001 0.0015 <.0001

15 15 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations

Capture varl var2 var3 var45 0.03495 0.15964 0.29020 0.30545 anti-Annexin V 0.8977 0.5548 0.2756 0.2500

16 16 16 16 var46 0.21956 0.26315 0.23719 0.19732 anti-Lipid A 0.4139 0.3248 0.3764 0.4639

16 16 16 16 var47 0.55360 0.67480 0.76636 0.70764 anti-isopeptide bond 0.0261 0.0041 0.0005 0.0022

16 16 16 16 var48 0.79115 0.83565 0.41706 0.31431 anti-vitronectin 0.0003 <.0001 0.1080 0.2358

16 16 16 16 var49 0.94414 0.91683 0.52135 0.42238 anti-thrombin <.0001 <-0001 0.0384 0.1031

16 16 16 16 var50 0.72244 0.75733 0.75291 0.73235 anti-osteocalcin 0.0016 0.0007 0.0008 0.0013

16 16 16 16 var51 0.57268 0.64825 0.87832 0.90882 anti-Troponin T 0.0204 0.0066 <.0001 <.0001

16 16 16 16 var52 0.63099 0.75103 0.96176 0.97582 anti-vimentin 0.0088 0.0008 <.0001 <.0001

16 16 16 16 var53 0.43379 0.59600 0.92297 0.94925 a-tropomyosin 0.0932 0.0148 <.0001 <.0001

16 16 16 16 var54 0.48395 0.36530 0.10316 0.15254 anti-HSA 0.0575 0.1641 0.7038 0.5728

16 16 16 16 var55 0.64933 0.74974 0.62637 0.54707

Troponin I cardiac 0.0065 0.0008 0.0094 0.0283

16 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations var4 var5 var6 var7 var45 0.31538 -0.14667 0.10421 0.06172 anti-Annexin V 0.2341 0.5878 0.7009 0.8204

16 16 iε 16 var4S 0.20853 0.73822 0.25282 0.86477 anti-Lipid A 0.4383 0.0011 0.3448 ■c.OOOl

16 16 16 16 var47 0.74546 0.43452 0.57691 0.19175 anti-isopeptide bond 0.0009 0.0926 0.0193 0.4768

16 16 16 16 var48 0.35799 0.69951 0.87166 0.09382 anti-vitronectin 0.1734 0.0026 <.0001 0.7296

16 16 16 16 var49 0.46083 0.60215 0.93105 0.08564 anti-thrombin 0.0724 0.0136 <.0001 0.7525

16 16 16 16 var50 0.74009 0.42892 0.49309 0.28445 anti-osteocalcin 0.0010 0.0974 0.0523 0.2856

16 16 16 16 varSl 0.89003 0.46340 0.50840 0.56279 anti-Troponin T <.0001 0.0706 0.0443 0.0232

16 16 16 16 var52 0.97125 0.36698 0.61073 0.37175 anti-vimentin <.0001 0.1621 0.0120 0.1562

16 16 16 16 var53 0.93901 0.39691 0.47832 0.69094 a-tropomyosin <.0001 0.1280 0.0609 0.0030

16 16 16 16 var54 0.10624 0.30313 0.21445 -0.07686 anti-HSA 0.6954 0.2538 0.4251 0.7772

16 16 16 16 var55 0.59234 0.63205 0.59726 0.16578

Troponin I cardiac 0.0156 0.0086 0.0146 0.5395

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rh.o=0 Number of Observations var8 var9 varlO varll var45 0.03383 0.32514 0.31803 -0.16726 anti-Annexin V 0.9010 0.2191 0.2300 0.5358

16 16 16 16 var46 0.78915 0.14419 0.20798 0.22172 anti-Lipid A 0.0003 0.5942 0.4396 0.4092

16 16 16 16 var47 0.44063 0.75133 0.72932 0.43601 anti-isopeptide bond 0.0876 0.0008 0.0013 0.0914

16 16 16 16 var48 0.55368 0.37987 0.33594 0.75698 anti-vitronectin 0.0261 0.1467 0.2033 0.0007

16 16 16 16 var49 0.57969 0.49640 0.44806 0.74985 anti-thrombin 0.0186 0.0505 0.0818 0.0008

16 16 16 16 var50 0.48975 0.82780 0.74625 0.51525 anti-osteocalcin 0.0542 <.0001 0.0009 0.0411

16 16 16 16 var51 0.68347 0.86965 0.89152 0.16622 anti-Troponin T 0.0035 <.0001 <.0001 0.5384

16 16 16 16 var52 0.S0284 0.959Ξ1 0.96673 0.22668 ant i - vitnent in 0.0134 <.0001 ■=.0001 0.3985

16 16 16 16 var53 0.73244 0.88444 0.94098 -0.00729 a-tropomyosin 0.0013 <.0001 <.0001 0.9786

16 16 16 16 varS4 0.23078 0.17287 0.11055 0.51270 anti-HSA 0.3898 0.5220 0.6836 0.0423

IS 16 16 16 var55 0.43852 0.65086 0.57397 0.66477

Troponin I cardiac 0.0893 0.0063 0.0201 0.0050

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl2 varl3 varl4 varlδ var45 0.33641 0.22438 -0.06278 -0.21443 anti-Annexin V 0.2027 0.4035 0.8173 0.4252

16 16 16 16 var46 0.13863 0.20930 0.91176 0.87709 anti-Lipid A 0.6086 0.4366 <.0001 <.0001

16 16 16 16 var47 0.75109 0.74007 -0.00820 0.25678 anti-isopeptide bond 0.0008 0.0010 0.9759 0.3370

16 16 16 16 var48 0.34627 0.71016 0.03253 0.23233 anti-vitronectin 0.1889 0.0021 0.9048 0.3866

16 16 16 16 var49 0.45538 0.81796 0.00259 0.23144 anti-thrombin 0.07S3 0.0001 0.9924 0.3884

16 16 16 16 var50 0.78830 0.82512 0.06330 0.21895 anti-osteocalσin 0.0003 <.0001 0.8158 0.4152

16 16 16 16 var51 0.86583 0.77849 0.33714 0.49767 anti-Troponin T <.0001 0.0004 0.2016 0.0498

16 16 16 16 var52 0.95919 0.87891 0.10145 0.28965 anti-vimentin <.0001 <.0001 0.7085 0.2765

16 16 16 16 var53 0.89977 0.73528 0.45892 0.53804 a-tropomyosin <.0001 0.0012 0.0738 0.0316

16 16 16 16 var54 0.11732 0.31116 -0.10351 -0.03914 anti-HSA 0.6652 0.2408 0.7028 0.8856

16 16 16 16 var55 0.62440 0.75163 -0.02055 0.25511

Troponin I cardiac 0.0097 0.0008 0.9398 0.3403

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rh.o=0 Number of Observations varl6 varl7 varlδ varl9 var45 0.23453 0.27476 0.28198 0.35948 anti-Annexin V 0.3819 0.3031 0.2900 0.1715

16 16 16 16 var46 0.30727 0.24720 0.18215 0.22513 anti-Lipid A 0.2470 0.3560 0.4996 0.4018

16 16 16 16 var47 0.63315 0.74875 0.77357 0.72003 anti-isopeptide bond 0.0085 0.0008 0.0004 0.0017

16 16 16 16 var48 0.26150 0.43840 0.42833 0.28133 anti-vitronectin 0.3279 0.0894 0.0979 0.2912

16 16 16 16 var49 0.36389 0.54486 0.51891 0.39417 anti-thrombin 0.1659 0.0291 0.0394 0.1309

16 16 16 16 var50 0.69980 0.84959 0.78341 0.68151 anti-osteocalcin 0.0025 <.0001 0.0003 0.0036

16 16 16 16 var51 0.89864 0.90391 0.89368 0.82222 anti-Troponin T <.0001 <.0001 <.0001 <.0001

16 16 16 16 var52 0.92978 0.95897 0.98978 0.89904 ant i - viiπent in <.0001 <.0001 <.0001 <.0001

16 16 16 16 var53 0.91169 0.89930 0.91148 0.91950 a-tropomyosin <-0001 <.0001 <.0001 <.0001

16 16 16 16 var54 0.16219 0.23649 0.20430 -0.06604 anti-HSA 0.5484 0.3779 0.4479 0.8080

16 16 16 16 var55 0.52854 0.67429 0.66347 0.51565

Troponin I cardiac 0.0353 0.0042 0.0051 0.0409

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var20 var21 var22 var23 var45 0.30347 0.14157 -0.02318 0.03432 anti-Annexin V 0.2532 0.6010 0.9321 0.8996

16 16 16 16 var46 0.07759 0.24338 0.12040 0.81032 anti-Lipid A 0.7752 0.3637 0.6569 0.0001

16 16 16 16 var47 0.64043 0.67953 0.37343 0.31643 anti-isopeptide bond 0.0075 0.0038 0.1542 0.2325

16 16 16 16 var48 0.23912 0.89086 0.22206 0.26387 anti-vitronectin 0.3724 <.0001 0.4085 0.3234

16 16 16 16 var49 0.32529 0.93764 0.17383 0.31423 anti-thrombin 0.2189 <.0001 0.5197 0.2359

16 16 16 16 var50 0.62551 0.49789 0.21688 0.39226 anti-osteocalcin 0.0096 0.0497 0.4198 0.1329

16 16 16 16 var51 0.86467 0.49407 0.52676 0.61892 anti-Troponin T <.0001 0.0517 0.0360 0.0106

16 16 16 16 var52 0.96273 0.64028 0.33094 0.40017 anti-vimentin <.0001 0.0075 0.2106 0.1246

16 16 16 16 var53 0.91554 0.49335 0.34213 0.63373 a-tropomyosin <.0001 0.0521 0.1946 0.0084

16 16 16 16 var54 0.18158 0.13307 -0.09464 0.04480 anti-HSA 0.5009 0.6232 0.7274 0.8691

16 16 16 16 var55 0.45481 0.65958 0.24944 0.25135

Troponin I cardiac 0.0767 0.0054 0.3515 0.3477

16 16 16 16

Pearson Correlation Coefficients Prob > |r] under HO: Rho=0 Number of Observations var24 var25 var26 var27 var45 0.18753 0.29354 0.26701 0.30991 anti-Annexin V 0.4868 0.2698 0.3175 0.2428

16 16 16 16 var46 0.10917 0.25829 0.30156 0.20321 anti-Lipid A 0.6873 0.3341 0.2564 0.4503

16 16 16 16 var47 0.73097 0.72439 0.75436 0.73183 anti-isopeptide bond 0.0013 0.0015 0.0007 0.0013

16 16 16 16 var48 0.29990 0.38558 0.46756 0.35658 anti-vitronectin 0.2591 0.1402 0.0678 0.1752

16 16 16 16 var49 0.35097 0.48041 0.55695 0.45813 anti-thrombin 0.1826 0.0596 0.0250 0.0743

16 16 16 16 var50 0.62911 0.74082 0.76214 0.74109 anti-osteocalcin 0.0090 0.0010 0.0006 0.0010

16 16 16 16 var51 0.86729 0.90336 0.87233 0.89602 anti-Troponin T <.0001 <.0001 <.0001 <.0001

16 16 16 16 var52 0.85371 0.97463 0.94907 0.97795 anti-vimentin <.0001 <.0001 <.0001 <.0001

16 16 16 16 var53 0.82281 0.95139 0.91751 0.94240 a-tropomyosin <.0001 <.0001 <.0001 <.0001

16 16 16 16 var54 0.02942 0.15948 0.14194 0.13294 anti-HSA 0.9139 0.5552 0.6000 0.6236

16 16 16 16 var55 0.54073 0.58716 0.64760 0.59109

Troponin I cardiac 0.0306 0.0168 0.0067 0.0159

16 16 16 16 Pearson. Correlation Coefficients Prob > |r| under HO: Rho=0 ^' Number of Observations var28 var29 var30 var31 var45 -0.16207 -0.15529 0.03930 0.00522 anti-Annexin V 0.5487 0.5658 0.8851 0.9847

16 16 16 16 var46 0.62380 0.19585 0.91040 0.91505 anti-Lipid A 0.0098 0.4673 <.0001 <.0001

16 16 16 16 var47 0.37651 0.18601 0.17721 0.19549 anti-isopeptide bond 0.1506 0.4904 0.5115 0.4681

16 16 16 16 var48 0.67969 0.53903 0.20989 0.29548 anti-vitronectin 0.0038 0.0312 0.4353 0.2665

16 16 16 16 var49 0.62362 0.53210 0.21456 0.28601 anti-thrombin 0.0098 0.0339 O.4249 0.2829

16 16 16 16 varSO 0.27241 0.66159 0.29931 0.29635 anti-osteocalcin 0.3074 0.0053 0.2601 0.2651

16 16 16 16 var51 0.16820 0.20016 0.53798 0.51459 anti-Troponin T 0.5335 0.4573 0.0316 0.0414

16 16 16 16 var52 0.12842 0.15670 0.34163 0.33011 anti-vimentin 0.6355 0.5622 0.1953 0.2118

16 16 16 16 var53 0.12246 -0.06106 0.63377 0.58898 a-tropomyosin 0.6514 0.8223 0.0084 0.0164

16 16 16 16 var54 0.17927 0.76639 0.01292 0.11505 anti-HSA 0.5065 0.0005 0.9621 0.6714

16 16 16 16 var55 0.49238 0.64050 0.18810 0.21661

Troponin I cardiac 0.0527 0.0075 0.4854 0.4204

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var32 var33 var34 var35 var45 0.21549 0.29072 0.33018 0.64927 anti-Annexin V 0.4228 0.2747 0.2117 0.0065

16 16 16 16 var46 0.32752 0.15395 0.11132 -0.13045 anti-Lipid A 0.2156 0.5692 0.6815 0.6301

16 16 16 16 var47 0.09473 0.74772 0.74813 0.47584 anti-isopeptide bond 0.7271 0.0009 0.0009 0.0625

16 16 16 16 var48 0.26500 0.40864 0.35477 -0.04070 anti-vitronectin 0.3213 0.1161 0.1775 0.8810

16 16 16 16 var49 0.10982 0.51992 0.50441 0.02163 anti-thrombin 0.6856 0.0390 0.0463 0.9366

16 16 16 16 var50 0.11374 0.87200 0.67004 0.41198 anti-osteocalcin 0.6749 < .0001 0.0045 0.1128

IS 16 16 16 var51 0.29282 0.88837 0.76379 0.37998 anti-Troponin T 0.2711 <.0001 0.0006 0.1466

16 16 16 16 var52 0.15691 0.96626 0.88412 0.55529 anti-vimentin 0.5617 <.0001 <.0001 0.0256

16 16 16 16 var53 0.05715 0.86924 0.83244 0.54976 a-tropomyosin 0.8335 <.0001 <.0001 0.0274

16 16 16 16 var54 0.20487 0.27755 -0.00919 -0.13650 anti-HSA 0.4466 0.2980 0.9731 0.6142

16 16 16 16 var55 0.13109 0.68824 0.49047 0.27710

Troponin I cardiac 0.6284 0.0032 0.0537 0.2988

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var36 var37 var38 var39 var45 0.35092 0.25301 0.05855 0.33041 anti-Annexin V 0.1826 0.3444 0.8295 0.2113

16 16 16 16 var46 0.18793 0.19027 0.13297 0.14029 anti-Lipid A 0.4858 0.4803 0.6235 0.6043

16 16 16 16 var47 0.72153 0.74263 0.78013 0.72774 anti-isopeptide bond 0.0016 0.0010 0.0004 0.0014

16 16 16 16 var48 0.27949 0.45342 0.69611 0.33326 anti-vitronectin 0.2945 0.0777 0.0027 0.2072

16 16 16 16 var49 0.39455 0.55054 0.52600 0.45470 anti-thrombin 0.1305 0.0271 0.0364 0.0768

16 16 16 16 var50 0.69268 0.80532 0.27626 0.81565 anti-osteocalcin 0.0029 0.0002 0.3003 0.0001

16 16 16 16 varδl 0.83013 0.90522 0.31320 0.87686 anti-Troponin T <-0001 <.0001 0.2375 <.0001

16 16 16 16 var52 0.91143 0.98500 0.52780 0.95830 anti-vimentin <.0001 <.0001 0.0356 <.0001

16 16 16 16 var53 0.91756 0.89672 0.35954 0.89666 a-tropomyosin <.0001 <.0001 0.1714 <.0001

16 16 16 16 var54 -0.04132 0.29448 -0.06781 0.16567 anti-HSA 0.8792 0.2682 0.8030 0.5398

16 16 16 16 var55 0.51887 0.64850 0.82753 0.61518

Troponin I cardiac 0.0395 0.0066 <.0001 0.0112

16 16 16 16 Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var40 var41 var42 var43 var45 0.14194 0.18511 0.45420 0.33075 anti-Annexin V O.SOOO 0.4925 0.0772 0.2108

16 16 16 16 var46 0.16294 0.21452 0.02325 0.06114 anti-Lipid A 0.5466 0.4250 0.9319 0.8220

16 16 16 16 var47 0.81138 0.73364 0.60691 0.68956 anti-isopeptide bond 0.0001 0.0012 0.0127 0.0031

16 16 16 16 var48 0.73448 0.75968 0.26575 0.21478 anti-vitronectin 0.0012 0.0006 0.3198 0.4244

16 16 16 16 var49 0.70812 0.85142 0.35818 0.29904 anti-thrombin 0.0021 <.0001 0.1731 0.2605

16 16 16 16 var50 0.82143 0.72116 0.74354 0.65150 anti-osteocalcin <.0001 0.0016 0.0010 0.0063

16 16 16 16 var51 0.65610 0.73042 0.79008 0.84862 anti-Troponin T 0.0058 0.0013 0.0003 <.0001

16 16 16 16 var52 0.79740 0.84353 0.81693 0.86974 anti-vimentin 0.0002 <-0001 0.0001 <.0001

16 16 IS 16 var53 0.57876 0.70635 0.76970 0.85358 a-tropomyosin 0.0188 0.0022 0.0005 <.0001

IS 16 IS 16 var54 0.37474 0.24541 0.05806 -0.05149 anti-HSA 0.1527 0.3596 0.8309 0.8498

IS IS 16 16 var55 0.97648 0.71788 0.53149 0.48969

Troponin I cardiac <.0001 0.0017 0.0341 0.0542

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 var45 1.00000 -0.12563 0.12452 0.09626 anti-Annexin V 0.6429 0.6459 0.7229

16 16 16 16 var46 -0.12563 1.00000 0.02688 0.22142 anti-Lipid A 0.6429 0.9213 0.4099

16 16 16 16 var47 0.12452 0.02688 1.00000 0.59404 anti-isopeptide bond 0.6459 0.9213 0.0152

16 16 16 16 var48 0.09626 0.22142 0.59404 1.00000 anti-vitronectin 0.7229 0.4099 0.0152

16 16 16 16 var49 0.05695 0.17708 0.59518 0.91522 anti-thrombin 0.8341 0.5118 0.0150 <.0001 is 16 16 16 var50 0.18778 0.14749 0.56697 0.44630 anti-osteocalcin 0.4862 0.5857 0.0220 0.0831

16 16 16 16 var51 0.08085 0.36982 0.56831 0.28973 anti-Troponin T 0.7660 0.1586 0.0216 0.2764

16 16 16 16 var52 0.26721 0.15026 0.75770 0.43249 anti-vimentin 0.3171 0.5786 0.0007 0.0943

16 16 16 16 var53 0.27179 0.41915 0.58532 0.22018 a-tropomyosin 0.3085 0.1061 0.0172 0.4125

16 16 16 16 var54 0.16048 0.06397 0.00095 0.28226 anti-HSA 0.5527 0.8139 0.9972 0.2895

16 IS 16 16 var55 0.08578 0.14572 0.77735 0.76198

Troponin 1 cardiac 0.7521 0.5902 0.0004 0.0006

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var49 var50 varδl var52 var45 0.05695 0.18778 0.08085 0.26721 anti-Annexin V 0.8341 0.4862 0.7660 0.3171

16 16 16 16 var46 0.17708 0.14749 0.36982 0.15026 anti-Lipid A 0.5118 0.5857 0.1586 0.5786

16 16 16 16 var47 0.59518 0.56697 0.56831 0.75770 anti-isopeptide bond 0.0150 0.0220 0.0216 0.0007

16 16 16 16 var48 0.91522 0.44630 0.28973 0.43249 anti-vitronectin <.0001 0.0831 0.2764 0.0943

16 16 16 16 var49 1.00000 0.56848 0.37016 0.50507 anti-thrombin 0.0216 0.1582 0.0460

16 16 16 16 var50 0.56848 1.00000 0.74202 0.76126 anti-osteocalcin 0.0216 0.0010 0.0006

16 16 16 16 var51 0.37016 0.74202 1.00000 0.88880 anti-Troponin T 0.1582 0.0010 <.0001

16 16 16 16 var52 0.50507 0.76126 0.88880 1.00000 anti-vimentin 0.0460 0.0006 <.0001

16 16 16 16 var53 0.28425 0.60012 0.89967 0.89882 a-tropomyosin 0.2860 0.0140 <.0001 <.0O01

16 16 16 16 var54 0.31134 0.57724 0.34221 0.27318 anti-HSA 0.2405 0.0192 0.1945 0.3060

16 16 16 16 var55 0.69199 0.73051 0.51562 0.66712

Troponin I cardiac 0.0030 0.0013 0.0409 0.0048

16 16 16 16 Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var53 var54 var55 var56 var45 0.27179 -0.16048 0.08578 0.22451 anti-Annexin V 0.3085 0.5527 0.7521 0.4032

16 16 16 16 var46 0.41915 0.06397 0.14572 0.12790 anti-Lipid A 0.1061 0.8139 0.5902 0.6369

16 16 16 16 var4₇ 0.58532 0.00095 0.77735 0.60112 anti-isopeptide bond 0.0172 0.9972 0.0004 0.0138

16 16 16 16 var48 0.22018 0.28226 0.76198 0.42181 anti-vltronectin 0.4125 0.2895 0.0006 0.1037

16 16 16 16 var49 0.28425 0.31134 0.69199 0.54438 anti-thrombin 0.2860 0.2405 0.0030 0.0292

16 16 16 16 var50 0.60012 0.57724 0.73051 0.99383 anti-osteocalcin 0.0140 0.0192 0.0013 <.0001

16 16 16 16 var51 0.89967 0.34221 0.51562 0.76602 anti-Troponin T <-0001 0.1945 0.0409 0.0005

16 16 16 16 var52 0.89882 0.27318 0.66712 0.80044 anti-vimentin <.0001 0.3060 0.0048 0.0002

16 16 16 16 var53 1.00000 0.07559 0.42358 0.64886 a-tropomyosin 0.7808 0.1021 0.0065

16 16 16 16 var54 0.07559 1.00000 0.35216 0.50657 anti-HSA 0.7808 0.1810 0.0452

16 16 16 16 var55 0.42358 0.35216 1.00000 0.73409

Troponin I cardiac 0.1021 0.1810 0.0012

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var57 var58 var59 var60 var45 0.09029 -0.03494 0.14438 0.14086 anti-Annexin V 0.7395 0.8978 0.5937 0.6028

16 16 16 16 var46 0.19281 0.47730 0.24193 0.12904 anti-Lipid A 0.4743 0.0615 0.3667 0.6339

16 16 16 16 var47 0.74525 0.52047 0.76952 0.47664 anti-isopeptide bond 0.0009 0.0387 0.0005 0.0620

16 16 16 16 var48 0.82139 0.77267 0.67235 0.44203 anti-vitronectin <.0001 0.0005 0.0043 0.0865

16 16 16 16 var49 0.90037 0.85767 0.77875 0.55361 anti-thrombin <.0001 <.0001 0.0004 0.0261

16 16 16 16 var50 0.41239 0.54216 0.67755 0.98509 anti-osteocalcin 0.1124 0.0300 0.0039 <.0001

IS 16 16 16 var51 0.37751 0.55753 0.62568 0.65645 anti-Troponin T 0.1494 0.0248 0.0095 0.0057

16 16 16 16 var52 0.55998 0.57185 0.74075 0.65942 anti-vimentin 0.0241 0.0206 0.0010 0.0055

IS 16 16 16 var53 0.38928 0.47978 0.61047 0.47741 a-tropomyosin 0.1361 0.0600 0.0120 0.0615

16 16 16 16 var54 0.00485 0.34553 0.17747 0.66249 anti-HSA 0.9858 0.1899 0.5108 0.0052

16 16 16 16 var55 0.65616 0.65347 0.S5002 0.71871

Troponin I cardiac 0.0058 0.0060 0.0064 0.0017

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var61 var62 var63 var64 var45 0.26632 0.13746 0.25776 0.35195 anti-Annexin V 0.3188 0.6117 0.3351 0.1813

16 16 16 16 var46 0.22113 0.25363 0.21299 0.09194 anti-Lipid A 0.4105 0.3432 0.4284 0.7349

16 16 16 16 var47 0.72819 0.75958 0.83471 0.72862 anti-isopeptide bond 0.0014 0.0006 <.0001 0.0014

16 16 16 16 var48 0.43197 0.67371 0.65991 0.28297 anti-vitronectin 0.0947 0.0042 0.0054 0.2883

16 16 16 16 var49 0.58615 0.76213 0.74300 0.39656 anti-thrombin 0.0170 0.0006 0.0010 0.1283

16 16 16 16 var50 0.66931 0.53327 0.74455 0.75026 anti-osteocalcin 0.0046 0.0334 0.0009 0.0008

16 16 16 16 var51 0.70345 0.56034 0.78936 0.85461 anti-Troponin T 0.0024 0.0240 0.0003 <.0001

16 16 16 16 var52 0.79713 0.69132 0.92184 0.95719 anti-vimentin 0.0002 0.0030 <.0001 <-0001

16 16 16 16 var53 0.75866 0.60527 0.80495 0.90426 a-tropomyosin 0.0007 0.0130 0.0002 <.0001

16 16 16 16 var54 0.00430 -0.04395 0.13738 0.09619 anti-HSA 0.9874 0.8716 0.6119 0.7230

16 16 16 16 var55 0.49752 0.58590 0.75189 0.56752

Troponin I cardiac 0.0499 0.0171 0.0008 0.0219 16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var65 var66 var67 var68 var45 0.40772 0.23719 0.15609 0.03199 anti-Annexin V 0.1170 0.3764 0.5638 0.9064

16 16 16 16 var46 0.19440 0.20832 -0.11290 -0.14114 anti-Lipid A 0.4706 0.4388 0.6772 0.6021

16 16 16 16 var47 0.72196 0.83543 0.44538 0.68313 anti-isopeptide bond 0.0016 <.0001 0.0838 0.0035

16 16 16 16 var48 0.59588 0.61899 0.09024 0.25463 anti-vitronectin 0.0149 0.0106 0.7396 0.3412

16 16 16 16 var49 0.73715 0.70252 0.32675 0.44265 anti-thrombin 0.0011 0.0024 0.2167 0.0860

16 16 16 16 var50 0.64325 0.65150 0.40296 0.58801 anti-osteocalcin 0.0072 0.0063 0.1217 0.0166

16 16 16 16 var51 0.63022 0.69992 0.54828 0.57999 anti-Troponin T 0.0089 0.0025 0.0279 0.0185

16 16 16 16 var52 0.77181 0.84369 0.58958 0.64506 anti-vimentin 0.0005 <.0001 0.0162 0.0070

16 16 16 16 var53 0.68533 0.75791 0.52193 0.50456 a-tropomyosin 0.0034 0.0007 0.0381 0.0462

16 16 16 16 var54 0.01617 -0.02660 -0.01937 0.08509 anti-HSA 0.9526 0.9221 0.9432 0.7540

16 16 16 16 var55 0.57327 0.67219 0.28581 0.51984

Troponin I cardiac 0.0203 0.0043 0.2832 0.0390

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var69 var70 var71 var72 var45 0.61706 0.09202 0.12469 0.17306 anti-Annexin V 0.0109 0.7346 0.6454 0.5215

16 16 16 16 var46 -0.08724 0.18374 0.19963 0.25847 anti-Lipid A 0.7480 0.4958 0.4585 0.3337

16 16 16 16 var47 -0.01994 0.59535 0.67700 0.74752 anti-isopeptide bond 0.9416 0.0150 0.0040 0.0009

16 16 16 16 var48 0.20353 0.81952 0.85037 0.67561 anti-vitronectin 0.4496 0.0001 <.0001 0.0041

16 16 16 16 var49 0.10389 0.92782 0.94463 0.73885 anti-thrombin 0.7018 <.0001 <-0001 0.0011

16 16 16 16 var50 0.00506 0.58111 0.56372 0.80211 anti-osteocalcin 0.9852 0.0182 0.0230 0.0002

16 16 16 16 var51 0.09538 0.54414 0.50852 0.83541 anti-Troponin T 0.7253 0.0293 0.0443 <.0001

16 16 16 IS var52 0.00870 0.65303 0.64939 0.88081 anti-vimentin 0.9745 0.0061 0.0065 <.0001

16 16 16 16 var53 0.01548 0.47787 0.47727 0.75281 a-tropomyosin 0.9546 0.0612 0.0616 0.0008

16 16 16 16 var54 0.07009 0.30717 0.18028 0.35546 anti-HSA 0.7965 0.2472 0.5040 0.1767

16 16 16 16 var5S 0.05479 0.65955 0.69882 0.75765

Troponin I cardiac 0.8403 0.0054 0.0026 0.0007

16 IS 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var74 var75 var76 var77 var45 0.01481 0.01809 0.02818 0.16908 anti-Annexin V 0.9566 0.9470 0.9175 0.5313

16 16 16 16 var46 0.2S942 0.26907 0.27840 0.38657 anti-Lipid A 0.3129 0.3136 0.2964 0.1391

16 16 16 16 var47 0.58474 0.65180 0.62342 0.41490 anti-isopeptide bond 0.0174 0.0062 0.0099 0.1100

16 16 16 16 var48 0.942S2 0.88988 0.89675 0.70586 anti-vitronectin <.0001 <.0001 <.O001 0.0022

16 16 16 16 var49 0.9S775 0.93214 0.93101 0.77642 anti-thrombin <.0001 <.0001 <.0001 0.0004

16 16 16 16 var50 0.49822 0.75929 0.74504 0.47244 anti-osteocalcin 0.0495 0.0006 0.0009 0.0646

16 IS 16 16 var51 0.42540 0.55778 0.56584 0.50537 anti-Troponin T 0.1004 0.0248 0.0223 0.0458

16 16 16 16 var52 0.52156 0.62885 0.62684 0.53718 anti-vimentin 0.0383 0.0091 0.0094 0.0319

16 16 16 16 var53 0.34116 0.41420 0.41974 0.45260 a-tropomyosin 0.1960 0.1107 0.1055 0.0783

16 16 16 16 var54 0.30294 0.51025 0.50961 0.36926 anti-HSA 0.2541 0.0434 0.0438 0.1593

16 16 16 16 var55 0.69171 0.83699 0.82510 0.50350 Troponin I cardiac 0.0030 <.0001 <.0001 0.0468 16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 varδl var45 0.15344 -0.00012 0.02275 0.00114 anti-Annexin V 0.5705 0.9996 0.9334 0.9970

16 16 16 13 var46 0.50589 0.26566 0.26363 0.20119 anti-Lipid A 0.0456 0.3200 0.3239 0.5098

16 16 16 13 var47 0.49555 0.59261 0.66792 0.38017 anti-isopeptide bond 0.0509 0.0156 0.0047 0.2001

16 16 16 13 var48 0.26571 0.97884 0.93991 0.07649 anti-vitronectin 0.3199 <.0001 <.0001 0.8039

16 16 16 13 var49 0.34132 0.89570 0.9S959 0.18516 anti-thrombin 0.1957 <.0001 <.0001 0.5448

16 16 16 13 var50 0.59779 0.38623 0.59303 0.36874 anti-osteocalcin 0.0145 0.1395 0.0155 0.2150

16 16 16 13 var51 0.90986 0.31123 0.49975 0.80630 anti-Troponin T <.0001 0.2406 0.0487 0.0009

16 16 16 13 var52 0.86032 0.44672 0.60360 0.78560 anti-vimentin <-0001 0.0828 0.0133 0.0015

16 16 16 13 var53 0.94832 0.25123 0.41006 0.79761 a-tropomyosin <.0001 0.3480 0.1147 0.0011

16 16 16 13 var54 0.29946 0.27107 0.34418 0.27684 anti-HSA 0.2598 0.3099 0.1918 0.3598

16 16 16 13 var5S 0.38861 0.75701 0.76376 0.19666

Troponin I cardiac 0.1369 0.0007 0.0006 0.5196

16 16 16 13

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations var82 var83 var84 var85 var45 0.35636 0.12338 0.14713 0.00784 anti-Annexin V 0.2320 0.6880 0.6315 0.9797

13 13 13 13 var46 0.14974 0.19926 0.11299 0.26233 anti-Lipid A 0.6254 0.5140 0.7132 0.3866

13 13 13 13 var47 0.73157 0.73000 0.55574 0.58086 anti-isopeptide bond 0.0045 0.0046 0.0486 0.0374

13 13 13 13 var48 0.87007 0.73518 0.45914 0.90005 anti-vitronectin 0.0001 0.0042 0.1145 <.0001

13 13 13 13 var49 0.83489 0.87109 0.67201 0.96497 anti-thrombin 0.0004 0.0001 0.0119 <.0001

13 13 13 13 var50 0.45841 0.92359 0.99926 0.76211 anti-osteocalcin 0.1152 <.0001 <.0001 0.0025

13 13 13 13 varSl 0.39339 0.72892 0.71723 0.56361 anti-Troponin T 0.1836 0.0047 0.0058 0.0449

13 13 13 13 var52 0.60780 0.81278 0.73689 0.61991 anti-vimentin 0.0276 0.0007 0.0041 0.0238

13 13 13 13 var53 0.45228 0.61157 0.56042 0.40991 a-tropomyosin 0.1207 0.0263 0.0464 0.1642

13 13 13 13 var54 0.00322 0.49093 0.58324 0.55211 anti-HSA 0.9917 0.0885 0.0364 0.0504

13 13 13 13 varSS 0.76988 0.90512 0.72051 0.87658

Troponin I cardiac 0.0021 <.0001 0.0055 <.0001

13 13 13 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var86 var87 var88 var89 var45 0.16030 0.13726 -0.03433 0.29108 anti-Annexin V 0.5531 0.6257 0.9033 0.2925

16 15 15 15 var46 0.13209 0.03988 -0.04472 0.11229 anti-Lipid A 0.6258 0.8878 0.8743 0.6903

16 15 15 15 var47 0.46762 0.51893 0.14043 0.68753 anti-isopeptide bond 0.0678 0.0475 0.6177 0.0046

16 15 15 15 var48 0.84744 0.83109 0.05417 0.38535 anti-vitronectin ■c.OOOl 0.0001 0.8479 0.1561

16 15 15 15 var49 0.93391 0.82339 0.04889 0.51636 anti-thrombin <.0001 0.0002 0.8626 0.0488

16 15 15 15 varSO 0.42658 0.55534 0.17754 0.93840 anti-osteocalcin 0.0994 0.0316 0.5267 <.0001

IS 15 15 15 var51 0.21207 0.33082 0.45285 0.82998 anti-Troponin T 0.4304 0.2284 0.0901 0.0001

16 15 15 15 var52 0.34963 0.47719 0.49315 0.89537 anti-vimentin 0.1844 0.0721 0.0618 <.0001

16 15 15 15 var53 0.17138 0.26804 0.41280 0.77965 a-tropomyosin 0.5257 0.3341 0.1262 0.0006

16 15 15 15 var54 0.15341 0.22091 0.54954 0.32346 anti-HSA 0.5706 0.4288 0.0338 0.2396

16 15 15 15 var55 0.53294 0 ^■74251 0.06021 0.70362

Troponin I cardiac 0.0335 0 .0015 0.8312 0.0034

16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var90 var91 var92 var93 var45 0.30716 0.31161 0.24657 0.36594 anti-Annexin V 0.2654 0.2582 0.3573 0.1633

15 15 16 16 var46 0.38427 0.24404 0.13869 0.146S0 anti-Lipid A 0.1573 0.3807 0.6085 0.5880

15 15 16 16 var47 0.62082 0.75377 0.61455 0.72193 anti-isopeptide bond 0.0135 0.0012 0.0113 0.0016

15 15 16 16 var48 0.18671 0.51452 0.47584 0.27292 anti-vitronectin 0.5052 0.0497 0.0625 0.3065

15 15 16 16 var49 0.27383 0.66294 0.60380 0.38026 anti-thrombin 0.3234 0.0071 0.0133 0.1463

15 15 16 16 var50 0.63228 0.79051 0.96543 0.70399 anti-osteocalcin 0.0114 0.0005 <.0001 0.0023

15 15 16 16 var51 0.83371 0.80112 0.81250 0.84266 anti-Troponin T 0.0001 0.0003 0.0001 <.0001

15 15 16 16 var52 0.84705 0.89373 0.86154 0.93617 anti-vimentin <.0001 <.0001 <.0001 <.0001

15 15 16 16 var53 0.93877 0.82827 0.70344 0.92101 a-tropomyosin <.0001 0.0001 0.0024 ■c.OOOl

15 15 16 16 var54 -0.09653 0.12604 0.54381 0.00237 anti-HSA 0.7319 0.6544 0.0294 0.9931

15 15 16 16 var55 0.4S724 0.62452 0.71998 0.53740

Troponin I cardiac 0.0791 0.0128 0.0017 0.0318

15 15 16 16

Capture varl var2 var3 var56 0.69446 0.75106 0.79709 0.77993 anti-Apo Al 0.0028 0.0008 0.0002 0.0004

IS 16 16 16 var57 0.80940 0.81508 0.61271 0.50427

MHC class I 0.0001 0.0001 0.0116 0.0464

16 16 16 16 var58 0.87903 0.84176 0.58190 0.50814

Amyloid P protein <.0001 <.0001 0.0180 0.0445

16 16 16 16 var59 0.81297 0.85281 0.80618 0.72366 anti-sCD40 L 0.0001 <.0001 0.0002 0.0015 16 IS lβ 16 var60 0.70252 0.7097B 0.63399 0.61426 anti-kal1ikrein 0.0024 0.0021 0.0084 0.0114

16 16 16 16 varSl 0.66731 0.74929 0.89920 0.84440 Anti-Prothr Fl 0.0047 0.0008 <.0001 <.0001

16 16 16 16 var62 0.74555 0.82864 0.78790 0.69336 goat-ATIII 0.0009 <.0001 0.0003 0.0029

16 16 16 16 var63 0.78627 0.90029 0.95060 0.90188 anti-Throπibin 0.0003 ■=.0001 <.0001 <.0001

16 16 16 16 var64 0.52532 0.66836 0.97252 0.98407 anti-Factor VIII 0.0367 0.0047 <.0001 <.0001

16 16 16 16 var65 0.75676 0.80573 0.84106 0.78745 anti-heparan Sulph 0.0007 0.0002 <.0001 0.0003

16 16 16 16 var66 0.71633 0.84745 0.91876 0.84891 anti-Factor XI 0.0018 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var4 var5 var6 var7 var56 0.78983 0.38871 0.48720 0.29890 anti-Apo Al 0.0003 0.1368 0.0556 0.2608

16 16 16 16 var57 0.55305 0.57313 0.86634 0.15782 MHC class 0.0263 0.0203 <.0001 0.5594

16 16 16 16 var58 0.53091 0.76733 0.86073 0.40620

Amyloid P protein 0.0343 0.0005 <.0001 0.1185

16 16 16 16 var59 0.75251 0.58350 0.76827 0.31165 anti-sCD40 L 0.0008 0.0177 0.0005 0.2400

16 16 16 16 var60 0.62090 0.41865 0.43998 0.21638 anti-kallikrein 0.0103 0.1065 0.0881 0.4209

16 16 16 16 var61 0.86675 0.39770 0.63590 0.41933 Anti-Prothr Fl <.0001 0.1271 0.0081 0.1059

16 16 16 16 var62 0.73329 0.53435 0.80429 0.33497 goat-ATIII 0.0012 0.0330 0.0002 0.2047

16 16 16 16 var63 0.92769 0.51241 0.80973 0.38471 anti-Thrombin <.0001 0.0424 0.0001 0.1412

16 16 16 16 var64 0.98742 0.22030 0.50244 0.39449 anti-Factor VIII <.0001 0.4123 0.0473 0.1305

16 16 16 16 var65 0.81763 0.39117 0.75314 0.33425 anti-heparan Sulph 0.0001 0.1341 0.0008 0.2058

16 16 16 16 var66 0.88468 0.47963 0.77155 0.38685 anti-Factor XI <.0001 0.0601 0.0005 0.1388

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var8 var9 varlO varll var56 0.47836 0.87310 0.79596 0.44546 anti-Apo Al 0.0609 <.0001 0.0002 0.0838

16 16 16 16 var57 0.57779 0.54194 0.53467 0.62708

MHC class I 0.0191 0.0301 0.0329 0.0093

16 16 16 16 var58 0.77801 0.51938 0.51875 0.61759

Amyloid P protein 0.0004 0.0392 0.0395 0.0108

16 16 16 16 var59 0.67238 0.75615 0.74441 0.67062 anti-sCD40 L 0.0043 0.0007 0.0009 0.0045

16 16 16 16 var60 0.42431 0.72579 0.62790 0.55119 anti-kallikrein 0.1014 0.0015 0.0092 0.0269

16 16 16 16 var61 0.63326 0.86002 0.86704 0.38848 Anti-Prothr Fl 0.0085 <.0001 <.0001 0.1370

16 16 16 16 var62 0.65936 0.71780 0.72304 0.55262 goat-ATIII 0.0055 0.0017 0.0016 0.0264

16 16 16 16 var63 0.68114 0.92693 0.91901 0.41270 anti-Thrombin 0.0037 <.0001 <.0001 0.1121

16 16 16 16 var64 0.50997 0.98805 0.98909 0.07530 anti-Factor VIII 0.0436 <.0001 <.0001 0.7817

16 16 16 16 var65 0.60958 0.82108 0.81349 0.32148 anti-heparan Sulph 0.0122 <.0001 0.0001 0.2247

16 16 16 16 var66 0.65038 0.87679 0.87627 0.41788 anti-Factor XI 0.0064 ς.0001 <.0001 0.1073

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations varl2 varl3 varl4 varl5 var56 0.83955 0.84071 0.05527 0.21003 anti-Apo Al <-0001 <.0001 0.8389 0.4349

16 16 16 16 var57 0.52562 0.76332 0.06398 0.34104

MHC class I 0.0365 0.0006 0.8139 0.1961

16 16 16 16 var58 0.48868 0.77498 0.32614 0.56383 Amyloid P protein 0.0548 0.0004 0.2177 0.0229

16 16 16 16 var59 0.73594 0.85378 0.17704 0.40781 anti-sCD40 L 0.0012 <.0001 0.5119 0.1169

16 16 16 16 varδO 0.67821 0.75491 0.02053 0.16203 anti-kallikrein 0.0039 0.0007 0.9399 0.5488

16 16 16 16 varSl 0.85565 0.82565 0.23724 0.40091 Anti-Prothr Fl ■=.0001 <.0001 0.3763 0.1238

16 16 16 16 var62 0.70974 0.82780 0.20422 0.41789 goat-ATIII 0.0021 <.0001 0.4481 0.1072

16 16 16 16 varS3 0.91899 0.9S728 0.14700 0.37340 anti-Thrombin <.0001 <.0001 0.5870 0.1543

16 16 16 16 var64 0.99501 0.83476 0.10338 0.24730 anti-Factor VIII <.0001 <.0001 0.7032 0.3558

16 16 16 16 var65 0.81185 0.86723 0.13009 0.28841 anti-heparan Sulph 0.0001 •=.0001 0.6311 0.2787

16 16 16 16 var66 0.87477 0.90574 0.17852 0.39021 anti-Factor XI <.0001 <-0001 0.5083 0.1351

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varlβ varl7 varlδ var!9 var56 0.74659 0.88291 0.82448 0.74048 anti-Apo Al 0.0009 <.0001 <.0001 0.0010

16 16 16 16 var57 0.45311 0.57520 0.58563 0.52259

MHC class I 0.0780 0.0197 0.0171 0.0378

16 16 16 16 var58 0.47465 0.59516 0.57377 0.44263

Amyloid P protein 0.0632 0.0150 0.0201 0.0860

16 16 16 16 var59 0.66951 0.80243 0.78448 0.73373 anti-sCD40 L 0.0046 0.0002 0.0003 0.0012

16 16 16 16 var60 0.59197 0.75149 0.67462 0.55135 anti-kallikrein 0.0157 0.0008 0.0041 0.0268

16 16 16 16 var61 0.78682 0.87694 0.85881 0.89284 Anti-Prothr Fl 0.0003 <.0001 <.0001 .= .0001

16 16 16 16 var62 0.64443 0.75035 0.74488 0.74650 goat-ATIII 0.0070 0.0008 0.0009 0.0009

16 16 16 16 var63 0.83962 0.93913 0.94442 0.88991 anti-Thrombin <.0001 ■=.0001 <.0001 <.0001

16 16 16 16 var64 0.93208 0.96279 0.97633 0.96930 anti-Factor VIII <.0001 <.0001 <.0001 <.0001 16 16 16 IS var65 0.72328 0.82242 0.81097 0. 81231 anti-heparan Sulph 0.0015 •=.0001 0.0001 0 .0001

16 16 16 16 varS6 0.78802 0.88724 0.88911 0. 88985 anti-Factor XI 0.0003 <.0001 <.0001 < .0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var20 var21 var22 var23 var56 0.67681 0.49753 0.22494 0.38417 anti-Apo Al 0.0040 0.0499 0.4023 0.1418

16 16 16 16 var57 0.41117 0.93372 0.29462 0.37058

MHC class I 0.1136 <.0001 0.2680 0.1577

16 16 16 16 var58 0.40976 0.84607 0.21692 0.60158

Amyloid P protein 0.1150 <.0001 0.4197 0.0137

16 16 16 16 var59 0.61897 0.84044 0.40463 0.50236 anti-sCD40 L 0.0106 <.0001 0.1200 0.0474

16 16 16 16 var60 0.50703 0.43133 0.14342 0.33199 anti-kallikrein 0.0450 0.0953 0.5962 0.2090

16 16 16 16 varδl 0.74284 0.70785 0.40634 0.53714 Anti-Prothr Fl 0.0010 0.0022 0.1183 0.0319

16 16 16 16 var62 0.59106 0.87662 0.40248 0.47376 goat-ATIII 0.0159 <.0001 0.1222 0.0638

IS 16 16 16 var63 0.82516 0.85304 0.38460 0.47851 anti-Throitibin <.0001 <.0001 0.1413 0.0608

16 IS 16 16 var64 0.94536 0.54132 0.33089 0.39220 anti-Factor VIII <.0001 0.0303 0.2106 0.1330

16 16 16 16 var65 0.69255 0.80335 0.28951 0.47575 anti-heparan Sulph 0.0029 0.0002 0.2768 0.0625

16 16 16 16 var66 0.75683 0.83926 0.40822 0.47283 anti-Factor XI 0.0007 <.0001 0.1165 0.0644

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var24 var25 var26 var27 var56 0.67551 0.78264 0.79702 0.79080 anti-Apo Al 0.0041 0.0003 0.0002 0.0003

16 16 16 16 var57 0.48215 0.55904 0.63228 0.53890

MHC class I 0.0586 0.0244 0.0086 0.0312

16 16 16 16 var58 0.44511 0.56862 0.62135 0.53531

Amyloid P protein 0.0840 0.0215 0.0102 0.0326

16 16 16 16 var59 0.67769 0.77415 0.83905 0.73388 anti-sCD40 L 0.0039 0.0004 <.0001 0.0012

16 16 16 16 varβO 0.51345 0.62279 0.64657 0.62478 anti-kal1ikrein 0.0419 0.0100 0.0068 0.0097

16 16 16 16 varSl 0.77604 0.87119 0.90743 0.84650 Anti-Prothr Fl 0.0004 <.0001 <.0001 ■=.0001

16 16 16 16 var62 0.65030 0.74619 0.81597 0.71363 goat-ATIII 0.0064 0.0009 0.0001 0.0019

16 16 16 16 var63 0.81767 0.92749 0.95255 0.92365 anti-Thrombin 0.0001 <.0001 <.0001 <.0001

IS 16 16 16 var64 0.87107 0.96934 0.94312 0.98718 anti-Factor VIII <.0001 <.0001 <.0001 < .0001

16 16 16 16 var65 0.69820 0.805S3 0.82757 0.80614 anti-heparan Sulph 0.0026 0.0002 <-0001 0.0002

16 16 16 16 var66 0.78845 0.88287 0.92672 0.87102 anti-Factor XI 0.0003 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var28 var29 var30 var31 var56 0.21602 0.59164 0.29522 0.27810 anti-Apo Al 0.4217 0.0158 0.2670 0.2970

16 16 16 16 var57 0.62645 0.24026 0.25531 0.30454

MHC class I 0.0094 0.3701 0.3399 0.2515

16 16 16 16 var58 0.66042 0.47712 0.52320 0.58180

Amyloid P protein 0.0054 0.0617 0.0376 0.0181

16 16 16 16 var59 0.61188 0.32020 0.37758 0.40682 anti-sCD40 L 0.0118 0.2266 0.1494 0.1179

16 16 16 16 var60 0.27318 0.76254 0.24385 0.25247 anti-kallikrein 0.3060 0.0006 0.3628 0.3455

16 16 16 16 var61 0.38825 0.09001 0.42825 0.40472 Anti-Prothr Fl 0.1373 0.7403 0.0979 0.1200

16 16 16 16 var62 0.56782 0.14421 0.38008 0.38601 goat-ATIII 0.0218 0.5942 0.1465 0.1397

16 16 16 16 var63 0.36179 0.22794 0.39461 0.38756 anti-Thrombin 0.1685 0.3959 0.1304 0.1380

16 16 16 16 var64 0.00400 0.03748 0.32971 0.27582 ant x- Fact or VIII 0.9883 0.8904 0.2124 0.3011

IS 16 16 16 var65 0.32674 0.13972 0.37485 0.37037 anti-heparan Sulph 0.2168 0.6058 0.1526 0.1579

16 16 16 16 varS6 0.40956 0.12485 0.38881 0.36939 anti-Factor XI 0.1152 0.6450 0.1367 0.1591

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 var56 -0.14091 0.90785 0.71342 0.46757 anti-Apo Al 0.6027 <.0001 0.0019 0.0678

16 16 16 16 var57 0.19535 0.53527 0.63251 0.14443

MHC class I 0.4684 0.0326 0.0086 0.5936

16 16 16 16 var58 0.06370 0.55006 0.46316 0.00484

Amyloid P protein 0.8147 0.0273 0.0708 0.9858

16 16 16 16 var59 0.17611 0.76222 0.85748 0.33119 anti-sCD40 L 0.5141 0.0006 ■=.0001 0.2102

16 16 16 16 var60 -0.12495 0.78201 0.53727 0.32035 anti-kailikrein 0.6447 0.0003 0.0319 0.2264

16 16 16 16 var61 0.08377 0.83940 0.96884 0.50614 Anti-Prothr Fl 0.7577 <.0001 <.0001 0.0455

16 16 16 16 var62 0.17657 0.69824 0.85277 0.32331 goat-ATIII 0.5130 0.0026 <.0001 0.2219

16 16 16 16 var63 -0.01028 0.92123 0.90374 0.47699 anti-Thrombin 0.9698 <.0001 <.0001 0.0617

16 16 16 16 var64 -0.17696 0.97208 0.92853 0.66418 anti-Factor VIII 0.5121 <.0001 <.0001 0.0050

16 IS 16 16 var65 0.05781 0.80125 0.84070 0.39887 anti-heparan Sulph 0.8316 0.0002 <.0001 0.1259

16 16 16 16 var66 0.07932 0.85449 0.93263 0.48178 anti-Factor XI 0.7703 <.0001 <.0001 0.0588

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39 var56 0.75117 0.83431 0.30705 0.86289 anti-Apo Al 0.0008 <.0001 0.2474 <.0001

16 16 16 16 var57 0.51398 0.58502 0.67649 0.50527

MHC class I 0.0417 0.0173 0.0040 0.0459

16 16 16 16 var58 0.43449 0.59883 0.52808 0.49004

Amyloid P protein 0.0926 0.0142 0.0355 0.0540

16 16 16 16 var59 0.73186 0.81129 0.50116 0.73235 anti-sCD40 L 0.0013 0.0001 0.0480 0.0013

16 16 16 16 var60 0.56303 0.70232 0.22336 0.71110 anti-kallikrein 0.0232 0.0024 0.4057 0.0020

16 16 16 16 varSl 0.88936 0.86365 0.35988 0.85172 Anti-Prothr Fl <.0001 <.0001 0.1710 <.0001

16 16 16 16 var62 0.74073 0.75267 0.54910 0.69290 goat-ATIII 0.0010 0.0008 0.0276 0.0029

16 16 16 16 var63 0.89294 0.93591 0.63356 0.90927 ant i - Thr oπib in <.0001 <.0001 0.0084 <.0001

16 16 16 16 var64 0.97863 0.95190 0.41726 0.99274 anti-Factor VIII <.0001 <.0001 0.1078 <-0001

16 16 16 16 var65 0.80627 0.79624 0.45336 0.80551 anti-heparan Sulph 0.0002 0.0002 0.0778 0.0002

16 16 16 16 var6S 0.88826 0.87719 0.60729 0.85819 anti-Factor XI <.0001 <.0001 0.0126 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var40 var41 var42 var43 var56 0.83307 0.73718 0.79380 0.71406 anti-Apo Al <.0001 0.0011 0.0002 0.0019

16 16 16 16 var57 0.66543 0.81656 0.38580 0.41863

MHC class I 0.0049 0.0001 0.1400 0.1066

16 16 16 16 var58 0.67605 0.80244 0.34488 0.33310

Amyloid P protein 0.0040 0.0002 0.1908 0.2074

16 16 16 16 var59 0.72507 0.85369 0.62033 0.62800 anti-sCD40 L 0.0015 <.0001 0.0104 0.0092

16 16 16 16 varδo 0.78878 0.64375 0.64691 0.52844 anti-kallikrein 0.0003 0.0071 0.0068 0.0353

16 16 16 16 var61 0.62276 0.80547 0.76154 0.79138 Anti-Prothr Fl 0.0100 0.0002 0.0006 0.0003

16 16 16 16 var62 0.66267 0.86123 0.60829 0.63190 goat-ATIII 0.0052 <.0001 0.0124 0.0086

16 16 16 16 var63 0.85403 0.96038 0.80195 0.82545 anti-Thrombin <.0001 <.0001 0.0002 <.0001

16 16 16 16 varS4 0.71503 0.78161 0.89754 0.94416 anti-Factor VIII 0.0018 0.0003 <.0001 <.0001

16 16 16 16 var65 0.67051 0.84864 0.67643 0.72399 anti-heparan Sulph 0.0045 <.0001 0.0040 0.0015

16 16 16 16 var66 0.77183 0.91304 0.77315 0.80300 anti-Factor XI 0.0005 <.0001 0.0004 0.0002

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 var56 0.22451 0.12790 0.60112 0.42181 anti-Apo Al 0.4032 0.6369 0.0138 0.1037

16 16 16 16 var57 0.09029 0.19281 0.74525 0.82139

MHC class I 0.7395 0.4743 0.0009 <.0001

16 16 16 16 var58 -0.03494 0.47730 0.52047 0.77267

Amyloid P protein 0.8978 0.0615 0.0387 0.0005

16 16 16 16 var59 0.14438 0.24193 0.76952 0.67235 anti-sCD40 L 0.5937 0.3667 0.0005 0.0043

16 16 16 16 var60 0.14086 0.12904 0.47664 0.44203 anti-kallikrein 0.6028 0.6339 0.0620 0.0865

16 16 16 16 var61 0.26632 0.22113 0.72819 0.43197 Anti-Prothr Fl 0.3188 0.4105 0.0014 0.0947

16 16 16 16 var62 0.13746 0.25363 0.75958 0.67371 goat-ATIII 0.6117 0.3432 0.0006 0.0042

16 16 16 16 var63 0.25776 0.21299 0.83471 0.65991 anti-Thrombin 0.3351 0.4284 <.0001 0.0054

16 16 16 16 var64 0.35195 0.09194 0.72862 0.28297 anti-Factor VIII 0.1813 0.7349 0.0014 0.2883

16 16 16 16 var65 0.40772 0.19440 0.72196 0.59588 anti-heparan Sulph 0.1170 0.4706 0.0016 0.0149

16 16 16 16 var66 0.23719 0.20832 0.83543 0.61899 anti-Factor XI 0.3764 0.4388 <.0001 0.0106

16 15 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var49 var50 var51 var52 var56 0 .54438 0 .99383 0 .76602 0 .80044 anti-Apo Al 0.0292 <.0001 0.0005 0.0002

16 16 16 16 var57 0 .90037 0 .41239 0 .37751 0 .55998 MHC class I <.0001 0.1124 0.1494 0.0241

16 16 16 16 var58 0.85767 0.54216 0.55753 0.57185

Amyloid P protein <.0001 0.0300 0.0248 0.0206

16 16 16 16 var59 0.77875 0.67755 0.62568 0.74075 anti-sCD40 L 0.0004 0.0039 0.0095 0.0010

16 16 16 16 varSO 0.55361 0.98509 0.65645 0.65942 anti-kallikrein 0.0261 <.0001 0.0057 0.0055

16 16 16 16 varβl 0.58615 0.66931 0.70345 0.79713 Anti-Prothr Fl 0.0170 0.0046 0.0024 0.0002

16 16 16 16 var62 0.76213 0.53327 0.56034 0.69132 goat-ATIII O.O006 0.0334 0.0240 0.0030

16 16 16 16 varS3 0.74300 0.74455 0.78936 0.92184 anti-Thrombin O.OOIO 0.0009 0.0003 <.0001

16 16 16 16 var64 0.39656 0.75026 0.85461 0.95719 anti-Factor VIII 0.1283 0.0008 <.0001 <.0001

16 16 16 16 var65 0.73715 0.64325 0.63022 0.77181 anti-heparan Sulph 0.0011 0.0072 0.0089 0.0005

16 16 16 16 varS6 0.70252 0.65150 0.69992 0.84369 anti-Factor XI 0.0024 0.0063 0.0025 •=.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var53 var54 var55 var56 var56 0.64886 0.50657 0.73409 1.00000 anti-Apo Al 0.0065 0.0452 0.0012

16 16 16 16 var57 0.38928 -0.00485 0.65616 0.41510

MHC class I 0.1361 0.9858 0.0058 0.1099

16 16 16 16 var58 0.47978 0.34553 0.65347 0.52135

Amyloid P protein 0.0600 0.1899 0.0060 0.0384

16 16 16 16 var59 0.61047 0.17747 0.65002 0.67330 anti-sCD40 L 0.0120 0.5108 0.0064 0.0043

16 16 16 16 var60 0.47741 0.66249 0.71871 0.96717 anti-kallikrein 0.0615 0.0052 0.0017 <.0001

16 16 16 16 var61 0.75866 0.00430 0.49752 0.69367 Anti-Prothr Fl 0.0007 0.9874 0.0499 0.0029

16 16 16 16 var62 0.60527 -0.04395 0.58590 0.54758 goat-ATIII 0.0130 0.8716 0.0171 0.0281

16 16 16 16 var63 0.80495 0.13738 0.75189 0.77718 anti-Thrombin 0.0002 0.6119 0.0008 0.0004 16 16 16 IS var64 0.90426 0.09S19 0.56752 0.80673 anti-Factor VIII <.0001 0.7230 0.0219 0.0002

16 16 16 16 var65 0.68533 0.01617 0.57327 0.67354 anti-heparan Sulph 0.0034 0.9526 0.0203 0.0042

16 16 16 IS var66 0.75791 -0.02660 0.67219 0.68702 anti-Factor XI 0.0007 0.9221 0.0043 0.0033

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var57 var58 var59 var60 var56 0.41510 0.52135 0.67330 0.96717 anti-Apo Al 0.1099 0.0384 0.0043 <.0001

16 16 16 16 var57 1.00000 0.81416 0.84170 0.34311 MHC class 0.0001 <.0001 0.1932

16 16 lβ 16 var58 0.81416 1.00000 0.68754 0.51769

Amyloid P protein 0.0001 0.0032 0.0400

16 16 16 16 var59 0.84170 0.68754 1.00000 0.58632 anti-sCD40 L <.0001 0.0032 0.0170

16 16 16 16 var60 0.34311 0.51769 0.58632 1.00000 anti-kallikrein 0.1932 0.0400 0.0170

16 16 16 16 var61 0.69993 0.52850 0.93308 0.54622 Anti-Prothr Fl 0.0025 0.0353 <.0001 0.0286

16 16 16 16 var62 0.8S798 0.64905 0.95836 0.42345 goat-ATIII <.0001 0.0065 <.0001 0.1022

16 16 16 16 var63 0.79845 0.72849 0.87892 0.64372 anti-Thrombin 0.0002 0.0014 <.0001 0.0071

16 16 16 IS var64 0.47672 0.42968 0.69157 0.63566 anti-Factor VIII 0.0619 0.0967 0.0030 0.0081

16 16 IS 16 var65 0.80566 0.69091 0.80340 0.55196 anti-heparan Sulph 0.0002 0.0030 0.0002 0.0266

16 16 16 16 var66 0.80840 0.63199 0.92093 0.53321 anti-Factor XI 0.0002 0.0086 <.0001 0.0334

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var61 var62 var63 var64 var56 0.69367 0.54758 0.77718 0.80673 anti-Apo Al 0.0029 0.0281 0.0004 0.0002

16 16 16 16 var57 0.69993 0.86798 0.79845 0.47672 MHC class 0.0025 <.0001 0.0002 0.0619

16 16 16 16 var58 0.52850 0.64905 0.72849 0.42968

Amyloid P protein 0.0353 0.0065 0.0014 0.0967

16 16 16 16 var59 0.93308 0.95836 0.87892 0.69157 anti-sCD40 L <.0001 <.0001 <.0001 0.0030

16 16 16 16 varSO 0.54622 0.42345 0.64372 0.63566 anti-kallikrein 0.0286 0.1022 0.0071 0.0081

16 16 16 16 varδl 1.00000 0.92034 0.88109 0.83254 Anti-Prothr Pl ■=.0001 <.0001 <.0001

IS 16 16 16 var62 0.92034 1.00000 0.87693 0.67017 goat-ATIII <.0001 <.0001 0.0045

16 16 16 16 var63 0.88109 0.87693 1.00000 0.89101 anti-Thrombin <.0001 <.0001 <.0001

16 16 16 16 var64 0.83254 0.67017 0.89101 1.00000 anti-Factor VIII <.0001 0.0045 <.0001

16 16 16 16 var65 0.83324 0.79258 0.89485 0.78724 anti-heparan Sulph <.0001 0.0003 <-0001 0.0003

16 16 16 16 var66 0.94053 0.95546 0.96495 0.84577 anti-Factor XI <.0001 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 var67 var68 var56 0.67354 0.68702 0.45138 0.60675 anti-Apo Al 0.0042 0.0033 0.0793 0.0127

16 16 16 16 var57 0.80566 0.80840 0.42942 0.55575

MHC class I 0.0002 0.0002 0.0969 0.0254

16 16 16 16 var58 0.69091 0.63199 0.46419 0.49802

Amyloid P protein 0.0030 0.0086 0.0701 0.0496

16 16 16 16 var59 0.80340 0.92093 0.32669 0.63146 anti-sCD40 Ii 0.0002 <.0001 0.2168 0.0087

16 16 16 16 var60 0.55196 0.53321 0.33378 0.50861 anti-kallikrein 0.0266 0.0334 0.2064 0.0442

16 16 16 16 var61 0.83324 0.94053 0.43060 0.65134 Anti-Prothr Fl <.0001 <.0001 0.0959 0.0063

16 16 16 16 var62 0.79258 0.95546 0.31603 0.55917 goat-ATIII 0.0003 <.0001 0.2331 0.0243

16 16 16 16 var63 0.89485 0.96495 0.57403 0.67873 anti-Thrombin <.0001 <.0001 0.0201 0.0038

16 16 16 16 var64 0.78724 0.84577 0.62785 0.66180 anti-Factor VIII 0.0003 <-0001 0.0092 0.0052

16 16 16 16 var65 1.00000 0.85733 0.59657 0.59293 anti-heparan Sulph ■c.OOOl 0.0147 0.0155

16 16 16 16 var6S 0.85733 1.00000 0.46452 0.64405 anti-Factor XI <.0001 0.0699 0.0071

IS 16 16 16

Pearson Correlation Coefficients

Prob under HO : Rho=0

Number of Observations var69 var70 var71 var72 var56 0.00325 0.57872 0.57067 0.80475 anti-Apo Al 0.9905 0.0188 0.0210 0.0002

16 16 16 16 var57 0.02781 0.84444 0.90991 0.73000 MHC class 0.9186 <.0001 <.0001 0.0013

16 16 16 16 var58 -0.06297 0.89584 0.87850 0.76428

Amyloid P protein 0.8168 <.0001 <.0001 0.0006

16 16 16 16 var59 -0.05854 0.70912 0.74740 0.89142 anti-sCD40 L 0.8295 0.0021 0.0009 <.0001

16 16 16 16 var60 0.00376 0.54484 0.51836 0.72224 anti-kallikrein 0.9890 0.0291 0.0397 0.0016

16 16 16 16 var61 -0.02920 0.58184 0.62968 0.83652 Anti-Prothr Fl 0.9145 0.0181 0.0089 <.0001

16 ie 16 16 var62 -0.06574 0.71290 0.76943 0.82913 goat-ATIII 0.8089 0.0019 0.0005 <.0001

16 16 16 16 var63 0.02782 0.81662 0.84772 0.93618 anti-Thrombin 0.9185 0.0001 <.0001 <.0001

16 16 16 16 var64 0.03215 0.54616 0.56677 0.80233 anti-Factor VIII 0.9059 0.0286 0.0221 0.0002

16 16 16 16 var65 0.33185 0.76280 0.83777 0.77382 anti-heparan Sulph 0.2092 0.0006 <.0001 0.0004

16 16 16 16 var66 -0.02559 0.72691 0.78142 0.88560 anti-Factor XI 0.9251 0.0014 0.0004 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations var74 var75 var76 var77 var56 0.47378 0.72972 0.71552 0.45613 anti-Apo Al 0.0638 0.0013 0.0018 0.0758

16 16 16 16 var57 0.88747 0.79198 0.78583 0.70117

MHC class I <.0001 0.0003 0.0003 0.0025

16 16 16 16 var58 0.89351 0.86957 0.87507 0.89094

Amyloid P protein < .0001 <.0001 <.0001 < .0001

16 16 16 16 var59 0.76310 0.79359 0.78309 0.53380 anti-sCD40 L 0.0006 0.0002 0.0003 0.0332

16 16 16 16 varβO 0.47301 0.75358 0.73853 0.45899 anti-kallikrein 0.0643 0.0007 0.0011 0.0737

16 16 16 16 varβl 0.55563 0.60228 0.59142 0.41005 Anti-Prothr Fl 0.0254 0.0136 0.0158 0.1147

IS 16 16 16 var62 0.76474 0.71996 0.71531 0.47354 goat-ATIII 0.0006 0.0017 0.0018 0.0639

16 16 16 16 var63 0.74494 0.78812 0.78625 0.63812 anti-Thrombin 0.0009 0.0003 0.0003 0.0078

16 16 16 16 varS4 0.37788 0.50088 0.49419 0.40403 anti-Factor VIII 0.1490 0.0481 0.0517 0.1206

16 16 16 16 var65 0.67201 0.68335 0.67505 0.74450 anti-heparan Sulph 0.0044 0.0035 0.0041 0.0009

16 16 16 16 var66 0.70205 0.71249 0.70754 0.49117 anti-Factor XI 0.0024 0.0020 0.0022 0.0534

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var78 var79 var80 var81 var56 0.61788 0.36530 0.57287 0.39541 anti-Apo Al 0.0107 0.1641 0.0204 0.1811

16 16 16 13 var57 0.39071 0.83187 0.88875 0.32083

MHC class I 0.1346 <.0001 <.0001 0.2852

16 16 16 13 var58 0.58729 0.83022 0.89423 0.41410

Amyloid P protein 0.0168 <.0001 <.0001 0.1595

16 16 16 13 var59 0.61025 0.63506 0.79736 0.54952 anti-sCD40 L 0.0121 0.0082 0.0002 0.0517

16 16 16 13 var60 0.49864 0.37741 0.56517 0.26307 anti-kallikrein 0.0493 0.1496 0.0225 0.3852

16 16 16 13 var61 0.69006 0.38815 0.60344 0.60123 Anti-Prothr Fl 0.0031 0.1374 0.0133 0.0297

16 16 16 13 var62 0.55469 0.64833 0.78111 0.49617 goat-ATIII 0.0257 0.0066 0.0004 0.0846

16 16 16 13 var63 0.74530 0.65661 0.80276 0.58786 anti-Thrombin 0.0009 0.0057 0.0002 0.0346

16 16 16 13 varS4 0.79500 0.27214 0.46783 0.68834 anti-Factor VIII 0.0002 0.3079 0.0676 0.0093

16 16 16 13 var65 0.62433 0.55984 0.72023 0.45312 anti-heparan Sulph 0.0097 0.0241 0.0017 0.1200

16 16 16 13 var66 0.66492 0.60025 0.74791 0.53304 anti-Factor XI 0.0049 0.0140 0.0009 0.0607

16 16 16 13

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var82 var83 var84 var85 var56 0.48432 0.92253 0.99179 0.73830 anti-Apo Al 0.0935 <.0001 <.0001 0.0040

13 13 13 13 var57 0.92573 0.81050 0.53060 0.81822

MHC class I <.0001 0.0008 0.0621 0.0006

13 13 13 13 var58 0.71118 0.83827 0.62366 0.91534

Amyloid P protein 0.0064 0.0003 0.0227 <.0001

13 13 13 13 var59 0.74624 0.94484 0.82593 0.80785 anti-sCD40 L 0.0034 <.0001 0.0005 0.0008

13 13 13 13 var60 0.40728 0.89769 0.99065 0.77195 anti-kallikrein 0.1672 <.0001 <.0001 0.0020

13 13 13 13 var61 0.58827 0.78438 0.75388 0.54583 Anti-Prothr Fl 0.0344 0.0015 0.0029 0.0537

13 13 13 13 var62 0.78204 0.82710 0.64553 0.72327 goat-ATIII 0.0016 0.0005 0.0172 0.0052

13 13 13 13 var63 0.77616 0.88286 0.74148 0.75261 anti-Thrombin 0.0018 <.0001 0.0037 0.0030

13 13 13 13 var64 0.54320 0.73909 0.72522 0.48394 anti-Factor VIII 0.0551 0.0039 0.0050 0.0938

13 13 13 13 var65 0.84130 0.79524 0.69809 0.64623 anti-heparan Sulph 0.0003 0.0012 0.0080 0.0170

13 13 13 13 var66 0.74952 0.81911 0.67479 0.66844 anti-Factor XI 0.0032 0.0006 0.0114 0.0125

13 13 13 13

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var86 var87 var88 var89 var56 0.41392 0.56501 0.16775 0.96775 anti-Apo Al 0.1110 0.0282 0.5501 < .0001

16 15 15 15 var57 0.81703 0.65221 0.00616 0.47210

MHC class I 0.0001 0.0084 0.9826 0.0756 ie 15 15 15 var58 0.74754 0.67305 0.18205 0.51410

Amyloid P protein 0.0009 0.0060 0.5161 0.0499

16 15 15 15 var59 0.60014 0.47145 0.12895 0.71475 anti-sCD40 L 0.0140 0.0761 0.6469 0.0027

16 15 15 15 varδO 0.42452 0.56156 0.14615 0.87270 anti-kallikrein 0.1012 0.0294 0.6032 <.0O01

IS 15 15 15 varSl 0.44975 0.34650 0.09980 0.78971 Anti-Prothr Fl 0.0805 0.2058 0.7234 0.0005

16 15 15 15 var62 0.62512 0.51250 0.02517 0.63146 goat-ATIII 0.0096 0.0508 0.9290 0.0116

16 15 IS 15 var63 0.61964 0.67057 0.22992 0.86846 anti-Thrombin 0.0105 0.0062 0.4097 <-0001

16 15 15 15 var64 0.29243 0.42358 0.31938 0.92509 anti-Factor VIII 0.2717 0.1156 0.2459 <.0001

16 15 15 15 var65 0.73620 0.61551 0.09691 0.77124 anti-heparan Sulph 0.0011 0.0146 0.7312 0.0008

16 15 15 15 var66 0.57573 0.57814 0.09622 0.79402 anti-Factor XI 0.0196 0.0240 0.7330 0.0004

16 15 15 15

Pearson Correlation Coefficients Prob > I rI under HO : RhO=O Number of Observations var90 var91 var92 var93 var56 0.69417 0.81900 0.97314 0.76502 anti-Apo Al 0.0041 0.0002 <.0001 0.0006

15 15 16 16 var57 0.40616 0.71517 0.47773 0.49011

MHC class I 0.1330 0.0027 0.0613 0.0539

15 15 16 16 var58 0.40490 0.65629 0.60988 0.42569

Amyloid P protein 0.1344 0.0079 0.0121 0.1002

15 15 16 16 var59 0.62380 0.88281 0.67717 0.69832 anti-sCD40 L 0.0130 <.0001 0.0040 0.0026

15 15 16 16 var60 0.50800 0.68568 0.93325 0.57932 anti-kallikrein 0.0532 0.0048 <.0001 0.0187

15 15 16 16 var61 0.80517 0.94055 0.68708 0.85432 Anti-Prothr Fl 0.0003 <.0001 0.0033 <.0001

15 15 16 16 varS2 0.64852 0.84910 0.55244 0.69887 goat-ATIII 0.0089 ■c.OOOl 0.0265 0.0026

15 15 16 16 var63 0.81434 0.95644 0.82220 0.89091 anti-Thrombin 0.0002 <.0001 <.0001 <.0001

15 15 16 16 var64 0.92181 0.90994 0.83509 0.99289 anti-Factor VIII <.0001 <.0001 <.0001 <.0001

15 15 16 16 var65 0.72665 0.93190 0.74705 0.79661 anti-heparan Sulph 0.0022 <.0001 0.0009 0.0002

15 15 16 16 var66 0.80575 0.93380 0.69840 0.86555 anti-Factor XI 0.0003 <.0001 0.0026 <.0001

15 15 16 16

Capture varl var2 var3 var67 0.42853 0.41157 0.59364 0.61915 anti-c-jun 0.0977 0.1132 0.0153 0.0105

16 16 16 16 var68 0.53166 0.54156 0.68922 0.65043 anti-Fra-2 0.0340 0.0303 0.0031 0.0064

16 16 16 16 var69 0.02274 0.05661 -0.00684 0.00385 anti-Fra-1 0.9334 0.8350 0.9799 0.9887

16 16 16 16 var70 0.92490 0.93068 0.64023 0.58421 anti-Jun B <-0001 <.0001 0.0076 0.0175

16 16 16 16 var71 0.90084 0.92293 0.66398 0.58842 anti-P-c-Jun <.0001 ■=.0001 0.0050 0.0165

16 16 16 16 var72 0.83004 0.90725 0.89004 0.84504 anti-TGase3 <.0001 <.O001 <.0001 <.0001

16 16 16 16 var74 0.91067 0.91469 0.52639 0.43266 anti-PSA <.0001 <.0001 0.0362 0.0942

16 16 16 16 var75 0.93923 0.94447 0.61580 0.53344 anti-erbB2 <.0001 <.0001 0.0111 0.0333

16 16 16 16 var76 0.93867 0.94841 0.61244 0.53225 anti-VEGF <.0001 <.0001 0.0117 0.0338

16 16 16 16 var77 0.80153 0.74495 0.50938 0.47936 anti-alpha synuclein 0.0002 0.0009 0.0439 0.0603

16 16 16 16 var78 0.52692 0.62008 0.84333 0.88376 anti-mucin-1 0.0360 0.0104 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var4 var5 varS var7 var67 0.61710 0.00427 0.37975 0.13357 anti-c-jun 0.0109 0.9875 0.1468 0.6219

IS 16 16 16 varS8 0.66543 0.25592 0.42827 0.13663 anti-Fra-2 0.0049 0.3387 0.0979 0.6139

IS 16 16 16 var69 0.00753 -0.11547 0.10750 -0.08661 anti-Fra-1 0.9779 0.6702 0.6919 0.7498

16 16 16 16 var70 0.60531 0.54221 0.95539 0.18542 anti-Jun B 0.0130 0.0300 <.0001 0.4918

16 16 16 16 var71 0.62415 0.55053 0.94711 0.19951 anti-P-c-Juti 0.0098 0.0271 <.0001 0.4588

16 16 16 16 var72 0.85751 0.63843 0.79704 0.39437 anti-TGase3 <.0001 0.0078 0.0002 0.1306

16 16 16 16 var74 0.46552 0.70436 0.96401 0.17992 anti-PSA 0.0692 0.0023 <.0001 0.5049

16 16 16 16 var75 0.56283 0.73158 0.86383 0.22001 anti-erbB2 0.0232 0.0013 <-0001 0.4129

16 16 16 16 var76 0.56005 0.73956 0.87890 0.22946 anti-VEGF 0.0241 0.0011 <.0001 0.3926

16 16 16 16 var77 0.48453 0.59036 0.79045 0.31338 anti-alpha synuclein 0.0572 0.0161 0.0003 0.2372

16 16 16 16 var78 0.85582 0.49980 0.52267 0.68430 anti-mucin-1 <.0001 0.0487 0.0378 0.0035

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var8 var9 varlO varll var67 0.22358 0.61173 0.62043 -0.12295 anti-c-jun 0.4052 0.0118 0.0103 0.6501

16 16 16 16 var68 0.28187 0.68536 0.66200 0.28796 anti-Fra-2 0.2902 0.0034 0.0052 0.2795

16 16 16 16 var69 -0.02999 0.02069 0.00619 -0.14467 anti-Fra-1 0.9122 0.9394 0.9819 0.5929

16 16 16 16 var70 0.63683 0.61494 0.59467 0.52735 anti-Jun B 0.0080 0.0112 0.0151 0.0358

16 16 16 16 var71 0.62878 0.63529 0.61156 0.53343 anti-P-c-Jun 0.0091 0.0082 0.0118 0.0333

16 16 16 16 var72 0.71910 0.86242 0.84872 0.56131 anti-TGase3 0.0017 <.0001 <.0001 0.0237

16 16 16 16 var74 0.6S374 0.47162 O .44842 0.73061 anti-PSA 0.005α 0.0651 0.0815 0.0013

16 16 16 16 var75 0.65906 0.61180 0.55131 0.80934 anti-erbB2 0.0055 0.0118 0.0269 0.0001

16 16 16 16 var76 0.66896 0.60457 0.54822 0.79478 anti-VEGP O.0046 0.0131 0.0279 0.0002

16 16 16 16 var77 0.69043 0.46893 0.47549 0.42272 anti-alpha synuclein 0.0031 0.0669 0.0627 0.1028

16 16 16 16 var78 0.81845 0.79248 0.85780 0.11622 anti-mucin-1 0.0001 0.0003 <.0001 0.6682

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl2 varl3 varl4 varl5 var67 0.61679 0.54280 -0.07247 0.13983 anti-c-jun 0.0109 0.0298 0.7897 0.6055

16 16 16 16 var68 0.68076 0.63080 -0.04889 0.25971 anti-Fra-2 0.0037 0.0088 0.8573 0.3314

16 16 16 16 var69 0.02136 0.05276 -0.12048 -0.30785 anti-Fra-1 0.9374 0.8461 0.6567 0.2461

16 16 16 16 var70 0.58554 0.88222 0.04499 0.27441 anti-Jun B 0.0172 <.0001 0.8686 0.3037

16 16 16 16 var71 0.60999 0.88359 0.05231 0.28576 anti-P-c-Jun 0.0121 <.0001 0.8474 0.2833

16 16 16 16 var72 0.84298 0.93997 0.19567 0.44217 anti-TGase3 <.0001 <.0001 0.4677 0.0864

16 16 16 16 var74 0.43762 0.80426 0.11001 0.34622 anti-PSA 0.0900 0.0002 0.6851 0.1890

16 16 16 16 var75 0.56604 0.87246 0.10048 0.34367 anti-erbB2 0.0223 <.0O01 0.7112 0.1925

16 16 16 16 var76 0.55961 0.87311 0.11127 0.35154 anti-VEGF 0.0242 <.0001 0.6816 0.1818

16 16 16 16 var77 0.44101 0.69810 0.22494 0.36223 anti-alpha synuclein 0.0873 0.0026 0.4023 0.1680

16 16 16 16 var78 0.79527 0.71497 0.50326 0.59035 anti-mucin-1 0.0002 0.0019 0.0469 0.0161

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varlδ varl7 varlβ varl9 var67 0.53706 0.57283 0.59441 0.57943 anti-c-jun 0.0319 0.0204 0.0152 0.0187

16 16 16 16 varS8 0.51260 0.68478 0.68035 0.63805 anti-Fra-2 0.0423 0.0034 0.0037 0.0078

16 16 16 16 varS9 0.04334 -0.00357 -0.01090 0.02177 anti-Fra-1 0.8734 0.9895 0.9680 0.9362

16 16 16 16 var70 0.50985 0.64988 0.64786 0.51604 anti-Jun B 0.0436 0.0064 0.0067 0.0407

16 16 16 16 var71 0.52495 0.66178 0.65806 0.56163 anti-P-c-Jun 0.0368 0.0052 0.0056 0.0236

16 16 16 16 var72 0.77323 0.91075 0.89750 0.78679 anti-TGase3 0.0004 <.00Ol <-0001 0.0003

16 16 16 16 var74 0.36799 0.53769 0.52524 0.38440 anti-PSA 0.1608 0.0317 0.0367 0.1415

16 16 16 16 var75 0.48110 0.67662 0.63523 0.47099 anti-erbB2 0.0592 0.0040 0.0082 0.0656

16 16 IS 16 var76 0.47763 0.67179 0.63172 0.46544 anti-VEGF 0.0613 0.0044 0.0087 0.0692

16 16 16 16 var77 0.43650 0.52593 0.51696 0.38149 anti-alpha synuclein 0.0909 0.0364 0.0403 0.1448

16 16 16 16 var78 0.85528 0.84006 0.85031 0.78820 anti-mu.cin-1 <.00Ol <.0001 <.0001 0.0003

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var20 var21 var22 var23 var67 0.59244 0.36744 0.28597 0.25046 anti-c-jun 0.0156 0.1615 0.2829 0.3495

16 16 16 16 var68 0.56903 0.47412 0.47689 0.32901 anti-Fra-2 0.0214 0.0635 0.0618 0.2134

16 16 16 16 var69 0.02165 0.10728 -0.04982 -0.07514 anti-Fra-1 0.9366 0.6925 0.8546 0.7821

16 16 16 16 var70 0.52308 0.92718 0.20565 0.36143 anti-Jun B 0.0376 <.0001 0.4448 0.1690

16 16 16 16 var71 0.50688 0.95053 0.21673 0.37019 anti-P-c-Jun 0.0451 <.0001 0.4201 0.1581

16 16 16 16 var72 0.76413 0.81840 0.50831 0.54559 anti-TGase3 0.0006 0.0001 0.0444 0.0288 is 16 16 16 var74 0.35149 0.95978 0.27408 0.38757 ant i- PSA 0.1819 <.0001 0.3043 0.1380 16 16 16 16 var75 0.42577 0.86533 0.25279 0.42549 anti-erbB2 0.1001 <-0001 0.3449 0.1004 16 16 16 16 var76 0.42849 0.87340 0.28089 0.42965 anti-VEGF 0.0977 <.0001 0.2920 0.0967 16 16 16 16 var77 0.42877 0.75787 0.12496 0.49909 anti-alpha synuclein 0.0975 0.0007 0.6447 0.0491 16 16 16 16 var78 0.86762 0.50976 0.31054 0.68348 anti-mucin-1 <.0001 0.0437 0.2418 0.0035 16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var24 var25 var26 var27 var67 0.58568 0.57325 0.52746 0.62351 anti-c-jun 0.0171 0.0203 0.0358 0.0099

16 16 16 16 var68 0.72257 0.64678 0.67135 0.65394 anti-Fra-2 0.0016 0.0068 0.0044 0.0060

16 16 16 16 var69 -0.01632 -0.00277 -0.02433 0.00476 anti-Fra-1 0.9522 0.9919 0.9287 0.9860

16 16 16 16 var70 0.47125 0.62094 0.65707 0.61487 anti-Jun B 0.0654 0.0103 0.0057 0.0113

16 16 16 16 var71 0.49907 0.62795 0.67456 0.62615 anti-P-c-Jun 0.0491 0.0092 0.0042 0.0095

16 16 16 16 var72 0.80477 0.88124 0.91710 0.85460 anti-TGase3 0.0002 <.0001 <.0001 <.0001

16 16 16 16 var74 0.39007 0.49981 0.57436 0.46607 anti-PSA 0.1353 0.0487 0.0200 0.0688

16 16 16 16 var75 0.47632 0.59027 0.66022 0.56387 anti-erbB2 0.0622 0.0161 0.0054 0.0229

16 16 16 16 var76 0.47975 0.58972 0.65849 0.56222 anti-VEGF 0.0600 0.0162 0.0055 0.0234

16 16 16 16 var77 0.38345 0.51624 0.52604 0.49485 anti-alpha synuclein 0.1426 0.0406 0.0363 0.0513

16 16 16 16 var78 0.73429 0.89379 0.85524 0.86565 anti-mucin-1 0.0012 <.0001 •s.OOOl <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var28 var29 var30 var31 var67 -0.17081 -0.08778 0.11340 0.07338 anti-c-jun 0.5271 0.7465 0.6758 0.7871

16 16 16 16 var68 0.16420 0.16111 0.13694 0.11746 anti-Fra-2 0.5434 0.5511 0.6131 0.6648

16 16 16 16 varS9 -0.11775 -0.07612 -0.05449 -0.03480 anti-Fra-1 0.6641 0.7793 0.8411 0.8982

16 16 16 16 var70 0.43094 0.38816 0.27936 0.32948 anti-Jun B 0.0956 0.1374 0.2947 0.2127

16 16 16 16 var71 0.47471 0.35087 0.28579 0.32729 anti-P-c-Jun 0.0632 0.1827 0.2833 0.2159

16 16 16 16 var72 0.47191 0.40126 0.43645 0.45442 anti-TGase3 0.0650 0.1235 0.0910 0.0770

16 16 16 16 var74 0.67016 0.48158 0.30589 0.38207 anti-PSA 0.0045 0.0589 0.2492 0.1442

16 16 16 16 var75 0.65566 0.70844 0.32558 0.39411 anti-erbB2 0.0058 0.0021 0.2185 0.1309

16 16 16 16 var76 0.64894 0.69568 0.33665 0.40391 anti-VEGF 0.0065 0.0028 0.2023 0.1208

16 16 16 16 var77 0.46085 0.36963 0.43507 0.50848 anti-alpha synuclein 0.0724 0.1588 0.0921 0.0443

16 16 16 16 var78 0.22928 0.06561 0.67583 0.67640 anti-mucin-1 0.3930 0.8092 0.0041 0.0040

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 var67 -0.40034 0.59336 0.53830 0.46208 anti-c-jun 0.1244 0.0154 0.0315 0.0715

16 16 16 16 var68 -0.09636 0.68759 0.67100 0.49240 anti-Fra-2 0.7226 0.0032 0.0044 0.0527

16 16 16 16 var69 0.19049 0.00431 0.00817 -0.01213 anti-Fra-1 0.4798 0.9874 0.9760 0.9644

16 16 16 16 var70 -0.07057 0.63168 0.56866 0.16099 anti-Jun B 0.7951 0.0087 0.0215 0.5514

16 16 16 16 var71 0.00714 0.63974 0.60927 0.15738 anti-P-c-Jun 0.9791 0.0076 0.0122 0.5605

16 16 16 16 var72 0.00418 0.88551 0.82439 0.40197 anti-TGase3 0.9878 <.0001 <.0001 0.1227

16 16 16 16 var74 0.13563 0.49700 0.47641 -0.00462 anti-PSA 0.6165 0.0502 0.0621 0.9864

16 16 16 16 var7S 0.08541 0.65905 0.53106 0.10186 anti-erbB2 0.7531 0.0055 0.0343 0.7074

16 16 16 16 var76 0.08062 0.65121 0.52236 0.08856 anti-VEGF 0.7666 0.0063 0.0379 0.7443

16 16 16 16 var77 0.02011 0.49786 0.39315 -0.03366 anti-alpha synuclein 0.9411 0.0497 0.1319 0.9015

16 16 16 16 var78 0.07247 0.80448 0.73783 0.39892 anti-mucin-1 0.7897 0.0002 0.0011 0.1259

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var36 var37 var38 var39 var67 0.58688 0.55732 0.22510 0.61853 anti-c-jun 0.0169 0.0249 0.4019 0.0106

16 16 16 16 var68 0.65348 0.67599 0.38560 0.67970 anti-Fra-2 0.0060 0.0040 0.1402 0.0038

16 16 16 16 var69 0.01906 -0.01488 -0.06376 0.01856 anti-Fra-1 0.9441 0.9564 0.8145 0.9456

16 16 16 16 var70 0.52190 0.66884 0.52937 0.58468 anti-Jun B 0.0381 0.0046 0.0350 0.0174

16 16 16 16 var71 0.56091 0.66114 0.60600 0.60159 anti-P-c-Jun 0.0238 0.0053 0.0128 0.0137

16 16 16 16 var72 0.79553 0.92486 0.55741 0.84468 anti-TGase3 0.0002 <.0001 0.0249 <.0001

16 16 16 16 var74 0.38484 0.56197 0.59716 0.43122 anti-PSA 0.1411 0.0235 0.0146 0.0954

16 16 16 16 var75 0.47475 0.67289 0.57319 0.57358 anti-erbB2 0.0631 0.0043 0.0203 0.0202

16 16 16 16 var76 0.46956 0.67125 0.56879 0.56694 anti-VEGF 0.0665 0.0044 0.0215 0.0220

16 16 16 16 var77 0.37564 0.54232 0.38141 0.44786 anti-alpha synuclein 0.1516 0.0300 0.1449 0.0819

16 16 16 16 var78 0.78821 0.86844 0.28150 0.80386 anti-tnucin-1 0.0003 <.O001 0.2909 0.0002

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var40 var41 var42 var43 var67 0.37484 0.52505 0.61100 0.64056 anti-c- jun 0.1526 0.0368 0.0119 0.0075

16 16 16 16 var68 0.57783 0.60023 0.66437 0.68247 anti-Fra-2 0.0191 0.0140 0.0050 0.0036

16 16 16 16 var69 -0.03795 0.03180 0.00912 0.03521 anti-Fra-1 0.8890 0.9069 0.9732 0.8970

16 16 16 16 var70 0.71784 0.92170 0.49813 0.45243 ant i -Jun B 0.0017 <.0001 0.0496 0.0785

16 16 16 16 var71 0.74462 0.92003 0.49451 0.48240 ant i- P- c -Jun 0.0009 <.0001 0.0515 0.0584

16 16 16 16 var72 0.84932 0.92626 0.77917 0.75966 anti-TGase3 <.0001 <.0001 0.0004 0.0006

16 16 16 16 var74 0.70504 0.86168 0.35303 0.30614 ant i- PSA 0.0023 <.0001 0.1798 0.2488

16 16 16 16 var75 0.85909 0.86838 0.47794 0.40103 anti-erbB2 <.0001 <.0001 0.0611 0.1237

16 16 16 16 var7S 0.84900 0.87437 0.48662 0.40507 anti-VEGF <.0001 <.0001 0.0559 0.1196

16 16 16 16 var77 0.54431 0.71124 0.27216 0.29781 anti-alpha synuclein 0.0293 0.0020 0.3079 0.2626

16 16 16 16 var78 0.53796 0.69320 0.63578 0.71350 anti-mucin-1 0.0316 0.0029 0.0081 0.0019

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var45 var46 var47 var48 var67 0.15609 -0.11290 0.44538 0.09024 anti-c-jun 0.5638 0.6772 0.0838 0.7396

16 16 16 16 var68 0.03199 -0.14114 0.68313 0.25463 anti-Fra-2 0.9064 0.6021 0.0035 0.3412

16 16 16 16 var69 0.61706 -0.08724 -0.01994 0.20353 anti-Fra-1 0.0109 0.7480 0.9416 0.4496

16 16 16 16 var70 0.09202 0.18374 0.59535 0.81952 anti-Jun B 0.7346 0.4958 0.0150 0.0001

16 16 16 16 var71 0.12469 0.19963 0.67700 0.85037 anti-P-c-Jun 0.6454 0.4585 0.0040 <.0001

16 16 16 16 var72 0.1730S 0.25847 0.74752 0.67561 anti-TGase3 0.5215 0.3337 0.0009 0.0041

16 16 16 16 var74 0.01481 0.26942 0.58474 0.94262 anti-PSA 0.9566 0.3129 0.0174 <.0001

16 16 16 16 var75 0.01809 0.26907 0.65180 0.88988 anti-erbB2 0.9470 0.3136 0.0062 <.0001

16 16 16 16 var76 0.02818 0.27840 0.62342 0.89675 anti-VEGF 0.9175 0.2964 0.0099 <.0001

16 16 16 16 var77 0.16908 0.38657 0.41490 0.70586 anti-alpha synuclein 0.5313 0.1391 0.1100 0.0022

16 16 16 16 var78 0.15344 0.50589 0.49555 0.26571 anti-mucin-1 0.5705 0.045S 0.0509 0.3199

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var49 var50 var51 var52 var67 0.32675 0.40296 0.54828 0.58958 anti-c-jun 0.2167 0.1217 0.0279 0.0162

16 16 16 16 var68 0.44265 0.58801 0.57999 0.64506 anti-Fra-2 0.0860 0.0166 0.0185 0.0070

16 16 16 16 var69 0.10389 -0.00506 -0.09538 -0.00870 anti-Fra-1 0.7018 0.9852 0.7253 0.9745

16 16 16 16 var70 0.92782 0.58111 0.54414 0.65303 anti-Jun B <.0001 0.0182 0.0293 0.0061

16 16 16 16 var71 0.944S3 0.56372 0.50852 0.64939 anti-P-c-Jun <.0001 0.0230 0.0443 0.0065

16 16 16 16 var72 0.73885 0.80211 0.83541 0.88081 anti-TGase3 0.0011 0.0002 <.0001 •=.0001

16 16 16 16 var74 0.96775 0.49822 0.42540 0.52156 anti-PSA <.0001 0.0495 0.1004 0.0383

16 16 16 16 var75 0.93214 0.75929 0.55778 0.62885 anti-erbB2 <-0001 0.0006 0.0248 0.0091

16 16 16 16 var76 0.93101 0.74504 0.56584 0.62684 anti-VEGF <.0001 0.0009 0.0223 0.0094

16 16 16 16 var77 0.77642 0.47244 0.50537 0.53718 anti-alpha synuclein 0.0004 0.0646 0.0458 0.0319

16 16 16 16 var78 0.34132 0.59779 0.90986 0.86032 anti-mucin-1 0.1957 0.0145 <.0O01 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var53 var54 var55 varSβ var67 0.52193 -0.01937 0.28581 0.45138 anti-c-jun 0.0381 0.9432 0.2832 0.0793

16 16 16 16 var68 0.50456 0.08509 0.51984 0.60675 anti-Fra-2 0.0462 0.7540 0.0390 0.0127

16 16 16 16 var69 -0.01548 -0.07009 -0.05479 0.00325 anti-Fra-1 0.9546 0.7965 0.8403 0.9905

16 16 16 16 var70 0.47787 0.30717 0.65955 0.57872 anti-Jun B 0.0612 0.2472 0.0054 0.0188

16 16 16 16 var71 0.47727 0.18028 0.69882 0.57067 anti-P-c-Jun 0.0616 0.5040 0.0026 0.0210

16 16 16 16 var72 0.75281 0.35546 0.75765 0.80475 anti-TGase3 0.0008 0.1767 0.0007 0.0002

16 16 16 16 var74 0.34116 0.30294 0.69171 0.47378 anti-PSA 0.1960 0.2541 0.0030 0.0638

16 16 16 16 var75 0.41420 0.51025 0.83699 0.72972 anti-erbB2 0.1107 0.0434 <.0001 0.0013

16 16 16 16 var76 0.41974 0.50961 0.82510 0.71552 anti-VEGF 0.1055 0.0438 <-0001 0.0018

16 16 16 16 var77 0.45260 0.36926 0.50350 0.45613 anti-alpha synuclein 0.0783 0.1593 0.0468 0.0758

16 16 16 16 var78 0.94832 0.29946 0.38861 0.61788 anti-mucin-1 <.0001 0.2598 0.1369 0.0107

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var57 var58 var59 var60 var67 0.42942 0.46419 0.32669 0.33378 anti-c-jun 0.0969 0.0701 0.2168 0.2064

16 16 16 16 var68 0.55575 0.49802 0.63146 0.50861 anti-Fra-2 0.0254 0.0496 0.0087 0.0442

16 16 16 16 var69 0.02781 -0.06297 -0.05854 0.00376 anti-Fra-1 0.9186 0.8168 0.8295 0.9890

16 16 16 16 var70 0.84444 0.89584 0.70912 0.54484 anti-Jun B <.0001 <.0001 0.0021 0.0291

16 16 16 16 var71 0.90991 0.87850 0.74740 0.51836 anti-P-c-Jun <.0001 <.0001 0.0009 0.0397

16 16 16 16 var72 0.73000 0.76428 0.89142 0.72224 anti-TGase3 0.0013 0.0006 ■=.0001 0.0016

16 16 16 16 var74 0.88747 0.89351 0.76310 0.47301 anti-PSA <.0001 ■=.0001 0.0006 0.0643

16 16 16 16 var75 0.79198 0.86957 0.79359 0.75358 anti-erbB2 0.0003 <.0001 0.0002 0.0007

16 16 16 16 var76 0.78583 0.87507 0.78309 0.73853 anti-VEGF 0.0003 <.0001 0.0003 0.0011

16 16 16 16 var77 0.70117 0.89094 0.53380 0.45899 anti-alpha synuclein 0.0025 ■=.0001 0.0332 0.0737

16 16 16 16 var78 0.39071 0.58729 0.61025 0.49864 anti-mucin-1 0.1346 0.0168 0.0121 0.0493

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var61 var62 var63 var64 var67 0.43060 0.31603 0.57403 0.62785 anti-c-jun 0.0959 0.2331 0.0201 0.0092

16 16 16 16 var68 0.65134 0.55917 0.67873 0.66180 anti-Fra-2 0.0063 0.0243 0.0038 0.0052

16 16 16 16 var69 -0.02920 -0.06574 0.02782 0.03215 anti-Fra-1 0.9145 0.8089 0.9185 0.9059

16 16 16 16 var70 0.58184 0.71290 0.81662 0.54616 anti-Jun B 0.0181 0.0019 0.0001 0.0286

16 16 16 16 var71 0.62968 0.76943 0.84772 0.56677 anti-P-c-Jun 0.0089 0.0005 ■=.0001 0.0221

16 16 16 16 var72 0.83652 0.82913 0.93618 0.80233 anti-TGase3 <.0001 <.0001 <.0001 0.0002

16 16 16 16 var74 0.55563 0.76474 0.74494 0.37788 anti-PSA 0.0254 0.0006 0.0009 0.1490

16 16 16 16 var75 0.60228 0.71996 0.78812 0.50088 anti-erbB2 0.0136 0.0017 0.0003 0.0481

16 16 16 16 var76 0.59142 0.71531 0.78625 0.49419 anti-VEGF 0.0158 0.0018 0.0003 0.0517

16 16 16 16 var77 0.41005 0.47354 0.63812 0.40403 anti-alpha synuclein 0.1147 0.0639 0.0078 0.1206

16 16 16 16 var78 0.69006 0.55469 0.74530 0.79500 anti-mucin-1 0.0031 0.0257 0.0009 0.0002

16 16 16 16 Pearson Correlation Coef ficients Prob > | r] under HO : Rho=0 Number of Observations varθ5 varbb var67 var68 var67 0.59S57 0.46452 1.00000 0.76676 anti-c-jun 0.0147 0.0699 0.0005

IS 16 16 16 varS8 0.59293 0.64405 0.76676 1.00000 anti-Fra-2 0.0155 0.0071 0.0005

16 16 IS 16 var69 0.33185 -0.02559 -0.13175 -0.29226 anti-Fra-1 0.2092 0.9251 0.62S7 0.2720

16 16 16 16 var70 0.7S280 0.72691 0.56617 0.53562 anti-Jun B 0.0006 0.0014 0.0222 0.0325

16 16 16 16 var71 0.83777 0.78142 0.54104 0.52181 anti-P-c-Jun <.0001 0.0004 0.0305 0.0382

16 16 IS 16 var72 0.77382 0.88560 0.48876 0.70922 anti-TGase3 0.0004 <.0001 0.0547 0.0021

16 16 16 16 var74 0.67201 0.70205 0.29295 0.42164 anti-PSA 0.0044 0.0024 0.2708 0.1038

16 16 IS 16 var75 0.68335 0.71249 0.30795 0.51000 anti-erbB2 0.0035 0.0020 0.2459 0.0436

16 16 16 16 var76 0.67505 0.70754 0.31035 0.49665 anti-VEGF 0.0041 0.0022 0.2420 0.0504

16 16 IS 16 var77 0.74450 0.49117 0.46114 0.33127 anti-alpha synuclein 0.0009 0.0534 0.0722 0.2101

16 16 16 16 var78 0.62433 0.66492 0.47954 0.46075 anti-mucin-1 0.0097 0.0049 0.0602 0.0725

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var69 var70 var71 var72 var67 -0.13175 0.56617 0.54104 0.48876 anti-c-jun 0.S267 0.0222 0.0305 0.0547

16 16 IS 16 var68 -0.29226 0.53562 0.52181 0.70922 anti-Fra-2 0.2720 0.0325 0.0382 0.0021

16 16 16 16 var69 1.00000 0.03601 0.11862 -0.07256 anti-Fra-1 0.8947 0.6617 0.7894

16 16 16 16 var70 0.03601 1.00000 0.97573 0.79618 anti-Jun B 0.8947 <.0001 0.0002

16 16 16 16 var71 0.11862 0.97573 1.00000 0.77619 anti-P-c-Jun 0.6617 <.0001 0.0004

16 16 16 16 var72 0.07256 0.79618 0.77619 1.00000 anti-TGase3 0.7894 0.0002 0.0004

IS 16 16 16 var74 0.03758 0.93345 0.92860 0.77729 anti-PSA 0.8901 <.0001 <.0001 0.0004

16 16 16 16 var75 0.00172 0.88568 0.87650 0.85269 anti-erbB2 0.9949 <.0001 <.0001 <.0001

16 16 16 16 var7S 0.00322 0.89535 0.87933 0.85869 anti-VEGF 0.9905 <.0001 <.0001 <.0001

16 16 16 16 var77 0.33185 0.83178 0.82926 0.62902 anti-alpha synuclein 0.2092 <-0001 <.0001 0.0090

16 16 16 16 var78 0.06278 0.52984 0.48846 0.76618 anti-mucin-1 0.8173 0.0348 0.0549 0.0005

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var74 var75 var76 var77 var67 0.29295 0.30795 0.31035 0.46114 anti-c-jun 0.2708 0.2459 0.2420 0.0722

16 16 16 16 var68 0.42164 0.51000 0.49665 0.33127 anti-Fra-2 0.1038 0.0436 0.0504 0.2101

16 16 16 16 var69 0.03758 -0.00172 0.00322 0.33185 anti-Fra-1 0.8901 0.9949 0.9905 0.2092

16 16 16 16 var70 0.93345 0.88568 0.89535 0.83178 anti-Jun B < .0001 <.0001 <.0001 <.0001

16 16 16 16 var71 0.92860 0.87650 0.87933 0.82926 anti-P-c-Jun <.0001 <.0001 <.0001 <.0001

16 16 16 16 var72 0.77729 0.85269 0.85869 0.62902 anti-TGase3 0.0004 <.0001 <.0001 0.0090

16 16 16 16 var74 1.00000 0.92707 0.93747 0.77992 anti-PSA <.0001 <.0001 0.0004

16 16 16 16 var75 0.92707 1.00000 0.99715 0.74590 anti-erbB2 <.0001 <.0001 0.0009

16 16 16 16 var76 0.93747 0.99715 1.00000 0.75325 anti-VEGF <.0001 <-0001 0.0008

16 16 16 16 var77 0.77992 0.74590 0.75325 1.00000 anti-alpha synuclein 0.0004 0.0009 0.0008

16 16 16 16 var78 0.41634 0.48545 0.49410 0.57147 anti-mucin-1 0.1087 0.0566 0.0517 0.0207

16 16 16 16 Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 varδl var67 0.47954 0.15778 0.33688 0.64166 anti-c-jun 0.0602 0.5595 0.2020 0.0181

IS 16 16 13 var68 0.46075 0.28408 0.48120 0.44750 anti-Fra-2 0.0725 0.2863 0.0591 0.1252

16 16 16 13 var69 -0.06278 0.08902 0.04308 -0.17828 anti-Fra-1 0.8173 0.7430 0.8741 0.5601

16 16 16 13 var70 0.52984 0.84617 0.94222 0.41560 anti-Jun B 0.0348 <-0001 <-0001 0.1578

16 16 16 13 var71 0.48846 0.86254 0.94450 0.34463 anti-P-c-Jun 0.0549 <.0001 <.0001 0.2489

16 16 16 13 var72 0.7S618 0.67008 0.82634 0.61774 anti-TGase3 0.0005 0.0045 <.0001 0.0245

16 16 16 13 var74 0.41634 0.95065 0.98876 0.27095 anti-PSA 0.1087 <.0001 ■=.0001 0.3706

16 16 16 13 var75 0.48545 0.87365 0.96072 0.26561 anti-erbB2 0.0566 <.0001 <.0001 0.3804

16 16 16 13 var76 0.49410 0.88261 0.96496 0.27819 anti-VEGF 0.0517 <.0001 <.0001 0.3574

16 16 16 13 var77 0.57147 0.73498 0.78772 0.42677 anti-alpha synuclein 0.0207 0.0012 0.0003 0.1458

16 16 16 13 var78 1.00000 0.31464 0.47320 0.86681 anti-mucin-1 0.2353 0.0641 0.0001

16 16 16 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var82 var83 var84 var85 var67 0.37159 0.61402 0.59378 0.39210 anti-c-jun 0.2112 0.0256 0.0324 0.1851

13 13 13 13 var68 0.37430 0.70749 0.67924 0.50449 anti-Fra-2 0.2077 0.0068 0.0107 0.0787

13 13 13 13 var69 0.45195 -0.02502 -0.02988 0.01338 anti-Fra-1 0.1210 0.9353 0.9228 0.9654

13 13 13 13 var70 0.77554 0.85275 0.65090 0.91975 anti-Jun B 0.0018 0.0002 0.0160 <.0001

13 13 13 13 var71 0.88482 0.85897 0.63550 0.90123 cuiuj.- f-c-uun <-0001 0.0002 0.0196 <.0001

13 13 13 13 var72 0.6S781 0.92509 0.80877 0.83565 anti-TGase3 0.0126 <-0001 0.0008 0.0004

13 13 13 13 var74 0.80487 0.81050 0.55723 0.94751 anti-PSA 0.0009 0.0008 0.0479 <.0001

13 13 13 13 var75 0.73352 0.94321 0.79128 0.99619 anti-erbB2 0.0043 <.0001 0.0013 <.0001

13 13 13 13 var76 0.73188 0.93182 0.77244 0.99832 anti-VEGF 0.0045 <.0001 0.0020 <.0001

13 13 13 13 var77 0.78437 0.73055 0.55244 0.81040 anti-alpha synuclein 0.0015 0.0046 0.0503 0.0008

13 13 13 13 var78 0.37276 0.61204 0.56517 0.46888 anti-raucin-1 0.2097 0.0262 0.0441 0.1060

13 13 13 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var86 var87 var88 var89 var67 0.30616 0.32378 0.18520 0.55294 anti-c-jun 0.2488 0.2391 0.5087 0.0325

16 15 15 15 varS8 0.26966 0.32604 0.12252 0.68480 anti-Fra-2 0.3125 0.2356 0.6636 0.0049

16 15 15 15 var69 0.34950 0.22719 0.00424 0.02419 anti-Fra-1 0.1845 0.4155 0.9880 0.9318

16 15 15 15 var70 0.86006 0.83933 0.23505 0.59769 anti-Jun B <.0001 <.0001 0.3991 0.0186

16 15 15 15 var71 0.90804 0.86254 0.11790 0.60951 anti-P-c-Jun <.0001 <.0001 0.6756 0.0159

16 15 15 15 var72 0.53956 0.59748 0.31152 0.83985 anti-TGase3 0.0310 0.0187 0.2584 <.0001

16 15 15 15 var74 0.86642 0.79718 0.13236 0.45863 anti-PSA <.0001 0.0004 0.6382 0.0855

16 15 15 15 var75 0.79197 0.80613 0.14755 0.67165 anti-erbB2 0.0003 0.0003 0.5997 0.0061

16 15 15 15 var76 0.79127 0.81229 0.15681 0.65948 anti-VEGF 0.0003 0.0002 0.5768 0.0075

16 15 15 15 var77 0.78131 0.64579 0.32006 0.45934 anti-alpha synuclein 0.0004 0.0093 0.2448 0.0850

16 15 15 15 var78 0.19213 0.21806 0.58223 0.70499 anti-mucin-1 0.4759 0.4350 0.0228 0.0033 16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var90 var91 var92 var93 varS₇ 0.5069S 0.55416 0.53638 0.61175 anti-c-jun 0.0538 0.0321 0.0322 0.0118

15 15 16 16 var68 0.53034 0.69375 0.60305 0.64438 anti-Fra-2 0.0420 0.0041 0.0134 0.0071

15 15 16 16 varS9 -0.01252 0.09838 0.08803 0.03360 anti-Fra-1 0.9647 0.7272 0.7458 0.9017

15 15 16 16 var70 0.41728 0.71321 0.67887 0.52584 anti-Jun B 0.1217 0.0028 0.0038 0.0364

15 15 16 16 var71 0.46588 0.75622 0.65157 0.55874 anti-P-c-Jun 0.0801 0.0011 0.0053 0.0245

15 15 16 16 var72 0.70872 0.89462 0.83460 0.78943 anti-TGase3 0.0031 <.0001 <.0001 0.0003

15 15 16 16 var74 0.28355 0.62473 0.54461 0.36999 anti-PSA 0.3058 0.0128 0.0292 0.1584

15 15 16 16 var75 0.38415 0.70883 0.76073 0.47032 anti-erbB2 0.1575 0.0031 0.0006 0.0660

15 15 16 16 var76 0.38121 0.70037 0.75113 0.46559 anti-VEGF 0.1609 0.0036 0.0008 0.0S91

15 15 16 16 var77 0.33650 0.60770 0.60732 0.38812 anti-alpha synuclein 0.2201 0.0163 0.0126 0.1374

15 15 16 16 var78 0.80854 0.76806 0.70411 0.79565 anti-mucin-1 0.0003 0.0008 0.0023 0.0002

15 15 16 16

Capture varl var2 var3 var79 0.77586 0.81681 0.41588 0.31976 anti-Cystatin A 0.0004 0.0001 0.1091 0.2273

16 16 16 16 var80 0.92726 0.94615 0.60073 0.51284 anti-Cystatin S <.0001 <.0001 0.0139 0.0422

16 16 16 16 var81 0.40299 0.40855 0.69511 0.77714 Prostein 0.1721 0.1657 0.0084 0.0018

13 13 13 13 var82 0.68495 0.77161 0.61683 0.53139 Aquaporin 4 0.0098 0.0020 0.0247 0.0616

13 13 13 13 var83 0.93635 0.93032 0.79740 0.73836 Trypsin •=.0001 <.0001 0.0011 0.0039

13 13 13 13 var84 0.83437 0.78479 0.73270 0.70511 Osteonectin 0.0004 0.0015 0.0044 0.0071

13 13 13 13 var85 0.96109 0.93519 0.58442 0.50913 RAGE ■=.0001 <.0001 0.0359 0.0756

13 13 13 13 var86 0.83523 0.80522 0.38817 0.29482 PGRP-I Beeta <.0001 0.0002 0.1374 0.2677

16 16 16 16 var87 0.73230 0.81257 0.47010 0.39007 PGRP-S 0.0019 0.0002 0.0770 0.1506

15 15 15 15 var88 0.20993 0.19853 0.29036 0.41067

Gram positive bacteria 0.4527 0.4781 0.2938 0.1284

15 15 15 15 var89 0.65948 0.75658 0.91093 0.89759

Troponin C Cardiac 0.0075 0.0011 .= .0001 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var4 var5 varδ var7 var79 0.35929 0.72880 0.88030 0.13304 anti-Cystatin A 0.1717 0.0014 <.0001 0.6233

16 16 16 16 var80 0.54530 0.71339 0.95302 0.20478 anti-Cystatin S 0.0289 0.0019 ■=.0001 0.4468

16 16 16 16 var81 0.72543 0.18341 0.39801 0.32499 Prostein 0.0050 0.5487 0.1780 0.2786

13 13 13 13 var82 0.58096 0.52732 0.80693 0.18374 Aquaporin 4 0.0373 0.0640 0.0009 0.5479

13 13 13 13 var83 0.76321 0.62196 0.77498 0.28352 Trypsin 0.0024 0.0232 0.0019 0.3479

13 13 13 13 var84 0.71362 0.41579 0.54191 0.23791 Osteonectin 0.0062 0.1576 0.0557 0.4338

13 13 13 13 var85 0.53623 0.73554 0.87345 0.22248 RAGE 0.0589 0.0042 <.0001 0.4650

13 13 13 13 var86 0.33832 0.44373 0.86399 0.03687 PGRP-I Beeta 0.1999 0.0851 •=.0001 0.8922

16 16 16 16 var87 0.43573 0.42901 0.79661 0.04733 PGRP-S 0.1045 0.1106 0.0004 0.8670

15 15 15 15 var88 0.33465 0.02229 0.20360 -0.02347

Gram positive bacteria 0.2228 0.9372 0.4667 0.9338

15 15 15 15 var89 0.90955 0.33604 0.52020 0.35640 Troponin C Cardiac <.0001 0.2207 0.04S8 0.1923

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var8 var9 varlO varll var79 0.588S0 0.36059 0.33502 0.71412 anti-Cystatin A 0.0165 0.1700 0.2046 0.0019

16 16 16 16 var80 0.57966 0.56088 0.52908 0.73756 anti-Cystatin S 0.0038 0.0238 0.0351 0.0011

16 16 16 16 var81 0.52456 0.64036 0.72315 -0.06200 Prostein 0.0657 0.0184 0.0052 0.8405

13 13 13 13 var82 0.50253 0.58738 0.55925 0.48047 Aquaporin 4 0.0801 0.0348 0.0469 0.0965

13 13 13 13 var83 0.61969 0.82489 0.75638 0.74094 Trypsin 0.0239 0.0005 0.0028 0.0038

13 13 13 13 var84 0.47941 0.80677 0.72029 0.62320 Osteonectin 0.0974 0.0009 0.0055 0.0229

13 13 13 13 var85 0.63289 0.59061 0.52326 0.84541 RAGE 0.0203 0.0336 0.0665 0.0003

13 13 13 13 var86 0.46995 0.37861 0.32913 0.56056 PGRP-I Beeta 0.0662 0.1482 0.2132 0.0239

16 16 16 16 var87 0.38155 0.49897 0.42311 0.44995 PGRP-S 0.1605 0.0583 0.1161 0.0924

15 15 15 15 var88 0.24761 0.26989 0.33066 -0.04510

Gram positive bacteria 0.3736 0.3306 0.2287 0.8732

15 15 15 15 var89 0.51022 0.96468 0.91407 0.30534

Troponin C Cardiac 0.0520 <.0001 <.0001 0.2684

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl2 varl3 varl4 varl5 var79 0.33210 0.69272 0.07602 0.30459 anti-Cystatin A 0.2089 0.0029 0.7796 0.2514

16 16 16 16 var80 0.52599 0.85821 0.10254 0.35054 anti-Cystatin S 0.0364 <.0001 0.7055 0.1831

16 16 16 16 varδl 0.65660 0.52857 0.15805 0.29365 Prostein 0.0148 0.0633 0.6061 0.3302

13 13 13 13 var82 0.58147 0.74321 0.01497 0.18582 Aquaporin 4 0.0371 0.0036 0.9613 0.5433

13 13 13 13 var83 0.78973 0.93526 0.06883 0.31994 Trypsin 0.0013 <.0001 0.8232 0.2866

13 13 13 13 var84 0.7S447 0.83087 0.02500 0.20383 Osteonectin 0.0023 0.0004 0.9354 0.5042

13 13 13 13 var85 0.54763 0.85037 0.08346 0.32036 RAGE 0.0527 0.0002 0.78S3 0.2859

13 13 13 13 var86 0.34180 0.70610 -0.03169 0.10780 PGRP-I Beeta 0.1951 0.0022 0.9073 0.6911

16 16 16 16 var87 0.46955 0.76052 -0.11296 0.05410 PGRP-S 0.0774 0.0010 0.6885 0.8481

15 15 15 15 var88 0.27249 0.24316 -0.10412 -0.06559

Gram positive bacteria 0.3258 0.3825 0.7119 0.8163

15 15 15 15 var89 0.94643 0.88401 0.07838 0.24146

Troponin C Cardiac <.0001 <.O001 0.7813 0.3860

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations varl6 varl7 varl8 varl9 var79 0.27119 0.42274 0.42984 0.26669 anti-Cystatin A 0.3096 0.1028 0.0966 0.3181

16 16 16 16 var80 0.44790 0.62217 0.60672 0.46019 anti-Cystatin S 0.0819 0.0101 0.0127 0.0729

16 16 16 16 var81 0.79691 0.65764 0.73338 0.61900 Prostein 0.0011 0.0146 0.0043 0.0241

13 13 13 13 var82 0.47235 0.59570 0.61132 0.54441 Aquaporin 4 0.1031 0.0317 0.0264 0.0544

13 13 13 13 var83 0.69515 0.86010 0.82209 0.68372 Trypsin 0.0083 0.0002 0.0006 0.0100

13 13 13 13 var84 0.67323 0.82954 0.75999 0.65436 Osteonectin 0.0117 0.0005 0.0026 0.0152

13 13 13 13 var85 0.46406 0.65197 0.61289 0.43053 RAGE 0.1102 0.0157 0.0259 0.1420

13 13 13 13 var86 0.23497 0.40447 0.37087 0.30424 PGRP-I Beeta 0.3810 0.1202 0.1573 0.2519

16 16 16 16 var87 0.32721 0.50226 0.48021 0.37976 PGRP-S 0.2339 0.0564 0.0700 0.1627

15 15 15 15 var88 0.38832 0.28902 0.38347 0.16249

Gram positive bacteria 0.1526 0.29S1 0.1583 0.5629

15 15 15 15 var89 0.85475 0.95925 0.92392 0.87793

Troponin C Cardiac <.0001 <.0001 <.0001 <.0001 15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var20 var21 var22 var23 var79 0.26034 0.89180 0.20353 0.28704 anti-Cystatin A 0.3301 <.0001 0.4496 0.2811

16 16 16 16 var80 0.42630 0.95676 0.28317 0.40430 anti-Cystatin S 0.0996 <.0001 0.2879 0.1204

16 16 16 16 var81 0.86955 0.38922 0.30684 0.32168 Prostein 0.0001 0.1887 0.3079 0.2838

13 13 13 13 var82 0.47022 0.88600 0.22772 0.25043 Aquaporin 0.1049 <.0001 0.4543 0.4092

13 13 13 13 var83 0.63508 0.81126 0.26621 0.42017 Trypsin 0.0197 0.0008 0.3793 0.1529

13 13 13 13 var84 0.59523 0.55610 0.19408 0.37841 Osteonectin 0.0319 0.0484 0.5252 0.2023

13 13 13 13 var85 0.41630 0.87178 0.22301 0.36884 RAGE 0.1571 0.0001 0.4640 0.2149

13 13 13 13 var86 0.19825 0.85636 0.05963 0.23780 PGRP-I Beeta 0.4617 <.0001 0.8264 0.3751

16 16 16 16 var87 0.31319 0.77212 0.07123 0.10912 PGRP-S 0.2557 0.0007 0.8009 0.6987

15 15 15 15 var88 0.58513 0.14609 -0.01943 -0.04305

Gram positive bacteria 0.0219 0.6034 0.9452 0.8789

15 15 15 15 var89 0.80639 0.54597 0.28179 0.40914

Troponin C Cardiac 0.0003 0.0352 0.3089 0.1299

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var24 var25 var26 var27 var79 0.30063 0.39160 0.46587 0.36281 anti-Cystatin A 0.2579 0.1336 0.0690 0.1672

16 16 16 16 var80 0.45887 0.57354 0.64315 0.54586 anti-Cystatin S 0.0738 0.0202 0.0072 0.0287

16 16 16 16 varδl 0.64069 0.75980 0.69004 0.74362 Prostein 0.0183 0.0026 0.0090 0.0036

13 13 13 13 var82 0.50640 0.57854 0.63416 0.57667 Aquaporin 4 0.0774 0.0383 0.0199 0.0391 13 13 13 13 var83 0.65650 0.77360 0.82640 0.76547 Trypsin 0.0148 0.0019 0.0005 0.0023

13 13 13 13 var84 0.59977 0.71544 0.74754 0.71446 Osteonectin 0.0303 0.0060 0.0033 0.0061

13 13 13 13 var85 0.44385 0.56577 0.63719 0.54498 RAGE 0.1287 0.0439 0.0192 0.0541

13 13 13 13 var86 0.21783 0.34017 0.40451 0.33571 PGRP-I Beeta 0.4177 0.1973 0.1202 0.2037

16 16 16 16 var87 0.31953 0.42678 0.48423 0.44580 PGRP-S 0.2457 0.1126 0.0674 0.0958

15 15 15 15 var88 0.23308 0.38751 0.29364 0.36860

Gram positive bacteria 0.4031 0.1536 0.2881 0.1764

15 15 15 15 var89 0.79133 0.89479 0.89956 0.90855

Troponin C Cardiac 0.0004 <.0001 <.0001 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var28 var29 var30 var31 var79 0.67326 0.48866 0.24523 0.33280 anti-Cystatin 0.0043 0.0548 0.3600 0.2078

16 16 16 16 var80 0.65255 0.52424 0.31718 0.39030 anti-Cystatin 0.0061 0.0371 0.2313 0.1350

16 16 16 16 varδl -0.08034 -0.16507 0.30240 0.30984 Prostein 0.7942 0.5900 0.3153 0.3029

13 13 13 13 var82 0.47768 0.24791 0.22648 0.25167 Aquaporin 4 0.0988 0.4141 0.4568 0.4068

13 13 13 13 var83 0.52272 0.64874 0.32738 0.34773 Trypsin 0.0668 0.0165 0.2749 0.2443

13 13 13 13 var84 0.32356 0.67284 0.26638 0.26635 Osteonectin 0.2809 0.0117 0.3790 0.3791

13 13 13 13 var85 0.65713 0.73526 0.31167 0.36828 RAGE 0.0147 0.0042 0.2999 0.2157

13 13 13 13 var86 0.48755 0.40572 0.15923 0.21697 PGRP-I Beeta 0.0554 0.1190 0.5558 0.4196

16 16 16 16 var87 0.29018 0.48447 0.09587 0.10963 PGRP-S 0.2941 0.0672 0.7340 0.6973

15 15 15 15 var88 -0.20129 -0.03521 -0.01090 0.06935

Gram positive bacteria 0.4719 0.9009 0.9692 0.8060

15 15 15 15 var89 0.13548 0 38106 0.32655 0.28539

Troponin C Cardiac 0.6302 0 .1611 0.2349 0.3025

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 var79 0.22819 0.38975 0.32359 -0.06996 anti-Cystatin A 0.3953 0.1356 0.2215 0.7968

16 16 16 16 var80 0.12247 0.58989 0.53765 0.06518 anti-Cystatin S 0.6514 0.0162 0.0317 0.8105

16 16 16 16 varδl -0.35933 0.65310 0.66785 0.29302 Prostein 0.2279 0.0155 0.0126 0.3313

13 13 13 13 var82 0.30626 0.58045 0.55573 0.19015 Aquaporin 4 0.3088 0.0375 0.0486 0.5338

^■ 13 13 13 13 var83 0.01168 0.86594 0.71543 0.32627 Trypsin 0.9698 0.0001 0.0060 0.2766

13 13 13 13 var84 -0.13013 0.85353 0.69032 0.37546 Osteonectin 0.6718 0.0002 0.0090 0.2062

13 13 13 13 var85 0.08622 0.64343 0.45952 0.07151 RAGE 0.7794 0.0177 0.1142 0.8164

13 13 13 13 var86 0.09605 0.38276 0.38397 -0.04561 PGRP-I Beeta 0.7235 0.1434 0.1420 0.8668

16 16 16 16 var87 0.00141 0.50955 0.35263 0.08464 PGRP-S 0.9960 0.0524 0.1974 0.7642

15 15 15 15 var88 -0.26377 0.31852 0.21694 0.09773

Gram positive bacteria 0.3422 0.2473 0.4374 0.7290

15 15 15 15 var89 -0.13603 0.97706 0.83898 0.56450

Troponin C Cardiac 0.6288 <.0001 <-0001 0.0284

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var36 var37 var38 var39 var79 0.26490 0.45077 0.74801 0.31572 anti-Cystatin A 0.3214 0.0797 0.0009 0.2336

16 16 16 16 var80 0.46234 0.63870 0.63416 0.52141 anti-Cystatin S 0.0714 0.0077 0.0083 0.0383

16 16 16 16 var81 0.63759 0.76235 0.19901 0.66136 Prostein 0.0191 0.0024 0.5145 0.0138

13 13 13 13 var82 0.54224 0.58882 0.78195 0.55451 Aquaporin 4 0.0556 0.0342 0.0016 0.0492

13 13 13 13 var83 0.69328 0.83978 0.57381 0.79934 Trypsin 0.0086 0.0003 0.0403 0.0010

13 13 13 13 var84 0.S6693 0.78811 0.24142 0.79374 Osteonectin 0.0128 0.0014 0.4268 0.0012

13 13 13 13 var85 0.44041 0.64893 0.59641 0.55462 RAGE 0.1320 0.0164 0.0314 0.0492

13 13 13 13 var86 0.29887 0.38401 0.40341 0.33880 PGRP-I Beeta 0.2608 0.1420 0.1213 0.1993

16 16 16 16 var87 0.38895 0.47218 0.58521 0.46107 PGRP-S 0.1519 0.0755 0.0219 0.0837

15 15 15 15 var88 0.19603 0.44464 0.05425 0.28806

Gram positive bacteria 0.4838 0.0968 0.8477 0.2978

15 15 15 15 var89 0.88780 0.91610 0.37059 0.95906

Troponin C Cardiac <.0001 <.0001 0.1739 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var40 var41 var42 var43 var79 0.72491 0.75803 0.22022 0.19494 anti-Cystatin A 0.0015 0.0007 0.4125 0.4694

16 16 16 16 var80 0.78562 0.89735 0.42259 0.38563 anti-Cystatin S 0.0003 <.0001 0.1030 0.1402

16 16 16 16 var81 0.34493 0.53899 0.48653 0.62413 Prostein 0.2484 0.0573 0.0918 0.0226

13 13 13 13 var82 0.77606 0.76995 0.44387 0.48573 Aquaporin 4 0.0018 0.0021 0.1287 0.0924

13 13 13 13 var83 0.96451 0.89006 0.69609 0.63333 Trypsin <.0001 <.0001 0.0082 0.0201

13 13 13 13 var84 0.81173 0.73386 0.71876 0.61974 Osteonectin 0.0008 0.0043 0.0056 0.0239

13 13 13 13 var85 0.89335 0.84841 0.47375 0.38410 RAGE <.0001 0.0002 0.1020 0.1951

13 13 13 13 var86 0.54724 0.74193 0.26176 0.21049 PGRP-I Beeta 0.0282 0.0010 0.3274 0.4339

16 16 16 16 var87 0.75446 0.77645 0.43135 0.34784 PGRP-S 0.0012 0.0007 0.1084 0.2039

15 15 15 15 var88 0.15603 0.25603 0.08840 0.18804

Gram positive bacteria 0.5787 0.3570 0.7541 0.Ξ022 15 15 15 15 var89 0.826S5 0.79502 0.88031 0.84804

Troponin C Cardiac 0.0001 0.0004 <.0001 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var45 var46 var47 var48 var79 -0.00012 0.26566 0.59261 0.97884 anti-Cystatin A 0.9996 0.3200 0.0156 <-0001

16 16 16 16 var80 0.02275 0.26363 0.66792 0.93991 anti-Cystatin S 0.9334 0.3239 0.0047 <.0001

16 16 16 16 var81 0.00114 0.20119 0.38017 0.07649 Prostein 0.9970 0.5098 0.2001 0.8039

13 13 13 13 var82 0.35636 0.14974 0.73157 0.87007 Aquaporin 4 0.2320 0.6254 0.0045 0.0001

13 13 13 13 var83 0.12338 0.19926 0.73000 0.73518 Trypsin 0.6880 0.5140 0.0046 0.0042

13 13 13 13 var84 0.14713 0.11299 0.55574 0.45914 Osteonectin 0.6315 0.7132 0.0486 0.1145

13 13 13 13 var85 0.00784 0.26233 0.58086 0.90005 RAGE 0.9797 0.3866 0.0374 <.0001

13 13 13 13 var86 0.16030 0.13209 0.46762 0.84744 PGRP-I Beeta 0.5531 0.6258 0.0678 <.0001

16 16 16 16 var87 0.13726 0.03988 0.51893 0.83109 PGRP-S 0.6257 0.8878 0.0475 0.0001

15 15 15 15 var88 -0.03433 -0.04472 0.14043 0.05417

Gram positive bacteria 0.9033 0.8743 0.6177 0.8479

15 15 15 15 var89 0.29108 0.11229 0.68753 0.38535

Troponin C Cardiac 0.2925 0.6903 0.0046 0.1561

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var49 var50 var51 var52 var79 0.89570 0.38623 0.31123 0.44672 anti-Cystatin A <.0001 0.1395 0.2406 0.0828

16 16 16 16 var80 0.96959 0.59303 0.49975 0.60360 anti-Cystatin S <.0001 0.0155 0.0487 0.0133

16 16 16 16 varδl 0.18516 0.36874 0.80630 0.78560 Prostein 0.5448 0.2150 0.0009 0.0015

13 13 13 13 var82 0.83489 0.45841 0.39339 0.60780 Aquaporin 4 0.0004 0.1152 0.1836 0.0276

13 13 13 13 var83 0.87109 0.92359 0.72892 0.81278 Trypsin 0.0001 <.0001 0.0047 0.0007

13 13 13 13 var84 0.67201 0.99926 0.71723 0.73689 Osteonectin 0.0119 <.0001 0.0058 0.0041

13 13 13 13 var85 0.96497 0.76211 0.56361 0.61991 RAGE <.0001 0.0025 0.0449 0.0238

13 13 13 13 var86 0.93391 0.42658 0.21207 0.34963 PGRP-I Beeta <.0001 0.0994 0.4304 0.1844

16 16 16 16 var87 0.82339 0.55534 0.33082 0.47719 PGRP-S 0.0002 0.0316 0.2284 0.0721

15 15 15 15 var88 0.04889 0.17754 0.45285 0.49315

Gram positive bacteria 0.8S26 0.5267 0.0901 0.0618

15 15 15 15 var89 0.51636 0.93840 0.82998 0.89537

Troponin C Cardiac 0.0488 <-0001 0.0001 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var53 var54 var55 var56 var79 0.25123 0.27107 0.75701 0.36530 anti-Cystatin A 0.3480 0.3099 0.0007 0.1641

16 16 16 16 var80 0.4100S 0.34418 0.76376 0.57287 anti-Cystatin S 0.1147 0.1918 0.0006 0.0204

16 16 16 16 varδl 0.79761 0.27684 0.19666 0.39541 Prostein 0.0011 0.3598 0.5196 0.1811

13 13 13 13 var82 0.45228 0.00322 0.76988 0.48432 Aquaporin 4 0.1207 0.9917 0.0021 0.0935

13 13 13 13 var83 0.61167 0.49093 0.90512 0.92253 Trypsin 0.0263 0.0885 <.0001 <.0001

13 13 13 13 var84 0.56042 0.58324 0.72051 0.99179 Osteonectin 0.0464 0.0364 0.0055 <.0001

13 13 13 13 var85 0.40991 0.55211 0.87658 0.73830 RAGE 0.1642 0.0504 <.0001 0.0040

13 13 13 13 var86 0.17138 0.15341 0.53294 0.41392 PGRP-I Beeta 0.5257 0.5706 0.0335 0.1110

16 16 16 16 var87 0.26804 0.22091 0.74261 0.56501 PGRP-S 0.3341 0.4288 0.0015 0.0282

15 15 15 15 var88 0.41280 0.54954 0.06021 0.16775 Gram positive bacteria 0.1262 0.0338 0.8312 0.5501

15 15 15 15 var89 0.77965 0.32346 0.70362 0.96775

Troponin C Cardiac 0.0006 0.2396 0.0034 <.0001

15 15 IS 15

Pearson Correlation Coefficients Prob > I r I under HO : Rho=0 Number of Observations var57 var58 var59 var60 var79 0.83187 0.83022 0.S350S 0.37741 anti-Cystatin A <.0001 <.0001 0.0082 0.1496

16 16 16 16 var80 0.88875 0.89423 0.7973S 0.56517 anti-Cystatin S <.0001 <.0001 0.0002 0.0225

16 16 16 16 varδl 0.32083 0.41410 0.54952 0.26307 Prostein 0.2852 0.1595 0.0517 0.3852

13 13 13 13 var82 0.92573 0.71118 0.74624 0.40728 Aquaporin 4 <.0001 0.0064 0.0034 0.1672

13 13 13 13 var83 0.81050 0.83827 0.94484 0.89769 Trypsin 0.0008 0.0003 <.0001 <.0001

13 13 13 13 var84 0.53060 0.62366 0.82593 0.99065 Osteonectin 0.0621 0.0227 0.0005 <.0001

13 13 13 13 var85 0.81822 0.91534 0.80785 0.77195

RAGE 0.0006 <.0001 0.0008 0.0020

13 13 13 13 var86 0.81703 0.74754 0.60014 0.42452 PGRP-I Beeta 0.0001 0.0009 0.0140 0.1012

16 16 IS 16 var87 0.65221 0.67305 0.47145 0.56156 PGRP-S 0.0084 0.0060 0.0761 0.0294

15 15 15 15 var88 0.00616 0.18205 0.12895 0.14615

Gram positive bacteria 0.9826 0.5161 0.6469 0.6032

15 15 15 15 var89 0.47210 0.51410 0.71475 0.87270

Troponin C Cardiac 0.0756 0.0499 0.0027 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var61 var62 var63 var64 var79 0.38815 0.64833 0.65661 0.27214 anti-Cystatin A 0.1374 0.0066 0.0057 0.3079

16 16 16 16 var80 0.60344 0.78111 0.80276 0.46783 anti-Cystatin S 0.0133 0.0004 0.0002 0.0676

16 16 16 16 var81 0.60123 0.49617 0.58786 0.68834 Prostein 0.0297 0.0846 0.0346 0.0093

13 13 13 13 var82 0.58827 0.78204 0.77616 0.54320 Aquaporin 4 0.0344 0.0016 0.0018 0.0551

13 13 13 13 var83 0.78438 0.82710 0.88286 0.73909 Trypsin 0.0015 0.0005 <.0001 0.0039

13 13 13 13 var84 0.75388 0.64553 0.74148 0.72522 Osteonectin 0.0029 0.0172 0.0037 0.0050

13 13 13 13 var85 0.54583 0.72327 0.75261 0.48394 RAGE 0.0537 0.0052 0.0030 0.0938

13 13 13 13 var8S 0.44975 0.62512 0.61964 0.29243 PGRP-I Beeta 0.0805 0.0096 0.0105 0.2717

IS 16 16 16 var87 0.34650 0.51250 0.67057 0.42358 PGRP-S 0.2058 0.0508 0.0062 0.1156

15 15 15 15 var88 0.09980 0.02517 0.22992 0.31938

Gram positive bacteria 0.7234 0.9290 0.4097 0.2459

15 15 15 15 var89 0.78971 0.63146 0.86846 0.92S09

Troponin C Cardiac 0.0005 0.0116 <.0001 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 var67 var68 var79 0.55984 0.60025 0.15778 0.28408 anti-Cystatin A 0.0241 0.0140 0.5595 0.2863

16 16 16 16 var80 0.72023 0.74791 0.33688 0.48120 anti-Cystatin S 0.0017 0.0009 0.2020 0.0591

16 16 16 16 varδl 0.45312 0.53304 0.64166 0.44750 Prostein 0.1200 0.0607 0.0181 0.1252

13 13 13 13 var82 0.84130 0.74952 0.37159 0.37430 Aquaporin 4 0.0003 0.0032 0.2112 0.2077

13 13 13 13 var83 0.79524 0.81911 0.61402 0.70749 Trypsin 0.0012 0.0006 0.0256 0.0068

13 13 13 13 var84 0.69809 0.67479 0.59378 0.67924 Osteonectin 0.0080 0.0114 0.0324 0.0107

13 13 13 13 var85 0.64623 0.66844 0.39210 0.50449 RAGE 0.0170 0.0125 0.1851 0.0787

13 13 13 13 var86 0.73620 0.57573 0.30616 0.26966 PGRP-I Beeta 0.0011 0.0196 0.2488 0.3125

16 16 16 16 var87 0.61551 0.57814 0.32378 0.32604 PGRP-S 0.0146 0.0240 0.2391 0.2356

15 15 15 15 var88 0.09591 0.09622 0.18520 0.12252

Gram positive bacteria 0.7312 0.7330 0.5087 0.6636

15 15 15 15 var89 0.77124 0.79402 0.55294 0.68480

Troponin C Cardiac 0.0008 0.0004 0.0325 0.0049

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var69 var70 var71 var72 var79 0.08902 0.84617 0.86254 0.S7O08 anti-Cystatin A 0.7430 <.0001 <.0001 0.0045

16 16 16 16 var80 0.04308 0.94222 0.94450 0.82634 anti-Cystatin S 0.8741 <.0001 <.0001 <.0001

16 16 16 16 varδl -0.17828 0.41560 0.34463 0.61774 Prostein 0.5601 0.1578 0.2489 0.0245

13 13 13 13 var82 0.45195 0.77554 0.88482 0.6S781 Aquaporin 4 0.1210 0.0018 <.0001 0.0126

13 13 13 13 var83 -0.02502 0.85275 0.85897 0.92509 Trypsin 0.9353 0.0002 0.0002 <.0001

13 13 13 13 var84 -0.02988 0.65090 0.63550 0.80877 Osteonectin 0.9228 0.0160 0.0196 0.0008

13 13 13 13 var85 0.01338 0.91975 0.90123 0.83565 RAGE 0.9654 <.0001 <.0001 0.0004

13 13 13 13 var86 0.34950 0.86006 0.90804 0.53956 PGRP-I Beeta 0.1845 <.0001 <.0001 0.0310

16 16 16 16 var87 0.22719 0.83933 0.86254 0.59748 PGRP-S 0.4155 <.0001 <.0001 0.0187

15 15 15 15 var88 0.00424 0.23505 0.11790 0.31152

Gram positive bacteria 0.9880 0.3991 0.6756 0.2584

15 15 15 15 var89 0.02419 0.59769 0.60951 0.83985

Troponin C Cardiac 0.9318 0.0186 0.0159 <.0001

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var74 var75 var76 var77 var79 0.95065 0.87365 0.88261 0.73498 anti-Cystatin A <.0001 <.0001 <.0001 0.0012

16 16 16 16 var80 0.98876 0.96072 0.96496 0.78772 anti-Cystatin S <.0001 <.0001 <.0001 0.0003

16 16 16 16 varδl 0.27095 0.26561 0.27819 0.42677 Prostein 0.3706 0.3804 0.3574 0.1458 13 13 13 13 var82 0.80487 0.73352 0.73188 0.78437 Aquaporin 4 0.0009 0.0043 0.0045 0.0015

13 13 13 13 var83 0.81050 0.94321 0.93182 0.73055 Trypsin 0.0008 <.0001 <.0001 0.0046

13 13 13 13 var84 0.55723 0.79128 0.77244 0.55244 Osteonectin 0.0479 0.0013 0.0020 0.0503

13 13 13 13 var85 0.94751 0.99619 0.99832 0.81040 RAGE <.0001 <.0001 <.0001 0.0008

13 13 13 13 var86 0.86542 0.79197 0.79127 0.78131 PGRP-I Beeta <.0001 0.0003 0.0003 0.0004

IS 16 16 16 var87 0.79718 0.80613 0.81229 0.64579 PGRP-S 0.0004 0.0003 0.0002 0.0093

15 15 15 15 var88 0.13236 0.14755 0.15681 0.32006

Gram positive bacteria 0.6382 0.5997 0.5768 0.2448

15 15 15 15 var89 0.45863 0.671S5 0.65948 0.45934

Troponin C Cardiac 0.0855 0.0061 0.0075 0.0850

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 var81 var79 0.31464 1.00000 0.94281 0.15784 anti-Cystatin A 0.2353 <.0001 0.6066

16 16 16 13 var80 0.47320 0.94281 1.00000 0.30607 anti-Cystatin S 0.0641 <.0001 0.3091

16 16 16 13 var81 0.86681 0.15784 0.30607 1.00000 Prostein 0.0001 0.6066 0.3091

13 13 13 13 var82 0.37276 0.83045 0.82337 0.18530 Aquaporin 4 0.2097 0.0004 0.0005 0.5445

13 13 13 13 var83 0.61204 0.70372 0.87067 0.39375 Trypsin 0.0262 0.0073 0.0001 0.1831

13 13 13 13 var84 0.56517 0.39409 0.63937 0.35047 Osteonectin 0.0441 0.1827 0.0186 0.2404

13 13 13 13 var85 0.46888 0.88071 0.96645 0.25094 RAGE 0.1060 <.0001 <.0001 0.4083

13 13 13 13 var86 0.19213 0.80751 0.85976 -0.01466 PGRP-I Beeta 0.4759 0.0002 <.0001 0.9621

16 16 16 13 var87 0.21806 0.81081 0.82333 0.02490 PGRP-S 0.4350 0.0002 0.0002 0.9356

15 15 15 13 vara8 0.58223 0.12S25 0.16569 0.79652

Gram positive bacteria 0.0228 0.6539 0.5551 0.0011

15 15 15 13 var89 0.70499 0.34280 0.55916 0.50989

Troponin C Cardiac 0.0033 0.2110 0.0302 0.0751

15 15 15 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var82 var83 var84 var85 var79 0.83045 0.70372 0.39409 0.88071 anti-Cystatin A 0.0004 0.0073 0.1827 <.0001

13 13 13 13 var80 0.82337 0.87067 0.63937 0.96645 anti-Cystatin S 0.0005 0.0001 0.0186 <.0001

13 13 13 13 var81 0.18530 0.39375 0.35047 0.25094 Prostein 0.5445 0.1831 0.2404 0.4083

13 13 13 13 var82 1.00000 0.70084 0.44332 0.72579 Aguaporin 4 0.0076 0.1292 0.0050

13 13 13 13 var83 0.70084 1.00000 0.91879 0.92161 Trypsin 0.0076 <.0001 <.0001

13 13 13 13 var84 0.44332 0.91879 1.00000 0.76145 Osteonectin 0.1292 <.0001 0.0025

13 13 13 13 var85 0.72579 0.92161 0.76145 1.00000 RAGE 0.0050 <.0001 0.0025

13 13 13 13 var86 0.85694 0.70150 0.51983 0.82418 PGRP-I Beeta 0.0002 0.0075 0.0686 0.0005

13 13 13 13 var87 0.82189 0.76185 0.56874 0.86854 PGRP-S 0.0006 0.0025 0.0425 0.0001

13 13 13 13 var88 0.05410 0.18930 0.15744 0.17584

Gram positive bacteria 0.8607 0.5357 0.6075 0.5656

13 13 13 13 var89 0.55202 0.89433 0.92821 0.67189

Troponin C Cardiac 0.0505 <.0001 <.0001 0.0119

13 13 13 13

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var86 var87 var88 var89 var79 0.80751 0.81081 0.12625 0.34280 anti-Cystatin A 0.0002 0.0002 0.6539 0.2110

16 15 15 15 var80 0.85976 0.82333 0.16569 0.55916 anti-Cystatin S <.0001 0.0002 0.5551 0.0302

16 15 15 15 varδl 0.01466 0.02490 0.79652 0.50989 Prostein 0.9621 0.9356 0.0011 0.0751

13 13 13 13 var82 0.85694 0.82189 0.05410 0.55202 Aquaporin 4 0.0002 0.0006 0.8607 0.0505

13 13 13 13 var83 0.₇0150 0.76185 0.18930 0.89433 Trypsin 0.0075 0.0025 0.5357 <.0O01

13 13 13 13 var84 0.51983 0.56874 0.15744 0.92821 Osteonectin 0.0686 0.0425 0.6075 <.0O01

13 13 13 13 var85 0.82418 0.86854 0.17584 0.67189 RAGE 0.0005 0.0001 0.5656 0.0119

13 13 13 13 var86 1.00000 0.85133 -0.09081 0.39731 PGRP-I Beeta <.0001 0.7476 0.1425

16 15 15 15 var87 0.85133 1.00000 -0.03480 0.55209 PGRP-S <.0001 0.9020 0.0328

15 15 15 15 var88 0.09081 -0.03480 1.00000 0.19550

Gram positive bacteria 0.7476 0.9020 0.4850

15 15 IS 15 var89 0.39731 0.55209 0.19550 1.00000

Troponin C Cardiac 0.1425 0.0328 0.4850

15 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var90 var91 var92 var93 var79 0.18730 0.48182 0.43874 0.26314 anti-Cystatin A 0.5039 0.0690 0.0891 0.3248

15 15 16 16 var80 0.36078 0.69165 0.63886 0.45250 anti-Cystatin S 0.1865 0.0043 0.0077 0.0784

15 15 16 16 varβl 0.61938 0.58318 0.51539 0.6S757 Prostein 0.0240 0.0364 0.0715 0.0127

13 13 13 13 var82 0.48371 0.68835 0.55887 0.54800 Aquaporin 4 0.0940 0.0093 0.0471 0.0525

13 13 13 13 var83 0.62546 0.85621 0.93306 0.70198 Trypsin 0.0222 0.0002 <.0001 0.0075

13 13 13 13 var84 0.59980 0.80843 0.96761 0.67539 Osteonectin 0.0302 0.0008 <.0001 0.0113

13 13 13 13 var85 0.38074 0.66193 0.77204 0.44669 RAGE 0.1993 0.0137 0.0020 0.1260

13 13 13 13 var86 0.19127 0.56243 0.49232 0.28596 PGRP-I Beeta 0.4947 0.0291 0.0527 0.2830

15 15 16 16 var87 0.31719 0.54130 0.61012 0.40117 PGRP-S 0.2493 0.0372 0.0157 0.1383

15 15 15 15 var88 0.13040 0.18053 0.32210 0.25384

Gram positive bacteria 0.6432 0.5197 0.2417 0.3613

15 15 15 15 var89 0.83106 0.90625 0.96099 0.89939

Troponin C Cardiac 0.0001 <.0001 <.0001 <.0001

15 15 IS 15

Capture varl var2 var3 var90 0.39089 0.56636 0.92862 0.92091 Protein C 0.1497 0.0277 <.0001 <.0001

15 15 15 15 var91 0.75S47 0.84200 0.96143 0.91769

Macrophage Scavenger Receptor Type I 0.0011 <.0001 <.0001 <.0001

15 15 15 15 var92 0.75787 0.79912 0.82839 0.82862 anti-anti-Thrombin 0.0007^" 0.0002 <.0001 <.0001

16 16 16 16 var93 0.49591 0.65320 0.97719 0.97947 Protein S 0.0508 0.0061 <-0001 <.0001

16 ^" 16 16 16

Pearson Correlation Coefficients Prob > I rI under HO : Rho=0 Number of Observations var4 var5 var6 var7 var90 0.93604 0.33069 0.41406 0.65986 Protein C <-0001 0.2286 0.1249 0.0074

15 15 15 15 var91 0.93836 0.44561 0.71031 0.44826

Macrophage Scavenger Receptor Type • I <.0001 0.0960 0.0030 0.0938

15 15 15 15 var92 0.82857 0.39380 0.57954 0.29249 anti-anti-Thrombin <.0001 0.1312 0.0186 0.2716

16 16 16 16 var93 0.98817 0.24174 0.50233 0.45812 Protein S <.0001 0.3671 0.0474 0.0743

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var8 var9 varlO varll var90 0.62900 0 .91107 0 .93905 -0. 01375 Protein C 0.0120 <.0001 <.0001 0.9612 15 15 15 15 var91 0.68505 0 .94536 0 .93775 0. 35659

Macrophage Scavenger Receptor Type I 0.0048 ■c.OOOl <.0001 0.1920 15 15 15 15 var92 0.53943 0 .89165 0 .83272 0. 40558 anti-anti-Thrombin 0.0310 <.0001 <.0001 0.1191 16 16 16 16 var93 0.54033 0.97842 0.989S3 0.04830 Protein S 0.0307 <.0001 <.0001 0.8590

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations varl2 varl3 varl4 varlδ var90 0.92726 0.72997 0.40661 0.49882 Protein C <.0001 0.0020 0.132S 0.0584

15 15 15 15 var91 0.93549 0.93149 0.21533 0.39060

Macrophage Scavenger Receptor Type I <.0001 <.0001 0.4409 0.1500

15 15 15 15 var92 0.85985 0.88703 0.04224 0.20077 anti-anti-Thrombin <-0001 <.0001 0.8766 0.4559

16 16 16 16 var93 0.99001 0.81880 0.17569 0.30888 Protein S <-0001 0.0001 0.5151 0.2444

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations varl6 varl7 varlβ varl9 var90 0.92471 0.90355 0.89337 0.96844 Protein C <.0001 <.0001 <-0001 <.0001

15 15 15 15 var91 0.86142 0.95866 0.93764 0.92907

Macrophage Scavenger Receptor Type I <.0001 <.0001 <.0001 <.0001

15 15 15 15 var92 0.78859 0.90290 0.86536 0.74990 anti-anti-Thrombin 0.0003 <.0001 <.0001 0.0008

16 16 16 16 var93 0.92812 0.95522 0.96613 0.98995 Protein <.0001 <.0001 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var20 var21 var22 var23 var90 0.83621 0.46146 0.34787 0.59281 Protein C 0.0001 0.0834 0.2039 0.0199

15 15 15 15 var91 0.81715 0.75722 0.35555 0.55086

Macrophage Scavenger Receptor Type I 0.0002 0.0011 0.1934 0.0333

15 15 15 15 var92 0.75626 0.57468 0.21047 0.38958 anti-anti-Thrombin 0.0007 0.0199 0.4340 0.1358

16 16 16 16 var93 0.92874 0.54815 0.35786 0.44471 Protein S <.0001 0.0279 0.1735 0.0844

16 16 16 16

Pearson Correlation Coefficients .Prob > |r| under HO: Rho=0 Number of Observations var24 var25 var26 var27 var90 0.81509 0.92104 0.91406 0.92859 Protein C 0.0002 <.0001 <.0001 <.0001 15 15 15 15 var91 0.81524 0.93846 0.95348 0.92813

Macrophage Scavenger Receptor Type I 0.0002 <.0001 <.0001 <.0001

15 15 15 15 var92 0.69475 0.82751 0.82293 0.83603 anti-anti-Thrombin 0.0028 <.0001 <.0001 <.0001

15 16 16 16 var93 0.88083 0.96984 0.94976 0.98437 Protein S <-0001 <.0001 <.0001 <.0001

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var28 var29 var30 var31 var90 0.10430 -0.05699 0.58160 0.49631 Protein C 0.7114 0.8401 0.0230 0.0599

15 15 15 15 var91 0.32557 0.20112 0.45893 0.43517

Macrophage Scavenger Receptor Type I 0.2364 0.4723 0.0853 0.1050

15 15 15 15 var92 0.18775 0.53809 0.30412 0.30531 anti-anti-Thrombin 0.4862 0.0315 0.2521 0.2502

16 16 16 16 var93 0.03568 -0.02353 0.38924 0.32536 Protein S 0.8956 0.9311 0.1362 0.2188

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var32 var33 var34 var35 var90 -0.03387 0.87849 0.86538 0.60007 Protein C 0.9046 <.0001 <.0001 0.0180

15 15 15 15 var91 0.03050 0.93609 0.94676 0.49530

Macrophage Scavenger Receptor Type I 0.9141 <.0001 <.0001 0.0605

15 15 15 15 var92 -0.18950 0.92807 0.72969 0.43441 anti-anti-Thrombin 0.4821 <.0001 0.0013 0.0927

16 16 16 16 var93 -0.12895 0.95257 0.94057 0.66225 Protein S 0.6341 <.0001 <.0001 0.0052

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var36 var37 var38 var39 var90 0.96074 0.85235 0.37928 0.91863 Protein C <.0001 <.0001 0.1632 <.0001

15 15 15 15 var91 0.92961 0.93565 0.42820 0.93554

Macrophage Scavenger Receptor Type I <.0001 <.0001 0.1113 <.0001

15 15 15 15 var92 0.76278 0.87988 0.33103 0.88277 anti-anti-Thrombin 0.0006 ■=.0001 0.2104 <.0001 16 16 16 16 var93 0.99433 0 .93529 0.42358 0.98343 Protein S <.0001 <.0001 0.1021 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var40 var41 var42 var43 var90 0.60794 0.68118 0.83233 0.89750 Protein C 0.0162 0.0052 0.0001 <.0001

15 15 15 15 var91 0.75267 0.89318 0.81371 0.84086

Macrophage Scavenger Receptor Type I 0.0012 <.0001 0.0002 <.0001

15 15 15 15 var92 0.83115 0.79922 0.77212 0.72378 anti-anti-Thrombin <.0001 0.0002 0.0005 0.0015

16 16 16 16 var93 0.68543 0.77315 0.89769 0.95311 Protein S 0.0034 0.0004 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > I r I under HO : RhO=O Number of Observations var45 var46 var47 var48 var90 0.30716 0.38427 0.62082 0.18671 Protein C 0.2654 0.1573 0.0135 0.5052

15 15 15 15 var91 0.31161 0.24404 0.75377 0.51452

Macrophage Scavenger Receptor Type I 0.2582 0.3807 0.0012 0.0497

15 15 15 15 var92 0.24657 0.13869 0.61455 0.47584 anti-anti-Thrombin 0.3573 0.6085 0.0113 0.0625

16 16 16 16 var93 0.36594 0.14660 0.72193 0.27292 Protein S 0.1633 0.5880 0.0016 0.3065

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var49 var50 var51 var52 var90 0.27383 0.63228 0.83371 0.84705 Protein C 0.3234 0.0114 0.0001 <.0001

15 15 15 15 var91 0.66294 0.79051 0.80112 0.89373

Macrophage Scavenger Receptor Type I 0.0071 0.0005 0.0003 <.0001

15 15 15 15 var92 0.60380 0.96543 0.81250 0.86154 anti-anti-Thrombin 0.0133 <.0001 0.0001 <.0001

16 16 16 16 var93 0.38026 0.70399 0.84266 0.93617 Protein S 0.1463 0.0023 <.0001 <.0001

16 16 16 16 Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var53 var54 var55 var56 var90 0.93877 -0.09663 0.46724 0.69417 Protein C <.0001 0.7319 0.0791 0.0041

15 15 15 15 var91 0.82827 0.12604 0.62452 0.81900

Macrophage Scavenger Receptor Type I 0.0001 0.6544 0.0128 0.0002

15 15 15 15 var92 0.70344 0.54381 0.71998 0.97314 anti-anti-Thrombin 0.0024 0.0294 0.0017 <.0001

IS 16 16 16 var93 0.92101 0.00237 0.53740 0.76502 Protein S <.0001 0.9931 0.0318 0.0006

IS 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var57 var58 var59 var60 var90 0.40616 0.40490 0.62380 0.50800 Protein C 0.1330 0.1344 0.0130 0.0532

15 15 15 15 var91 0.71517 0.65629 0.88281 0.68568

Macrophage Scavenger Receptor Type I 0.0027 0.0079 <.0001 0.0048

15 15 15 15 var92 0.47773 0.60988 0.67717 0.93325 anti-anti-Thrombin 0.0613 0.0121 0.0040 <.0001

16 16 16 16 var93 0.49011 0.42569 0.69832 0.57932 Protein S 0.0539 0.1002 0.0026 0.0187

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var61 var62 var63 var64 var90 0.80517 0.64852 0.81434 0.92181 Protein C 0.0003 0.0089 0.0002 <.0001

15 15 15 15 var91 0.94055 0.84910 0.95644 0.90994

Macrophage Scavenger Receptor Type I <.0001 <.0001 <.0001 <.0001

15 15 15 15 var92 0.68708 0.55244 0.82220 0.83509 anti-anti-Thrombin 0.0033 0.0265 <.0001 <.0001

16 16 16 16 var93 0.85432 0.69887 0.89091 0.99289 Protein S <.0001 0.0026 <.0001 <.0001

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var65 var66 var67 var68 var90 0.72665 0.80575 0.50696 0.53034 Protein C 0.0022 0.0003 0.0538 0.0420

15 15 15 15 var91 0.93190 0.93380 0.55416 0.69375

Macrophage Scavenger Receptor Type I <.0001 <.0001 0.0321 0.0041

IS 15 15 15 var92 0.74705 0.69840 0.53S38 0.60305 anti-anti-Thrombin 0.0009 0.0026 0.0322 0.0134

16 16 16 ^■ 16 var93 0.79661 0.86555 0.61175 0.64438 Protein S 0.0002 <.0001 0.0118 0.0071

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var69 var70 var71 var72 var90 -0.01252 0.41728 0.46588 0.70872 Protein C 0.9647 0.1217 0.0801 0.0031

15 15 15 15 var91 0.09838 0.71321 0.75622 0.89462

Macrophage Scavenger Receptor Type I 0.7272 0.0028 0.0011 <.0001

15 IS 15 15 var92 0.08803 0.67887 0.66157 0.83460 anti-anti-Thrombin 0.7458 0.0038 0.0053 <.0001

16 16 16 16 var93 0.03360 0.52584 0.55874 0.78943 Protein S 0.9017 0.0364 0.0245 0.0003

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var74 var75 var76 var77 var90 0.28355 0.38415 0.38121 0.33650 Protein C 0.3058 0.1575 0.1609 0.2201

15 15 15 15 var91 0.62473 0.70883 0.70037 0.60770

Macrophage Scavenger Receptor Type I 0.0128 0.0031 0.0036 0.0163

15 15 15 15 var92 0.54461 0.76073 0.75113 0.60732 anti-anti-Thrombin 0.0292 0.0006 0.0008 0.0126

16 16 16 16 var93 0.36999 0.47032 0.46559 0.38812 Protein 0.1584 0.0660 0.0691 0.1374

16 16 16 16

Pearson Correlation Coefficients Prob > |r| under HO: Rho=0 Number of Observations var78 var79 var80 var81 var90 0.80854 0.18730 0.36078 0.61938 Protein C 0.0003 0.5039 0.1865 0.0240

15 15 15 13 var91 0.76806 0.48182 0.69165 0.58318

Macrophage Scavenger Receptor Type I 0.0008 0.0690 0.0043 0.0364

15 15 15 13 var92 0.70411 0.43874 0.63886 0.51539 anti-anti-Thrombin 0.0023 0.0891 0.0077 0.0715

16 16 16 13 var93 0.79565 0.26314 0.45250 0.66757 Protein S 0.0002 0.3248 0.0784 0.0127 16 16 \6 13

Pearson Correlation Coefficients fit) Prob > |r| under HO: Rho=0 Number of Observations var82 var83 var84 var85 var90 0.48371 0.6254S 0.59980 0.38074 Protein C 0.0940 0.0222 0.0302 0.1993

13 13 13 13 var91 0.68835 0.85S21 0.80843 0.66193

Macrophage Scavenger Receptor Type I 0.0093 0.0002 0.0008 0.0137

13 13 13 13 var92 0.55887 0.93306 0.96761 0.77204 anti-anti-Throinbin 0.0471 <.0001 <.0001 0.0020

13 13 13 13 var93 0.54800 0.70198 0.67539 0.44669 Protein S 0.0525 0.0075 0.0113 0.1260

13 13 13 13

Pearson Correlation Coefficients Prob > I rI under HO : RhO=O Number of Observations var86 var87 var88 var89 var90 0.19127 0.31719 0.13040 0.83106 Protein C 0.4947 0.2493 0.6432 0.0001

15 15 15 15 var91 0.56243 0.54130 0.18053 0.90625

Macrophage Scavenger Receptor Type I 0.0291 0.0372 0.5197 <.0001

15 15 15 15 var92 0.49232 0.61012 0.32210 0.96099 anti-anti-Thrombin 0.0527 0.0157 0.2417 <.O0Ol

16 15 15 15 var93 0.28596 0.40117 0.25384 0.89939 Protein S 0.2830 0.1383 0.3613 <.0001

16 15 15 15

Pearson Correlation Coefficients Prob > |r| under HO: RhO=O Number of Observations var90 var91 var92 var93 var90 1.00000 0.86141 0.69682 0.95200 Protein C <.0001 0.0039 <.0001

15 15 15 15 var91 0.86141 1.00000 0.84966 0.91518

Macrophage Scavenger Receptor Type I <.0001 <.0001 <.O0Ol

15 15 15 15 var92 0.69682 0.84966 1.00000 0.78758 anti-anti-Thrombin 0.0039 <.0001 0.0003

15 15 16 16 var93 0.95200 0.91518 0.78758 1.00000 Protein S <.0001 <.0001 0.0003

15 15 16 16 Table 12. Marker Versus Capture Data

Statistical Analysis: Comparisons of Disease for a given Biomarker

Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatin A

Kalβ Kallikrein 6

AIpS Alpha synuclein

Onctin Osteonectin

Olcin Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquaporin-4

Capture Time DATA: Summary table of Cap by Disease

Capture Time DATA: Summary table of MHCI by Disease

Capture Time DATA: Summary table of MaSR by Disease

Macrophage scavenger receptor

I I I I |Medi-| I Mean I Min I Max I Ql I an Q3

I Disease

II - . _-

Aortic 110.00 I 26.64111.43 I 59.90114.92) 20.97 37.38

Arthriti 110.00 I 215.2 j 33.89 I 288.31183.9 | 249.5 | 269.6

Ostitis 110.001158.9112.40 I 320.9119.771143.91269.2 Endoaden 110.00 I 41.54 J 11.78 I 76.91139.52 I 44.67 I 48.22

KidSton 110.00 I 38.40 I 22.02 I 45.21136.36 I 40.20 I 43.42 J I I Parkinso 110.00 ) 20.94117.26 I 24.60 I 20.46 I 21.07 I 21.50

Prostate I 9.00112.90110.21116.39110.65111.96115.61 Prostati 110.00 I 25.42113.18 I 40.89 J 15.61123.95 I 34.32

Capture Time DATA: Summary table of CysA by Disease

Cystatin A

I I I I |Medi-| N ] Mean | Min | Max | Ql | an | Q3

Disease

-- -

Aortic 10.00 22.33 20.03 25.03 20.98 21.76 24.00

Arthriti 10.00 8.72 2.33 13.35 3.43 12.09 12.22

Ostitis 10.00 8.63 4.26 13.18 4.45 8.19|l2.92

Endoaden 10.00|21.58 2.97 29.38 23.14 24.86 26.82

KidSton 10.00 3.96 1.58 7.00 2.42 3.48 5.09

Parkinso |l0.00 3.44 2.97 3.90 3.25 3.34 3.62

Prostate 10.00 4.49 0.19 13.70 0.47 0.93 8.43

Prostati |l0.00 25.47|22.36 31.76 23.91 24.08|26.48

Capture Time DATA: Summary table of Kal6 by Disease

Kallikrein 6

I Medi¬

N Mean Min I Max I Ql an Q3

_ __ _ _ . Disease I I I Aortic 10.00 0.05 II o.oo I| 0.28 I| 0.00 0.00 0.00 -_ - Arthriti 10.00 1.27| o.oo| 2.42| 0.00 1.81 2.23

_ Ostitis 10.00 1.65 I 0.5S I 3.07| 0.75 1.16 2.79

_ __ --

Endoaden 10.00 1.79| 0.09 I 2.88 J 0.93 1.95 2.88

KidSton 10.00 0.2l| o.oo| 0.47| 0.09 0.19 0.28 __ _ j Parkinso 110.001 2.60| 2.42| 3.43| 2.42| 2.5l| 2.60 I Prostate I XO .00 I 0.25| 0.09 I 0.56| 0.19 | 0.19| 0.37 j

I I

I Prostati I XO .00 I 0.82| 0.09 I 1.58| 0.56 | 0.79 | 1.12J

Capture Time DATA: Summary table of Alps by Disease

Alpha synuclein

I I I I lMedi-1 N I Mean | Min | Max | Ql j an | Q3

Disease Aortic J 10.00 j 14.27 J 12. S6115.78 j 13.53 14.31115.09 j

Arthriti llO.OO 37.24 23.57 44.40 35.68 I 37.30 I 42.54 Ostitis 110.00 I 26.04 J 5.73 I 34.49 I 22.54 I 30.91133.21

Endoaden 110.00 J 36.71110.91146.66 I 37.55 I 42.63 I 43.60 KidSton 110.00115.75 I 9.85 I 21.67 I 13.01115.52118.64

Parkinso 110.00 I 24.57 I 23.74 I 28.19 I 23.91124.26 I 24.43 Prostate |10.00| 5.74| 0.00|10.2l| 2.42| 6.90 | 9.15 Prostati 110.00 I 35.10 I 22.71147.94 I 30.91 J 32.87 J 42.90

Capture Time DATA: Summary table of Onctin by Disease

Osteonectin

|Medi-

N Mean Min Max Ql an Q3

Disease __ Aortic 110.00 0.89 0.72 1.18 0.72 0.81 1.09

Arthriti 10.00 1.72 0.62 3.13 0.81 1.74 2.20

Ostitis 10.00 1.09 0.25 3.03| 0.44 0.58 1.46

Endoaden 10.00 1.11 0.34 2.39 0.81 1.04 1.46

KidSton 10.00 0.32 0.25 0.53 0.25 0.25 0.44

Parkinso 10.00 2.89 2.20 4.05| 2.48 2.53 3.77

Prostate 10.00 0.44 0.25 0.72 0.34 0.39 0.53

Prostati 10.00 0.97 0.53 1.65 0.81 0.95 1.09

Capture Time DATA: Summary table of Olcin by Disease

Osteocalcin

I I I I |Medi-| N I Mean | Min | Max | Ql | an | Q3

Disease

Aortic 10 .00 4 .35 3 .52 6 .04 3 .73 4- 10 I 4 .78

Arthriti 10 .oo|io .71 1 .38 16 .76 6 .14 12. 37 16 .29

Cstitis 10 .00 10 .12 3 .63 19 .84 4 .05 '^• 51118 .77 ] j 10.001 2.7l| 0.00| 3.84| 2.35| 3.2l| 3.63 _IEndoaden

I KidSton 110.00 I 0.14 I 0.00 I 0.4l| 0.00| 0.19| 0.19

I IP-a—rkinso 110.00 I 2.57| 1.59| 3.2θ| 1.811 2.82 | 2.98

I

I Prostate 110.001 0.00] 0.00| O.OO] 0.00| 0.00| O.OO

_. _ _-

Prostati 110.001 2. ll| 1.17| 3.42| 1.4δ| 1.87| 2.78

Capture Time DATA: Summary table of TroC by Disease

Capture Time DATA: Summary table of AbT by Disease 10

Abeam Transglutaminase 2

I 1 I I |Medi-| N ]Mean | Min | Max | Ql | an | Q3

Disease Aortic jlθ.00 3.81 j 0.65|l6.74| 1.2l| 1.4θj 1.68

Arthriti 110.001 2.56| 1.30| 4.17] 1.4θ| 3.021 3.16 Cstitis 110.00 I 0.50 I 0.09| 1.03| 0.09| 0.42] 0.84

Endoaden J 10.00 ] 0.34] O.OO] 1.12| 0.091 0.141 0.47 KidSton 110.00 I 0.05 I 0.0θ| 0.28 I 0.00| 0.00| 0.09 j

Parkinso 110.001 3.07| 2.70| 4.17] 2.79] 2.97] 3.16 Prostate 110.001 0.07] O.OO] 0.281 O.Oθ| 0.09| 0.09 Prostati 110.00 ] 0.5l| 0.00| 1.77| 0.09| 0.14| 0.75

Capture Time DATA: Summary table of PGRP by Disease 11

PGRP-I Beeta

I I I I |Medi-| N IMean | Min | Max | Ql | an | Q3

Disease Aortic 110.00 j 308.21127.6 I 640.01164.8 j 195.9 441.2

Capture Time DATA: Summary table of PSA by Disease 12

PSA

I I I I |Medi-|

I Mean I Min 1 Max | Ql I an Q3

Disease Aortic jl0.00|41.65 20.41 49.16 j 39.69 j 43.12 | 46.17

Arthriti 110.00 I 24.62 I 4.45 I 41.01112.00 I 25.67 I 38.81 Ostitis 110.00 I 24.02111.69 I 38.02112.08 I 21.46 I 36.69 I I

Endoaden 110.00 I 34.50 I 0.04 I 46.26 J 40.66 I 42.10 I 43.55 I KidSton 110.00 I 4.34| 3.27| 4.96 | 4.12 | 4.33| 4.75| __ι

I

Parkinso 110.00112.41112.00113.82112.10 I 12.14112.58 I Prostate 110.00 I 0.25 J 0.04| 0.47| 0.04 | 0.2S | 0.47 Prostati 10.00 I 40.42 I 35.13 I 45.14 I 38.46 J 40.77 I 43.34

Capture Time DATA: Summary table of Lab by Disease 13

Labvision Tgase 2

I I I I |Medi-| N I Mean | Min | Max | Ql | an | Q3

Disease

Aortic 110.00 I 1.04J 0.80 j 1.45) 0.80 1.02 j 1.23

Arthriti 110.001 0.441 0.04 I 0.801 0.261 0.471 0.58

Cstitis I XO .001 9.10| 0.22|25.64| 0.44| 5.74|14.53

Endoaden 110.00 I 3.28 I O.OOl 8.65| 0.871 2.70 I 4.92

I KidSton I 9.00| 2.651 0.00|l4.34| 0.221 0.44| 2.38

Parkinso ] 10.00 I 0.46| 0.3S I 0.69| 0.36 | 0.42J 0.58

Prostate 110.001 1.121 0.00| 3.66| O.Oθ| 0.33| 2.81 Prostati 110.001 0.461 O.OOl 1.30| 0.151 0.401 0.65

Capture Time DATA: Summary table of Aqua by Disease 14

I N I Mean | Min | Max | Ql | an | Q3 |

Disease I I I I I ^'"] ϊ^" Aortic I 110.00II 344.611119.8II 640.0I1129.6II 203.2II 636.7

|Arthriti 110.00 I 506.9 I 87.57 I 640.0 I 434.0 I 640.0 I 640.0 I Ostitis I 9.00]285.9| 7.83|640.0|91.18|l46.4|640.0

I Endoaden I 8.00|480.0| 0.00|640.0|320.0|640.0|640.0

II

I KidSton 110.00 J 54.24 I 33.69 I 65.62 I 44.02 I 57.34 I 62.22

Parkinso 110 .00 I 88.73 I 83 .44 I 96 .42 I 84 .111 88.01191.77 j Prostate I XO . 00 1 0 . 49 | 0 . 00 | 1 . 32 | O . Oθ | 0 . 47 | 0 . 81

Prostati 1 10 . 00 I 413 . 8 I 107 . 0 | 640 . 0 1 180 . 7 | 486 .4 | 640 . 0

Capture Time DATA: Summary table of Aqua by Disease Disease=Aortic

The CORR Procedure

14 Variables : Cap MHCI MaSR CysA KaI 6 AIpS Onctin Olcin TroC

AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 193.35880 57.46218 1934 126.40200 284.26200

MHCI 10 316.51770 178.59011 3165 129.75100 640.00000

MaSR 10 26.63810 15.80507 266.38100 11.43400 59.90200

CysA 10 22.33410 1.87045 223.34100 20.02900 25.02800

KaI 6 10 0.04670 0.10086 0.46700 0 0.28000

AIpS 10 14.27370 1.00644 142.73700 12.65700 15.78400

Onctin 10 0.89170 0.18831 8.91700 0.71500 1.18000

Olcin 10 4.34790 0.82234 43.47900 3.51500 6.03500

TroC 10 0.23310 0.22508 2.33100 0 0.55900

AbT 10 3.81430 5.54836 38.14300 0.65300 16.73700

PGRP 10 308.20130 194.39359 3082 127.58400 640.00000

PSA 10 41.64730 8.06573 416.47300 20.41200 49.15800

Lab 10 1.03670 0.22155 10.36700 0.79800 1.44800

Aqua 10 344.57210 250.47222 3446 119.83200 640.00000

Capture Time DATA: Summary table of Aqua by Disease Disease=Aortic

The CORR Procedure Pearson Correlation Coefficients 10

Prob > |r| under HO: RhO=O

Cap MHCI CysA KaI6

Cap 1.00000 0.77937 0.91001 0.88507 0.28388 Capture 0.0079 0.0003 0.0007 0.4267

MHCI 0.77937 1.00000 0.74390 0.60917 0.45890 MHC-I 0.0079 0.0136 0.0616 0.1822

MaSR 0.91001 0.74390 1.00000 0.91742 0.38707 Macrophage scavenger receptor 0.0003 0.0136 0.0002 0.2692

CysA 0.88507 0.60917 0.91742 1.00000 0.08807 Cystatin A 0.0007 0.0616 0.0002 0.8088

Kal6 0.28388 0.45890 0.38707 0.08807 1.00000 Kallikrein 6 0.4267 0.1822 0.2692 0.8088

AIpS 0.61478 0.40868 0.57675 0.63386 -0.00844 Alpha synuclein 0.0586 0.2410 0.0809 0.0491 0.9815

Onctin 0.63957 0.81997 0.69384 0.48709 0.78761 Osteonectin 0.0464 0.0037 0.0260 0.1S33 0.0068

Olcin 0.81900 0.68190 0.95162 0.80644 0.58545 Osteocalcin 0.0038 0.0299 ■=.0001 0.0048 0.0754

TroC 0.06893 0.29550 0.22927 -0.02898 0.57466 Troponin C 0.8499 0.4071 0.5240 0.9367 0.0823

AbT -0.02341 0.24309 0.05379 0.08844 -0.21895 Abeam Transglutaminase 2 0 94SS 0 4986 0 8827 0 8080 0 5434

PGRP 0 91946 0 79173 0 95391 0 92665 0 20306

PGRP 1 Beeta 0 0002 0 0063 < 0001 0 0001 0 5737

PSA 0 S3188 0 40037 0 56966 0 58485 0 23093

PSA 0 1136 0 2516 0 0856 0 0758 0 5209

Lab 0 77213 0 66404 0 89974 0 72932 0 50397

Labvision Tgase 2 0 0089 0 0363 0 0004 0 0167 0 1375

Aqua 0 92857 0 65337 0 90041 0 94063 0 10228

Aquaporin-4 0 0001 0 0405 0 0004 < 0001 0 7786

Capture Time DATA Summary table of Aqua by Disease 1

The CORR Procedure

Pearson Correlation Coefficients, N = 10

Prob > | r| under HO Rho=0

AIpS Onctm 01cm TroC AbT

Cap 0 61478 0 63957 0 81900 0 06893 -0 02341

Capture 0 0586 0 0464 0 0038 0 8499 0 9488

MHCI 0 40868 0 81997 0 68190 0 29550 0 24309

MHC-I 0 2410 0 0037 0 0299 0 4071 0 4986

MaSR 0 57675 0 69384 0 95162 0 22927 0 05379

Macrophage scavenger receptor 0 0809 0 0260 < 0001 0 5240 0 8827

CysA 0 63386 0 48709 0 80644 -0 02898 0 08844

Cystatin A 0 0491 0 1533 0 0048 0 9367 0 8080

Kal6 -0 00844 0 78761 0 58545 0 57466 -0 21895

Kallikrem 6 0 9815 0 0068 0 0754 0 0823 0 5434

AIpS 1 00000 0 25886 0 50408 -0 19435 -0 10261

Alpha synuclem 0 4702 0 1374 0 5906 0 7779

Onetin 0 25886 1 00000 0 80654 0 66999 0 15630

Osteonectin 0 4702 0 0048 0 0340 0 6663

01cm 0 50408 0 80654 1 00000 0 44482 0 00008

Osteocalcin 0 1374 0 0048 0 1977 0 9998

TroC -0 19435 0 66999 0 44482 1 00000 0 39567

Troponin C 0 5906 0 0340 0 1977 0 2577

AbT -0 10261 0 15630 0 00008 0 39567 1 00000

Abeam TransglutammaE _>e 2 0 7779 0 6663 0 9998 0 2577

PGRP 0 61786 0 65572 0 86128 0 21545 0 25927

PGRP-I Beeta 0 0570 0 0395 0 0014 0 5500 0 4695

PSA 0 55543 0 51852 0 63095 0 32187 0 19342

PSA 0 0955 0 1247 0 0505 0 3644 0 5924

Lab 0 40713 0 78408 0 94621 0 56328 0 09840

Labvision Tgase 2 0 2429 0 0073 < 0001 0 0900 0 7868

Aqua 0 61658 0 55396 0 80621 0 14018 0 21783

Aquaporin-4 0 0576 0 0966 0 0048 0 6993 0 5455

Capture Time DATA Summary table of Aqua by Disease 18

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO RhO=O

PGRP PSA Lab Aqua

Cap 0 91946 0 53188 0 77213 0 92857 Capture 0 0002 0 1136 0 0089 0 0001

MHCI 0 79173 0 40037 0 66404 0 65337 MHC-I 0 0063 0 2516 0 0363 0 0405

MaSR 0 95391 0 56966 0 89974 0 90041 Macrophage scavenger receptor < 0001 0 0856 0 0004 0 0004

CysA 0 92665 0 58485 0 72932 0 94063 Cystatm A 0 0001 0 0758 0 0167 < 0001

Kal6 0 20306 0 23093 0 50397 0 10228 Kallikrem 6 0.5737 0 5209 0.1375 0.7786

AIpS 0.61786 0.55543 0.40713 0.61S58

Alpha synuclem 0.0570 0 0955 0.2429 0 0576

Onctin 0.65572 0.51852 0.78408 0.55396 Osteonectin 0.0395 0 1247 0.0073 0.0966

Olcin 0.86128 0 63095 0 94621 0.80621 Osteocalcin 0.0014 0 0505 <.0001 0.0048

TroC 0.21545 0.32137 0 56328 0.14018 Troponin C 0.5500 0.3644 0.0900 0.6993

AbT 0.25927 0.19342 0.09840 0.21783

Abeam Transglutaminase 2 0.4695 0.5924 0.7868 0.5455

PGRP 0.56921 0.85486 0.95877

PGRP-I Beeta 0.0859 0.0016 <.0001

PSA 0.56921 0.47426 0.59432 PSA 0.0859 0.1661 0.0700

Lab 0.85486 0.47426 1.00000 0.79552

Labvision Tgase 2 0.0016 0.1661 0.0059

Aqua 0.95877 0.59432 0.79552 1.00000 Aquaporm-4 <.0001 0.0700 0 0059

Capture Time DATA: Summary table of Aqua by Disease 19

-- Disease=Arthriti

The CORR Procedure

14 Variables: Cap MHCI MaSR CysA Kal6 AIpS Onctin Olcin TroC AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 273.44670 105.74732 2734 99.29800 376.80300

MHCI 10 433.06410 268.22001 4331 61.32000 640.00000

MaSR 10 215.18610 78.01752 2152 33.89000 288.26300

CysA 10 8.71720 4.81053 87.17200 2.32500 13.35300

KaI6 10 1 26510 1.10598 12.65100 0 2.41800

AIpS 10 37.23840 6.17773 372.38400 23.56900 44.40200

Onctin 10 1.71790 0.88313 17.17900 0.62200 3.12700

01cm 10 10.71290 6.18346 107.12900 1.37600 16.76200

TroC 10 0.96820 0.84432 9.68200 0 1.86100

AbT 10 2.56350 1.10726 25.63500 1 30400 4.17000

PGRP 10 449.03710 249.41922 4490 59.38500 640.00000

PSA 10 24.61580 15.83829 246.15800 4 44900 41.00700

Lab 10 0.43950 0.26663 4.39500 0.03600 0.79800

Aqua 10 506.91800 200.50050 5069 87.57400 640.00000

Simple Statistics Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatm A

Kal6 Kallikrein 6

Alps Alpha synuclem

Onctm Osteonectin

01cm Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquaporm-4

Capture Time DATA: Summary table of Aqua by Disease 20 Disease=Arthriti

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO: RhO=O

Cap MHCI MaSR CysA KaI6

Cap 1.00000 0.98634 0.91859 0.98662 0.9S744 Capture <.0001 0.0002 <.0001 <.0001 MHCI 0.98634 1.00000 0.87162 0.99673 0.98057 MHC-I <-0001 0.0010 <.0001 <-0001

MaSR 0.91859 0.87162 1.00000 0.86645 0.82802

Macrophage scavenger receptor 0.0002 0.0010 0.0012 0.0031

CysA 0.98662 0.99673 0.86645 1.00000 0.99016 Cystatin A <.0001 <.0001 0.0012 <.0001

Kal6 0.96744 0.98057 0.82802 0.99016 1.00000 Kallikrein 6 <.0001 <.0001 0.0031 <.0001

AIpS 0.00025 -0.11970 0.32917 -0.13513 -0.18165

Alpha synuclein 0.9995 0.7419 0.3530 0.7097 0.6155

Onctin 0.81068 0.81629 0.67695 0.81476 0.84096 Osteonectin 0.0044 0.0040 0.0316 0.0041 0.0023

Olcin 0.89121 0.91872 0.87741 0.91072 0.87232 Osteocalcin 0.0005 0.0002 0.0008 0.0002 0.0010

TroC 0.97069 0.98302 0.81928 0.98987 0.99690 Troponin C <.0001 <-0001 0.0037 <.0001 <.0001

AbT 0.95182 0.94049 0.81726 0.96321 0.97608

Abeam Transglutaminase 2 <.0001 <.0001 0.0039 <.0001 <.0001

PGRP 0.99210 0.99654 0.90516 0.99146 0.97038

PGRP-I Beeta <.0001 <.0001 0.0003 <.0001 •=.0001

PSA 0.72508 0.77606 0.73763 0.76786 0.71640 PSA 0.0177 0.0083 0.0149 0.0095 0.0198

Lab 0.71789 0.77911 0.72889 0.76173 0.73877

Labvision Tgase 2 0.0194 0.0079 0.0168 0.0105 0.0147

Aqua 0.92572 0.89410 0.96586 0.88054 0.84360 Aquaporin-4 0.0001 0.0005 ■=.0001 0.0008 0.0022

Capture Time DATA: Summary table of Aqua by Disease Disease=Arthriti

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO: Rho=0

AIpS Onctin Olcin TroC AbT

Cap -0.00025 0.81068 0.89121 0.97069 0.95182 Capture 0.9995 0.0044 0.0005 <.0001 <.0001

MHCI -0.11970 0.81629 0.91872 0.98302 0.94049 MHC-I 0.7419 0.0040 0.0002 <.0001 <.0001

MaSR 0.32917 0.67695 0.87741 0.81928 0.81726

Macrophage scavenger receptor 0.3530 0.0316 0.0008 0.0037 0.0039

CysA -0.13513 0.81476 0.91072 0.98987 0.96321 Cyatatin A 0.7097 0.0041 0.0002 <.0001 <.0001

KaI6 -0.18165 0.84096 0.87232 0.99690 0.97608 Kallikrein 6 0.6155 0.0023 0.0010 <.0001 <.0001

Alps 1.00000 -0.09078 -0.04573 -0.17474 -0.13800

Alpha synuclein 0.8031 0.9002 0.6292 0.7038

Onctin -0.09078 1.00000 0.60931 0.84182 0.80392 Osteonectin 0.8031 0.0615 0.0023 0.0051

Olcin -0.04573 0.60931 1.00000 0.85904 0.81453 Osteocalcin 0.9002 0.0615 0.0015 0.0041

TroC -0.17474 0.84182 0.85904 1.00000 0.97251 Troponin C 0.6292 0.0023 0.0015 <.0001

AbT -0.13800 0.80392 0.81453 0.97251 1.00000

Abeam Transglutaminase 2 0.7038 0.0051 0.0041 <.0001

PGRP -0.04653 0.80340 0.92675 0.97286 0.93163

PGRP-I Beeta 0.8984 0.0051 0.0001 <.oooi <.0001

PSA -0.08985 0.40653 0.94475 0.69442 0.64698 PSA 0.8050 0.2437 <.0001 0.0259 0.0432

Lab -0.11203 0.52083 0.92626 0.71582 0.62879

Labvision Tgase 2 0.7580 0.1227 0.0001 0.0199 0.0515 Aqua 0 24S81 0 S6186 0 89157 0 84571 0 81053 Aquaporm 4 0 4936 0 0371 0 0005 0 0020 0 0045

Capture Time DATA Summary table of Aqua by Disease 22 Disease=Arthπti

The CORR Procedure

Pearson Correlation Coefficients N Prob > |r| under HO RhO=O

PGRP PSA Lab Aqua

Cap 0 99210 0 72508 0 71789 0 92572 Capture < 0001 0 0177 0 0194 0 0001

MHCI 0 99654 0 77606 0 77911 0 89410 MHC-I < 0001 0 0083 0 0079 0 0005

MaSR 0 90516 0 73763 0 72889 0 96586

Macrophage scavenger receptor 0 0003 0 0149 0 0168 < 0001

CysA 0 99146 0 76786 0 76173 0 88054 Cystatm A < 0001 0 0095 0 0105 0 0008

KaIS 0 97038 0 71640 0 73877 0 84360 Kallikrem 6 < 0001 0 0198 0 0147 0 0022

AIpS -0 04653 -0 08985 -0 11203 0 24581

Alpha synuclem 0 8984 0 8050 0 7580 0 4936

Onctin 0 80340 0 40653 0 52083 0 65186 Osteonectin 0 0051 0 2437 0 1227 0 0371

01cm 0 92675 0 94475 0 9262S 0 89157 Osteocalcin 0 0001 < 0001 0 0001 0 0005

TroC 0 97286 0 69442 0 71582 0 84571 Troponin C < 0001 0 0259 0 0199 0 0020

AbT 0 93163 0 64698 0 62879 0 81053

Abeam Transglutaminase 2 < 0001 0 0432 0 0515 0 0045

PGRP 1 00000 0 77887 0 78734 0 92678

PGRP-I Beeta 0 0079 0 0069 0 0001

PSA 0 77887 1 00000 0 90065 0 72263 PSA 0 0079 0 0004 0 0182

Lab 0 78734 0 90065 1 00000 0 78082

Labvision Tgase 2 0 0069 0 0004 0 0077

Aqua 0 92678 0 72263 0 78082 1 00000 Aquaporin-4 0 0001 0 0182 0 0077

Capture Time DATA Summary table of Aqua by Disease 23

- Disease=Cstitis -- The CORR Procedure

14 Variables Cap MHCI MaSR CysA KaIS AIpS Onctm 01cm AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 256 00540 123 82985 2560 106 70700 414 54800

MHCI 10 329 35080 271 41116 3294 42 20500 640 00000

MaSR 10 158 90600 116 541S8 1589 12 39500 320 93000

CysA 10 8 63020 4 04581 86 30200 4 26200 13 17900

KaI6 10 1 64630 0 99759 16 46300 0 55900 3 06500

AIpS 10 26 03880 10 98058 260 38800 5 72600 34 48500

Onctm 10 1 085S0 0 96504 10 85600 0 24900 3 03400

01cm 10 10 12300 6 95485 101 23000 3 63000 19 84400

TroC 10 0 71S90 0 85S40 7 16900 0 1 95400

AbT 10 0 50330 0 37848 5 03300 0 09300 1 02500

PGRP 10 190 69570 123 63813 1907 41 94700 408 02100

PSA 10 24 01950 12 28713 240 19500 11 68900 38 01900

Lab 10 9 09740 9 79116 90 97400 0 21800 25 63600

Aqua 9 285 87011 273 88971 2573 7 83300 S40 00000

Simple Statistics Varxable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatin A

KaI 6 Kallikrem 6

AlpS Alpha synuclem

Onctm Osteonectin

01cm Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquapoπn-4

Capture Time DATA: Summary table of Aqua by Disease 24 Disease=Cstitis

The CORR Procedure

Pearson Correlation Coefficients Prob > ]r| under HO: Rho=0 Number of Observations

Cap MHCI MaSR CysA KaI6

Cap 1.00000 0.95641 0.82670 0.91453 0 87827 Capture <.0001 0.0032 0.0002 0.0008 10 10 10 10 10

MHCI 0.95641 1.00000 0.90941 0.90916 0.93626 MHC-I ■=.0001 0.0003 0.0003 <.0001 10 10 10 10 10

MaSR 0.82670 0.90941 1.00000 0.67233 0.74594 Macrophage scavenger receptor 0.0032 0.0003 0.0332 0.0132 10 10 10 10 10

CysA 0.91453 0.90916 0.67233 1.00000 0.91639 Cystatm A 0.0002 0.0003 0.0332 0.0002 10 10 10 10 10

Kalβ 0.87827 0.93626 0.74594 0.91639 1.00000 Kallikrem 6 0.0008 <.0001 0.0132 0 0002 10 10 10 10 10

AIpS 0.52544 0.50601 0.70078 0.23659 0.22053 Alpha synuclem 0.1188 0.1356 0.0240 0 5105 0.5404 ' 10 10 10 10 10

Onctm 0.83571 0.83203 0.64072 0.77838 0.91815 Osteonectin 0.0026 0.0028 0.0459 0.0080 0.0002 10 10 10 10 10

01cm 0.87317 0.88057 0.63830 0.91800 0.92637 Osteocalcin 0.0010 0.0008 0.0470 0.0002 0.0001 10 10 10 10 10

TroC 0.80609 0.87799 0.71275 0.81031 0.96820 Troponin C 0.0049 0.0008 0.0207 0.0045 <.0001 10 10 10 10 10

AbT 0.88232 0.92304 0.80190 0.83333 0.91686 Abeam Transglutaminase 2 0.0007 0.0001 0.0053 0.0027 0.0002 10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 25 Disease=Cstitis

The CORR Procedure

AIpS Onctm 01cm TroC AbT

Cap 0.52544 0.83571 0.87317 0.80609 0.88232 Capture 0.1188 0.0026 0.0010 0.0049 0.0007

10 10 10 10 10 MHCI 0.50601 0.83203 0.88057 0.87799 0.92304 MHC-I 0.135S 0.0028 0.0008 0.0008 0.0001 10 10 10 10 10

MaSR 0.70078 0.64072 0.63830 0.71275 0.80190 Macrophage scavenger receptor 0.0240 0.0459 0.0470 0.0207 0.0053 10 10 10 10 10

CysA 0.23659 0.77838 0.91800 0.81031 0.83333 Cystatin A 0.5105 0.0080 0.0002 0.0045 0.0027 10 10 10 10 10

KaIS 0.22053 0.91815 0.92637 0.96820 0.91686 Kallikrein 6 0.5404 0.0002 0.0001 <.0001 0.0002 10 10 10 10 10

AIpS 1.00000 0.27066 0.31775 0.21856 0.41225 Alpha synuclein 0.4494 0.3709 0.5441 0.2365 10 10 10 10 10

Onctin 0.27066 1.00000 0.88355 0.93315 0.86389 Osteonectin 0.4494 0.0007 ■=.0001 0.0013 10 10 10 10 10

Olcin 0.31775 0.88355 1.00000 0.89458 0.85062 Osteocalcin 0.3709 0.0007 0.0005 0.0018 10 10 10 10 10

TroC 0.21856 0.93315 0.89458 1.00000 0.88674 Troponin C 0.5441 <.0001 0.0005 0.0006 10 10 10 10 10

AbT 0.41225 0.86389 0.85062 0.88674 1.00000 Abeam Transglutaminase 2 0.2365 0.0013 0.0018 0.0006

10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 26 -~—- Diseasp=(

The CORR Procedure

PGRP PSA Lab Aqua

Cap 0.80845 0.95426 0.31939 0.90753 Capture 0.0046 <.0001 0.3683 0.0007 10 10 10 9

MHCI 0.72160 0.94363 0.19241 0.98088 MHC-I 0.0185 <-0001 0.5944 <.0001 10 10 10 9

MaSR 0.62576 0.75191 0.26245 0.91647

Macrophage scavenger receptor 0.0530 0.0121 0.4638 0.0005 10 10 10 9

CysA 0.59826 0.98627 0.14071 0.82478 Cystatin A 0.0677 <.0001 0.6982 0.0062 10 10 10 9

KaI6 0.68144 0.90268 0.01507 0.92033 Kallikrein 6 0.0300 0.0003 0.9670 0.0004 10 10 10 9

AIpS 0.60121 0.37831 0.41294 0.52221

Alpha synuclein 0.0660 0.2811 0.2356 0.1492 10 10 10 9

Onctin 0.86313 0.77187 0.03567 0.87980 Osteonectin 0.0013 0.0089 0.9221 0.0018 10 10 10 9

Olcin 0.76370 0.91520 0.12575 0.90739 Osteocalcin 0.0101 0.0002 0.7292 0.0007 10 10 10 9

TroC 0.71226 0.80076 0.03652 0.92019 Troponin C 0.0208 0.0054 0.9202 0.0004 10 10 10 9

AbT 0.72102 0.85941 -0.01474 0.95450 Abeam Transglutaminase 2 0.0186 0.0014 0.9578 < .0001 10 10 10 9

Capture Time DATA: Summary table of Aqua by Disease 27 Disease=Cstitis

The CORR Procedure

Cap MHCI CysA KaIS

PGRP 0.80845 0.72160 0.62576 0.59826 0.68144

PGRP-I Beeta 0.0046 0.0185 0.0530 0.0677 0.0300 10 10 10 10 10

PSA 0.95426 0.94363 0.75191 0.98627 0.90268 PSA <.0001 <.0001 0.0121 <.0001 0.0003 10 10 10 10 10

Lab 0.31939 0.19241 0.26245 0.14071 0.01507

Labvision Tgase 2 0.3683 0.5944 0.4638 0.6982 0.9670 10 10 10 10 10

Aqua 0.90753 0.98088 0.91647 0.82478 0.92033 Aquaporin-4 0.0007 <.0001 0.0005 0.0062 0.0004 9 9 9 9 9

AIpS Onctin Olcin TroC AbT

PGRP 0.60121 0.86313 0.76370 0.71226 0.72102

PGRP-I Beeta 0.0660 0.0013 0.0101 0.0208 0.0186 10 10 10 10 10

PSA 0.37831 0.77187 0.91520 0.80076 0.85941 PSA 0.2811 0.0089 0.0002 0.0054 0.0014 10 10 10 10 10

Lab 0.41294 0.03567 0.12575 0.03652 -0.01474

Labvision Tgase 2 0.2356 0.9221 0.7292 0.9202 0.9678 10 10 10 10 10

Aqua 0.52221 0.87980 0.90739 0.92019 0.95450 Aquaporin-4 0.1492 0.0018 0.0007 0.0004 <.0001 9 9 9 9 9

Capture Time DATA: Summary table of Aqua by Disease Disease=Cstitis

The CORR Procedure

PGRP PSA Lab Aqua

PGRP 1.00000 0.65447 0.34242 0.80585

PGRP-I Beeta 0.0400 0.3328 0.0087 10 10 10 9

PSA 0.65447 1.00000 0.20387 0.87132 PSA 0.0400 0.5721 0.0022 10 10 10 9

Lab 0.34242 0.20387 1.00000 0.10452

Labvision Tgase 2 0.3328 0.5721 0.7890 10 10 10 9

Aqua 0.80585 0.87132 0.10452 1.00000 Aquaporin-4 0.0087 0.0022 0.7890 9 9 9 9

Capture Time DATA: Summary table of Aqua by Disease 29 - Disease=Endoaden - The CORR Procedure

14 Variables: Cap MHCI MaSR CysA KaIS AIpS Onctin Olcin TroC AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 360.44070 188.93038 3604 14.93600 511.90200

MHCI 10 512.03070 269.78297 5120 0.10700 640.00000

MaSR 10 41.54070 18.59603 415.40700 11.78400 76.91000

CysA 10 21.58380 9.26001 215.83800 2.97300 29.38200

KaI6 10 1.79480 1.00869 17.94800 0.09300 2.88000

AIpS 10 36.71480 12.97864 367.14800 10.90800 46.65600

Onctin 10 1.11450 0.58642 11.14500 0.34200 2.38700

Olcin 10 2.71050 1.44573 27.10500 0 3.84200

TroC 10 0.95020 0.53733 9.50200 0 1.49000

AbT 10 0.33550 0.37329 3.35500 0 1.11800

PGRP 10 512.19500 269.43699 5122 0 640.00000

PSA 10 34.50430 18.23594 345.04300 0.03600 46.26100

Lab 10 3.28460 3.00742 32.84600 0 8.64500

Aqua S 480.00000 296.26243 3840 0 640.00000

Simple Statistics

Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatin A

KaI6 Kallikrein 6

AIpS Alpha synuclein

Onctin Osteonectin

Olcin Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquaporin-4

Capture Time DATA: Summary table of Aqua by Disease 30

- Disease=Endoaden

The CORR Procedure

Cap MHCI MaSR CysA KaI6

Cap 1.00000 0.96376 0.84037 0.93959 0.75633 Capture <.0001 0.0023 <.0001 0.0114 10 10 10 10 10

MHCI 0.96376 1.00000 0.82606 0.97574 0.74291 MHC-I <.0001 0.0032 ■=.0001 0.0138 10 10 10 10 10

MaSR 0.84037 0.82606 1.00000 0.85034 0.46638 Macrophage scavenger receptor 0.0023 0.0032 0.0018 0.1742 10 10 10 10 10

CysA 0.93959 0.97574 0.85034 1.00000 0.61080 Cystatin A <.0001 <.0001 0.0018 0.0607 10 10 10 10 10

KaI6 0.75633 0.74291 0.46638 0.61080 1.00000 Kallikrein 6 0.0114 0.0138 0.1742 0.0607 10 10 10 10 10

AIpS 0.96541 0.97717 0.85665 0.98239 0.68743 Alpha synuclein ■=.0001 <-0001 0.0015 <.0001 0.0280 10 10 10 10 10

Onctin 0.68432 0.65249 0.62803 0.60834 0.73335 Osteonectin 0.0291 0.0409 0.0519 0.0620 0.0158 10 10 10 10 10 Olcin 0.94440 0.95331 0.82627 0.88595 0.84359

Osteocalcin <.O001 <.0001 0.0032 0.0006 0.0022

10 10 10 10 10

TroC 0.87441 0.88642 0.55715 0.79901 0.93146

Troponin C 0.0009 0.0006 0.0943 0.0056 <.0001

10 10 10 10 10

AbT 0.29201 0.40805 0.26835 0.37351 0.44274

Abeam Transglutaminase 2 0.4130 0.2418 0.4535 0.2877 0.2001

10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 31 Disease=Endoaden ->

The CORR Procedure

AIpS Onctin Olcin AbT

Cap 0.96541 0.68432 0.94440 0.87441 0.29201 Capture <.0001 0.0291 <.0001 0.0009 0.4130 10 10 10 10 10

MHCI 0.97717 0.65249 0.95331 0.88642 0.40805 MHC-I <.0001 0.0409 <.0001 0.0006 0.2418 10 10 10 10 10

MaSR 0.85665 0.62803 0.82627 0.55715 0.26835 Macrophage scavenger receptor 0.0015 0.0519 0.0032 0.0943 0.4535 10 10 10 10 10

CysA 0.98239 0.60834 0.88595 0.79901 0.37351 Cystatin A <.0001 0.0620 0.0006 0.0056 0.2877 10 10 10 10 10

KaI6 0.68743 0.73335 0.84359 0.93146 0.44274 Kallikrein 6 0.0280 0.0158 0.0022 <.0001 0.2001 10 10 10 10 10

AIpS 1.00000 0.67143 0.92545 0.83936 0.42979 Alpha synuclein 0.0335 0.0001 0.0024 0.2151 10 10 10 10 10

Onctin 0.67143 1.00000 0.67134 0.71616 0.59940 Osteonectin 0.0335 0.0335 0.0198 0.0670 10 10 10 10 10

Olcin 0.92545 0.67134 1.00000 0.88669 0.39437 Osteocalcin 0.0001 0.0335 0.0006 0.2594 10 10 10 10 10

TroC 0.83936 0.71616 0.88S69 1.00000 0.42242 Troponin C 0.0024 0.0198 0.0006 0.2239 10 10 10 10 10

AbT 0.42979 0.59940 0.39437 0.42242 1.00000 Abeam Transglutaminase 2 0.2151 0.0670 0.2594 0.2239 10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 32 Disease=Endoaden

The CORR Procedure

PGRP PSA Lab Aqua

Cap 0. 96376 0 .97122 -0.14327 0 .96445 Capture < .0001 ■=.0001 0.6929 0.0001

10 10 10 8

MHCI 1. 00000 0 .99619 -0.06446 1 .00000 MHC-I < .0001 •=.0001 0.8596 <.0001

10 10 10 8

MaSR 0. 82603 0 .83295 0.18383 0 .97386 Macrophage scavenger receptor 0 0032 0.0028 0 6112 < 0001 10 10 10 8

Cy sA 0.97S8S 0.98012 -0.05370 0 98303 Cystatm A <.0001 <.0001 0.8829 _< 0001 10 10 10 8

Kal6 0.74312 0.72410 -0.08313 0.79327 Kallikrem 6 0.0138 0 0179 0.8194 0.0188 10 10 10 8

AIpS 0.97727 0.98881 0.01686 0.98434 Alpha synuclem .= .0001 <.0001 0.9631 _<.0001 10 10 10 8

Onctxn 0.65255 0.65235 0.00868 0.63375 Osteonectin 0.0408 0.0409 0.9810 0.0916 10 10 10 8

01cm 0.9533S 0.94703 0.04880 0.95813 Osteocalcin <.0001 .= .0001 0.8935 0.0002 10 10 10 8

TroC 0.88S48 0.87231 -0.19613 0.94818 Troponin C 0.0006 0.0010 0.5871 0.0003 10 10 10 8

AbT 0.40814 0.41668 0.47827 0.39427 Abeam Transglutaminase 2 0.2416 0.2310 0.1620 0.3338 10 10 10 8

Capture Time DATA: Summary table of Aqua by Disease 33

Tin α£»a eρ»=TϋnHr>ΛrIρ

The CORR Procedure

Cap MHCI MaSR CysA Kal6

PGRP 0.96376 1.00000 0 82603 0.97586 0.74312

PGRP-I Beeta ■=.0001 <.0001 0.0032 <.0001 0.0138

10 10 10 10 10

PSA 0.97122 0.99619 0.83295 0.98012 0.72410 PSA ■=.0001 <.0001 0.0028 <.0001 0.0179 10 10 10 10 10

Lab -0.14327 -0.06446 0.18383 -0.05370 -0.08313

Labvision Tgase 2 0.6929 0.8596 0.6112 0.8829 0.8194 10 10 10 10 10

Aqua 0.96445 1.00000 0.97386 0.98303 0.79327 Aquaporm-4 0.0001 <.0001 <.0001 ■=.0001 0.0188 8 8 8 8 8

AIpS Onctm 01cm TroC AbT

PGRP 0.97727 0.65255 0.95336 0.88648 0.40814

PGRP-I Beeta ■=.0001 0.0408 <.0001 0.0006 0.2416 10 10 10 10 10

PSA 0.98881 0.65235 0.94703 0.87231 0.41668 PSA <.0001 0.0409 ■=.0001 0.0010 0.2310 10 10 10 10 10

Lab 0.01686 0.00868 0.04880 -0.19613 0.47827

Labvision Tgase 2 0.9631 0.9810 0.8935 0.5871 0.1620 10 10 10 10 10

Aqua 0.98434 0.6337S 0.95813 0.94818 0.39427 Aquaporin-4 <.0001 0.0916 0.0002 0.0003 0.3338 8 8 8 8 8

Capture Time DATA: Summary table of Aqua by Disease 34

Disease=Endoaden The CORR Procedure

Pearson Correlation Coefficients Prob > |r| under HO Rho=0 Number of Observations

PGRP PSA Lab Aqua

PGRP 1 00000 0 99618 -0 06419 1 00000

PGRP-I Beeta < 0001 0 8602 < 0001

10 10 10

PSA 0 99618 1 00000 -0 05250 0 99672 PSA < 0001 0 8855 < 0001

10 10 10

Lab -0 06419 -0 05250 1 00000 -0 16265

Labvision Tgase 2 0 8602 0 8855 0 7004

10 10 10 8

Aqua 1 00000 0 99672 -0 16265 1 00000 Aquaporin-4 < 0001 < 0001 0 7004

8

Capture Time DATA Summary table of Aqua by Disease 35

- Disease=KidSton -- The CORR Procedure 4 Variables Cap MHCI MaSR CysA KaIS AIpS Onctin 01cm AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 95 16090 17 20700 951 60900 64 14100 118 40900

MHCI 10 41 84380 8 74930 418 43800 24 44000 51 97800

MaSR 10 38 40090 6 94747 384 00900 22 01900 45 20800

CysA 10 3 96070 1 84093 39 60700 1 58300 6 99600

KaI6 10 0 20520 0 15723 2 05200 0 0 46600

AIpS 10 15 75160 3 69162 157 51600 9 85300 21 67400

Onctm 10 0 32340 0 10558 3 23400 0 24900 0 52800

01cm 10 0 13640 0 13484 1 36400 0 0 40900

TroC 10 0 06530 0 13940 0 65300 0 0 37300

AbT 10 0 04660 0 09067 0 4S600 0 0 28000

PGRP 10 55 48600 11 25769 554 86000 31 53500 68 32000

PSA 10 4 33550 0 51775 43 35500 3 26800 4 95600

Lab 9 2 64822 4 61973 23 83400 0 14 34200

Aqua 10 54 23880 10 56889 542 38800 33 69100 65 62000

Simple Statistics

Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatm A

Kal6 Kallikrem 6

AIpS Alpha synuclem

Onctm Osteonectin

Olcin Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquaporin-4

Capture Time DATA Summary table of Aqua by Disease 36 Disease=KidSton

The CORR Procedure

Pearson Correlation Coefficients Prob > |r| under HO RhO=O Number o£ Observations

Cap MHCI MaSR CysA KaI6 Cap 1.00000 0.S9283 0.61847 0 42444 -0 21123 Capture 0.0263 0.056S 0 2215 0 5580 10 10 10 10 10

MHCI 0.69283 1.00000 0.75367 0.09322 0.22823 MHC-I 0.0263 0 0118 0.7979 0.5260 10 10 10 10 10

MaSR 0.61847 0.75367 1 00000 0 34193 -0.02822 Macrophage scavenger receptor 0.0566 0 0118 0.3335 0.9383 10 10 10 10 10

CysA 0.42444 0.09322 0.34193 1.00000 0.19813 Cystatin A 0.2215 0 7979 0.3335 0.5832 10 10 10 10 10

KaI6 -0.21123 0 22823 -0.02822 0.19813 1.00000 Kallikrem S 0.5580 0.5260 0.9383 0.5832 10 10 10 10 10

AIpS 0.77161 0.36158 0.60763 0.76271 -0.15288 Alpha synuclein 0.0089 0.3046 0.0624 0.0103 0.6733 10 10 10 10 10

Onetin -0.54737 -0.43340 -0.71135 -0.26351 0.31459 Osteonectin 0.1015 0.2108 0.0211 0.4620 0.3760 10 10 10 10 10

01cm -0.23124 0.22114 0.01920 0.23146 0.74621 Osteocalcin 0.5203 0.5392 0.9S80 0.5200 0.0132 10 10 10 10 10

TroC -0.01212 -0.25605 -0.01617 -0.11260 -0.32568 Troponin C 0.9735 0.4752 0.9646 0.7568 0.3584 10 10 10 10 10

AbT -0.40960 -0 55546 -0.79005 0.03998 0.06800 Abeam Transglutaminase 2 0.2398 0.0955 0.0065 0.9127 0.8519 10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 37

The CORR Procedure

AIpS Onctm 01cm TroC AbT

Cap 0.77161 -0.54737 -0.23124 0.01212 -0.40960 Capture 0.0089 0.1015 0.5203 0.9735 0.2398

10 10 10 10 10

MHCI 0.36158 -0.43340 0.22114 0.25605 -0.55546 MHC-I 0.3046 0.2108 0.5392 0.4752 0.0955

10 10 10 10 10

MaSR 0.60763 -0.71135 0.01920 0.01617 -0.79005

Macrophage scavenger receptor 0.0624 0.0211 0.9580 0.9646 0.0065

10 10 10 10 10

CysA 0.76271 -0.26351 0.23146 0.11260 0.03998 Cystatin A 0.0103 0.4620 0.5200 0.7568 0.9127

10 10 10 10 10

KaI6 -0.15288 0.31459 0.74621 0.32568 0.06800 Kallikrein 6 0.6733 0.3760 0.0132 0.3584 0.8519

10 10 10 10 10

Alps 1.00000 -0.67662 -0.03392 0.13684 -0.45005

Alpha synuclein 0.0317 0.9259 0.7062 0.1919

10 10 10 10 10

Onctm -0.67662 1.00000 0.03978 0.15699 0.70510 Osteonectin 0.0317 0.9131 0.6649 0.0228

10 10 10 10 10

01cm -0.03392 0.03978 1.00000 0.52651 0.06981 Osteocalcin 0.9259 0.9131 0.1179 0.8480

10 10 10 10 10

TroC 0.13684 0.15699 -0.52651 1.00000 -0.26752 Troponin C 0.7062 0.6649 0.1179 0.4549 10 10 10 10 10

AbT -0.4S005 0.70510 0.06981 -0.267S2 1.00000 Abeam Tr;msglutaminase 2 0.1919 0.0228 0.8480 0.4549 10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 38 fnrtRhnπ -.

The CORR procedure

PGRP PSA Lab Aqua

Cap 0.75S49 0.65187 0.55551 0.86384 Capture 0.0113 0.0411 0.1205 0.0013 10 10 9 10

MHCI 0.93S17 0.84620 -0.10550 0.91965 MHC-I <.0001 0.0020 0.7871 0.0002 10 10 9 10

MaSR 0.77649 0.57646 0.10460 0.76161 Macrophage scavenger receptor 0.0083 0.0811 0.7888 0.0105 10 10 9 10

CysA 0.18204 -0.20022 0.46254 0.33460 Cystatin A 0.6147 0.S791 0.2100 0.3446 10 10 9 10

KaIS 0.16819 0.03654 -0.50114 0.08297 Kallikrein 6 0.6423 0.9202 0.1693 0.8197 10 10 9 10

AIpS 0.52134 0.24395 0.79340 0.62853 Alpha synuclein 0.1223 0.4970 0.0107 0.0516

10 10 9 10

Onctin -0.50342 -0.41605 -0.39573 -0.57265 Osteonectin 0.1380 0.2317 0.2918 0.0836 10 10 9 10

Olcin 0.21775 -0.00988 -0.27813 0.17747 Osteocalcin 0.5456 0.9784 0.4687 0.6238 10 10 9 10

TroC -0.13991 -0.13071 0.42422 -0.26905 Troponin C 0.6999 0.7189 0.2551 0.4522 10 10 9 10

AbT -0.66677 -0.64255 -0.24182 -0.53312 Abeam Transglutaminase 2 0.0352 0.0451 0.5307 0.1126 10 10 9 10

Capture Time DATA: Summary table ooff AAqαuuaa bbyv Disease Disease=KidSton

The CORR Procedure

Cap MHCI MaSR CysA KaI6

PGRP 0.75649 0.93617 0.77649 0.18204 0.16819

PGRP-I Beeta 0.0113 •=.0001 0.0083 0.6147 0.6423 10 10 10 10 10

PSA 0.65187 0.84620 0.57646 -0.20022 0.03654 PSA 0.0411 0.0020 0.0811 0.5791 0.9202 10 10 10 10 10

Lab 0.55551 -0.10550 0.10460 0.46254 -0.50114

Labvision Tgase 2 0.1205 0.7871 0.7888 0.2100 0.1693 9 9 9 9 9

Aqua 0.86384 0.91965 0.76161 0.33460 0.08297 Aquaporin-4 0.0013 0.0002 0.0105 0.3446 0.8197 10 10 10 10 10 Pearson Correlation Coefficients Prob > |r] under HO. Rho=0 Number of Observations

AIpS Onctm Olcin TroC AST

PGRP 0.52134 -0.50342 0.21775 -0.13991 -0.66677

PGRP-I Beeta 0.1223 0.1380 0.5456 0.6999 0.0352 10 10 10 10 10

PSA 0.24395 -0.41605 -0.00988 -0.13071 -0.64255 PSA 0.4970 0 2317 0.9784 0.7189 0.0451 10 10 10 10 10

Lab 0.79340 -0 39573 -0.27813 0.42422 -0.24182

Labvision Tgase 2 0.0107 0.2918 0.4687 0.2551 0.5307 9 9 9 9 9

Aqua 0.62853 -0 57265 0.17747 -0.26905 -0.53312 Aquapoπn-4 0.0516 0.0836 0.6238 0.4522 0.1126 10 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease Disease=KidSton

The CORR Procedure

PGRP PSA Lab Aqua

PGRP 1 00000 0.88435 0.17987 0.95761

PGRP-I Beeta 0.0007 0.6433 •c.OOOl 10 10 9 10

PSA 0 88435 1.00000 0.09052 0.81472 PSA 0.0007 0.8168 0.0041 10 10 9 10

Lab 0.17987 0.09052 1.00000 0.23673

Labvision Tgase 2 0.6433 0.8168 0.5397 9 9 9 9

Aqua 0.95761 0.81472 0.23673 1.00000 Aquaponn-4 •=.0001 0.0041 0.5397 10 10 9 10

Capture Time DATA: Summary table of Aqua by Disease 41

- Disease=Parkmso - The CORR Procedure

14 Variables : Cap MHCI MaSR CysA KaI6 AIpS Onctm 01cm TroC

AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 140.76800 4.79112 1408 132.68700 149.97200

MHCI 10 75.27820 2.40413 752.78200 72.06000 78.48000

MaSR 10 20.93600 1.93571 209.36000 17.25600 24.59900

CysA 10 3.44330 0.28307 34.43300 2.97300 3.89500

KaI6 10 2.60260 0.30483 26.02600 2.41800 3.43400

AIpS 10 24.57190 1.30393 245.71900 23.74100 28.18900

Onctm 10 2.88520 0.72984 28.85200 2.20100 4.04800

01cm 10 2.56660 0.61919 25.66600 1.59100 3.19700

TroC 10 2.54700 0.30273 25.47000 2.23200 3.15700

AbT 10 3.07390 0.42222 30.73900 2.69500 4.17000

PGRP 10 83.54920 6.30202 835.49200 71.95300 92.86900

PSA 10 12.41210 0.57932 124.12100 11.99800 13.82000

Lab 10 0.46160 0.11950 4.61600 0.36400 0.69000

Aqua 10 88.73120 4.65456 887.31200 83.43500 96.41800

Simple Statistics

Variable Label Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatm A

Kal6 Kallikrem 6

AIpS Alpha synuclem

Onctm Osteonectin

01cm Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquapoπn-4

Capture Time DATA: Summary table of Aqua by Disease 42

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > I r1 under HO : Rho=

Cap MHCI MaSR CysA KaI 6

Cap 1.00000 0.40729 0.32739 0.13402 0.11594

Capture 0.2427 0.3558 0.7120 0.7498

MHCI 0.40729 1.00000 0.59675 0.36542 0.41736

MHC-I 0.2427 0.0686 0.2991 0.2301

MaSR 0.32739 0.59675 1.00000 0.49821 0.70498

Macrophage scavenger receptor 0.3558 0.0686 0.1428 0.0228

CysA 0.13402 0.36542 0.49821 1.00000 -0.08738

Cystatm A 0.7120 0.2991 0.1428 0.8103

KaI 6 0.11594 0.41736 0.70498 -0.08738 1.00000

Kallikrein 6 0.7498 0 2301 0.0228 0.8103

Alps 0.11346 0.52543 0.69683 -0.06779 0.93627

Alpha synuclein 0.7550 0.1188 0.0251 0.8524 ■c.OOOl

Onctm 0.05742 -0.14166 0.28106 -0.30809 0.65152

Osteonectin 0.8748 0.6963 0.4315 0.3865 0.0413

01cm 0.37458 0.61922 0.05486 0.15567 0.14529

Osteocalcin 0.28S2 0.0563 0.8804 0.6676 0.6888

TroC 0.30886 0.75048 0.73720 0.22803 0.66836

Troponin C 0.3852 0.0124 0.0150 0.5263 0.0346

AbT 0.48667 0.54392 0.29415 -0.15789 0.18430

Abeam Transglutaminase 2 0.1537 0.1041 0.4094 0.6631 0.6103

PGRP 0.38247 -0.23058 -0.19406 -0.30086 -0.31852

PGRP-I Beeta 0.2754 0.5216 0.5911 0.3983 0.3697

PSA -0.10871 0.49744 0.75491 0.27017 0.81303

PSA 0.7650 0.1435 0.0116 0.4503 0.0042

Lab -0.10739 -0.43033 -0 12240 0.10362 -0.12164

Labvision Tgase 2 0.7678 0.2145 0.7362 0.7758 0.7378

Aqua -0.26871 -0.29200 -0.42779 -0.44809 0.08336

Aquapoπn-4 0.4528 0.4130 0.2175 0.1940 0.8189

Capture Time DATA: Summary table of Aqua by Disease 43 Disease=Parkmso

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO: Rho=o

AIpS Onctm 01cm TroC AbT

Cap 0.11346 0.05742 0.37458 0.30886 0.48667 Capture 0.7550 0.8748 0.2862 0.3852 0.1537

MHCI 0.52543 -0.14166 0.61922 0.75048 0.54392 MHC-I 0.1188 0.6963 0.0563 0.0124 0.1041 MaSR 0.69683 0 28106 0 05486 0 73720 0 29415 Macrophage scavenger receptor 0.0251 0 431S 0.8804 0.0150 0.4094

CysA -0.06779 -0.30809 0.15567 0.22803 -0.15789 Cystatm A 0.8524 0.3865 0.6676 0.5263 0.6631

KaIS 0.93627 0.65152 0.14529 0.66336 0.18430 Kallikrem 6 <.oooi 0.0413 0.6888 0.0346 0.6103

AIpS 1 00000 0 46561 0.21582 0.73704 0.24337 Alpha synuclem 0 1750 0.5493 0.0150 0.4981

Onctxn 0.46561 1 00000 0.01110 0.34165 0 15943 Osteonectin 0.1750 0.9757 0.3339 0.6600

01cm 0 21582 0.01110 1.00000 0.56110 0.22243 Osteocalcin 0.5493 0.9757 0.0915 0.5368

TroC 0.73704 0.34165 0.56110 1.00000 0 54689 Troponin C 0.0150 0.3339 0.0915 0.1019

AbT 0.24337 0.15943 0.22243 0.54689 1.00000 Abeam Transglutaminase 2 0.4981 0.6600 0.5368 0.1019

PGRP -0.31801 -0.10663 -0 38152 -0.47197 0.15215 PGRP-I Beeta 0.3705 0.7694 0.2767 0.1684 0.6748

PSA 0.83712 0.38239 0.28814 0.80194 0.02259 PSA 0.0025 0.2755 0.4195 0.0053 0.9506

Lab -0.20676 0.10686 -0.38236 -0.23383 -0.06547 Labvision Tgase 2 0.5666 0.7689 0.2755 0.5156 0.8574

Aqua 0.14421 0.25295 0.37833 -0.02862 -0.42585 Aquaporm-4 0.6910 0.4807 0.2810 0.9374 0.2198

Capture Time DATA: Summary table of Aqua by Disease 44 Disease=Parkmso

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO: Rho=0

PGRP PSA Lab Aqua

Cap 0.38247 -0.10871 -0.10739 -0.26871

Capture 0.2754 0.7650 0.7678 0.4528

MHCI -0.23058 0.49744 -0.43033 -0.29200

MHC-I 0.5216 0.1435 0.2145 0.4130

MaSR -0.19406 0.75491 -0.12240 -0.42779

Macrophage scavenger receptor 0.5911 0.0116 0.7362 0.2175

CysA -0.30086 0.27017 0.10362 -0.44809

Cystatm A 0.3983 0.4503 0.7758 0.1940

Kal6 -0.31852 0.81303 -0.12164 0.08336

Kallikrein 6 0.3697 0.0042 0.7378 0.8189

Alps -0.31801 0.83712 -0.20676 0.14421

Alpha synuclem 0.3705 0.0025 0.5666 0.6910

Onctin -0.10663 0.38239 0.10686 0.25295

Osteonectin 0.7694 0.2755 0.7689 0.4807

01cm -0.38152 0.28814 -0.38236 0.37833

Osteocalcin 0.2767 0.4195 0.2755 0.2810

TroC -0.47197 0.80194 -0.23383 -0.02862

Troponin C 0.1684 0.0053 0.5156 0.9374

AbT 0.15215 0.02259 -0.06547 -0.42585

Abeam Transglutaminase 2 0.6748 0.9506 0.8574 0.2198

PGRP 1.00000 -0.64289 -0.30951 -0.22524

PGRP-I Beeta 0.0450 0.3842 0.5315

PSA -0.64289 1.00000 -0.17663 0.14115

PSA 0.0450 0.6254 0.6973

Lab -0.30951 -0.17663 1.00000 -0.24482 Labvision Tgase 2 0 3842 0 6254 0 4954

Aqua -0.22524 0.14115 -0.24482 1 00000 Aquaponn-4 0.5315 0.6973 0.4954

Capture Time DATA: Summary table of Aqua by Dxsease 45

- Disease=Prostate - The CORR Procedure

14 Variables - Cap MHCI MaSR CysA Kal6 AIpS Onctm 01cm TroC AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 7.29580 5.26111 72.95800 2.85800 17.34900

MHCI 10 0.37690 0.32405 3.76900 0.01300 1.03800

MaSR 9 12.90044 2.60770 116.10400 10.20500 16.39000

CysA 10 4 49120 5.30736 44.91200 0.18700 13.70100

KaI 6 10 0.25190 0.14597 2.51900 0.09300 0.55900

Alps 10 5.73920 3.94053 57.39200 0 10.20500

Onctm 10 0.43520 0.14576 4.35200 0.24900 0.71500

01cm 10 0 0 0 0 0

TroC 10 0.11190 0.22335 1.11900 0 0.65300

AbT 10 0.07450 0.08573 0.74500 0 0.28000

PGRP 10 1.03370 1.64244 10.33700 0 5.13100

PSA 10 0.25420 0.20553 2.54200 0.03S00 0.47200

Lab 10 1.12160 1.52791 11.21600 0 3.65700

Aqua 10 0.49200 0.50196 4.92000 0 1.32300

Simple Statistics

Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatm A

Kal6 Kallikrem 6

AIpS Alpha synuclem

Onctm Osteonectin

01cm Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquaponn-4

Capture Time DATA: Summary table of Aqua by Disease 46 Disease=Prostate

The CORR Procedure

Cap MHCI MaSR CysA KaI 6

Cap 1.00000 0.17724 -0.33618 -0.48848 0.42208 Capture 0.6242 0.3764 0.1520 0.2244 10 10 9 10 10

MHCI 0.17724 1.00000 0.69645 -0.10621 0.54427

MHC-I 0.6242 0.0371 0.7703 0.1038 10 10 9 10 10

MaSR -0.33618 0.69645 1.00000 0.12921 -0.50955 Macrophage scavenger receptor 0.3764 0.0371 0.7404 0.1611 9 9 9 9 9

CysA -0.48848 -0.10621 0.12921 1.00000 -0.34519 Cystatm A 0.1520 0.7703 0.7404 0.3286 10 10 9 10 10

Kal6 0.42208 0.54427 -0.50955 -0.34519 1.00000 Kallikrem 6 0.2244 0.1038 0.1611 0.3286 10 10 9 10 10 AIpS -0 49137 -0 07041 0 S7993 0 02676 -0 76164 Alpha synuclein 0 1492 0 8467 0 0439 0 9415 0 0105 10 10 9 10 10

Onetin -0 11502 -0 02118 0 38860 -0 16763 0 49858 Osteonectin 0 7517 0 9537 0 3013 0 6434 0 1424 10 10 9 10 10

01cm Osteocalcin

10 10 9 10 10

TroC 0 39425 -0 18410 0 30405 -0 05819 -0 22025 Troponin C 0 2596 0 SlOS 0 4263 0 8731 0 5409 10 10 9 10 10

AbT 0 03154 0 58396 0 44987 0 05112 0 03146 Abeam Transglutaminase 2 0 9311 0 07S3 0 2244 0 8885 0 9312 10 10 9 10 10

Capture Time DATA Summary table of Aqua by Disease Disease=Prostate

The CORR Procedure

AIpS Onctm Olciix TroC AbT

Cap -0 49137 -0 11502 -0 39425 0 03154 Capture 0 1492 0 7517 0 2596 0 9311 10 10 10 10

MHCI -0 07041 0 02118 -0 18410 0 58396 MHC I 0 8467 0 9537 0 6106 0 0763 10 10 10 10

MaSR 0 67993 -0 38860 0 30405 0 44987 Macrophage scavenger receptor 0 0439 0 3013 0 4263 0 2244 9 9 9 9

CysA 0 02676 0 16763 -0 05819 0 05112 Cystatin A 0 9415 0 6434 0 8731 0 8885 10 10 10 10

Kal6 0 76164 0 49858 -0 22025 0 03146 Kallikrein 6 0 0105 0 1424 0 5409 0 9312 10 10 10 10 10

AIpS 1 00000 -0 33057 0 12742 0 26730 Alpha synuclein 0 3509 0 7257 0 4553 10 10 10 10 10

Onctin -0 33057 1 00000 0 11890 -0 15514 Osteonectin 0 3509 0 7435 0 6687 10 10 10 10

01cm Osteocalcin

10 10 10 10

TroC 0 12742 0 11890 1 00000 -0 33266 Troponin C 0 7257 0 7435 0 3476

10 10 10 10 10

AbT 0 26730 -0 15514 -0 33266 1 00000

Abeam Transglutaminase 2 0 4553 0 6687 0 3476

10 10 10 10

Capture Time DATA Summary table of Aqua by Disease 48 Disease=Prostate

The CORR Procedure

Pearson Correlation Coefficients Prob > |r| under HO RhO=O Number of Observations

PGRP PSA Lab Aqua

Cap -0 29751 -0 31933 0 .13579 -0 35832 Capture 0.4038 0.3685 0.7084 0.3093 10 10 10 10

MHCI 0.33086 0.60982 -0.45848 -0.20438 MHC-I 0.3504 0.0612 0.1826 0.5711 10 10 10 10

MaSR 0.S9740 0.59381 -0.26097 0.03778

Macrophage scavenger receptor 0.0368 0.0918 0.4976 0.9231 9 9 9 9

CysA 0.37478 -0.06584 0.13492 -0.57072 Cystatin A 0.2859 0.8566 0.7102 0.0849 10 10 10 10

KaI6 -0.43377 -0.00002 -0.25307 0.04596 Kallikrein S 0.2104 1.0000 0.4805 0.8997 10 10 10 10

AIpS 0.45679 0.57981 -0.06024 0.21474

Alpha synuclein 0.1845 0.0789 0.8687 0.5513 10 10 10 10

Onctin -0.40936 0.14970 -0.41988 0.27743 Osteonectin 0.2401 0.6798 0.2270 0.4377 10 10 10 10

Oloin Osteocalcin

10

TroC 0.26471 -0.14670 -0.35569 0.45394 Troponin C 0.4598 0.6859 0.3131 0.1876

10 10 10 10

AbT 0.63779 0.64027 -0.41866 -0.21907

Abeam Transglutaminase 2 0.0473 0.0461 0.2285 0.5431

10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 49

- Disease=Prostate - The CORR Procedure

Cap MHCI MaSR CysA KaI6

PGRP -0.29751 0.33086 0.69740 0.37478 -0.43377

PGRP-I Beeta 0.4038 0.3504 0.0368 0.2859 0.2104 10 10 9 10 10

PSA -0.31933 0.60982 0.59381 -0.06584 -0.00002 PSA 0.3685 0.0612 0.0918 0.8566 1.0000 10 10 9 10 10

Lab 0.13579 -0.45848 -0.26097 0.13492 -0.25307

Labvision Tgase 2 0.7084 0.1826 0.4976 0.7102 0.4805 10 10 9 10 10

Aqua -0.35832 -0.20438 0.03778 -0.57072 0.04596 Aquaporin-4 0.3093 0.5711 0.9231 0.0849 0.8997 10 10 9 10 10 son Correlation Coefficients rob > r| under HO: RhO=O

Number of Observations

AIpS Onctin Olcin TroC AbT

PGRP 0.45679 -0.40936 0.26471 0.63779

PGRP-I Beeta 0.1845 0.2401 0.4598 0.0473

10 10 10 10 10

PSA 0.57981 0.14970 0.14670 0.64027 PSA 0.0789 0.6798 0.6859 0.0461

10 10 10 10 10

Lab -0.06024 -0.41988 0.35569 -0.41866

Labvision Tgase 2 0.8687 0.2270 0.3131 0.2285

10 10 10 10 10

Aqua 0.21474 0.27743 0.45394 -0.21907 Aquapoπn-4 5513 0 4377 0.1876 0 5431 10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease 50 Disease=Prostate

The CORR Procedure

PGRP PSA Lab Aqua

PGRP 1.00000 0 3839B -0.28960 -0.29585

PGRP-I Beeta 0.2733 0.4170 0.4066

10 10 10 10

PSA 0.38398 1.00000 -0.58122 0.08793 PSA 0.2733 0.0780 0 8091

10 10 10 10

Lab -0.289SO -0.S8122 1.00000 -0.17247

Labvision Tgase 2 0.4170 0.0780 0.6337

10 10 10 10

Aqua -0.29585 0.08793 -0.17247 1.00000 Aquapoπn-4 0.4066 0.8091 0.6337

10 10 10 10

Capture Time DATA: Summary table of Aqua by Disease

- Disease=Prostati - The CORR Procedure

14 Variables : Cap MHCI MaSR CysA KaI6 AIpS Onctin 01cm TroC

AbT PGRP PSA Lab Aqua

Simple Statistics

Variable N Mean Std Dev Sum Minimum Maximum

Cap 10 521.09460 128.07561 5211 359.19200 640.00000

MHCI 10 468.35620 198.75867 4684 161.30300 640.00000

MaSR 10 25.42470 9.46639 254. 24700 13.17900 40.88900

CysA 10 25.46760 2.74424 254. 67600 22.36400 31.76400

KaI6 10 0.81990 0.47641 8. 19900 0.09300 1.58300

AIpS 10 35.09740 8.17385 350. 97400 22.70900 47.93900

Onetin 10 0.96590 0.32558 9. 65900 0.52800 1.64500

01cm 10 2.11220 0.81542 21. 12200 1.16900 3.41800

TroC 10 0.64320 0.28267 6. 43200 0.28000 1.21100

AbT io 0.51210 0.69392 5. 12100 0 1.76800

PGRP 10 387.16540 267.57223 3872 96.45500 640.00000

PSA 10 40.41940 3.35955 404. 19400 35.13200 45.14300

Lab 10 0.46470 0.41452 4. 64700 0 1.30400

Aqua 10 413.84040 245 35230 4138 107.04900 640.00000

Simple Statistics

Variable Label

Cap Capture

MHCI MHC-I

MaSR Macrophage scavenger receptor

CysA Cystatin A

KaI6 Kallikrein 6

AIpS Alpha synuclem

Onctm Osteonectin

01cm Osteocalcin

TroC Troponin C

AbT Abeam Transglutaminase 2

PGRP PGRP-I Beeta

PSA PSA

Lab Labvision Tgase 2

Aqua Aquapoπn-4

Capture Time DATA: Summary table of Aqua by Disease 52

Disease=Prostati The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO RhO=O

Cap MHCI MaSR CysA KaI6

Cap 1 00000 0 91434 0 72694 0 03555 0 78486 Capture 0 0002 0 0172 0 9223 0 0072

MHCI 0 91434 1 00000 0 73538 0 16379 0 78355 MHC-I 0 0002 0 0154 0 6512 0 0073

MaSR 0 72694 0 73538 1 00000 0 45348 0 86737

Macrophage scavenger receptor 0 0172 0 0154 0 1881 0 0012

CysA 0 03555 0 16379 0 45348 1 00000 0 29975 Cystatm A 0 9223 0 S512 0 1881 0 4001

KaI6 0 78486 0 78355 0 86737 0 29975 1 00000 Kallikrem S 0 0072 0 0073 0 0012 0 4001

AIpS 0 78187 0 83427 0 88609 0 45560 0 73854

Alpha synuclem 0 0075 0 0027 0 0006 0 1858 0 0147

Onctm 0 70996 0 57386 0 48744 0 39636 0 45550 Osteonectin 0 0214 0 0828 0 1530 0 2568 0 1859

01cm 0 89045 0 86870 0 88859 0 37656 0 88636 Osteocalcin 0 0006 0 0011 0 0006 0 2835 0 0006

TroC 0 43436 0 31430 0 47835 0 64809 0 58499 Troponin C 0 2097 0 3764 0 1620 0 0427 0 0757

AbT -0 22819 0 28518 -0 56752 -0 30728 -0 66100

Abeam Transglutaminase 2 0 5260 0 4245 0 0870 0 3878 0 0374

PGRP 0 97503 0 94115 0 79501 0 10705 0 87024

PGRP-I Beeta < 0001 < 0001 0 0060 0 7685 0 0011

PSA 0 38693 0 38415 0 22525 0 24452 0 05800 PSA 0 2693 0 2731 0 5315 0 4960 0 8736

Bab 0 58722 0 71291 0 69512 0 32085 0 78473

Labvision Tgase 2 0 0743 0 0207 0 0257 0 3660 0 0072

Aqua 0 95162 0 97871 0 79088 0 14776 0 85849 Aquaponn-4 < 0001 < 0001 0 0064 0 6837 0 0015

Capture Time DATA Summary table of Aqua by Disease 53 Disease=Prostati - -

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO Rho=0

AIpS Onctm 01cm TroC AbT

Cap 0 78187 0 70996 0 89045 0 43436 -0 22819

Capture 0 0075 0 0214 0 0006 0 2097 0 5260

MHCI 0 83427 0 57386 0 86870 0 31430 -0 28518

MHC-I 0 0027 0 0828 0 0011 0 3764 0 4245

MaSR 0 88S09 0 48744 0 88859 0 47835 -0 56752

Macrophage scavenger receptor 0 0006 0 1530 0 0006 0 1620 0 0870

CysA 0 45560 0 39636 0 37656 0 64809 -0 30728

Cystatm A 0 1858 0 2568 0 2835 0 0427 0 3878

KaI6 0 73854 0 45550 0 88636 0 58499 -0 66100

Kallikrem 6 0 0147 0 1859 0 0006 0 0757 0 0374

AIpS 1 00000 0 61101 0 93571 0 44771 -0 25825

Alpha synuclem 0 0606 < 0001 0 1945 0 4713

Onctm 0 61101 1 00000 0 68591 0 70842 0 16024

Osteonectin 0 0606 0 0285 0 0218 0 6583

01cm 0 93571 0 68591 1 00000 0 59115 -0 35623

Osteocalcin < 0001 0 0285 0 0719 0 3123

TroC 0 44771 0 70842 0 59115 1 00000 -0 32611 Troponin C 0.1945 0.0218 0.0719 0.3578

AbT 0.25825 0.16024 -0.35623 -0.32611 1.00000

Abeam Transglutaminase 2 0.4713 0.6583 0.3123 0.3578

PGHP 0.78471 0.62351 0.89608 0.44221 -0.41191

PGRP-I Beeta 0.0072 0.0541 0.0004 0.2007 0.2369

PSA 0.59808 0.65048 0.46557 0.25207 0.57498 PSA 0.0678 0.0417 0.1751 0.4823 0.0821

Lab 0.77545 0.35711 0.80455 0.39314 -0.27253

Labvision Tgase 2 0.0084 0.3111 0.0050 0.2610 0.4462

Aqua 0.81176 0.58657 0.89310 0.39068 -0.40354 Aquaporin-4 0.0043 0.0747 0.0005 0.2643 0.2475

Capture Time DATA: Summary table of Aqua by Disease 54 Disease=Prostati

The CORR Procedure

Pearson Correlation Coefficients, N = 10 Prob > |r| under HO: RhO=O

PGRP PSA Lab Aqua

Cap 0.97503 0.38693 0.58722 0.95162

Capture <.0001 0.2693 0.0743 <.0001

MHCI 0.94115 0.38415 0.71291 0.97871

MHC-I <.oooi 0.2731 0.0207 <.0001

MaSR 0.79501 0.22525 0.69512 0.79088

Macrophage scavenger receptor 0.0060 0.5315 0.0257 0.0064

CysA 0.10705 0.24452 0.32085 0.14776

Cystatin A 0.7685 0.4960 0.3660 0.6837

KaI6 0.87024 0.05800 0.78473 0.85849

Kallikrein 6 0.0011 0.8736 0.0072 0.0015

AIpS 0.78471 ' 0.59808 0.77545 0.81176

Alpha synuclein 0.0072 0.0678 0.0084 0.0043

Onctin 0.62351 0.65048 0.35711 0.58657

Osteonectin 0.0541 0.0417 0.3111 0.0747

Olcin 0.89608 0.46557 0.80455 0.89310

Osteocalcin 0.0004 0.1751 0.0050 0.0005

TroC 0.44221 0.25207 0.39314 0.39068

Troponin C 0.2007 0.4823 0.2610 0.2643

AbT -0.41191 0.57498 -0.27253 -0.40354

Abeam Transglutaminase 2 0.2369 0.0821 0.4462 0.2475

PGRP 1.00000 0.24166 0.62520 0.98838

PGRP-I Beeta 0.5012 0.0532 <.0001

PSA 0.24166 1.00000 0.42169 0.26843

PSA 0.5012 0.2248 0.4533

Lab 0.62520 0.42169 1.00000 0.67312

Labvision Tgase 2 0.0532 0.2248 0.0329

Aqua 0.98838 0.26843 0.67312 1.00000

Aquaporin-4 <.0001 0.4533 0.0329

Comparison in CaDture for Cstitis and KidSton 55

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Ξtd Dev Std Dev Std Dev Std Err

Cap Cstitis 10 167.42 256.01 344. 59 85 .175 123 .83 226 .07 39.158

Cap KidSton 10 82.852 95.161 107. 47 11 .836 17. 207 31. 413 5.4413

Cap Diff (1-2) 77.785 160.84 243 .9 66 .798 88. 402 130 .73 39.535 T-Tests

Variable Method Variances DF t Value Pr |t|

Cap Pooled Equal 18 4.07 0.0007

Cap Satterthwaite Unequal 9 35 4.07 0.0026

Equality of Variances

Variable Method NUm DF Den DF F Value Pr > F

Cap Folded F 9 9 51 79 <.0001

Comparison xn Capture for Cstitis and Endoaden 56

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Cstitis 10 167 42 256.01 344.59 85.175 123.83 226.07 39.158

Cap Endoaden 10 225. 29 360.44 495.59 129.95 188.93 344.91 59.745

Cap Diff (1-2) -254 .5 -104.4 45.642 120.7 159.73 236.22 71.434

T-Tests

Variable Method Variances t Value Pr > |t|

Cap Pooled Equal 18 -1.46 0.1610 Cap Satterthwaite Unequal 15.5 -1.46 0.1637

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 2.33 0.2241

Comparison m Capture for Cstitis and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Cstitis 10 167.42 256.01 344.59 85.175 123.83 226.07 39.158 Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6637 Cap Diff (1-2) 166.37 248.71 331.05 66.222 87.64 129.6 39.194

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 6.35 <.0001 Cap Satterthwaite Unequal 9.03 S.35 0.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 553.98 <.0001

Comparison in Capture for Cstitis and Prostati 58

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Cstitis 10 167.42 256.01 344. .59 85, .175 123 .83 226 .07 39 .158 Cap Prostati 10 429.47 521.09 612..71 88..095 128.08 233.82 40.501 Cap Diff (1-2) -383.4 -265.1 -14«5.7 95.,185 125.97 186.29 56.336 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -4 71 0 .0002 Cap Satterthwaite Unequal 18 -4.71 0.0002

Equality of Variances

Variable Method Nutn DF Den DF F Value Pr > F

Cap Folded F 9 9 1.07 0.9216

Comparison in Capture for Cstitis and Arthπti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Arthπti 10 197.8 273.45 349 .09 72 .737 105 .75 193.05 33 .44 Cap Cstitis 10 167.42 256.01 344.59 85.175 123.83 226.07 39.158 Cap Diff (1-2) -90.74 17.441 125.63 87.004 115 .14 170.28 51.494

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 0 .34 0 .7388 Cap Satterthwaite Unequal 17.6 0 .34 0.7388

Equality of Variances

Variable Method Nutn DF Den DF F Value Pr > F

Cap Folded F 9 9 1.37 0.6457

Comparison m Capture for Cstitis and Aortic 60

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152.25 193.36 234.46 39. .525 57. 462 104.9 18. 171 Cap Cstitis 10 167.42 256.01 344.59 85,.175 123.83 226.07 39.158 Cap Diff (1-2) -153.3 -62.65 28.048 72..939 96.529 142.75 43.169

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -1.45 0.1639 Cap Satterthwaite Unequal 12.7 -1.45 0.1710

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 4.64 0.0319

Comparison m Capture for Cstitis and Parkmso 61

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Cstitis 10 167.42 256.01 344.59 85.175 123.83 226.07 39.158 Cap Parkmso 10 137.34 140.77 144.2 3.2955 4.7911 8.7467 1.5151 Cap Diff (1-2) 32.907 115.24 197.57 66.212 87.626 129.58 39.188 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 2.94 0.0087 Cap Satterthwaite unequal 9.03 2.94 0.0164

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 668.00 <.0001

Comparison in Capture for KidSton and Endoaden 62

The TTEST Procedure Statistics

Lower CL Dpper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Endoaden 10 225 .29 360.44 49S .59 129 .95 188 .93 344.91 59.745 Cap KidSton 10 82.1352 95 161 107.47 11.836 17.207 31.413 5.4413 Cap Diff (1-2) 139.24 265.28 391.32 101.36 134 .15 198.38 59.992

T-Tests

Variable Method Variances DF t Value

Cap Pooled Equal 18 4.42 0.0003 Cap Satterthwaite Unequal 9 .15 4.42 0.0016

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 120 56 <.0001

Comparison in Capture for KidSton and Prostate 63

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap KidSton 10 82.852 95.161 107.47 11.836 17.207 31.413 5.4413

Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6637

Cap Diff (1-2) 75.911 87.865 99.819 9.6138 12.723 18.815 5.69

T-Tests

Variable Method Variances DF t Value Pr |t|

Cap Pooled Equal 18 15.44 <.0001 Cap Satterthwaite Unequal 10.7 15.44 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 10.70 0.0016

Comparison in Capture for KidSton and Prostati 64

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

Cap KidSton 10 82.852 95.161 107.47 11 .836 17. 207 31. 413 5. 4413 Cap Prostati 10 429.47 521.09 612.71 88 .095 128 .08 233 .82 40 .501 Cap Diff (1-2) -511.8 -425.9 -340.1 69 .045 91. 377 135 .13 40 .865 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -10 42 <.0001 Cap Satterthwaite Unequal 9.32 -10 42 <.0001

Equality of Variances

Variable Method Nura DF Den DP F Value Pr =■ F

Cap Folded F 9 9 55.40 < 0001

Comparison in Capture for KidSton and Arthnti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Arthnti 10 197.8 273.45 349 .09 72.737 1OS .75 193.05 33 .44 Cap KidSton 10 82.852 95.161 107 .47 11.836 17. 207 31.413 5.4413 Cap Diff (1-2) 107.11 178.29 249 .47 57.244 75. 758 112.03 33 .88

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 5. .26 < .0001 Cap Satterthwaite Unequal 9 .48 5 .26 0 .0004

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 37.77 <.0001

Comparison in Capture for KidSton and Aortic 66

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152.25 193 .36 234 .46 39 .525 57 .462 104.9 18 .171 Cap KidSton 10 82.852 95.161 107.47 11.836 17.207 31.413 5.4413 Cap Diff (1-2) 58.347 98.198 138.05 32.049 42.415 62.724 18.968

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 5.18 < .0001 Cap Satterthwaite Unequal 10.6 5.18 0.0003

Equality o£ Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 11.15 0.0014

Comparison m Capture for KidSton and Parkmso 67

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap KidSton 10 82.852 95.161 107. 47 11 .836 17.207 31 .413 5 .4413 Cap Parkmso 10 137.34 140.77 144 .2 3. 2955 4.7911 8. 7467 1 .5151 Cap Diff (1-2) -57.47 -45.61 -33. 74 9. 5434 12.63 18 .678 5 .6483 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -8.07 <.0001 Cap Satterthwaite unequal 10.4 -8.07 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 12.90 0.0008

Comparison in Capture for Endoaden and Prostate 68

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Endoaden 10 225.29 360.44 495.59 129.95 188.93 344.91 59.745 Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6637 Cap Diff (1-2) 227.58 353.14 478.71 100.98 133.65 197.64 59.768

T-Tests

Variable Method Variances t Value Pr > |t|

Cap Pooled Equal 18 5.91 <.0001 Cap Satterthwaite Unequal 9.01 5.91 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 1289.58 <.0001

Comparison in Capture for Endoaden and Prostati 69

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Endoaden 10 225.29 360.44 495 .59 129 .95 188. 93 344.91 59.745 Cap Prostati 10 429.47 521.09 612.71 88.095 128.08 233.82 40.501 Cap Diff (1-2) -312.3 -160.7 -9.011 121.95 161.4 238.68 72.179

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -2.23 0.0390 Cap Satterthwaite Unequal 15.8 -2.23 0.0409

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 2.18 0.2623

Comparison in Capture for Endoaden and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

Cap Arthriti 10 197.8 273.45 349 .09 72. 737 105. 75 193. 05 33 .44 Cap Endoaden 10 225.29 360.44 495 .59 129 .95 188. 93 344. 91 59. 745 Cap Diff (1-2) -230.8 -86.99 56 .85 115 .68 153 .1 226 .4 68. 467 T-Tests

Variable Method Variances DF t Value Pr >

Cap Pooled Equal 18 -1 27 0 2200 Cap Satterthwaite Unequal 14.1 -1.27 0 2244

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 3 19 0.0989

Comparison in Capture for Endoaden and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152.25 193.36 234. .46 39.525 57. 462 104.9 18 .171 Cap Endoaden 10 225.29 360.44 495..59 129.95 188.93 344.91 59.745 Cap Diff (1-2) -298.3 -167.1 -35..89 105.51 139.64 206.5 62.447

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -2 .68 0.0154 Cap Satterthwaite Unequal 10.7 -2.68 0.0221

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 10.81 0.0015

Comparison in Capture for Endoaden and Parkmso

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Endoaden 10 225.29 360.44 495. .59 129.95 188. .93 344 91 59 .745

Cap Parkmso 10 137.34 140.77 144.2 3.2955 4.7911 8.7467 1. 5151

Cap Diff (1-2) 94.113 219.67 345. .23 100.98 133 .64 197.63 59 .764

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 3 .68 0 .0017

Cap Satterthwaite Unequal 9 .01 3 .68 0 .0051

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 1555.00 <.0001

Comparison m Capture for Prostate and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6637 Cap Prostati 10 429.47 521.09 612.71 88.095 128.08 233.82 40.501 Cap Diff (1-2) -599 -513.8 -428.6 68.488 90.64 134.04 40.535 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -12.68 <.0001 Cap Satterthwaite Unequal 9.03 -12.68 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr =. F

Cap Folded F 9 9 592.62 <.0001

Comparison in Capture for Prostate and Arthriti

The TTEST Procedure Statistics

Lower CJj Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Arthriti 10 197.8 273.45 349.09 72 .737 105.75 193.05 33.44 Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6S37 Cap Diff (1-2) 195.81 266.15 336.49 56.571 74.867 110.72 33.482

T-Tests

Variable Method Variances DF t Value Pr > It

Cap Pooled Equal 18 7.95 <.0001 Cap Satterthwaite Unequal 9.04 7.95 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 404.00 <.0001

Comparison in Capture for Prostate and Aortic 75

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152.25 193.36 234.46 39.525 57 .462 104.9 18 .171 Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.SS37 Cap Diff (1-2) 147.73 186.06 224.4 30.83 40.802 60.339 18.247

T-Tests

Variable Method Variances DF t Value Pr ^» |t|

Cap Pooled Equal 18 10.20 < .0001 Cap Satterthwaite Unequal 9.15 10.20 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 119.29 <.0001

Comparison in Capture for Prostate and Parkinso 76

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev std Err

Cap Parkinso 10 137.34 140.77 144.2 3.2955 4.7911 8.7467 1.5151

Cap Prostate 10 3.5322 7.2958 11.059 3.6188 5.2611 9.6047 1.6637

Cap Diff (1-2) 128.74 133.47 138.2 3.8019 5.0316 7.4409 2.2502 T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 59 .32 < .0001 Cap Satterthwaite Unequal 17.8 59.32 < .0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 1.21 0.7850

Comparison in Capture for Prostati and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Arthriti 10 197.8 273.45 349.09 72.737 105.75 193.05 33.44

Cap Prostati 10 429.47 521.09 612.71 88.095 128.08 233.82 40.501

Cap Diff (1-2) -358 -247.6 -137.3 88.742 117.44 173.68 52.522

T-Tests

Variable Method Variances t Value Pr > |t|

Cap Pooled Equal 18 -4.72 0.0002 Cap Satterthwaite Unequal 17.4 -4.72 0.0002

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Cap Folded F 9 9 1.47 0.5773

Comparison in Capture for Prostati and Aortic 78

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean std Dev Std Dev std Dev Std Err

Cap Aortic 10 152.25 193.36 234. 46 39 .525 57. 462 104.9 18 .171

Cap Prostati 10 429.47 521.09 612. 71 88 .095 128 .08 233.82 40 .501

Cap Diff (1-2) -421 -327.7 -234 .5 75 .002 99 .26 146.79 44 .391

T-Tests

Variable Method Variances DF t Value Pr > |t|

Cap Pooled Equal 18 -7.38 < .0001

Cap Satterthwaite Unequal 12.5 -7.38 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 4.97 0.0256

Comparison m Capture for Prostati and Parkmso 79

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

Cap Parkmso 10 137.34 140.77 144.2 3. 2955 4.7911 8.7467 1. 5151 Cap Prostati 10 429.47 521.09 612.71 88 .095 128.08 233.82 40 .501 Cap Diff (1-2) -465.5 -380.3 -295.2 68 .479 90.626 134.02 40 .529 T-Tests

Variable Method Variances DF t Value Pr > |t

Cap Pooled Equal 18 -9.38 ■=.0001 Cap Satterthwaite Unequal 9.03 -9.38 <.0001

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

Cap Folded F 9 9 714.59 <.0001

Comparison in Capture for Arthriti and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152.25 193.36 234.46 39.525 57.462 104.9 18.171

Cap Arthriti 10 197.8 273.45 349.09 72.737 105.73 193.05 33.44

Cap Diff (1-2) -160 -80.09 -0.13 64.303 85.101 125.85 38.058

T-Tests

Variable Method Variances t Value Pr > |t|

Cap Pooled Equal 18 -2.10 0.0497 Cap Satterthwaite Unequal 13.9 -2.10 0.0541

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 3.39 0.0836

Comparison in Capture for Arthriti and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Arthriti 10 197.8 273.45 349.09 72.737 105.75 193.05 33.44 Cap Parkinso 10 137.34 140.77 144.2 3.2955 4.7911 8.7467 1.5151 Cap Diff (1-2) 62.351 132.68 203.01 56.559 74.851 110.69 33.475

T-Tests

Variable Method Variances DF t Value

Cap Pooled Equal 18 3 .96 0.0009 Cap Satterthwaite Unequal 9.04 3.96 0.0033

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 487.15 <.0001

Comparison in Capture for Aortic and Parkinso 82

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Cap Aortic 10 152 .25 193 .36 234.46 39 .525 57 .462 104.9 18.171

Cap Parkinso 10 137 .34 140 .77 144.2 3. 2955 4. 7911 8.7467 1.5151

Cap Diff (1-2) 14. 282 52. 591 90.899 30 .809 40 .773 60.296 18.234 T-Tests

Variable Method Variances DF t Value Pr > I^tI

Cap Pooled Equal 18 2.88 0 .0099 Cap Satterthwaite Unequal 9.13 2.88 0.0178

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Cap Folded F 9 9 143-84 <.0001

Comparison in MHC-I for Cstitis and KidSton

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MHCI Cstitis 10 135.19 329.35 523.51 186.69 271.41 495.49 85.828

MHCI KidSton 10 35.585 41.844 48.103 6.0181 8.7493 15.973 2.7668

MHCI Diff (1-2) 107.1 287.51 467.92 145.09 192.02 283.96 85.872

T-Tests

Variable Method Variances t Value Pr lt|

MHCI Pooled Equal 18 3.35 0.0036 MHCI Satterthwaite Unequal 9.02 3.35 0.0085

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 962.30 <.0001

Comparison in MHC-I for Cstitis and Endoaden

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Cstitis 10 135.19 329.35 523 .51 186 .69 271.41 495.49 85. 828

MHCI Endoaden 10 319.04 512.03 705 .02 185. .57 269.78 492.52 85. 313

MHCI Diff (1-2) -436.9 -182.7 71.564 204, .47 270.6 400.17 121 .02

T-Tests

Variable Method Variances DF t ^' Value Pr > |t|

MHCI Pooled Equal 18 -1.51 0.1485

MHCI Satterthwaite Unequal 18 -1.51 0.1485

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.01 0.9860

Comparison in MHC-I for Cstitis and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Cstitis 10 135.19 329.35 523.51 186.69 271.41 495.49 85.828

MHCI Prostate 10 0.1451 0.3769 0.6087 0.2229 0.3241 0.5916 0.1025

MHCI Diff (1-2) 148.66 328.97 509.29 145.01 191.92 283.81 85.828 T-Tests

Variable Method Variances DF t Value Pr > |t]

MHCI Pooled Equal 18 3.83 0.0012

MHCI Satterthwaite Unequal 9 3.83 0.0040

Equality of Variances

Variable Method Num DP Den DF F Value Pr _> F

MHCI Folded F 9 9 701503 < 0001

Comparison in MHC-I for Ostitis and Prostati 86

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev std Err

MHCI Cstltis 10 135. 19 329.35 523.51 186.69 271.41 495.49 85.828 MHCI Prostati 10 326. 17 468.36 610.54 136.71 198.76 362.86 62.853 MHCI Diff (1-2) -362 .5 -139 84.493 179.74 237.87 351.78 106.38

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -1.31 0.2078 MHCI Satterthwaite Unequal 16.5 -1.31 0.2092

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.86 0.3670

Comparison m MHC-I for Cstitis and Arthriti

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Arthriti 10 241.19 433.06 624. .94 184.49 268 .22 489.67 84. 819

MHCI Cstitis 10 135.19 329.35 523. .51 186.69 271 .41 495.49 85. 828

MHCI Diff (1-2) -149.8 103.71 357. .23 203.88 269 .82 399.02 120 .67

T-Tests

Variable Method Variances DF t Value Pr > ItI

MHCI Pooled Equal 18 0.86 0 .4014

MHCI Satterthwaite Unequal 18 0.86 0 .4014

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.02 0.9725

Comparison in MHC-I for Cstitis and Aortic 88

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122.84 178.59 326.04 56.475

MHCI Cstitis 10 135.19 329.35 523.51 186.69 271.41 495.49 B5.828

MHCI Diff (1-2) -228.7 -12.83 203.02 173.59 229.74 339.74 102.74 T-Tests

Variable Method Variances DF t Value Pr > It]

MHCI Pooled Equal 18 -0 12 0. 9020

MHCI Satterthwaite Unequal 15.6 -0.12 0. 9022

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 2.31 0.2283

Comparison m MHC-I for Cstitis and Parkmso 89

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Cstitis 10 135.19 329.35 523.51 186. .69 271. .41 495.49 85 .828

MHCI Parkmso 10 73.558 75.278 76.998 1.6536 2.4041 4.389 0. 7603

MHCI Diff (1-2) 73.748 254.07 434.4 145 .02 191. .92 283.82 85 .831

T-Tests

Variable Method Variances DF t Value Pr >

MHCI Pooled Equal 18 2.96 0 .0084

MHCI Satterthwaite Unequal 9 2.96 0 .0160

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 12745.0 <.0001

Comparison m MHC-I for KidSton and Endoaden 90

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean std Dev Std Dev Std Dev Std Err

MHCI Endoaden 10 319 .04 512 .03 705 .02 185 .57 269.78 492.52 85.313

MHCI KidSton 10 35. 585 41. 844 48. 103 6.0181 8.7493 15.973 2.7668

MHCI Diff (1-2) 290 .86 470 .19 649 .52 144. .22 190.87 282.26 85.358

T-Tests

Variable Method Variances DF t Value Pr > | t |

MHCI Pooled Equal 18 5.51 <.0001 MHCI Satterthwaite Unequal 9.02 5.51 0.0004

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 950.79 <.0001

Comparison in MHC-I for KidSton and Prostate 91

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI KidSton 10 35.585 41 .844 48.103 6 .0181 8 .7493 15.973 2.7668

MHCI Prostate 10 0.1451 0. 3769 0.6087 0 .2229 0 .3241 0.5916 0.1025

MHCI Diff (1-2) 35.65 41 .467 47.284 4 .6779 6 .1909 9.1553 2.7687 T-Tests

Variable Method Variances DP t Value Pr > |t|

MHCI Pooled Equal 18 14.98 <.0001

MHCI Satterthwaite Unequal 9.02 14.98 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 728.99 <.0001

Comparison in MHC-I for KidSton and Prostati 92

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Ston 10 35.585 41.844 48.103 S.0181 8.7493 15.973 2.7668 MHCI stati 10 326.17 468.36 610.54 136.71 198 .76 3S2.86 62.853 MHCI f (1-2) -558.7 -426.5 -294.3 106.3 140 .68 208.04 62.914

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -6.78 <.0001

MHCI Satterthwaite Unequal 9 .03 -6.78 <-0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 516.07 <.0001

Comparison m MHC-I for KidSton and Arthπti 93

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI hπti 10 241 .19 433.06 624 .94 184 .49 268.22 489.67 84 .819 MHCI Ston 10 35.585 41.844 48. 103 6.0181 8.7493 15.973 2. 7668 MHCI f (1-2) 212 .93 391.22 569 .51 143 .39 189.76 280.62 84 .864

T-Tests

Variable Method Variances DF t Value Pr >

MHCI Pooled Equal 18 4.61 0 .0002

MHCI Satterthwaite Unequal 9 .02 4.61 0 .0013

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 939.80 <.0001

Comparison in MHC-I for KidSton and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188 .76 316 .52 444 .27 122.84 178.59 326 .04 S6 .475

MHCI KidSton 10 35. 585 41. 844 48. 103 6.0181 8.7493 15. 973 2. 7668

MHCI Diff (1-2) 155 .88 274 .67 393 .47 95.535 126.43 186 .97 56 .543 T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 4.86 0. 0001

MHCI Satterthwaite Unequal 9.04 4.86 0 0009

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 416 65 <.0001

Comparison m MHC-I for KidSton and Parkmso 95

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI KidSton 10 35.585 41. 844 48.103 6.0181 8.7493 15.973 2.7668

MHCI Parkmso 10 73.558 75. 278 76.998 1.6536 2.4041 4.389 0.7603

MHCI Diff (1-2) -39.46 -33 .43 -27.41 4.848 6.416 9.4881 2.8693

T-Tests

Variable Method Variances t Value Pr > |t|

MHCI Pooled Equal 18 -11.65 <.0001 MHCI Satterthwaite Unequal 10.4 -11.65 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 13.24 0.0007

Comparison in MHC-I for Endoaden and Prostate 96

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Endoaden 10 319.04 512 03 705.02 185.57 269.78 492.52 85.313 MHCI Prostate 10 0.1451 0.3769 0.6087 0.2229 0.3241 0.5916 0.1025 MHCI Diff (1-2) 332.42 511.65 690.89 144.14 190.77 282.11 85.313

T-Tests

Variable Method Variances DF t Value Pr |t|

MHCI Pooled Equal 18 6.00 <.0001 MHCI Satterthwaite Unequal 9 6.00 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 693112 <.0001

Comparison m MHC-I for Endoaden and Prostati 97

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Endoaden 10 319.04 512 .03 705. 02 185 .57 269 .78 492. 52 85. 313

MHCI Prostati 10 326.17 468.36 610. 54 136 .71 198 .76 362. 86 62. 853

MHCI Diff (1-2) -179 43 .675 266 .3 179 .04 236 .95 350 .4 105 .97 T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 0.41 0.6851 MHCI Satterthwaite Unequal 16 5 0.41 0.6855

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.84 0.3762

Comparison in MHC-I for Endoaden and Arthπti 98

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Arthπti 10 241. 19 433 .06 624.94 184.49 268.22 489.67 84.819

MHCI Endoaden 10 319. 04 512 .03 705.02 185.57 269.78 492.52 85.313

MHCI Diff (1-2) -331 .7 -78 .97 173.78 203.26 269 397.81 120.3

T-Tests

Variable Method Variances t Value Pr > |t|

MHCI Pooled Equal 18 -0.66 0.5199 MHCI Satterthwaite Unequal 18 -0.66 0.5199

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.01 0.9865

Comparison in MHC-I for Endoaden and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122 .84 178 .59 326.04 56.475

MHCI Endoaden 10 319.04 512.03 705.02 185 .57 269 .78 492.52 85.313

MHCI Diff (1-2) -410.5 -195.5 19.436 172 .87 228 .78 338.32 102.31

T-TeStS

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -1.91 0.0721

MHCI Satterthwaite Unequal 15.6 -1.91 0.0745

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 2.28 0.2349

Comparison in MHC-I for Endoaden and Parkinso 100

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Endoaden 10 319.04 512.03 705.02 185.57 269.78 492 .52 85.313

MHCI Parkinso 10 73.558 75.278 76.998 1.6536 2.4041 4.389 0.7603

MHCI Diff (1-2) 257.51 436.75 616 144.15 190.77 282 .12 85.316 T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 5.12 <.0001

MHCI Satterthwaite Unequal 9 5.12 0.0006

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 12592.5 <.0001

Comparison in MHC-I for Prostate and Prostatl 101

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Prostate 10 0 1451 0.3769 0.6087 0.2229 0.3241 0.5916 0.1025

MHCI Prostatl 10 326.17 468.36 610.54 136.71 198.76 362.86 62.853

MHCI Dlff (1-2) -600 -468 -335.9 106.2 140.54 207.84 62.853

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -7.45 ■c.OOOl MHCI Satterthwaite Unequal 9 -7.45 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 376207 <.0001

Comparison m MHC-I for Prostate and Arthriti

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Arthriti 10 241.19 433.06 624.94 184.49 268.22 489.67 84 .819 MHCI Prostate 10 0 1451 0.3769 0.6087 0.2229 0.3241 0.5916 0. 1025 MHCI Diff (1-2) 254.49 432.69 610.88 143.31 189.56 280.47 84 .819

T-TestS

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 5.10 < .0001

MHCI Satterthwaite Unequal 9 5.10 0 .0006

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 685104 <.0001

Comparison in MHC-I for Prostate and Aortic 103

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122.84 178.59 326.04 56.475

MHCI Prostate 10 0.1451 0.3759 0.6087 0.2229 0.3241 0.5915 0.1025

MHCI Diff (1-2) 197.49 316.14 434.79 95.421 126.28 186.75 56.475 T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 5.S0 < 0001 MHCI Satterthwaite Unequal 9 5 60 0.0003

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F MHCI Folded F 9 9 303731 <.0001

Comparison m MHC-I for Prostate and Parkmso 104

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Parkmso 10 73.5S8 75.278 76 .998 1 .6536 2.4041 4.389 0 .7603

MHCI Prostate 10 0.14S1 0.3769 0. 6087 0 .2229 0.3241 0.5916 0 .1025

MHCI Diff (1-2) 73.29 74.901 76 .513 1 .2961 1.7154 2.5367 0 .7671

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 97. .64 < .0001

MHCI Satterthwaite Unequal 9 .33 97 .64 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 55.04 <.0001

Comparison in MHC-I for Prostati and Arthnti 105

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Arthπti 10 241.19 433.06 624.94 184 .49 268 .22 489.67 84. 819

MHCI Prostati 10 326.17 468.36 610.54 136, .71 198 .76 362.86 62. 853

MHCI Diff (1-2) -257.1 -35.29 186.5 178. .37 236 .06 349.09 105 .57

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -0 .33 0.7420

MHCI Satterthwaite Unequal 16.6 -0. .33 0.7423

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F MHCI Folded F 9 9 1.82 0.3852

Comparison in MHC-I for Prostati and Aortic 1

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std : Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122 .84 178 .59 326.04 56.475

MHCI Prostati 10 326.17 468.36 610.54 136 .71 198 .76 362.86 62.853

MHCI Diff (1-2) -329.4 -151.8 2S.686 142 .77 188 .94 279.41 84.498 T-Tests

Variable Method Variances DF t Value Pr > ]t|

MHCI Pooled Equal 18 -1 80 0.0891 MHCI Satterthwaite Unequal 17.8 -1.80 0.0893

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 1.24 0 7551

Comparison in MHC-I for Prostati and Parkmso 107

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MHCI Parkmso 10 73.558 75.278 76.998 1.6536 2.4041 4.389 0.7603

MHCI Prostati 10 326.17 468.36 610.54 136.71 198.76 362.86 62.853

MHCI Diff (1-2) -525.1 -393.1 -261 106.2 140.55 207.85 62.858

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 -6.25 ■c.OOOl MHCI Satterthwaite Unequal 9 -6.25 0.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 6834.95 <.0001

Comparison m MHC-I for Arthriti and Aortic 108

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122.84 178.59 326.04 56.475

MHCI Arthriti 10 241.19 433.06 624.94 184.49 268.22 489.67 84.819

MHCI Dlff (1-2) -330.6 -116.5 97.538 172.17 227.86 336.96 101.9

T-Tests

Variable Method Variances DF t Value Pr >

MHCI Pooled Equal 18 -1.14 0.2677 MHCI Satterthwaite Unequal 15.7 -1.14 0.2699

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 2.26 0.2414

Comparison m MHC-I for Arthriti and Parkmso 109

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Arthriti 10 241 .19 433.06 624.94 184.49 268 .22 489.67 84 .819

MHCI Parkmso 10 73.558 75.278 76.998 1.6536 2.4041 4.389 0. 7603

MHCI Dlff (1-2) 179. .58 357.79 535.99 143.32 189. .67 280.49 84 .822 T-Tests

Variable Method Variances DF t Value Pr > |t]

MHCI Pooled Equal 18 4.22 0.0005 MHCI Satterthwaite Unequal 9 4.22 0.0022

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 12447.0 <.0001

Comparison in MHC-I for Aortic and Parkinso

The TTEST Procedure Statistics

Lower CIi Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MHCI Aortic 10 188.76 316.52 444.27 122.84 178.59 326.04 56.475 MHCI Parkinso 10 73.558 75.278 76.998 1.653S 2.4041 4.389 0.7603 MHCI Diff (1-2) 122.58 241.24 359.9 95.429 126.29 186.77 56.48

T-Tests

Variable Method Variances DF t Value Pr > |t|

MHCI Pooled Equal 18 4.27 0.0005 MHCI Satterthwaite Unequal 9 4.27 0.0021

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MHCI Folded F 9 9 5518.21 <.0001

Comparison in Macrophage scavenger receptor for Cstitis and Kidston 111

The TTEST Procedure Statistics

Lower CB Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Cstitis 10 75.537 158.91 242.27 80 .161 116.54 212.76 36 .854 MaSR KidSton 10 33.431 38.401 43.371 4.7787 6.9475 12.683 2.197 MaSR Diff (1-2) 42.941 120.51 198.07 62.379 82.554 122.08 36.919

T-Tests

Variable Method Variances DF t Value Pr > |t)

MaSR Pooled Equal 18 3.26 0.0043 MaSR Satterthwaite Unequal 9.06 3.26 0.0097

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 281.39 <.0001

Comparison in Macrophage scavenger receptor for Cstitis and Endoaden 112

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Cstitis 10 75 .537 158.91 242.27 80.161 116 .54 212 .76 36.854

MaSR Endoaden 10 28 .238 41.541 S4.844 12.791 18. 596 33. 949 5.8806

MaSR Diff (1-2) 38 .959 117.37 195.77 63.056 83 .45 123 .41 37.32 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 3.14 0. 0056

MaSR Satterthwaite Unequal 9.46 3.14 0. 0111

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 39 28 <.0001

Comparison in Macrophage scavenger receptor for Cstitis and Prostate 113

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MaSR Cstitis 10 75.537 158.91 242.27 80.161 116.54 212.76 36.854

MaSR Prostate 9 10.896 12.9 14.905 1.7614 2.6077 4.9957 0.8692

MaSR Diff (1-2) 63.786 146.01 228.23 63.644 84.81S 127.15 38.97

T-Tests

Variable Method Variances DF t Value Pr > ]t|

MaSR Pooled Equal 17 3.75 0 0016 MaSR Satterthwaite Unequal 9.01 3.96 0.0033

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 1997.33 <.0001

Comparison m Macrophage scavenger receptor for Cstitis and Prostati 114

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Cstitis 10 75.537 158.91 242 .27 80 .161 116 .54 212.76 36 .854

MaSR Prostati 10 18.653 25.425 32. 197 6. 5113 9.4664 17.282 2. 9935

MaSR Diff (1-2) 55.8 133.48 211 .16 62 .473 82. 679 122.27 36 .975

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 3.61 0 .0020

MaSR Satterthwaite Unequal 9 .12 3.61 0 .0055

Equality of Variances

Variable Method Mum DF Den DF F Value Pr > F

MaSR Folded F 9 9 151.56 <.0001

Comparison in Macrophage scavenger receptor for Cstitis and Arthriti 115

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Arthriti 10 159.38 215.19 271 53 .663 78. .018 142 .43 24. 671

MaSR Cstitis 10 75.537 158.91 242.27 80 .161 116.54 212 .76 36. 854

MaSR Diff (1-2) -36.89 56.28 149.45 74. .933 99. .168 146. .65 44. 349 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 1.27 0.2206

MaSR Satterthwaxte Unequal 15.7 1.27 0.2229

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 2 23 0.2476

Comparison in Macrophage scavenger receptor for Cstitis and Aortic HS

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15.332 26.638 37.944 10.871 15 805 28.854 4.998

MaSR Cstitis 10 75.537 158.91 242.27 80.161 116.54 212.76 35.854

MaSR Dlff (1-2) -210.4 -132.3 -54.13 62.838 83.162 122.98 37.191

T-Tests

Variable Method Variances t Value Pr > |t|

MaSR Pooled Equal 18 -3.56 0.0023 MaSR Satterthwaite Unequal 9.33 -3.56 0.0058

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 54 37 <.0001

Comparison in Macrophage scavenger receptor for Cstitis and Parkmso 117

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Cstitis 10 75.537 158.91 242.27 80. .161 116.54 212.76 36 .854

MaSR Parkmso 10 19.551 20.936 22.321 1.3314 1.9357 3.5339 0. 6121

MaSR Diff (1-2) 60 533 137.97 215.41 62, .277 82. .419 121.88 36 .859

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 3.74 0.0015

MaSR Satterthwaite Unequal 9 3.74 0.0046

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 3624.78 <.0001

Comparison m Macrophage scavenger receptor for KidSton and Endoaden 118

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MaSR Endoaden 10 28.238 41.541 54 .844 12. .791 18 .596 33 .949 5.8806

MaSR KidSton 10 33.431 38.401 43 .371 4.7787 6. 9475 12 .683 2.197

MaSR Dlff (1-2) -10.05 3.1398 16 .329 10. .607 14 .037 20 .758 6.2776 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 0.50 0 .6230 MaSR Satterthwaite Unequal 11.5 0.50 0.6264

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

MaSR Folded F 9 9 7.16 0.0072

Comparison in Macrophage scavenger receptor for KidSton and Prostate 119

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MaSR KidSton 10 33 .431 38.401 43.371 4.7787 6.9475 12.683 2.197

MaSR Prostate 9 10 .896 12.9 14.905 1.7614 2.6077 4.9957 0.8692

MaSR Diff (1-2) 20 .302 25.5 30.699 4.0237 5.3622 8.0387 2.4638

T-Tests

Variable Method Variances t Value Pr > |t|

MaSR Pooled Equal 17 10.35 <.0001 MaSR Satterthwaite Unequal 11.7 10.79 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 7.10 0.0111

Comparison in Macrophage scavenger receptor for KidSton and Prostati

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR KidSton 10 33 .431 38 .401 43 .371 4.7787 6. 9475 12.683 2.197

MaSR Prostati 10 18. .653 25 .425 32 .197 6.5113 9. 4664 17.282 2.9935

MaSR Diff (1-2) 5. .175 12 .976 20 .777 6.2739 8 .303 12.279 3.7132

T-Tests

Variable Method Variances DF t Value Pr > It=I

MaSR Pooled Equal 18 3.49 0.0026

MaSR Satterthwaite Unequal 16.5 3.49 0.0029

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 1.86 0.3703

Comparison in Macrophage scavenger receptor for KidSton and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Arthriti 10 159 .38 215 .19 271 53.663 78.018 142.43 24.671

MaSR KidSton 10 33. 431 38. 401 43. 371 4.7787 6.9475 12.683 2.197

MaSR Diff (1-2) 124 .75 176 .79 228 .82 41.85 55.385 81.905 24.769 T-Tests

Variable Method Variances DF t Value Pr > ]t|

MaSR Pooled Equal 18 7 14 < 0001

MaSR Satterthwaite Unequal 9.14 7.14 <-0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 126 10 < 0001

Comparison in Macrophage scavenger receptor for KidSton and Aortic 122

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15. 332 26. 638 37 944 10.871 15 805 28.854 4.998

MaSR KidSton 10 33. 431 38 401 43 371 4.7787 6 9475 12.683 2.197

MaSR Diff (1-2) -23 23 -11 .76 -0.293 9.2245 12.208 18.053 5.4596

T-Tests

Variable Method Variances t Value Pr > |t|

MaSR Pooled Equal 18 -2.15 0.0450 MaSR Satterthwaite Unequal 12.4 -2.15 0.0516

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 5 18 0.0224

Comparison m Macrophage scavenger receptor for KidSton and Parkmso 123

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Ston 10 33 431 38 .401 43 371 4 .7787 6.9475 12.683 2.197 MaSR kmso 10 19 551 20 .936 22 321 1 .3314 1.9357 3.5339 0 .6121 MaSR f (1-2) 12 .673 17 .465 22 .256 3 .8534 5.0997 7.5416 2 .2807

T-Tests

Variable Method Variances DF t Value Pr > It|

MaSR Pooled Equal 18 7.66 < .0001

MaSR Satterthwaite Unequal 10.4 7 66 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 12.88 0 0008

Comparison in Macrophage scavenger receptor for Endoaden and Prostate 124

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Endoaden 10 28. 238 41.541 54 .844 12 .791 18.596 33 .949 S .8806

MaSR Prostate 9 10. 896 12 9 14 .905 1. 7614 2.6077 4. 9957 0 .8692

MaSR Diff (1-2) 15 .41 28.64 41 .871 10 242 13.648 20 .461 6.271 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 17 4.57 0.0003

MaSR Satterthwaite Unequal 9.39 4.82 o.oooa

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 50.85 c.OOOl

Comparison in Macrophage scavenger receptor for Endoaden and Prostati 125

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

MaSR Endoaden 10 28 .238 41 .541 54.844 12.791 18.596 33.949 5.8806 MaSR Prostati 10 18 .653 25.425 32.197 6.5113 9.4664 17.282 2.9935 MaSR Diff (1-2) 2. 2527 16 . HS 29.979 11.149 14.755 21.82 6.5987

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 2 44 0.0251 MaSR Satterthwaite Unequal 13.4 2.44 0.0292

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 3.86 0.0569

Comparison m Macrophage scavenger receptor for Endoaden and Arthπti 126

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR hriti 10 159.38 215.19 271 53 .663 78 .018 142.43 24 .671 MaSR oaden 10 28.238 41.541 54. 844 12 .791 18 .596 33.949 5. 8806 MaSR f (1-2) 120.36 173.65 226 .93 42 .852 56 .712 83.867 25 .362

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 6 85 < .0001

MaSR Satterthwaite Unequal 10 6.85 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 17.60 0.0002

Comparison in Macrophage scavenger receptor for Endoaden and Aortic 127

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15.332 26.638 37 .944 10.871 15 .805 28. 854 4.998 MaSR Endoaden 10 28.238 41.541 54 .844 12.791 18 .596 33. 949 5 .8806 MaSR Diff (1-2) -31.12 -14.9 1. 3115 13.04 17 .257 25 .52 7 .7176 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 -1 93 0 0694

MaSR Satterthwaite Unequal 17 5 -1.93 0 0S98

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 1.38 0 6359

Comparison in Macrophage scavenger receptor for Endoaden and Parkmso 128

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Endoaden 10 28 238 41 .541 54.844 12.791 18.596 33.949 5. 8806

MaSR Parkmso 10 19 551 20 .936 22.321 1.3314 1 9357 3 5339 0 6121

MaSR Diff (1-2) 8.1833 20 .605 33.026 9.9895 13.22 19.551 5. 9124

T-Tests

Variable Method Variances DP t Value Pr > |t|

MaSR Pooled Equal 18 3.49 0 0026

MaSR Satterthwaite Unequal 9.2 3.49 0 0067

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 92 29 <.0001

Comparison m Macrophage scavenger receptor for Prostate and Prostati 129

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Prostate 9 10.896 12 9 14.905 1 7614 2 6077 4.9957 0.8692

MaSR Prostati 10 18 653 25.425 32 197 6.5113 9.4664 17.282 2.9935

MaSR Diff (1-2) -19 42 -12.52 -5.626 5.34 7.1163 10 668 3.2697

T-Tests

Variable Method Variances t Value Pr > |t|

MaSR Pooled Equal 17 -3.83 0.0013 MaSR Satterthwaite Unequal 10.5 -4.02 0.0022

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 13.18 0.0013

Comparison m Macrophage scavenger receptor for Prostate and Arthriti 130

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Arthriti 10 159 .38 215. 19 271 53 .663 78 .018 142.43 24.671

MaSR Prostate 9 10. 896 12 .9 14. 905 1. 7614 2. 6077 4.9957 0.8692

MaSR Diff (1-2) 147 .23 202. 29 257 .34 42 .618 56 .794 85.143 26.095 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 17 7.75 < oooi

MaSR Ξatterthwaite Unequal 9.02 8.19 <-0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 895.10 <.0001

Comparison in Macrophage scavenger receptor for Prostate and Aortic 131

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR tic 10 15 .332 26 .638 37. 944 10 .871 15 .805 28.854 4.998 MaSR state 9 10 .89S 12.9 14. 90S 1. 7614 2. 5077 4.9957 0 .8692 MaSR f (1-2) 2.4S57 13 .738 25 .02 8. 7331 11 .638 17.447 5 .3474

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 17 2.57 0 .0199

MaSR Satterthwaite Unequal 9 .54 2.71 0 .0229

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 8 36.73 <.0001

Comparison m Macrophage scavenger receptor for Prostate and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Parkmso 10 19.551 20.936 22. 321 1 .3314 1.9357 3.5339 0. .6121

MaSR Prostate 9 10.896 12.9 14. 905 1 .7614 2.6077 4.9957 0, .8692

MaSR Diff (1-2) 5.8285 8.0356 10. 243 1 .7085 2.2768 3.4132 1. .0461

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 17 7.68 <.oooi

MaSR Satterthwaite Unequal 14.7 7.56 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F MaSR Folded F 8 9 1.81 0.3927 Comparison m Macrophage scavenger receptor for Prostati and Arthπti 133

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Arthriti 10 159.38 215.19 271 53.663 78.018 142.43 24.671

MaSR Prostati 10 18.653 25.425 32.197 6.5113 9.4664 17.282 2.9935

MaSR Diff (1-2) 137.55 189.76 241.97 41.99 55.571 82.18 24.852 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 7 64 ■=.0001 MaSR Satterthwaite Unequal 9.26 7.64 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 67.92 <.0001

Comparison m Macrophage scavenger receptor for Prostati and Aortic 134

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15. 332 26 .638 37. 944 10 .871 15 .805 28.854 4 .998

MaSR Prostati 10 18. 653 25 .425 32. 197 6. 5113 9. 4664 17.282 2. 9935

MaSR Diff (1-2) -11 .03 1. 2134 13. 453 9. 8435 13 .027 19.265 5. 8259

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 0.21 0 .8374

MaSR Satterthwaite Unequal 14.7 0.21 0 .8379

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 2.79 0.1427

Comparison in Macrophage scavenger receptor for Prostati and Parkmso 135

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Parkmso 10 19.551 20.936 22.321 1.3314 1.9357 3.5339 0.6121 MaSR Prostati 10 18.653 25.425 32.197 6.5113 9.4664 17.282 2.9935 MaSR Diff (1-2) -10.91 -4.489 1.9306 5.1625 6.8323 10.104 3.0555

T-Tests

Variable Method Variances t Value Pr > |t|

MaSR Pooled Equal 18 -1.47 0.1591

MaSR Satterthwaite Unequal 9.75 -1.47 0.1733

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 23.92 <.0001

Comparison in Macrophage scavenger receptor for Arthnti and Aortic 136

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15.332 26.638 37.944 10 .871 15 .805 28. 854 4 .998 MaSR Arthnti 10 159.38 215 .19 271 53 .663 78 .018 142 .43 24 .671 MaSR Diff (1-2) -241.4 -188.5 -135.7 42 .531 56 .287 83. 239 25 .172 T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 -7.49 <.0001 MaSR Satterthwaite Unequal 9.74 -7.49 <.O001

Equality of Variances

Variable Method Nutn DF Den DF F Value Pr > F

MaSR Folded F 9 9 24.37 <-0001

Comparison in Macrophage scavenger receptor for Arthriti and Parkinso 137

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Arthriti 10 159.38 215.19 271 53.663 78 .018 142.43 24.671

MaSR Parkinso 10 19.551 20.935 22.321 1.3314 1. 9357 3.5339 0.6121

MaSR Diff (1-2) 142.4 194.25 246.1 41.697 55 .184 81.607 24.679

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 7.87 <.0001

MaSR Satterthwaite Unequal 9 .01 7.87 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 1624.44 <.0001

Comparison in Macrophage scavenger receptor for Aortic and Parkinso 138

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

MaSR Aortic 10 15.332 26 .638 37 .944 10.871 15 .805 28.854 4.998

MaSR Parkinso 10 19.551 20 .936 22 .321 1.3314 1. 9357 3.5339 0.6121

MaSR Diff (1-2) -4.877 5. 7021 16 .281 8.5077 11 .259 16.651 5.0353

T-Tests

Variable Method Variances DF t Value Pr > |t|

MaSR Pooled Equal 18 1.13 0.2723

MaSR Satterthwaite Unequal 9 .27 1.13 0.2859

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

MaSR Folded F 9 9 66.67 <.0001

Comparison in Cystatin A for Cstitis and KidSton 139

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Cstitis 10 5.736 8 .6302 11.524 2 .7829 4 .0458 7.3861 1.2794

CysA KidSton 10 2 .6438 3 .9607 5.2776 1 .2663 1 .8409 3.3608 0.5822

CysA Diff (1-2) 1 .7164 4 .6595 7.6226 2 .3749 3 .1431 4.648 1.4056 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 3.32 0. 0038 CysA Satterthwaite Unequal 12.6 3.32 0. O0S7

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

CysA Folded F 9 9 4.83 0.0281

Comparison in Cystatin A for Cstitis and Endoaden 140

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Cstitis 10 5.736 8.6302 11.524 2.7829 4.0458 7.3861 1.2794

CysA Endoaden 10 14.96 21.584 28.208 6.3694 9.26 16.905 2.9283

CysA Diff (1-2) -19.67 -12.95 -6.24 5.3992 7.1455 10.567 3.1956

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -4.05 0.0007 CysA Satterthwaite Unequal 12.3 -4.05 0.0015

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 5.24 0.0215

Comparison in Cystatin A for Cstitis and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean std Dev Std Dev Std Dev Std Err

CysA Cstitis 10 5.736 8.6302 11.524 2.7829 4.0458 7.3861 1.2794

CysA Prostate 10 0.6945 4.4912 8.2879 3.6506 5.3074 9.6892 1.6783

CysA Diff (1-2) -0.295 4.139 8.5727 3.5657 4.7189 6.9785 2.1104

T-Tests

Variable Method Variances t Value Pr > )t|

CysA Pooled Equal 18 1.96 0.0655 CysA Satterthwaite Unequal 16.8 1.96 0.0666

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 1.72 0.4311

Comparison in Cystatin A for Cstitis and Prostati 142

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Cstitis 10 5. 736 8.6302 11.524 2 .7829 4 .0458 7.3861 1.2794

CysA Prostati 10 23. 504 25.468 27.431 1 .8876 2 .7442 5.0099 0.8678

CysA Diff (1-2) -20 .09 -16.84 -13.59 2.612 3 .4568 5.1121 1.5459 T-Tests

Variable Method Variances DF t Value Pr > ItI

CysA Pooled Equal 18 -10 89 < 0001 CysA Satterthwaite Unequal 15.8 -10 89 < 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

CysA Folded F 9 9 2 17 0 2630

Comparison m Cystatm A for Ostitis and Arthriti 143

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Arthriti 10 5 276 8 7172 12. 158 3 .3089 4.8105 8.7821 1 5212 CysA Ostitis 10 5 .736 8 6302 11. 524 2 7829 4.0458 7.3861 1 .2794 CysA Diff (1-2) -4. .089 0 087 4. 263 3 .3584 4.4446 6.5729 1 .9877

T-TestS

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 0. .04 0 9656 CysA Satterthwaite Unequal 17.5 0 .04 0 .9656

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 1.41 0 6143

Comparison in Cystatm A for Ostitis and Aortic 144

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Aortic 10 20 996 22 334 23 .672 1. 2866 1.8705 3 4147 0.5915 CysA Ostitis 10 5 736 8.6302 11 524 2.7829 4.0458 7.3861 1 2794 CysA Diff (1-2) 10.743 13 704 16 665 2.3815 3.1518 4.6609 1.4095

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 ( 3.72 < 0001 CysA Satterthwaite Unequal 12.7 3.72 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 4.68 0.0311

Comparison m Cystatm A for Cstitis and Parkmso 145

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Ostitis 10 5.736 8.6302 11 .524 2 .7829 4 .0458 7 .3861 1 .2794 CysA Parkinso 10 3 2408 3.4433 3. 6458 0 .1947 0 .2831 0 .5168 0 .0895 CysA Diff (1-2) 2.4924 5.18S9 7. 8814 2.167 2 .8678 4.241 1 .2825 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 4.04 0.0008 CysA Satterthwaite Unequal 9.09 4.04 0.0029

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

CysA Folded F 9 9 204.28 <.0001

Comparison in Cystatin A for KidSton and Endoaden 146

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Endoaden 10 14.96 21.584 28.208 6.3694 9.26 16.905 2.9283

CysA KidSton 10 2.6438 3.9S07 5.2776 1.2663 1.8409 3.3608 0.5822

CysA Diff (1-2) 11.351 17.623 23.896 5.0444 6.676 9.8726 2.9856

T-Tesfcs

Variable Method Variances t Value |t|

CysA Pooled Equal 18 5.90 <.0001 CysA Satterthwaite Unequal 9.71 5.90 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 25.30 <.0001

Comparison in Cystatin A for KidSton and Prostate 147

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA KidSton 10 2.6438 3. 9607 5.2776 1.2663 1.8409 3.3608 0.5822

CysA Prostate 10 0.6945 4. 4912 8.2879 3.6506 5.3074 9.6892 1.6783

CysA Diff (1-2) -4.263 -0 .531 3.2016 3.0015 3.9722 5.8742 1.7764

T-Tests

Variable Method Variances t Value Pr > |t|

CysA Pooled Equal 18 -0.30 0.7686 CysA Satterthwaite Unequal 11.1 -0.30 0.7707

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 8.31 0.0042

Comparison in Cystatin A for KidSton and Prostati 148

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA. KidSton 10 2.6438 3.9607 5.2776 1 .2663 1 .8409 3 .3508 0.5822 CysA Prostati 10 23.504 25.468 27.431 1 .8876 2 .7442 5 .0099 0.8678 CysA Diff (1-2) -23.7 -21.51 -19.31 1 .7656 2 .3366 3 .4555 1.045 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -20.58 <.0001 CysA Satterthwaite Unequal 15.7 -20.58 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 2.22 0.2500

Comparison in Cystatm A for KidSton and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Arthriti 10 5.276 8 .7172 12.158 3.3089 4.810Ξ 8.7821 1.5212

CysA KidSton 10 2 .6438 3 .9507 5.2776 1.2663 1.8409 3.3608 0.5822

CysA Diff (1-2) 1 .3345 4 .7565 8.1785 2.752 3.6421 5.3861 1.6288

T-Tests

Variable Method Variances t Value Pr > |t]

CysA Pooled Equal 18 2.92 0.0091 CysA Satterthwaite Unequal 11.6 2.92 0.0133

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 S .83 0.0086

Comparison in Cystatm A for KidSton and Aortic 150

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Aortic 10 20.996 22 .334 23 .672 1 .2866 1. 8705 3.4147 0 .5915 CysA KidSton 10 2 6438 3. 9607 5. 2776 1 .2663 1. 8409 3.3608 0 .5822 CysA Diff (1-2) 16.63 18 .373 20 .117 1 .4022 1. 8558 2.7443 0 .8299

T-Tests

Variable Method Variances DF t Value Pr » |t|

CysA Pooled Equal 18 22.14 < 0001 CysA Satterthwaite Unequal 18 22.14 _< .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 1.03 0.9630

Comparison in Cystatm A for KidSton and Parkmso 151

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA KidSton 10 2 .6438 3 .9607 5 .2776 1 .2663 1 .8409 3.3608 0.5822

CysA Parkinso 10 3 .2408 3 .4433 3 .6458 0 .1947 0 .2831 0.5168 0.0895

CysA Diff (1-2) -0.72 0 .5174 1 .7548 0 .9952 1.317 1.9477 0.589 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 0.3913 CysA Satterthwaite Unequal 9.43 0.4015

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 42.30 <.0001

Comparison in Cystatin A for Endoaden and Prostate 152

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Endoaden 10 14.96 21 .584 28 .208 6 .3694 9.26 16.905 2 .9283 CysA Prostate 10 0.6945 4. 4912 8. 2879 3 .6506 5. 3074 9.6892 1 .6783 CysA Diff (1-2) 10.002 17 .093 24 .184 5 .7026 7 .547 11.161 3 .3751

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 5.06 < .0001 CysA Satterthwaite Unequal 14.3 5.06 0 .0002

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

CysA Folded F 9 9 3.04 0.1127

Comparison in Cystatin A for Endoaden and Prostati 153

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Endoaden 10 14.96 21 .584 28.208 6.3694 9.26 16.905 2.9283

CysA Prostati 10 23.504 25 .468 27.431 1.8876 2.7442 5.0099 0.8678

CysA Diff (1-2) -10.3 -3 .884 2.5327 5.1603 6.8293 10.099 3.0542

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -1.27 0.2197 CysA Satterthwaite Unequal 10.6 -1.27 0.2308

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 11.39 0.0013

Comparison in Cystatin A for Endoaden and Arthriti 154

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Arthriti 10 5.276 8.7172 12 .158 3 .3089 4 .8105 8. 7821 1.5212 CysA Endoaden 10 14.96 21.584 28 .208 6 .3694 9.26 16 .905 2.9283 CysA Diff (1-2) -19.8 -12.87 -5 .934 5 .5754 7 .3787 10 .912 3.2998 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -3 90 0.0011 CysA Satterthwaxte Unequal 13.5 -3.90 0.0017

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 3.71 0 0643

Comparison in Cystatm A for Endoaden and Aortic 155

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

CysA Aortic 10 20.99β 22.334 23.672 1.2866 1.8705 3.4147 0.5915

CysA Endoaden 10 14.96 21.584 28.208 6.3694 9.26 16.905 2.9283

CysA Diff (1-2) -5.526 0.7503 7 0266 5.0475 6.6801 9.8786 2.9874

T-Tests

Variable Method Variances t Value Pr > |t|

CysA Pooled Equal 18 0.25 0.8045 CysA Satterthwaite Unequal 9.73 0.25 0.8069

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 24.51 <.0001

Comparison m Cystatm A for Endoaden and Parkmso 156

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Endoaden 10 14.96 21.584 28.208 6.3694 9.26 16.905 2.9283 CysA Parkmso 10 3.2408 3.4433 3.6458 0.1947 0.2831 0.5168 0.0895 CysA Diff (1-2) 11.986 18.141 24.295 4.9499 6.5509 9.6876 2.9296

T-Tests

Variable Method Variances t Value Pr > |t|

CysA Pooled Equal 18 6.19 <.0001 CysA Satterthwaite Unequal 9.02 6.19 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 1070.13 <.0001

Comparison m Cystatm A for Prostate and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Prostate 10 0.6945 4.4912 8.2879 3 .6506 5 .3074 9 .6892 1 .6783 CysA Prostati 10 23.504 25.468 27.431 1 .8876 2 .7442 5 .0099 0 .8678 CysA Diff (1-2) -24.95 -20.98 -17.01 3 .1924 4 .2249 6 .2478 1 .8894 T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -11 10 0001 CysA Satterthwaite Unequal 13.5 -11 10 < 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

CysA Folded F 9 9 3 74 0 0625

Comparison m Cystatm A for Prostate and Arthriti 158

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

CysA Arthriti 10 5 276 8.7172 12.158 3.3089 4.8105 8 7821 1.5212

CysA Prostate 10 0 6945 4.4912 8 2879 3.6506 5.3074 9.6892 1 6783

CysA Diff (1-2) -0 533 4.226 8.9849 3.8272 5.065 7.4903 2.2652

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 1 87 0 0785 CysA Satterthwaite Unequal 17.8 1.87 0.0786

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 1 22 0 7744

Comparison in Cystatm A for Prostate and Aortic 159

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Aortic 10 20 .996 22.334 23.672 1 2866 1.8705 3.4147 0.5915 CysA Prostate 10 0 6945 4.4912 8 2879 3.6506 5 3074 9 6892 1.6783 CysA Diff (1-2) 14 104 17.843 21.582 3.0067 3.9791 5 8844 1.7795

T-Tests

Variable Method Variances DF t Value |t|

CysA Pooled Equal 18 10 03 <.0001 CysA Satterthwaite Unequal 11.2 10.03 ■=.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 8 05 0 0047

Comparison m Cystatm A for Prostate and Parkmso 160

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Parkmso 10 3. 2408 3. 4433 3.6458 0 .1947 0 .2831 0 .5168 0 .0895

CysA Prostate 10 0. 6945 4. 4912 8.2879 3 .6506 5 .3074 9 .6892 1 .6783

CysA Diff (1-2) -4 579 .048 2.4832 2 .8397 3 .7582 5 .5577 1 .6807 T-Tests

Variable Method Variances DF t Value Pr > It]

CysA Pooled Equal 18 -0.S2 0 .5408 CysA Satterthwaite Unequal 9.05 -0 62 0.5484

Equality of Variances

Variable Method Num DP Den DP F Value Pr > p

CysA Folded F 9 9 351.54 < 0001

Comparison in Cystatm A for Prostati and Arthriti 161

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Arthriti 10 5.276 8.7172 12.158 3.3089 4.8105 8.7821 1.5212

CysA Prostati 10 23.504 25.468 27.431 1.8876 2.7442 5.0099 0 8678

CysA Diff (1-2) -20.43 -16.75 -13.07 2.9591 3.9161 5.7913 1.7513

T-Tests

Variable Method Variances t Value Pr > |t|

CysA Pooled Equal 18 -9.56 <.0001 CysA Satterthwaite Unequal 14.3 -9.56 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 3.07 0.1099

Comparison m Cystatm A for Prostata, and Aortic 162

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Aortic 10 20. .996 22.334 23 .672 1 .2866 1.8705 3.4147 0. 5915 CysA Prostati 10 23. ,504 25.468 27 .431 1 .8876 2.7442 5.0099 0. 8678 CysA Diff (1-2) -5.34 -3.134 -0 .927 1 .7744 2 3483 3.4728 1. 0502

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 -2.98 0 .0080 CysA Satterthwaite Unequal 15.9 -2.98 0 .0088

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 2.15 0.2689

Comparison in Cystatm A for Prostati and Parkmso 163

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Parkmso 10 3.2408 3.4433 3.6458 0 .1947 0 .2831 0.5168 0.0895

CysA Prostati 10 23.504 25.468 27.431 1 .8876 2 .7442 5.0099 0.8678

CysA Diff (1-2) -23.86 -22.02 -20.19 1.474 1 .9508 2.8848 0.8724 T-Tests

Variable Method Variances DF t Value Pr > |t]

CysA Pooled Equal 18 -25.25 < 0001 CysA Satterthwaite Unequal 9.19 -25.25 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 93.98 <.0001

Comparison m Cystatm A for Arthriti and Aortic 1S4

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Aortic 10 20 .996 22 .334 23 .672 1 .2866 1 .8705 3.4147 0.5915 CysA Arthriti 10 S .276 8. 7172 12 .158 3 .3089 4 .8105 8.7821 1.5212 CysA Diff (1-2) 10 .188 13 .617 17 .046 2 .7577 3 .6496 5.3972 1.6322

T-Tests

Variable Method Variances DF t Value Pr |t|

CysA Pooled Equal 18 3.34 < 0001 CysA Satterthwaite Unequal 11.7 8.34 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

CysA Folded F 9 9 6.61 0.0096

Comparison in Cystatm A for Arthriti and Parkmso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

CysA Arthriti 10 5.276 8 .7172 12.158 3.3089 4.8105 8.7821 1.5212

CysA Parkmso 10 3 .2408 3 .4433 3.6458 0.1947 0.2831 0.5168 0.0895

CysA Diff (1-2) 2 .0724 5 .2739 8.4754 2.5747 3.4074 5.039 1.5239

T-Tests

Variable Method Variances DF t Value Pr > |t|

CysA Pooled Equal 18 3.46 0.0028 CysA Satterthwaite Unequal 9.06 3.46 0.0071

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

CysA Folded F 9 9 288.80 <.0001

Comparison in Cystatm A for Aortic and Parkmso 166

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

CysA Aortic 10 20 .996 22.334 23 .672 1 .2866 1 .8705 3.4147 0.5915

CysA Parkinso 10 3. 2408 3.4433 3. 6458 0 .1947 0 .2831 0.5168 0.0895

CysA Diff (1-2) 17 .634 18.891 20 .148 1 .0108 1 .3377 1.9782 0.5982 T-Tests

Variable Method Variances DP t Value Pr > t|

CysA Pooled Equal 18 31.58 < .0001 CysA Unequal 9 .41 31.58 < .0001

Equality of Variances

Variable Method Mum DF Den DF F Value Pr > F

CysA Folded F 9 9 43.66 <.0001

Comparison in Kallikrem 6 for Cstitis and KidSton 167

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Cstitis 10 0. .9327 1 .6453 2.3599 0 .6862 0.997S 1.8212 0 .3155

KaI6 KidSton 10 0. .0927 0 .2052 0.3177 0 .1081 0.1572 0.287 0 .0497

Kale Diff (1-2) 0, .7701 1 .4411 2.1121 0 .5396 0.7141 1.056 0 .3194

T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 4.51 0 .0003

Kal6 Satterthwaite Unequal 9 .45 4.51 0 .0013

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 40.26 <.0001

Comparison in Kallikrem 6 for Cstitis and Endoaden 168

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Cstitis 10 0.9327 1.6463 2.3599 0.6862 0.9976 1.8212 0.3155

KaI6 Endoaden 10 1.0732 1.7948 2.5164 0.6938 1.0087 1.8415 0.319

Kal6 Diff (1-2) -1.091 -0.148 0.794 0.758 1.0032 1.4835 0.4486

T-Tests

Variable Method Variances DF t Value Pr > ]t|

Kal6 Pooled Equal 18 -0.33 0.7445 Kal6 Satterthwaite Unequal 18 -0.33 0.7445

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

KaIS Folded F 9 9 1.02 0.9742

Comparison in Kallikrem 6 for Cstitis and Prostate 169

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Cstitis 10 0 .9327 1 .6463 2 .3599 0 .6862 0 .9976 1.8212 0.3155

Kal6 Prostate 10 0 .1475 0 .2519 0 .3563 0 .1004 0.146 0.2665 0.0462

Kal6 Diff (1-2) 0 .7246 1 .3944 2 .0642 0 .5387 0 .7129 1.0543 0.3188 T-Teεts

Variable Method Variances DF t Value Pr > |t|

Kal6 Pooled Equal 18 4 37 0.0004

KaI6 Satterthwaite Unequal 9.39 4 37 0.0016

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kalδ Folded F 9 9 46 70 < 0001

Comparison in Kallikrem 6 for Ostitis and Prostati 170

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Ostitis 10 0 .9327 1 .6463 2 3599 0 6862 0.9976 1 8212 0. 3155

KaI6 Prostati 10 0 .4791 0 8199 1 1607 0 3277 0.4764 0 8697 0 1507

KaI6 Diff (1-2) 0 .0919 0 8264 1. 5609 0 5907 0.7817 1.156 0 3496

T-Tests

Variable Method Variances DF t Value Pr > |t|

Kal6 Pooled Equal 18 2 36 0 0295

KaI6 Satterthwaite Unequal 12 9 2 36 0 .0345

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 4.38 0.0383

Comparison in Kallikrem 6 for Cstitis and Arthπti 1

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 hriti 10 0 .4739 1. 2S51 2.0563 0 7607 1 106 2.0191 0 .3497 KaI6 ItIS 10 0 .9327 1. 6463 2.3599 0 .6862 0.9976 1.8212 0 .3155 KaI6 f (1-2) - 1 371 -0 .381 0.6083 0 .7958 1.0532 1.5575 0.471

T-Tests

Variable Method Variances DF t Value Pr > It|

KaI6 Pooled Equal 18 -0 81 0 4289

KaI6 Satterthwaite Unequal 17.8 -0 81 0 .4290

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Kal6 Folded F 9 9 1.23 0.7636

Comparison in Kallikrem 6 for Cstitis and Aortic 1

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Aortic 10 -0 .025 0 .0467 0. 1189 0 .0694 0 .1009 0 .1841 0 .0319

Kal6 Cstitis 10 0. 9327 1 .6463 2. 3599 0 .6862 0 .9976 1 .8212 0 .3155

Kal6 Diff (1-2) -2 .266 -1.6 -0 .933 0 .5357 0.709 1 .0485 0 .3171 T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 -5 04 < 0001

Kal6 Satterthwaite U Unneeqquuaall 9 18 -5 04 0 0007

Equality of Variances

Variable Method Num DP Den DP F Value Pr > F

Kal6 Folded F 9 9 97 82 < 0001

Comparison m Kallikrem 6 for Ostitis and Parkmso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Cstitis 10 0 9327 1 6463 2 3599 0 6862 0 9976 1 8212 0 3155

KaI6 Parkmso 10 2 3845 2 602S 2 8207 0 2097 0 3048 0 5565 0 0964

KaI6 Diff (1-2) -1 649 0 956 -0 263 0 5573 0 7376 1 0908 0 3299

T Tests

Variable Method Variances t Value Pr > |t|

KaI6 Pooled Equal 18 -2 90 0 0096

Kal6 Satterthwaite Unequal 10 7 2 90 0 0149

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 10 71 0 0016

Comparison in Kallikrein 6 for Kidston and Endoaden 174

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Endoaden 10 1 0732 1 7948 2 5164 0 6938 1 0087 1 8415 0 319

KaI6 KidSton 10 0 0927 0 2052 0 3177 0 1081 0 1572 0 287 0 0497

KaI6 Diff (1-2) 0 9114 1 5896 2 2678 0 5455 0 7219 1 0675 0 3228

T-Tests

Variable Method Variances t Value Pr > |t|

KaI6 Pooled Equal 18 4 92 0 0001 Kal6 Satterthwaite Unequal 9 44 4 92 0 0007

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P

Kal6 Folded F 9 9 41 16 < 0001

Comparison m Kallikrem 6 for KidSton and Prostate 175

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 KidSton 10 0 0927 0 2052 0 3177 0 1081 0 1572 0 287 0 0497

KaI6 Prostate 10 0 1475 0 2519 0 3563 0 1004 0 146 0 2665 0 0462

KaI6 Diff (1-2) -0 189 -0 047 0 0958 0 1146 0 1S17 0 2243 0 0678 T-Tests

Variable Method Variances DF t Value Pr > ItI

Kal6 pooled Equal 18 -0.69 0.5000

KaIS Satterthwaite Unequal 17.9 -0.69 0.5001

Equality of Variances

Variable Method Num DP Den DP P Value Pr > F

Kal6 Folded P 9 9 1 16 0.8285

Comparison m Kallikrem 6 for KidSton and Prostati 17S

The TTEST Procedure Statistics

Lower CL upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 KidSton 10 0.0927 0. 2052 0.3177 0 .1081 0.1572 0.287 0. 0497

KaI6 Prostati 10 0.4791 0. 8199 1 1607 0 .3277 0.4764 0.8697 0. 1507

KaI6 Diff (1-2) -0.948 -0 .615 -0.281 0 .2681 0.3547 0.5246 0. 15S6

T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 -3.87 0.0011

Kal6 Satterthwaite unequal 10.9 -3.87 0.0026

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 9.18 0.0029

Comparison in Kallikrem 6 for KidSton and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Arthriti 10 0 .4739 1 .2651 2 .0563 0 .7607 1.106 2.0191 0.3497

Kal6 KidSton 10 0 .0927 0 .2052 0 .3177 0 .1081 0 .1572 0.287 0.0497

Kal6 Diff (1-2) 0 .3177 1 .0599 1 .8021 0 .5969 0 .7899 1.1681 0.3533

T-Tests

Variable Method Variances DF t Value Pr > |t|

Kal6 Pooled Equal 18 3.00 0.0077 KaI6 Satterthwaite Unequal 9.36 3 00 0.0143

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 49.48 <.0001

Comparison in Kallikrem 6 for KidSton and Aortic 178

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0.025 0.0467 0.1189 0 .0694 0 .1009 0.1841 0 .0319

KaI6 KidSton 10 0.0927 0.2052 0.3177 0 .1081 0 .1572 0.287 0 .0497

KaI6 Diff (1-2) -0.283 -0.159 -0.034 0 .0998 0 .1321 0.1953 0 .0591 T-Tests

Variable Method Variances DF t Value Pr > 1 t1

KaI6 Pooled Equal 18 -2 68 0.0152 Kal6 Satterthwaite Unequal IS.3 -2.68 0.0168

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded P 9 9 2.43 0.2021

Comparison in Kallikrem 6 for KidSton and Parkinso 179

The TTEST Procedure Statistics

Lower CL Upper CB Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

KaI6 Ston 10 0.0927 0.2052 0.3177 0 1081 0.1572 0.287 0 .0497 Kal6 kmso 10 2.3845 2.6026 2.8207 0 .2097 0.3048 0.5565 0 .0964 KaIS f (1-2) -2.625 -2.397 -2.17 0 .1833 0 2425 0.3587 0 .1085

T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 -22 .10 < .0001

Kal6 Satterthwaite Unequal 13.5 -22 .10 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 3 76 0.0616

Comparison in Kallikrem 6 for Endoaden and Prostate 180

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Endoaden 10 1 .0732 1 .7948 2 .5164 0 .6938 1 .0087 1.8415 0.319

Kal6 Prostate 10 0 .1475 0 .2519 0 .3563 0 .1004 0.146 0.2665 0.0462

Kalδ Diff (1-2) 0 .8658 1 .5429 2.22 0 .5446 0 .7207 1.0658 0.3223

T-Tests

Variable Method Variances t Value Pr |t|

KaI6 Pooled Equal 18 4.79 0.0001 KaI6 Satterthwaite Unequal 9.38 4.79 0.0009

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 47.75 <.0001

Comparison in Kallikrem 6 for Endoaden and Prostati 181

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Endoaden 10 1.0732 1.7948 2.5164 0.6938 1 .0087 1 .8415 0.319

Kal6 Prostati 10 0.4791 0 .8199 1.1607 0.3277 0 .4764 0 .8697 0 .1507

Kal6 Diff (1-2) 0.2338 0.9749 1.716 0.596 0 .7888 1 .1665 0 .3528 T-Tests

Varxable Method Variances DP t Value Pr > ]t|

Kal6 Pooled Equal 18 2 76 0 0128 Kalδ Satterthwaite Unequal 12 8 2 76 0 0163

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 4 48 0 0357

Comparison m Kallikrem 6 for Endoaden and Arthriti 182

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Arthriti 10 0 4739 1 2651 2 0563 0 7607 1 106 2 0191 0 3497

KaI6 Endoaden 10 1 0732 1 7948 2 5164 0 6938 1 0087 1 8415 0 319

KaI6 Diff (1-2) -1 524 -0 53 0 4648 0 7998 1 0585 1 5653 0 4734

T-Tests

Variable Method Variances DF t Value Pr |t|

KaI6 Pooled Equal 18 -1 12 0 2778 Kal6 Satterthwaite Unequal 17 8 -1 12 0 2780

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 1 20 0 7883

Comparison in Kallikrem 6 for Endoaden and Aortic 183

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0 025 0 0467 0 1189 0 0694 0 1009 0 1841 0 0319

KaI6 Endoaden 10 1 0732 1 7948 2 5164 0 6938 1 0087 1 8415 0 319

Kal6 Diff (1-2) -2 422 -1 748 -1 075 0 5416 0 7168 1 06 0 3206

T-Tests

Variable Method Variances t Value Pr > |t|

KaI6 Pooled Equal 18 -5 45 < 0001 KaI6 Satterthwaite Unequal 9 18 -5 45 0 0004

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 100 01 < 0001

Comparison in Kallikrem 6 for Endoaden and Parkinso 184

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Kal6 Endoaden 10 1 0732 1 7948 2 5164 0 6938 1 0087 1 8415 0 319

Kal6 Parkinso 10 2 3845 2 6026 2 8207 0 2097 0 3048 0 5565 0 0964

KaI6 Diff (1-2) -1 508 -0 808 -0 108 0 563 0 7451 1 1019 0 3332 T-Tests

Variable Method Variances DF t Value Pr > |t|

Kal6 Pooled Equal 18 -2.42 0.0261 KaIS Satterthwaite Unequal 10.6 -2.42 0.0345

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 10.95 0.0015

Comparison in Kallikrein 6 for Prostate and Prostati 185

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Prostate 10 0.1475 0. 2519 0.3563 0.1004 0.146 0.2665 0.0462

Kal6 Prostati 10 0.4791 0. 8199 1.1607 0.3277 0.4764 0.8697 0.1507

KaI6 Diff (1-2) -0.899 -0 .568 -0.237 0.2662 0.3523 0.521 0.1576

T-Tests

Variable Method Variances t Value Pr > |t|

KaI6 Pooled Equal 18 -3.60 0.0020 Kal6 Satterthwaite- Unequal 10.7 -3.60 0.0043

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 10.65 0.0016

Comparison in Kallikrein 6 for Prostate and Arthriti 186

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Arthriti 10 0.4739 1 .2651 2.0563 0.7607 1.106 2.0191 0.3497

KaI6 Prostate 10 0.1475 0 .2519 0.3563 0.1004 0.146 0.2665 0.0462

Kal6 Diff (1-2) 0.272 1 .0132 1.7544 0.596 0.7888 1.1665 0.3528

T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 2.87 0.0101 Kal6 Satterthwaite Unequal 9.31 2.87 0.0178

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 57.40 <.0001

Comparison in Kallikrein 6 for Prostate and Aortic 187

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0 .025 0. 0467 0.1189 0 .0694 0 .1009 0.1841 0.0319

KaI6 Prostate 10 0. 1475 0. 2519 0.3563 0 .1004 0.146 0.2665 0.0462

Kal6 Diff (1-2) -0 .323 -0 .205 -0.087 0 .0948 0 .1255 0.1855 0.0561 T-Tests

Variable Method Variances DF t Value Pr > |t|

KaIS Pooled Equal 18 -3.66 0 .0018 KaIS Satterthwaite Unequal 16 -3.66 0 0021

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

KaIS Folded F 9 9 2 09 0.2859

Comparison in Kallikrem S for Prostate and Parkmso 188

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaIS kmso 10 2 384S 2 .6026 2.8207 0 .2097 0. 3048 0 5565 0 .0964 KaI6 state 10 0 1475 0 .2519 0.3563 0 .1004 0 .146 0.2665 0 .0462 Kal6 f (1-2) 2 1262 2 .3507 2.5752 0 .1806 0 239 0.3534 0 1069

T-TeStS

Variable Method Variances DF t Value Pr > |t|

KaIS Pooled Equal 18 21 99 < .0001

KaIS Satterthwaite Unequal 12 9 21.99 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 4.36 0.0390

Comparison m Kallikrem 6 for Prostati and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaIS Arthriti 10 0. 4739 1 .2651 2.0563 0 7607 1.106 2.0191 0.3497

KaI6 Prostati 10 0 4791 0 .8199 1 1607 0 3277 0.47S4 0.8697 0.1507

KaI6 Diff (1-2) -0 .355 0 .4452 1 2453 0.6434 0.8515 1.2592 0.3808

T-Tests

Variable Method Variances t Value Pr > |t|

KaIS Pooled Equal 18 1.17 0.2576 KaI6 Satterthwaite Unequal 12.2 1.17 0 2S47

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

KaIS Folded F 9 9 5.39 0.0195

Comparison in Kallikrem 6 for Prostati and Aortic 190

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0.025 0. 0467 0 .1189 0 .0694 0 .1009 0.1841 0.0319

KaIS Prostati 10 0.4791 0. 8199 1 .1607 0 .3277 0 .4764 0.8697 0.1507

KaIS Diff (1-2) -1.097 -0 .773 -0.45 0 .2602 0 .3443 0.5092 0.154 T-Tests

Variable Method Variances DF t Value Pr > jt|

Kal6 Pooled Equal 18 -5.02 <.oooi

KaIS Satterthwaite Unequal 9.Bl -5.02 0.0006

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

Kal6 Folded F 9 9 22.31 <.0001

Comparison in Kallikrein 6 for Prostati and Parkinso 191

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Parkinso 10 2 .3845 2 .602S 2.8207 0.2097 0.3048 0.5565 0.09S4

KaIS Prostati 10 0 .4791 0 .8199 1.1607 0.3277 0.4764 0.8697 0.1507

KaI6 Diff (1-2) 1 .4069 1 .7827 2.1585 0.3022 0.3999 0.5914 0.1789

T-Tests

Variable Method Variances DF t Value Pr > |t|

KaI6 Pooled Equal 18 9.97 <.0001 Kal6 Satterthwaite Unequal 15.3 9.97 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kalδ Folded F 9 9 2.44 0.1995

Comparison in Kallikrein S for Arthriti and Aortic 192

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0 .025 0.04S7 0.1189 0.0694 0.1009 0.1841 0.0319

KaIS Arthriti 10 0. 4739 1.2651 2.0563 0.7607 1.106 2.0191 0.3497

KaI6 Diff (1-2) —1 .956 -1.218 -0.481 0.5934 0.7853 1.1613 0.3512

T-Tests

Variable Method Variances t Value Pr > |t|

Kal6 Pooled Equal 18 -3.47 0.0027 KaIS Satterthwaite Unequal 9.15 -3.47 0.0069

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 120.24 <.0001

Comparison in Kallikrein 6 for Arthriti and Parkinso 193

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Arthriti 10 0.4739 1. 2651 2.05S3 0.7607 1.106 2.0191 0.3497

KaI6 Parkinso 10 2.3845 2. 6026 2.8207 0.2097 0.3048 0.5565 0.0964

KaI6 Diff (1-2) -2.1 -1 .338 -0.575 0.613 0.8112 1.1996 0.3628 T-Tests

Variable Method Variances DF t Value Pr > | t |

Kal6 Pooled Equal 18 -3 .69 0 .0017 Kal6 Satterthwaite Unequal 10.4 -3 .69 0 .0040

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Kal6 Folded F - 9 9 13.16 0.0007

Comparison in Kallikrein 6 for Aortic and Parkinso 1

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

KaI6 Aortic 10 -0 .025 0. 0467 0.1189 0 .0694 0.1009 0 .1841 0 .0319

Kal6 Parkinso 10 2.384S 2. 6026 2.8207 0 .2097 0.3048 0 .5565 0 .0964

KaI6 Diff (1-2) -2 .769 -2 .556 -2.343 0 .1716 0.227 0 .3358 0 .1015

T-Tests

Variable Method Variances DF t Value Pr > |t|

Kal6 Pooled Equal 18 -25 .17 < .0001

KaI6 Satterthwaite Unequal 10.9 -25 .17 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Kal6 Folded F 9 9 9.13 0.0029

Comparison in Alpha synuclein for Ostitis and KidSton 195

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Ostitis 10 18 .184 26.039 33.894 7.5528 10.981 20.046 3.4724

AIpS KidSton 10 13 .111 15.752 18.392 2.5392 3.6916 6.7395 1.1674

Alps Diff (1-2) 2. 5908 10.287 17.984 6.1896 8.1915 12.114 3.6633

T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 2.81 0.0116 AIpS Satterthwaite Unequal 11 2.81 0.0170

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 8.85 0.0033

Comparison in Alpha synuclein for Ostitis and Endoaden 196

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Ostitis 10 18.184 26.039 33 .894 7. 5528 10 .981 20 .046 3 .4724 Alps Endoaden 10 27.43 36.715 45 .999 8. 9272 12 .979 23 .694 4 .1042 Alps Diff (1-2) -21.97 -10.68 0. 6186 9. 0834 12 .021 17 .777 5.376 T-Tests

Variable Method Variances DF t Value Pr > ]t|

AIpS Pooled Equal 18 -1.99 0 0625 AIpS Satterthwaite Unequal 17 5 -1.99 0.0629

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F AIpS Folded F 9 9 1.40 0.6265

Comparison m Alpha synuclem for Cstitis and Prostate 197

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

AIpS CstitlS 10 18.184 26.039 33.894 7.5528 10.981 20.046 3.4724 AIpS Prostate 10 2.9203 5.7392 8.5581 2.7104 3.9405 7.1939 1.2461 AIpS Dlff (1-2) 12.549 20.3 28.05 6.2333 8.2493 12.199 3.6892

T-Tests Variable Method Variances DF t Value Pr > 111

AIpS Pooled Equal 18 5.50 <.0001

AIpS Satterthwaite Unequal 11.3 5.50 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 7.76 0.0054

Comparison xn Alpha synuclem for Cstitis and Prostati 198

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Cstitis 10 18.184 26.039 33.894 7.5528 10.981 20.046 3.4724 AIpS Prostati 10 29.25 35.097 40.945 5.6223 8.1739 14.922 2.5848 AIpS Dlff (1-2) -18.15 -9.059 0.0359 7.3139 9.6795 14.314 4.3288

T-Tests Variable Method Variances DF t Value Pr > |t|

Alps Pooled Equal 18 -2.09 0.0508

Alps Satterthwaite Unequal 16.6 -2.09 0.0520

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Alps Folded F 9 9 1.80 0.3923

Comparison in Alpha synuclem for Cstitis and Arthπti 199

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL Variable Disease N N M Meeaann M Meeaann Mean Std Dev Std Dev Std Dev Std Err

AIpS Arthriti 10 32.819 37 .238 41. 658 4 .2493 6. 1777 11 .278 1 .9536 AIpS Cstitis 10 18.184 26 .039 33. 894 7 .5528 10 .981 20 .046 3 .4724 Alps Dlff (1-2) 2.8291 11.2 19 .57 6 .7317 8. 9089 13 .175 3 .9842 T-Tests

Variable Method Variances DP t Value Pr ^ |t|

AIpS Pooled Equal 18 2.81 0.0116 AIpS Satterthwaite Unequal 14.2 2.81 0.0137

Equality of Variances

Variable Method Nura DF Den DP F Value Pr > F AIpS Folded F 9 9 3.16 0.1017

Comparison m Alpha synuclem for Ostitis and Aortic 2

The TTEST Procedure Statistics

AIpS Aortic 1 100 1 133..555544 1 144.. 227744 14.994 0.6923 1.0064 1.8374 0.3183

AIpS Cstitis 1 100 1 188..118844 2 266.. 003399 33.894 7.SS28 10.981 20.046 3.4724

AIpS Diff (1-2) - -1199..0099 - -1111 ..7777 -4.439 5.8915 7.797 11.53 3.4869

T-Tests

Variable Method Variances DF t Value Pr > | t |

Alps Pooled Equal 18 -3.37 0.0034 AIpS Satterthwaite Unequal 9.15 -3.37 0.0080

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Alps Folded F 9 9 119.03 <.0001

Comparison in Alpha synuclem for Cstitis and Parkinso 201

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N M Meeaann M Meeaann Mean Std Dev Std Dev Std Dev Std Err

AIpS Cstitis 1100 1188..118844 2266 ..003399 33.894 7.5528 10.981 20.046 3.4724 AIpS Parkmso 1100 2233..663399 2244 ..557722 25.505 0.8969 1.3039 2.3805 0.4123 AIpS Dlff (1-2) --55..8888 11.. 44666699 8.8133 5.9081 7.819 11.563 3.4968

T-Tests Variable Method Variances DF t Value Pr > | t|

AIpS Pooled Equal 18 0.42 0.6798

AIpS Satterthwaite Unequal 9.25 0.42 0.6844

Equality o£ Variances

Variable Method Nura DF Den DF F Value Pr > F Alps Folded F 9 9 70.92 <.0001

Comparison in Alpha synuclem for KidSton and Endoaden 202

The TTEST Procedure Statistics

AIpS Endoaden 10 27.43 36.715 45 .999 8 .9272 12 .979 23.694 4 .1042 AIpS KidSton 10 13.111 15.752 18 .392 2 .5392 3. 6916 6.7395 1 .1674 AIpS Dlff (1-2) 11.999 20.963 29 .928 7 .2095 9. 5413 14.11 4.267 T-Tests

Variable Method Variances DF t Value Pr > It|

AIpS Pooled Equal 18 4 91 0 0001 AIpS Satterthwaite Unequal 10.4 4.91 0 0005

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 12 36 0 0009

Comparison m Alpha synuclem for KidSton and Prostate 203

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS KidSton 10 13.111 15.752 18.392 2.5392 3.S916 6.7395 1.1S74

AIpS Prostate 10 2.9203 5.7392 8 5581 2.7104 3.9405 7 1939 1.2461

AIpS Diff (1-2) 6.4251 10.012 13.6 2 885 3.8181 5.6463 1 7075

T-Tests

Variable Method Variances t Value Pr > |t|

AIpS Pooled Equal 18 5.86 <-0001 AIpS Satterthwaite Unequal 17 9 5.86 < 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 1 14 0.8490

Comparison in Alpha synuclem for KidSton and Prostati 204

The TTEST Procedure Statistics

Lower CB Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS KidSton 10 13.111 15.752 18.392 2.5392 3.6916 6 7395 1 1674

AIpS Prostati 10 29.25 35.097 40 945 5.6223 8.1739 14.922 2.5848

AIpS Diff (1-2) -25.3 -19.35 -13 39 4.792 6.3419 9.3786 2.8362

T-Tests

Variable Method Variances t Value Pr > |t|

AIpS Pooled Equal 18 -6.82 <.0001 AIpS Satterthwaite Unequal 12.5 -6.82 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 4.90 0 0267

Comparison m Alpha synuclein for KidSton and Arthriti 205

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Arthriti 10 32.819 37.238 41.658 4 .2493 6 .1777 11 .278 1 .9536 AIpS KidSton 10 13.111 15.752 18.392 2 .5392 3 .6916 6. 7395 1 .1674 AIpS Diff (1-2) 16.706 21.487 26.268 3 .8452 5 .0888 7. 5255 2 .2758 T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 9 44 <-0001 AIpS Satterthwaite Unequal 14 7 9.44 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr =■ F AIpS Folded F 9 9 2.80 0.1410

Comparison in Alpha synuclem for KidSton and Aortic 2

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS tic 10 13, .554 14 .274 14.994 0 .6923 1.0064 1.8374 0 .31B3 AIpS Ston 10 13. .111 15 .752 18.392 2 .5392 3.6916 6.7395 1 .1674 AIpS f (1-2) -4.02 -1 .478 1.0642 2 .0444 2.7056 4.0012 1.21

T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 -1.22 0 .2377

AIpS Satterthwaite Unequal 10.3 -1.22 0 .2491

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 13.45 0.0007

Comparison m Alpha synuclem for KidSton and Parkmso 207

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS KidSton 10 13.111 15.752 18.392 2.5392 3.6916 6.7395 1.1674 AIpS Parkmso 10 23.639 24.572 25.505 0.8969 1.3039 2.3805 0.4123 AIpS Dlff (1-2) -11.42 -8.82 -6.219 2.0919 2.7684 4.094 1.2381

T-Tests Variable Method Variances DF t Value Pr > |t|

Alps Pooled Equal 18 -7.12 <.0001

AIpS Satterthwaite Unequal 11.2 -7.12 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 8.02 0.0048

Comparison m Alpha synuclem for Endoaden and Prostate 208

The TTEST Procedure Statistics

AIpS Endoaden 10 27.43 36.715 45.999 8 .9272 12 .979 23 .694 4 .1042 Alps Prostate 10 2.9203 5.7392 8.5581 2 .7104 3. 9405 7. 1939 1 .2461 AIpS Diff (1-2) 21.964 30.976 39.987 7.247 9 .591 14 .183 4 .2892 T-Tests

Variable Method Variances DF t Value Pr >

AIpS Pooled Equal 18 7.22 <.0001 AIpS Satterthwaite Unequal 10.6 7.22 <.0001

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

AIpS Folded F 9 9 10.85 0.0015

Comparison in Alpha synuclein for Endoaden and Prostati 209

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Endoaden 10 27.43 36. .715 45.999 8.9272 12.979 23.694 ^•■, 4.1042

AIpS Prostati 10 29.25 35. .097 40.945 5.6223 8.1739 14.922 ^' 2.5848

AIpS Diff (1-2) -8.573 l-r6174 11.808 8.1951 10.846 16.039 4.8503

T-Tests

Variable Method Variances DF t Value Pr |t|

AIpS Pooled Equal 18 0.33 0.7426 rAlpS Satterthwaite Unequal 15.2 0.33 0.7434

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 2.52 0.1845

Comparison in Alpha synuclein for Endoaden and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS hriti 10 32. .819 37 .238 41. S58 4. 2493 6. 1777 11.278 1 .9536 AIpS oaden 10 27.43 36 .715 45. 999 8. 9272 12 .979 23.694 4 .1042 AIpS f (1-2) -9. .026 0. 5236 10. 073 7.58 10 .164 15.031 4 .5454

T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 0.12 0 .9096

AIpS Satterthwaite Unequal 12.9 0.12 0 .9101

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 4.41 0.0375

Comparison in Alpha synuclein for Endoaden and Aortic 211

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Aortic 10 13.554 14.274 14. 994 0 .6923 1. 0064 1. 8374 0 .3183 AIpS Endoaden 10 27.43 36.715 45. 999 8 .9272 12 .979 23 .694 4 .1042 AIpS Diff (1-2) -31.09 -22.44 -13 .79 6 .9553 9. 2048 13 .612 4 .1165 T-Tests

Variable Method Variances DF t Value Pr > |t|

Alps Pooled Equal 18 -5.45 <.0001 Alps Satterthwaite Unequal 9.11 -S.45 0.0004

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

AIpS Folded F 9 9 ISS.30 <.0001

Comparison in Alpha synuclein for Endoaden and Parkinso 212

The TTEST Procedure Statistics

Lower CL upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Endoaden 10 27.43 36.715 45.999 8. .9272 12 .979 23.694 4.1042 Alps Parkinso 10 23.S39 24.572 25.505 0..8969 1.3039 2.3805 0.4123 AIpS Diff (1-2) 3.4769 12.143 20.809 ε..9694 9.2235 13.64 4.1249

T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 2.94 0.0087 Alps Satterthwaite Unequal 9.18 2.94 0.0160

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 99.07 <-0001

Comparison in Alpha synuclein for Prostate and Prostati 213

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N N M Meeaann M Meeaann Mean Std Dev Std Dev Std Dev Std Err

AIpS Prostate 1100 22..99220033 55..77339922 8.5581 2.7104 3.9405 7.1939 1.2461 AIpS Prostati 1100 2299..2255 3355..009977 40.945 5.6223 8.1739 14.922 2.5848 AIpS Diff (1-2) --3355..3399 --2299..3366 -23.33 4.8483 S.4164 9.4887 2.8695

T-Tests Variable Method Variances DF t Value Pr > | t |

AIpS Pooled Equal 18 -10.23 <.0001 AIpS Satterthwaite Unequal 13 -10.23 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 4.30 0.0407

Comparison in Alpha synuclein for Prostate and Arthriti 214

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Arthriti 10 32.819 37.238 41.658 4 .2493 6 .1777 11 .278 1 .9536 AIpS Prostate 10 2.9203 5.7392 8.5581 2 .7104 3 .9405 7. 1939 1 .24Sl AIpS Diff (1-2) 26.631 31.499 36.367 3 .9151 S .1813 7. 6623 2 .3172 T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 13.59 <.0001 AIpS Satterthwaite Unequal 15.3 13.59 <.0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr _> F

AIpS Folded F 9 9 2.46 0 1965

Comparison in Alpha synuclem for Prostate and Aortic 215

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Aortic 10 13.554 14 .274 14.994 0.6923 1.0064 1.8374 0.3183

Alps Prostate 10 2.9203 5. 7392 8.5581 2.7104 3.9405 7.1939 1.2461

Alps Diff (1-2) 5.8325 8. 5345 11 237 2.173 2.8758 4.2528 1.2861

T-Tests

Variable Method Variances t Value Pr > |t|

AIpS Pooled Equal 18 6.64 <.0001 AIpS Satterthwaite Unequal 10.2 6.64 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 15.33 0.0004

Comparison in Alpha synuclem for Prostate and Parkmso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Parkinso 10 23.639 24 .572 25.505 0.8969 1.3039 2.3805 0.4123

AIpS Prostate 10 2.9203 5 7392 8.5581 2.7104 3.9405 7.1939 1.2461

AIpS Diff (1-2) 16.075 18 833 21.59 2.2177 2.935 4.3403 1.3126

T-Tests

Variable Method Variances t Value Pr > | t |

AIpS Pooled Equal 18 14.35 <.0001 AIpS Satterthwaite Unequal 10.9 14.35 ■=.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 9.13 0.0029

Comparison in Alpha synuclein for Prostati and Arthnti 217

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Arthπti 10 32.819 37.238 41.658 4.2493 6. mi 11.278 1.9536

Alps Prostati 10 29.25 35.097 40.945 5.6223 8.1739 14.922 2.5848

AIpS Diff (1-2) -4.666 2.141 8.948 5.4743 7.2449 10.714 3.24 T-Tests

Variable Method Variances DP t Value Pr > ItI

AIpS Pooled Equal 18 0.66 0 5171 AIpS Satterthwaite Unequal 16.8 0.S6 0 5177

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

AIpS Folded F 9 9 1.75 0 4168

Comparison in Alpha synuclem for Prostati and Aortic 218

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Aortic 10 13.554 14.274 14.994 0. .6923 1.0064 1.8374 0. 3183 AIpS Prostati 10 29.25 35.097 40.945 5 6223 8.1739 14.922 2.5848 AIpS Dlff (1-2) -26.3 -20.82 -15.35 4..4003 5.8234 8.6118 2.6043

T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 -i 3.00 <.0001 AIpS Satterthwaite Unequal 9.27 -i3.00 <.0O01

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 65.96 <.0001

Comparison in Alpha synuclem for Prostati and Parkmso 219

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AIpS Parkmso 10 23.639 24.572 25.505 0.8969 1.3039 2.3805 0.4123

AIpS Prostati 10 29.25 35.097 40.945 5.6223 8.1739 14.922 2.5848

AIpS Dlff (1-2) -16.02 -10.53 -5.02S 4.4225 5.8529 8.6554 2.6175

T-Tests

Variable Method Variances t Value Pr > |t|

AIpS Pooled Equal 18 -4.02 0.0008 AIpS Satterthwaite Unequal 9.46 -4.02 0 0027

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AIpS Folded F 9 9 39.30 <.0001

Comparison in Alpha synuclem for Arthriti and Aortic 220

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Alps Aortic 10 13.554 14.274 14. 994 0 .6923 1 .0064 1. 8374 0 .3183 AIpS Arthriti 10 32.819 37.238 41. 658 4 .2493 6 .1777 11 .278 1 .9536 AIpS Diff (1-2) -27.12 -22.96 -18 .81 3 .3443 4 .4259 6. 5451 1 .9793 T-Tests

Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 -11.60 <.0001 AIpS Satterthwaite unequal 9.48 -11.60 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 37.68 <.0001

Comparison in Alpha synuclein for Arthriti and Parkinso 221

The TTEST Procedure Statistics

AIpS Arthriti 10 32.819 37.238 41.6S8 4.2493 6.1111 11.278 1.9536 AIpS Parkinso 10 23.639 24.572 25.505 0.8969 1.3039 2.3805 0.4123 AIpS DiEf (1-2) 8.4718 12.667 16.861 3.3735 4.4646 6.6023 1.99S6

T-Tests Variable Method Variances DF t Value Pr > |t|

AIpS Pooled Equal 18 6.34 <.0001 AIpS Satterthwaite Unequal 9.8 6.34 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 22.45 <.0001

Comparison in Alpha synuclein for Aortic and Parkinso 222

The TTEST Procedure Statistics

AIpS Aortic 10 13.554 14.274 14.994 0.6923 1.0064 1.8374 0.3183

AIpS Parkinso 10 23.639 24.572 25.505 0.8969 1.3039 2.3805 0.4123 AIpS Diff (1-2) -11.39 -10.3 -9.204 0.8801 1.1647 1.7224 0.5209

T-Tests Variable Method Variances DF t Value Pr > | t |

Alps Pooled Equal 18 -19.77 <.0001 AIpS Satterthwaite Unequal 16.9 -19.77 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AIpS Folded F 9 9 1.68 0.4523

Comparison in Osteonectin for Cstitis and KidSton 223

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease K Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Cstitis 10 0 .3953 1 .0856 1.7759 0.6638 0.965 1 .7618 0.3052

Onctin KidSton 10 0 .2479 0 .3234 0.3989 0.0726 0.1056 0 .1928 0.0334

Onctin Diff (1-2) 0 .1172 0 .7622 1.4072 0.5187 0.6865 1 .0152 0.307 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 2.48 0 0231

Onctm Satterthwaite Unequal 9 22 2.48 0 0343

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

Onctm Folded F 9 9 83.54 <.0001

Comparison in Osteonectin for Ostitis and Endoaden 224

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Cstitis 10 0.3953 1.0856 1 7759 0.S638 0.965 1 7618 0.3052

Onctm Endoaden 10 0.695 1.1145 1 534 0.4034 0.5864 1.0706 0.1854

Onctm Diff (1-2) -0.779 -0.029 0.7213 0.6034 0.7985 1.1808 0.3571

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 -0 08 0 9364 Onctm Satterthwaite Unequal 14.8 -0.08 0.9366

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 2 71 0 1539

Comparison in Osteonectin for Cstitis and Prostate

The TTEST Procedure '

Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Cstitis 10 0 .3953 1 .0856 1.7759 0 .6638 0 965 1.7618 0 .3052

Onctm Prostate 10 0 .3309 0 .4352 0.5395 0 .1003 0. 1458 0.2661 0 .0461

Onctm Diff (1-2) 0.002 0 .6504 1.2988 0 .5215 0. 6901 1.0206 0 .3086

T-Tests

Variable Method Variances DF t Value Pr » |t|

Onctm Pooled Equal 18 2.11 0 .0494

Onctm Satterthwaite Unequal 9 .41 2.11 0 .0630

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P

Onctin Folded F 9 9 43.84 <.0001

Comparison m Osteonectin for Cstitis and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Cstitis 10 0.3953 1 .0856 1 .7759 0 .6638 0 965 1.7618 0.3052

Onctm Prostati 10 0.733 0 .9659 1 .1988 0 .2239 0 .3256 0.5944 0.103

Onctm Diff (1-2) -0.557 0 .1197 0 .7963 0 .5442 0 .7202 1.065 0.3221 T-Tests

Variable Method Variances DF t Value Pr > 111

Onctin Pooled Equal 18 0 37 0 .7145

Onctm Satterthwaite Unequal 11 0 37 0 7172

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 8 79 0.0034

Comparison in Osteonectin for Ostitis and Arthriti 227

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Arthriti 10 1 0861 1.7179 2.3497 0 6074 0.8831 1.6122 0 2793 Onetin Cstitis 10 0.3953 1.0856 1.7759 0 6638 0.965 1.7618 0.3052 Onctin Diff (1-2) -0.237 0.6323 1.5014 0.6989 0.925 1 3679 0.4137

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 1.53 0.1438

Onctin Satterthwaite Unequal 17.9 1 53 0.1439

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 1.19 0.7959

Comparison in Osteonectin for Cstitis and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Aortic 10 0.757 0.8917 1 02S4 0.1295 0.1883 0.3438 0 0595

Onctm Cstitis 10 0 3953 1.0856 1.7759 0.6638 0 965 1.7618 0.3052

Onctm Diff (1-2) -0 847 -0.194 0.4593 0.5253 0.6953 1.0282 0 3109

T-Tests

Variable Method Variances t Value Pr > |t|

Onctin Pooled Equal 18 -0.62 0.5407

Onctin Satterthwaite Unequal 9.68 -0.62 0.5473

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 26.26 <.0001

Comparison m Osteonectin for Cstitis and Parkmso 229

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Cstitis 10 0.3953 1 .0856 1.7759 0 .6638 0.965 1.7618 0.3052

Onctin Parkmso 10 2.3631 2 .8852 3.4073 0.502 0 .7298 1.3324 0.2308

Onctm Diff (1-2) -2 603 -1.8 -0.996 0 .6465 0 .8556 1.2652 0.3826 T-Tests

Variable Method Variances DP t Value Pr > |t|

Onctm Pooled Equal 18 -4.70 0.0002

Onetin Satterthwaite Unequal 16.8 -4.70 0.0002

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

Onctm Folded F 9 9 1.75 0 4179

Comparison in Osteonectin for KidSton and Endoaden

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

Onctm Endoaden 10 0.695 1.1145 1.534 0.4034 0.5864 1 0706 0.1854 Onctm KidSton 10 0.2479 0.3234 0.3989 0.0726 0.1056 0.1928 0.0334 Onctm Diff (1-2) 0.3952 0.7911 1.187 0.3184 0.4213 0.6231 0.1884

T-Tests

Variable Method Variances t Value Pr > |t|

Onctm Pooled Equal 18 4.20 0.0005 Onctm Satterthwaite Unequal 9.58 4.20 0.0020

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 30.85 <-0001

Comparison m Osteonectin for KidSton and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm KidSton 10 0.2479 0. 3234 0.3989 0 .0726 0.1056 0 .1928 0 .0334

Onctm Prostate 10 0.3309 0. 4352 0.5395 0 .1003 0.1458 0 .2661 0 .0461

Onctm Diff (1-2) -0.231 -0 .112 0.0078 0 .0962 0.1273 0 .1882 0 .0569

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 -1.96 0 .0651 Onctm Satterthwaite Unequal 16.4 -1.96 0 .0667

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 1.91 0.3507

Comparison m Osteonectin for KidSton and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm KidSton 10 0.2479 0. 3234 0. 3989 0 .0726 0 .1056 0.1928 0.0334

Onctin Prostati 10 0.733 0. 9659 1. 1988 0 .2239 0 .3256 0.5944 0.103

Onctin Diff (1-2) -0.87 -0 .643 -0 .415 0 .1829 0.242 0.3579 0.1082 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 -5.94 <.0001

Onctin Satterthwaite Unequal 10.9 -5.94 0.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 9.51 0.0025

Comparison in Osteonectin for KidSton and Arthriti 233

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Arthriti 10 1. .08Sl 1 .7179 2.3497 0 .6074 0.8831 1.6122 0.2793

Onctin KidSton 10 0. .2479 0 .3234 0.3989 0 .0726 0.1056 0.1928 0.0334

Onctin Diff (1-2) 0. .8036 1 .3945 1.9854 0 .4752 0.6289 0.9301 0.2813

T-Tests

Variable Method Variances DF t Value Pr

Onctin Pooled Equal 18 4.96 0.0001

Onctin Satterthwaite Unequal 9 .26 4.96 0.0007

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 69.96 <.0001

Comparison in Osteonectin for KidSton and Aortic 234

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev std Err

Onctm Aortic 10 0.757 0 .8917 1.0264 0 .1295 0.1883 0.3438 0.0595

Onctin KidSton 10 0.2479 0 .3234 0.3989 0 .0726 0.1056 0.1928 0.0334

Onctin Diff (1-2) 0.4249 0 .5683 . 0.7117 0 .1153 0.1527 0.2258 0.0683

T-Tests

Variable Method Variances DF t Value

Onctin Pooled Equal 18 8.32 <.0001

Onctin Satterthwaite Unequal 14 .1 8.32 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 3.18 0.0998

Comparison in Osteonectin for KidSton and Parkinso 235

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin KidSton 10 0. 2479 0.3234 0. 3989 0. 0726 0 .1056 0.1928 0.0334

Onctin Parkinso 10 2. 3631 2.8852 3. 4073 0 .502 0 .7298 1.3324 0.2308

Onctin Diff (1-2) -3 .052 -2.562 —2 .072 0 .394 0 .5214 0.7711 0.2332 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 -10.99 <.0001

Onctin Satterthwaite Unequal 9.38 -10.99 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 47.78 <.0001

Comparison in Osteonectin for Endoaden and Prostate 236

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Endoaden 10 0.695 1.1145 1.534 0.4034 0.5864 1.0706 0.1854

Onctin Prostate 10 0.3309 0.4352 0.5395 0.1003 0.1458 0.2661 0.0461

Onctin Diff (1-2) 0.2778 0.6793 1.0808 0.3229 0.4273 0.6319 0.1911

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 3.55 0.0023 Onctin Satterthwaite Unequal 10.1 3.55 0.0051

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 16.19 0.0003

Comparison in Osteonectin for Endoaden and Prostati 237

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Endoaden 10 0.695 1 .1145 1.534 0.4034 0.5864 1.0706 0.1854

Onctin Prostati 10 0.733 0 .9659 1.1988 0.2239 0.3256 0.5944 0.103

Onctin Diff (1-2) -0.297 0 .1486 0.5942 0.3584 0.4743 0.7014 0.2121

T-Tests

Variable Method Variances t Value Pr > |t|

Onctin Pooled Equal 18 0.70 0.4925 Onctin Satterthwaite Unequal 14.1 0.70 0.4950

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 3.24 0.0945

Comparison in Osteonectin for Endoaden and Arthriti 238

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Arthriti 10 1.0861 1 .7179 2.3497 0.6074 0 .8831 1.6122 0.2793

Onctin Endoaden 10 0.695 1 .1145 1.534 0.4034 0 .5864 1.0706 0.1854

Onctin Diff (1-2) -0.101 0 .6034 1.3077 0.5664 0 .7496 1.1085 0.3352 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 1 80 0 0887

Onctin Satterthwaite Unequal 15 6 1 80 0 0912

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 2 27 0 2384

Comparison m Osteonectin for Endoaden and Aortic 239

The TTEST Procedure Statistics

Lower CIJ Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onetin tic 10 0 757 0 8917 1 0264 0 1295 0 1883 0 3438 0 0595 Onctin oaden 10 0 695 1 1145 1 534 0 4034 0 5864 1 0706 0 1854 Onctm f (1-2) -0 632 -0 223 0 1864 0 3291 0 4355 0 6441 0 1948

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 -1 14 0 2676

Onctm Satterthwaite Unequal 10 8 -1 14 0 2773

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 9 70 0 0023

Comparison in Osteonectin for Endoaden and Parkmso 240

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Endoaden 10 0 695 1 1145 1 534 0 4034 0 5864 1 0706 0 1854

Onctm Parkmso 10 2 3631 2 8852 3 4073 0 502 0 7298 1 3324 0 2308

Onctm Diff (1-2) -2 393 -1 771 -1 149 0 5002 0 662 0 979 0 2961

T-Tests

Variable Method Variances t Value Pr > |t|

Onctm Pooled Equal 18 -5 98 0001 Onctm Satterthwaite Unequal 17 2 -5 98 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 1 55 0 5248

Comparison in Osteonectin for Prostate and Prostati 241

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Prostate 10 0 3309 0 4352 0 5395 0 1003 0 1458 0 2661 0 0461

Onctin Prostati 10 0 733 0 9659 1 1988 0 2239 0 3256 0 5944 0 103

Onctm Diff (1-2) -0 768 -0 531 -0 294 0 1906 0 2522 0 373 0 1128 T-Tests

Variable Method Varxances DF t Value Pr > |t|

Onctm Pooled Equal IS -4 70 0 .0002

Onctm Satterthwaite Unequal 12.5 -4 70 0 0005

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 4 99 o 0252

Comparison in Osteonectin for Prostate and Arthriti 242

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Arthriti 10 1 0851 1.7179 2.3497 0.6074 0.8831 1.6122 0 2793 Onctm Prostate 10 0.3309 0.4352 0.S395 0.1003 0.14S8 0.2661 0.0461 Onctm Diff (1-2) 0.688 1.2827 1.8774 0.4782 0.6329 0 93S 0 283

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 4.53 0 0003 Onctm Satterthwaite Unequal 9 49 4.53 0 0012

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 36 71 <.0001

Comparison in Osteonectin for Prostate and Aortic 243

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Aortic 10 0.757 0 .8917 1. .0264 0 1295 0.1883 0.3438 0 .0595

Onctm Prostate 10 0.3309 0 .4352 0. .5395 0 1003 0.1458 0 2661 0 .0461

Onctm Diff (1-2) 0.2983 0 .4565 0. .6147 0 .1272 0.1684 0 249 0 .0753

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 6.06 < .0001

Onctm Satterthwaite Unequal IS.9 6.06 < 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 1.67 0.4572

Comparison xn Osteonectin for Prostate and Parkmso 244

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Parkmso 10 2 .3631 2 8852 3 .4073 0.502 0. 7298 1.3324 0.2308

Onctm Prostate 10 0 .3309 0 .4352 0 .5395 0.1003 0. 1458 0.2661 0.0461

Onctm Diff (1-2) 1 .9555 2.45 2 .9445 0.3977 0. 5263 0.7783 0.2354 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onehin Pooled Equal 18 10.41 <.0001 Onctin Satterthwalte Unequal 9.72 10.41 <-0001

Equality of Variances

Variable Method Nutn DF Den DF F Value Pr > F

Onctin Folded F 9 9 25.07 <.0001

Comparison in Osteonectin for Prostati and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Arthriti 10 1.08S1 1 .7179 2.3497 0.S074 0.8831 1.S122 0.2793

Onctin Prostati 10 0.733 0 .9659 1.1988 0.2239 0.3256 0.5944 0.103

Onctin Diff (1-2) 0.12S7 0.752 1.3773 0.5029 0.6655 0.9842 0.297S

T-Tests

Variable Method Variances t Value Pr > |t|

Onctin Pooled Equal 18 2.53 0.0211 Onctin Satterthwaite Unequal 11.4 2.53 0.0275

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 7.36 O.OOSS

Comparison in Osteonectin for Prostati and Aortic 246

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin Aortic 10 0.757 0. 8917 1.0264 0.1295 0. 1883 0.3438 0.0595

Onctin Prostati 10 0.733 0. 9659 1.1988 0.2239 0. 3256 0.5944 0.103

Onctin Diff (1-2) -0.324 -0 .074 0.1757 0.201 0 .266 0.3933 0.1189

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 -0 .62 0.5405

Onctin Satterthwaite Unequal 14.4 -0 .62 0.5425

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 2.99 0.1185

Comparison in Osteonectin for Prostati and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev std Err

Onctm Parkmso 10 2 .3631 2 .8852 3 .4073 0 .502 0 .7298 1.3324 0.2308

Onctin Prostati 10 0.733 0 .9659 1 .1988 0. 2239 0 .3256 0.5944 0.103

Onctin Diff (1-2) 1 .3884 1 .9193 2 .4502 0 .427 0 .5651 0.8357 0.2527 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 7 59 <.0001

Onctm Satterthwaite Unequal 12 4 7.59 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 5 03 0.0247

Comparison in Osteonectin for Arthriti and Aortic 248

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm tic 10 0.757 0. 8917 1 0264 0 .1295 0.1883 0.3438 0 .0595 Onctm hπti 10 1.08S1 1. 7179 2.3497 0 .6074 0.8831 1 6122 0 .2793 Onctm f (1-2) ^■1 426 -0 .826 -0 226 0 .4825 0.6385 0 9442 0 .2855

T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctm Pooled Equal 18 -2.89 0 .0097

Onctm Satterthwaite Unequal 9 82 -2.89 0 .0163

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 21.99 < 0001

Comparison in Osteonectin for Arthriti and Parkmso 249

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctin hnti 10 1 0861 1.7179 2.3497 0 .6074 0. 8831 1.6122 0 2793 Onctm kmso 10 2. .3631 2.8852 3 4073 0.502 0. 7298 1.3324 0 .2308 Onctm f (1-2) -: L.928 -1.167 -0 406 0 .6121 0. 8101 1.198 0 .3623

T-Tests

Variable Method Variances DF t Value Pr > ]t|

Onctin Pooled Equal 18 -3.22 0 0047

Onctm Satterthwaite Unequal 17.4 -3 22 0 .0049

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctm Folded F 9 9 1.46 0.5791

Comparison in Osteonectin for Aortic and Parkmso 250

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Onctm Aortic 10 0.757 0.8917 1. 0264 0 .1295 0 .1883 0 .3438 0 .0595

Onctm Parkmso 10 2.3631 2.8852 3. 4073 0.502 0 .7298 1 .3324 0 .2308

Onctm Diff (1-2) -2.494 -1.994 -1 .493 0 .4027 0.533 0 .7882 0 .2384 T-Tests

Variable Method Variances DF t Value Pr > |t|

Onctin Pooled Equal 18 -S.36 <.0001

Onctin Satterthwaite Unequal 10.2 -S.3S <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Onctin Folded F 9 9 15.02 0.0004

Comparison in Osteocalcin for Cstitis and KidSton 251

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Cstitis 10 5 .1478 10 .123 15.098 4 .7838 6 .9549 12.697 2.1993 Olcin KidSton 10 0 .0399 0. 1364 0.2329 0 .0927 0 .1348 0.2462 0.0426 Olcin Diff (1-2) 5 .3651 9. 9866 14.608 3 .7167 4 .9187 7.274 2.1997

T-Tests

Variable Method Variances t Value Pr > |t|

Olcin Pooled Equal 18 4.54 0.0003 Olcin Satterthwaite Unequal 9.01 4.54 0.0014

Equality of Variances

Variable Method Num DE Den DF F Value Pr > F

Olcin Folded F 9 9 2660.35 <.0001

Comparison in Osteocalcin for Cstitis and Endoaden

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev std Err

Olcin itis 10 5 .1478 10.123 15 .098 4 .7838 6.9549 12.697 2 .1993 Olcin oaden 10 1 .6763 2.7105 3. 7447 0 .9944 1.4457 2.6393 0 .4572 Olcin f (1-2) 2 .6931 7.4125 12 .132 3 .7954 5.023 7.4281 2 .2463

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcin Pooled Equal 18 3.30 0 .0040

Olcin Satterthwaite Unequal 9 .78 3.30 0 .0083

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 23.14 <.0001

Comparison in Osteocalcin for Cstitis and Prostate

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Cstitis 10 5.1478 10 .123 15.098 4.7838 6.9549 12.697 2.1993

Olcin Prostate 10 0 0 0 0 0

Olcin Diff (1-2) 5.5024 10 .123 14.744 3.716 4.9178 7.2726 2.1993 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 4 60 0 0002 Olcm Satterthwaite Unequal 9 4 60 0 0013

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > P

Olcin Folded F 9 9 Infty < 0001

Comparison in Osteocalcin for Cstitis and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Cstitis 10 5. .1478 10 .123 15 098 4 7838 6.9549 12.697 2 1993

Olcm Prostati 10 1 5289 2 1122 2. 6955 0 5609 0.8154 1.4886 0 2579

Olcm Dlff (1-2) 3. .3586 8. 0108 12 663 3 .7414 4.9515 7 3224 2.2144

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 3. .62 0.0020

Olcm Satterthwaite Unequal 9 25 3. .62 0.0053

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 72 75 < 0001

Comparison m Osteocalcin for Cstitis and Arthriti 255

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthriti 10 6.2895 10 713 15 .136 4 2532 6.1835 11.289 1 .9554

Olcin Cstitis 10 5.1478 10 123 15 .098 4 .7838 6.9549 12 697 2 .1993

Olcin Diff (1-2) -5.593 0. 5899 6. 7727 4 .9723 6.5805 9.7314 2 .9429

T-Tests

Variable Method Variances DF t Value Pr » It

Olcin Pooled Equal 18 0 20 0 .8434

Olcm Satterthwaite Unequal 17 8 0.20 0 8434

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 1.27 0.7319

Comparison m Osteocalcin for Cstitis and Aortic 256

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Aortic 10 3.7596 4.3479 4 9362 0.5656 0.8223 1.5013 0.26 Olcm Cstitis 10 5.1478 10.123 15.098 4.7838 6.9549 12.697 2.1993 Olcin Dlff (1-2) -10.43 -5.775 -1.122 3.7419 4.9521 7.3233 2.2146 T-Tests

Variable Method Variances DF t Value Pr > ItI

Olcin Pooled Equal 18 -2.61 0 .0178 Olcin Satterthwaite Unequal 9.25 -2.Sl 0.0278

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 71.53 <.0001

Comparison in Osteocalcin for Ostitis and Parkinso 257

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Ostitis 10 5 .1478 10 .123 15 .098 4 .7838 S.9549 12.697 2.1993 Olcin Parkinso 10 2.1237 2.5S6S 3.0095 0.4259 0.6192 1.1304 0.1958 Olcin Diff (1-2) 2.9175 7.5564 12.195 3.7307 4.9373 7.3014 2.208

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcin Pooled Equal 18 3.42 0.0030 Olcin Satterthwaite Unequal 9.14 3.42 0.0074

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 126.16 <.0001

Comparison in Osteocalcin for KidSton and Endoaden 258

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Endoaden 10 1 .6763 2 .7105 3.7447 0 .9944 1.4457 2.6393 0.4572 Olcin KidSton 10 0.0399 0.1364 0.2329 0.0927 0.1348 0.2462 0.0426 Olcin Diff (1-2) 1.6094 2.5741 3.5388 0.7758 1.0267 1.5183 0.4592

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcin Pooled Equal 18 5.61 <,0001 Olcin Satterthwaite Unequal 9.16 5.61 0.0003

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 114.96 <.0001

Comparison in Osteocalcin for KidSton and Prostate 259

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

Olcin KidSton 10 0 .0399 0 .1364 0.2329 0.0927 0 .1348 0.2462 0 .0426

Olcin Prostate 10 0 0 0 0 0

Olcin Diff (1-2) 0 .0468 0 .1364 0.226 0.072 0 .0953 0.141 0 .0426 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 3 20 0.0050

Olcm Satterthwaite Unequal 9 3.20 0.0109

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 Infty _<.0001

Comparison in Osteocalcin for KidSton and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm KidSton 10 0.0399 0. 1364 0. 2329 0 .0927 0. 1348 0 2462 0 .0426 Olcm Prostati 10 1.5289 2. 1122 2. 5955 0 .5509 0. 8154 1.4886 0 .2579 Olcm Diff (1-2) -2.525 -1 .97S -1 .427 0 .4416 0. 5844 0.8643 0 .2614

T-Tests

Variable Method Variances DF t Value Pr » It

Olcm Pooled Equal 18 -7.56 < .0001 Olcm Satterthwaite Unequal 9 .49 -7.56 < .0001

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

Olcin Folded F 9 9 36.57 <.0001

Comparison in Osteocalcin for KidSton and Arthπti 261

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthriti 10 6. 2895 10 .713 15.136 4.2532 6.1835 11.289 1.9554

Olcin KidSton 10 0. 0399 0. 1364 0.2329 0.0927 0.1348 0.2462 0.0426

Olcm Diff (1-2) 6. 4674 10 .577 14.686 3.3046 4.3734 6.4675 1.9558

T-Tests

Variable Method Variances t Value Pr >

Olcm Pooled Equal 18 5.41 <.0001 Olcin Satterthwaite Unequal 9.01 5.41 0.0004

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 2102.94 <.0001

Comparison m Osteocalcin for KidSton and Aortic 262

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Aortic 10 3.7596 4.3479 4 .9362 0 .5656 0 .8223 1 .5013 0.26 Olcin KidSton 10 0.0399 0.1364 0 .2329 0 .0927 0 .1348 0 .2462 0 .0426 Olcin Diff (1-2) 3 .6579 4 .2115 4 .7651 0 .4452 0 .5892 0 .8714 0 .2635 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 15 98 ■=.0001

Olcm Satterthwaite Unequal 9 48 15.98 < 0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Olcm Folded F 9 9 37 19 < 0001

Comparison in Osteocalcin for Kidston and Parkmso 263

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm KidSton 10 0.0399 0.13S4 0.2329 0 .0927 0.1348 0 2462 0 0426 Olcm Parkmso 10 2 1237 2 SS66 3.0095 0.4259 0.6192 1 1304 0 1958 Olcm Diff (1-2) -2 851 -2 43 -2.009 0.3386 0.4481 0 6627 0 2004

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 -12 .13 < 0001 Olcm Satterthwaite Unequal 9.85 -12.13 <.0001

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

Olcm Folded F 9 9 21 09 0 0001

Comparison in Osteocalcin for Endoaden and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Endoaden 10 1 .6763 2 .7105 3.7447 0 9944 1.4457 2.6393 0.4572

Olcm Prostate 10 0 0 0 0 0

Olcm Diff (1-2) 1.75 2 .7105 3 671 0.7725 1.0223 1.5118 0.4572

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 5 93 <.0001 Olcm Satterthwaite Unequal 9 5 93 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 Infty <.0001

Comparison in Osteocalcin for Endoaden and Prostati 265

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Endoaden 10 1.6763 2.7105 3 .7447 0 .9944 1 .4457 2 .6393 0 .4572

Olcm Prostati 10 1.5289 2.1122 2 .6955 0 .5609 0 .8154 1 .4886 0 .2579

Olcm Diff (1-2) -0.504 0.5983 1.701 0 .8868 1 .1737 1 .7357 0 .5249 T-Tests

Variable Method Variances DF t Value Pr > lt|

Olcm Pooled Equal 18 1.14 0 .2693

Olcm Satterthwaite Unequal 14.2 1 14 0 .2732

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

Olcm Folded F 9 9 3 14 0.1032

Comparison in Osteocalcin for Endoaden and Arthriti 266

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthriti 10 6 .2895 10.713 15.136 4 2532 6.1835 11.289 1. 9554

01cm Endoaden 10 1 .6763 2.7105 3.7447 0 .9944 1.4457 2.6393 0. 4572

01cm Diff (1-2) 3 .7835 8.0024 12.221 3 .3929 4.4903 6.6403 2. 0081

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 3.99 0.0009

Olcm Satterthwaite Unequal 9 .98 3.99 0.0026

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 18.29 0.0002

Comparison in Osteocalcin for Endoaden and Aortic 267

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Aortic 10 3 .7596 4.3479 4.9362 0.5656 0.8223 1.5013 0.26 Olcm Endoaden 10 1 .6763 2.7105 3.7447 0.9944 1.4457 2.6393 0.4572 Olcin Diff (1-2) 0 .5324 1.6374 2.7424 0.8887 1.1761 1.7392 0.526

T-Tests

Variable Method Variances DF t Value Pr |t|

Olcm Pooled Equal 18 3.11 0.0060 Olcm Satterthwaite Unequal 14.3 3.11 0.0075

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcin Folded F 9 9 3.09 0.1081

Comparison in Osteocalcin for Endoaden and Parkmso 268

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Endoaden 10 1. 6763 2 .7105 3 .7447 0 .9944 1 .4457 2 .6393 0 .4572

Olcm Parkmso 10 2. 1237 2 .5666 3 .0095 0 .4259 0 .6192 1 .1304 0 .1958

Olcm Diff (1-2) -0 .901 0 .1439 1 .1888 0 .8403 1 .1121 1 .6446 0 .4973 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 0.29 0 7756 Olcm Satterthwaite Unequal 12 2 0 29 0.7772

Equality of Variances

Variable Method Nurn DF Den DF F Value Pr > F

Olcm Folded F 9 9 5.45 0 0188

Comparison m Osteocalcin for Prostate and Prostati 269

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Prostate 10 0 0 0 0 0 Olcm Prostati 10 1.5289 2.1122 2.6955 0 5609 0 8154 1.4886 0.2579 Olcm Dlff (1-2) -2.654 -2.112 -1.57 0 4357 0 5766 0.8527 0 2579

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 -! 3 19 <.0001 Olcm Satterthwaite Unequal 9 -S3.19 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 Infty <.0001

Comparison m Osteocalcin for Prostate and Arthriti 270

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthriti 10 6 2895 10.713 15. .136 4.2532 6.: L835 11 289 1 9554

Olcin Prostate 10 0 0 0 0 0

Olcm Dlff (1-2) 6 S048 10.713 14 821 3.3038 4.3724 6.466 1. 9554

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 5.48 <.0001

Olcm Satterthwaite Unequal 9 5.48 0.0004

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 Infty <.0001

Comparison m Osteocalcin for Prostate and Aortic 271

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Aortic 10 3 .7596 4 .3479 4 9362 0.5656 0 .8223 1 .5013 0 .26

Olcm Prostate 10 0 0 0 0 0

Olcm Dlff (1-2) 3 .8016 4 .3479 4 .8942 0.4394 0 .5815 0 .8599 0 .26 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 IS 72 0001

Olcin Satterthwaxte Unequal 9 16 72 < 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 Infty <.0001

Comparison m Osteocalcin for Prostate and Parkmso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Parkmso 10 2 1237 2 5666 3 0095 0.4259 0 6192 1 1304 0.1958

Olcm Prostate 10 0 0 0 0 0

Olcm Dlff (1-2) 2 .1552 2 .5666 2.978 0.3308 0 4378 0.6475 0.1958

T-Tests

Variable Method Variances DF t Value Pr > It

Olcm Pooled Equal 18 13 .11 < .0001 Olcm Satterthwaite Unequal 9 13 .11 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 Infty < 0001

Comparison m Osteocalcin for Prostati and Arthπti 273

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthπti 10 6.2895 10 .713 15 .136 4 .2532 6 .1835 11 289 1.9554 Olcm Prostati 10 1.5289 2. 1122 2 6955 0 5609 0 .8154 1.4886 0 2579 Olcm Diff (1-2) 4 457 8. 6007 12 .744 3 .3324 4 .4102 6.5219 1.9723

T-Tests

Variable Method Variances DF t Value Pr |t|

Olcm Pooled Equal 18 4.36 0.0004 Olcm Satterthwaite Unequal 9.31 4.36 0.0017

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 57.50 <.0001

Comparison m Osteocalcin for Prostati and Aortic 274

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcin Aortic 10 3 .7596 4 .3479 4 .9362 0 .5656 0 8223 1.5013 0.26 Olcin Prostati 10 1 .5289 2 .1122 2 .6955 0 .5609 0 8154 1.4886 0.2579 Olcm Diff (1-2) 1 .4663 2 .2357 3 .0051 0 .6188 0 .8189 1.211 0.3662 T-Tests

Variable Method Variances DF t Value Pr > 11

Oicin Pooled Equal 18 S.10 <-0001

01cm Satterthwaite Unequal 18 6.10 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

01cm Folded F 9 9 1.02 0.9803

Comparison in Osteocalcin for Prostati and Parkmso 275

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

01cm Parkmso 10 2 .1237 2 .5666 3.0095 0 .4259 0. 6192 1.1304 0 .1958

01cm Prostati 10 1 .5289 2 .1122 2.6955 0 .5609 0. 8154 1.4886 0 .2579

Olcm Diff (1-2) - 0.226 0 .4544 1.1346 0 .5471 0 .724 1.0706 0 .3238

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcm Pooled Equal 18 1.40 0 .1775

Olcm Satterthwaite Unequal 16.8 1.40 0 .1787

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 1.73 0.4246

Comparison m Osteocalcin for Arthπti and Aortic 276

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Aortic 10 3.7596 4.3479 4.9362 0.5656 0.8223 1.5013 0.26

Olcm Arthriti 10 6.2895 10.713 15.136 4.2532 6.1835 11.289 1.9554

Olcm Diff (1-2) -10.51 -6.3S5 -2.221 3.3329 4.4109 6.5229 1.9726

T-Tests

Variable Method Variances t Value Pr > |t|

Olcm Pooled Equal 18 -3.23 0.0047 Olcm Satterthwaite Unequal 9.32 -3.23 0.0099

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Olcm Folded F 9 9 56.54 <.0001

Comparison in Osteocalcin for Arthriti and Parkmso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Std Dev Std Dev Std Dev Std Err

Olcm Arthriti 10 6. .2895 10 .713 15.136 4 .2532 6.1835 11 .289 1 .9554 Olcm Parkmso 10 2. .1237 2 .5666 3 .0095 0 .4259 0 .6192 1 .1304 0 .1958 Olcm Diff (1-2 ) 4 .0176 8 .1463 12 .275 3 .3203 4 .3942 6 .4983 1 .9652 T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcxn Pooled Equal 18 4.15 0 .0006

01cm Ξatterthwaite Unequal 9.18 4.15 0 .0024

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

01cm Folded F 9 9 99.73 -=.0001

Comparison m Osteocalcin for Aortic and Parkmso 278

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

01cm Aortic 10 3 .7595 4 .3479 4.9362 0 .5656 0.8223 1.50 0.2S

Olcin Parkmso 10 2 .1237 2 .5666 3.0095 0 .4259 0.6192 1.13 0.1958

01cm Diff (1-2) 1 .0974 1 .7813 2.4652 0.55 0.7279 1.07 0.3255

T-Tests

Variable Method Variances DF t Value Pr > |t|

Olcin Pooled Equal 18 5 47 < .0001

01cm Satterthwaite Unequal 16.7 5.47 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

01cm Folded F 9 9 1.76 0.4107

Comparison in Troponin C for Cstitis and KidSton 279

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Cstitis 10 0.1043 0 .7169 1.3295 0.5891 0.8564 1.5635 0.2708

TroC KidSton 10 -0.034 0 .0653 0.165 0.09S9 0.1394 0.2545 0.0441

TroC Diff (1-2) 0.0751 0 .6516 1.2281 0.4636 0.6135 0.9073 0.2744

T-Tests

Variable Method Variances t Value Pr > |t|

TroC Pooled Equal 18 2.37 0.0289 TroC Satterthwaite Unequal 9.48 2.37 0.0403

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 37.74 <.0001

Comparison m Troponin C for Cstitis and Endoaden 280

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Cstitis 10 0.1043 0. 7169 1 .3295 0 .5891 0 .8564 1.5635 0.2708

TroC Endoaden 10 0.5658 0. 9502 1 .3346 0 .3696 0 .5373 0.9809 0.1699

TroC Diff (1-2) -0.905 -0 .233 0 .4384 0 .5402 0 .7149 1.0572 0.3197 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -0.73 0.4749 TroC Satterthwaite Unequal 15.1 -0.73 0.4767

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

TroC Folded F 9 9 2.54 0.1811

Comparison in Troponin C for Ostitis and Prostate 281

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Cstitis 10 0.1043 0.7169 1.3295 0.5891 0.8564 1.5635 0.2708

TroC Prostate 10 -0.048 0.1119 0.2717 0.1536 0.2234 0.4078 0.0706

TroC Diff (1-2) 0.017 0.605 1.193 0.4729 0.6258 0.9255 0.2799

T-Tests

Variable Method Variances t Value Pr > |t|

TroC Pooled Equal 18 2.16 0.0444 TroC Satterthwaite Unequal 10.2 2.16 0.0554

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 14 70 0.0005

Comparison in Troponin C for Cstitis and Prostati

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Cstitis 10 0.1043 0 .7169 1.3295 0. 5891 0.8564 1.5635 0. 2708

TroC Prostati 10 0.441 0 .6432 0.8454 0. 1944 0.2827 0.5161 0. 0894

TroC Diff (1-2) -0.525 0 .0737 0.6729 0. 4819 0.6377 0.943 0. 2852

T-Tests

Variable Method Variances DF t Value Pr > It=I

TroC Pooled Equal 18 0.26 0 .7990

TroC Satterthwaite Unequal 10.9 0.26 0 .8009

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 9.18 0.0029

Comparison in Troponin C for Cstitis and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Arthriti 10 0.3642 0.9682 1 .5722 0 .5807 0 .8443 1 .5414 0.267

TroC Cstitis 10 0.1043 0.7169 1 .3295 0 .5891 0 .8564 1 .5635 0 .2708

TroC Diff (1-2) -0.548 0.2513 1 .0503 0 .6426 0 .8504 1 .2576 0 .3803 T-Tests

Variable Method Variances DF t Value Pr > ItI

TroC Pooled Equal 18 0.66 0 5171

TroC Satterthwaite Unequal 18 0.66 0 5171

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 1.03 0 9669

Comparison m Troponin C for Ostitis and Aortic 284

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC ^■tic 10 0, .0721 0. 2331 0.3941 0. 1548 0 2251 0.4109 0.0712 TroC ltlS 10 0 1043 0 7169 1.3295 0 5891 0 8564 1 5635 0.2708 TroC f (1-2) -1.072 -0 484 0.1045 0 4731 0 6261 0.9259 0.28

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -1.73 0 .1011

TroC Satterthwaite Unequal 10.2 -1.73 0 .1140

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 14 48 0.0005

Comparison in Troponin C for Ostitis and Parkmso 285

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Ostitis 10 0 1043 0 7169 1.3295 0 .5891 0.8564 1.5635 0.2708 TroC Parkmso 10 2 3304 2 547 2 7636 0.2082 0.3027 0.5527 0.0957 TroC Dlff (1-2) Ϊ.434 -1.83 -1.227 0 4853 0.6423 0.9498 0.2872

T-TestS

Variable Method Variances DF t Value

TroC Pooled Equal 18 -6 37 <.0001 TroC Satterthwaite Unequal 11.2 -6..37 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 8.00 0.0048

Comparison in Troponin C for KidSton and Endoaden 286

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Endoaden 10 0. 5658 0 .9502 1 .3346 0 .3696 0 .5373 0 .9809 0 .1699

TroC KidSton 10 -0 .034 0 .0653 0.165 0 .0959 0 .1394 0 .2545 0 .0441

TroC Dlff (1-2) 0. 5161 0 .8849 1 .2537 0 .2966 0 .3925 0 .5805 0 .1755 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 S.04 <.0001

TroC Satterthwaite Unequal 10.2 5.04 0.0005

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 14.86 0.0004

Comparison in Troponin C for KidSton and Prostate

The TTEST Procedure Statistics

Lower CL . Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC KidSton 10 -0.034 0. 0S53 0.165 0. .0959 0.1394 0.2545 0. 0441

TroC Prostate 10 -0.048 0. 1119 0.2717 0. .1536 0.2234 0.4078 0. 0706

TroC Diff (1-2) -0.222 -0 .047 0.1283 0 .1407 0.1862 0.2753 0. 0833

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -0.56 0.5826

TroC Satterthwaite Unequal 15.1 -0.56 0.5839

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 2.57 0.1764

Comparison in Troponin C for KidSton and Prostati 288

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC KidSton 10 -0 .034 0. 0653 0.165 0.0959 0.1394 0.2545 0.0441

TroC Prostati 10 0 .441 0. 6432 0.8454 0.1944 0.2827 0.5161 0.0894

TroC Diff (1-2) -0 .787 -0 .578 -0.369 0.1684 0.2229 0.3296 0.0997

T-Tests

Variable Method Variances DP t Value

TroC Pooled Equal 18 -5.80 <-0001 TroC Satterthwaite Unequal 13.1 -5.80 ■=.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 4.11 0.0468

Comparison in Troponin C for KidSton and Arthriti

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Arthriti 10 0. 3642 0 .9682 1.5722 0 .5807 0. 8443 1. 5414 0.267

TroC KidSton 10 -0 .034 0 .0653 0.165 0 .0959 0. 1394 0. 2545 0.0441

TroC Diff (1-2) 0. 3344 0 .9029 1.4714 0, .4572 0. 6051 0. 8948 0.2706 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 3.34 0.0037

TroC Satterthwaite Unequal 9.49 3.34 0.0081

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

TroC Folded F 9 9 36.69 <.0001

Comparison in Troponin C for KidSton and Aortic 290

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0. 0721 0 .2331 0.3941 0.1548 0.2251 0.4109 0.0712

TroC KidSton 10 -0 .034 0 .0653 0.165 0.0959 0.1394 0.2545 0.0441

TroC Diff (1-2) -0 .008 0 .1678 0.3437 0.1415 0.1872 0.27S8 0.0837

T-Tests

Variable Method Variances t Value Pr > |t|

TroC Pooled Equal 18 2.00 0.0603 TroC Satterthwaite Unequal 15 2.00 0.0634

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 2.61 0.1697

Comparison in Troponin C for KidSton and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC KidSton 10 -0.034 0.0653 0.165 0.0959 0.1394 0.2545 0.0441

TroC Parkinso 10 2.3304 2.547 2.7636 0.2082 0.3027 0.5527 0.0957

TroC Diff (1-2) -2.703 -2.482 -2.26 0.1781 0.2357 0.3485 0.1054

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -23.55 < .0001 TroC Satterthwaite Unequal 12.7 -23.55 .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 4.72 0.0303

Comparison in Troponin C for Endoaden and Prostate 292

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Endoaden 10 0. 5S58 0 .9502 1 .3346 0.3696 0 .5373 0 .9809 0 .1699

TroC Prostate 10 -0 .048 0 .1119 0 .2717 0.1536 0 .2234 0 .4078 0 .0706

TroC Diff (1-2) 0. 4517 0 .8383 1 .2249 0.3109 0 .4115 0 .6085 0.184 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 4.56 0.0002

TroC Satterthwaite Unequal 12 4.56 0.0007

Equality of Variances

Variable Method Num DF Den DF F.Value Pr > F

TroC Folded F 9 9 5.79 0.0153

Comparison in Troponin C for Endoaden and Prostati 293

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Endoaden 10 0.5658 0 .9502 1. 3346 0 .3696 0.5373 0.9809 0.1699

TroC Prostati 10 0.441 0 .6432 0. 8454 0 .1944 0.2827 0.5161 0.0894

TroC Diff (1-2) -0.096 0.307 0. 7104 0 .3244 0.4293 0.6349 0.192

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 1.60 0 .1272

TroC Satterthwaite Unequal 13.6 1.60 0 .1327

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 3.61 0.0692

Comparison in Troponin C for Endoaden and Arthriti 294

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Arthriti 10 0.3642 0.9682 1.5722 0.5807 0.8443 1.5414 0.267

TroC Endoaden 10 0.5658 0.9502 1.3346 0.3696 0.5373 0.9809 0.1699

TroC Diff (1-2) -0.647 0.018 0.6829 0.5347 0.7077 1.0465 0.3165

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 0.06 0.9553

TroC Satterthwaite Unequal 15.3 0.06 0.9554

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 2.47 0.1943

Comparison in Troponin C for Endoaden and Aortic 295

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0.0721 0.2331 0 .3941 0 .1548 0 .2251 0 .4109 0 .0712

TroC Endoaden 10 0.5658 0.9502 1 .3346 0 .3696 0 .5373 0 .9809 0 .1699

TroC Diff (1-2) -1.104 -0.717 -0.33 0 .3113 0 .4119 0 .6092 0 .1842 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -3 89 0 0011 TroC Satterthwaite Unequal 12.1 -3.89 0 0021

Equality of Variances

Variable Method Nura DF Den DP F Value Pr _> F

TroC Folded F 9 9 S.70 0.0162

Comparison in Troponin C for Endoaden and Parkmso 29S

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Endoaden 10 0. 5658 0. 9502 1.3346 0.3S96 0 5373 0.9809 0.1699

TroC Parkmso 10 2. 3304 2 S47 2.7636 0.2082 0.3027 0 5527 0.0957

TroC Dlff (1-2) -2 007 -1 .597 -1.187 0.3295 0.43S1 0.6449 0.195

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -8.19 <.0001 TroC Satterthwaite Unequal 14.2 -8.19 <.0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

TroC Folded F 9 9 3.15 0.1025

Comparison m Troponin C for Prostate and Prostati 297

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Prostate 10 -0 048 0. 1119 0.2717 0.1536 0.2234 0.4078 0.0706

TroC Prostati 10 0 .441 0. 6432 0 8454 0 1944 0.2827 0.5161 0.0894

TroC Dlff (1-2) -0 .771 -0 531 -0 292 0.1925 0.2547 0.3767 0.1139

T-Tests

Variable Method Variances t Value Pr > |t|

TroC Pooled Equal 18 -4.66 0.0002 TroC Satterthwaite Unequal 17.1 -4.66 0 0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 1.60 0.4938

Comparison m Troponin C for Prostate and Arthriti 298

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Arthriti 10 0.3642 0 .9682 1. 5722 0 .5807 0 .8443 1.5414 0.267

TroC Prostate 10 -0.048 0 .1119 0. 2717 0 .1536 0 .2234 0.4078 0.0706

TroC Dlff (1-2) 0.2761 0 .8563 1. 4365 0 .4666 0 .6176 0.9133 0.2762 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 3.10 0 .00S2

TroC Satterthwaite Unequal 10.3 3.10 0 .0109

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 14.29 0.0005

Comparison in Troponin C for Prostate and Aortic

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0.0721 0 .2331 0.3941 0.1548 0.2251 0.4109 0.0712

TroC Prostate 10 -0.048 0 .1119 0.2717 0.1536 0.2234 0.4078 0.0706

TroC Diff (1-2) -0.089 0 .1212 0.3319 0.1694 0.2242 0.3316 0.1003

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 1.21 0.2424

TroC Satterthwaite Unequal 18 1.21 0.2424

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 1.02 0.9821

Comparison in Troponin C for Prostate and Parkinso 300

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Parkinso 10 2.3304 2 .547 2.7636 0.2082 0.3027 0.5527 0.0957

TroC Prostate 10 -0.048 0. 1119 0.2717 0.1536 0.2234 0.4078 0.0706

TroC Diff (1-2) 2.1852 2. 4351 2.685 0.201 0.266 0.3934 0.119

T-Tests

Variable Method Variances DF t Value Pr |t|

TroC Pooled Equal "^* 18 20.47 <.0001 TroC Satterthwaite Unequal 16.6 20.47 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F TroC Folded F 9 9 1.84 0.3784

Comparison in Troponin C for Prostati and Arthriti 3

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev std Dev Std Err

TroC Arthriti 10 0.3642 0 .9682 1 .5722 0 .5807 0 .8443 1 .5414 0.267

TroC Prostati 10 0.441 0 .6432 0 .8454 0 .1944 0 .2827 0 .5161 0 .0894

TroC Diff (1-2) -0.267 0.325 0 .9165 0 .4757 0 .6296 0 .9311 0 .2816 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 1.15 0 .2635 TroC Satterthwaite Unequal 11 1.15 0.2729

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 8.92 0.0032

Comparison in Troponin C for Prostati and Aortic 302

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0.0721 0.2331 0.3941 0.1548 0.2251 0.4109 0.0712 TroC Prostati 10 0.441 0.6432 0.8454 0.1944 0.2827 0.5161 0.0894 TroC Diff (1-2) -0.65 -0.41 -0.17 0.1931 0.2555 0.3778 0.1143

T-Tests

Variable Method Variances t value Pr > |t|

TroC Pooled Equal 18 -3.59 0.0021 TroC Satterthwaite Unequal 17.1 -3.59 0.0022

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 1.58 0.5079

Comparison in Troponin C for Prostati and Parkinso 303

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Parkinso 10 2.3304 2.547 2.7S36 0. .2082 0.3027 0.5527 0.0957

TroC Prostati 10 0.441 0.6432 0.8454 0. .1944 0.2827 0.5161 0.0894

TroC Diff (1-2) 1.6286 1.9038 2.179 0. .2213 0.2929 0.4331 0.131

T-TeStS

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 14.54 <.0001

TroC Satterthwaite Unequal 17.9 14.54 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 1.15 0.8415

Comparison in Troponin C for Arthriti and Aortic 304

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0.0721 0.2331 0.3941 0.1548 0.2251 0.4109 0.0712 TroC Arthriti 10 0.3642 0.9682 1.5722 0.5807 .0.8443 1.5414 0.267 TroC Diff (1-2) -1.316 -0.735 -0.155 0.4669 0.6179 0.9137 0.2763 T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -2.66 0.0159

TroC Satterthwaite Unequal 10.3 -2.66 0.0234

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 14.07 0.0005

Comparison in Troponin C for Arthriti and Parkinso 305

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Arthriti 10 0.3642 0.9682 1.5722 0 .5807 0 .8443 1 .5414 0.267 TroC Parkinso 10 2.3304 2.547 2.7636 0 .2082 0 .3027 0 .5527 0.0957 TroC Diff (1-2) -2.175 -1.579 -0.983 0 .4792 0 .6342 0 .9379 0.2836

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -5.57 <.0001 TroC Satterthwaite Unequal 11.3 -5.57 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

TroC Folded F 9 9 7.78 0.0054

Comparison in Troponin C for Aortic and Parkinso 306

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

TroC Aortic 10 0.0721 0. 2331 0.3941 0 .1548 0.2251 0.4109 0 .0712

TroC Parkinso 10 2.3304 2 .547 2.7636 0 .2082 0.3027 0.5527 0 .0957

TroC Diff (1-2) -2.565 -2 .314 -2.063 0 .2016 0.2667 0.3945 0 .1193

T-Tests

Variable Method Variances DF t Value Pr > |t|

TroC Pooled Equal 18 -19 .40 < .0001

TroC Satterthwaite Unequal 16.6 -19 .40 < .0001

Equality of Variances

Variable Method , Num DF Den DF F Value Pr > F TroC Folded F 9 9 1.81 0.3904 Comparison in Abeam Transglutaminase 2 for Cstitis and KldSton 307

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Cstitxs 10 0. 2326 0 .5033 0.774 0 .2603 0 .3785 0 .691 0.1197

AbT KidSton 10 -0 .018 0 .0466 0 .1115 0 .0624 0 .0907 0. 1655 0.0287

AbT Diff (1-2) 0. 1981 0 .4567 0 .7153 0 .2079 0 .2752 0 .407 0.1231 T-Tests

Variable Method Variances DF t Value Pr > M

AbT Pooled Equal 18 3.71 0 .0016 AbT Satterthwaite Unequal 10 3.71 0.0040

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 17.43 0.0002

Comparison, in Abeam Transglutaminase 2 for Cstitis and Endoaden 308

The TTEST Procedure Statistics

Lower CB Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Cstitis 10 0.232S 0.5033 0.774 0.2603 0.3785 0.691 0.1197

AbT Endoaden 10 0.0S85 0.3355 0.6025 0.2568 0.3733 0.S815 0.118

AbT Diff (1-2) -0.185 0.1678 0.521 0.284 0.3759 0.5559 0.1681

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 1.00 0.3314 AbT Satterthwaite Unequal 18 1.00 0.3314

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 1.03 0.9679

Comparison in Abeam Transglutaminase 2 for Cstitis and Prostate

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Cstitis 10 0.2326- 0 .5033 0.774 0.2603 0.3785 0.691 0.1197 AbT Prostate 10 0.0132 0.0745 0.1358 0.059 0.0857 0.1565 0.0271 AbT Diff (1-2) 0.171 0.4288 0.68S6 0.2073 0.2744 0.4058 0.1227

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 3.49 0.0026 AbT Satterthwaite Unequal 9.92 3.49 0.0059

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 19.49 0.0001

Comparison in Abeam Transglutaminase 2 for Cstitis and Prostati 310

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Cstitis 10 0. 2326 0. 5033 0.774 0 .2603 0 .3785 0.691 0.1197

AbT Prostati 10 0. 0157 0. 5121 1 .0085 0 .4773 0 .6939 1.2668 0.2194

AbT Diff (1-2) -0 .534 -0 .009 0 .5163 0 .4223 0 .5589 0.8265 0.25 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 -0 04 0 9723

AbT Satterthwaite Unequal 13.9 -0 04 0. 9724

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 3 36 0.0854 Comparison in Abeam Transglutaminase 2 for Cstitis and Arthπti 311

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N N M Meeaann M Meeaann Mean Std Dev Std Dev Std Dev Std Err

AbT Arthrαti 1 100 11 . .77771144 2 2 . .55663355 3 3556 0 7616 1.1073 2 0214 0 .3501

AbT Cstitis 1 100 00 . .22332266 0 0 . .55003333 0 774 0 2603 0.3785 0 691 0 .1197

AbT Diff (1-2) 1 1 . .22882288 2 2 . .00660022 2.8376 0 6252 0.8274 1.2236 0.37

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 5.57 < 0001

AbT Satterthwaite Unequal 11.1 5.57 0 0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 8 56 0.0038 Comparison m Abeam Transglutaminase 2 for Cstitis and Aortic 312

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0 155 3.8143 7.7834 3.8164 5 5484 10 129 1 7545

AbT Cstitis 10 0.2326 0.5033 0.774 0 2603 0.3785 0.691 0.1197

AbT Diff (1-2) -0.384 3.311 7.0057 2 9714 3.9324 5.8153 1 7586

T-Tests

Variable Method Variances DF t Value Pr > ItI

AbT Pooled Equal 18 1.88 0 0760

AbT Satterthwaite Unequal 9.08 1.88 0 .0921

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 214.91 <.0001

Comparison in Abeam Transglutaminase 2 for Cstitis and Parkinso 313

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Cstitis 10 0. 2326 0. 5033 0 .774 0.2603 0.3785 0.691 0.1197

AbT Parkinso 10 2. 7719 3. 0739 3. 3759 0.2904 0.4222 0.7708 0.1335

AbT Diff (1-2) -2 .947 -2 .571 -2 .194 0.303 0.4009 0.5929 0.1793 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 -14.34 <.0001

AbT Satterthwaite Unequal 17.8 -14.34 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 1.24 0.7499

Comparison in Abeam Transglutaminase 2 for Kidston and Endoaden

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Endoaden 10 0. 0S85 0 .3355 0.6025 0.2568 0.3733 0.6815 0.118

AbT KidSton 10 -0 .018 0 .0466 0.1115 0.0624 0.0907 0.1655 0.0287

AbT Diff (1-2) 0. 0337 0 .2889 0.5441 0.2052 0.2716 0.4017 0.1215

T-Tests

Variable Method Variances t Value Pr > ] t |

AbT Pooled Ec[UaI 18 2.38 0.0287 AbT Satterthwaite Unequal 10.1 2.38 0.0386

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

AbT Folded F 9 9 16.95 0.0003

Comparison in Abeam Transglutaminase 2 for KidSton and Prostate 315

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT KidSton 10 -0 .018 0. 0466 0. 1115 0. 0624 0. 0907 0 .1655 0 .0287 AbT Prostate 10 0.0132 0. 0745 0. 1358 0 .059 0. 0857 0 .1565 0 .0271 AbT Diff (1-2) -0 .111 -0 .028 0 .055 0. 0667 0. 0882 0 .1305 0 .0395

T-Tests

Variable Method Variances DF t Value Pr > ItI

AbT Pooled Equal 18 -0 .71 0 .4886 AbT Satterthwaite Unequal 17.9 -0 .71 0 .4886

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 1.12 0.8702

Comparison in Abeam Transglutaminase 2 for KidSton and Prostati 316

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT KidSton 10 -0.018 0. 0466 0.1115 0 .0624 0 .0907 0.1655 0.0287

AbT Prostati 10 0.0157 0. 5121 1.0085 0 .4773 0 .6939 1.2668 0.2194

AbT Diff (1-2) -0.93 -0 .466 -57E-5 0 .3739 0 .4948 0.7318 0.2213 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 -2.10 0.0498 AbT Satterthwaite Unequal 9.31 -2.10 0.0637

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 58.58 <.0001

Comparison in Abeam Transglutaminase 2 for KidSton and Arthriti 317

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Arthriti 10 1. 7714 2 .5635 3.355S 0.7616 1.1073 2.0214 0.3501

AbT KidSton 10 -0 .018 0 .046S 0.1115 0.0624 0.0907 0.1655 0.0287

AbT Diff (1-2) 1. 7788 2 .5169 3.255 0.5936 0.785S 1.1617 0.3513

T-Tests

Variable Method Variances DF t Value Pr > ]t|

AbT Pooled Equal 18 7.16 c.0001 AbT Satterthwaite Unequal 9.12 7.16 .= .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 149.15 <.0001 Comparison in Abeam Transglutaminase 2 for KidSton and Aortic 318

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0 .155 3 .8143 7.7834 3.8164 5.5484 10.129 1.7545

AbT KidSton 10 -0 .018 0 .0466 0.1115 0.0624 0.0907 0.1655 0.0287

AbT Diff (1-2) 0 .081 3 .7677 7.4544 2.9649 3.9238 5.8026 1.7548

T-Tests

Variable Method Variances t Value Pr > |t|

AbT Pooled Equal 18 2.15 0.0457 AbT Satterthwaite Unequal 9 2.15 0.0603

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

AbT Folded F 9 9 3744.92 <.0001

Comparison in Abeam Transglutaminase 2 for KidSton and Parkinso 319

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Std Dev Std Dev Std Dev Std Err

AbT KidSton 10 -0.018 0.0466 0 .1115 0 .0624 0 .0907 0 .1655 0 .0287 AbT Parkinso 10 2.7719 3.0739 3 .3759 0 .2904 0 .4222 0 .7708 0 .1335 AbT Diff (1-2) -3.314 -3.027 -2.74 0 .2307 0 .3054 0 .4516 0 .1366 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 -22 17 ■c.OOOl

AbT Satterthwaite Unequal 9.83 -22.17 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 21.69 <.0001

Comparison in Abeam Transglutaminase 2 for Endoaden and Prostate 320

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Endoaden 10 0.0685 0.335S 0.6025 0.2568 0.3733 0.6815 0.118 AbT Prostate 10 0.0132 0.074S 0.1358 0.059 0.0857 0.1565 0.0271 AbT Diff (1-2) 0.006S 0.261 0.5155 0.2046 0.2708 0.4005 0.1211

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 2 .15 0.0450 AbT Satterthwaite Unequal 9.95 2 .15 0.0567

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 18.96 0.0002

Comparison in Abeam Transglutaminase 2 for Endoaden and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Endoaden 10 0.0685 0 .3355 0. 6025 0 .2568 0.3733 0.6815 0.118

AbT Prostati 10 0.0157 0 .5121 1. 0085 0 .4773 0.6939 1.2668 0 .2194

AbT Diff (1-2) -0.7 - 0.177 0. 3469 0.421 0.5572 0.8239 0 .2492

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 -0 .71 0 .4876 AbT Satterthwaite unequal 13.8 -0 .71 0 .4903

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 3.46 0.0789

Comparison in Abeam Transglutaminase 2 for Endoaden and Arthriti 322

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Arthriti 10 1 .7714 2 .5635 3 .3556 0 .7616 1 .1073 2.0214 0.3501

AbT Endoaden 10 0 .0685 0 .3355 0 .6025 0 .2568 0 .3733 0.6815 0.118

AbT Diff (1-2) 1 .4517 2.228 3 .0043 0 .6243 0 .8262 1.2219 0.3695 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 6 03 < 0001

AbT Satterthwaite Unequal 11 6.03 <.0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F AbT Folded F 9 9 8.80 0.0034 Comparison in Abeam Transglutaminase 2 for Endoaden and Aortic 323

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0.1S5 3 .8143 7.7834 3.8164 5.5484 10.129 1.7545

AbT Endoaden 10 0.0685 0 .3355 0.6025 0.2568 0.3733 0.6815 0.118

AbT Diff (1-2) -0.216 3 .4788 7.1733 2.9712 3.9321 5.815 1.7585

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 1.98 0.0634 AbT Satterthwaite Unequal 9.08 1.98 0.0790

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 220.92 <.0001

Comparison in Abeam Transglutaminase 2 for Endoaden and Parkmso 324

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Endoaden 10 0. 0685 0. 3355 0.6025 0.2568 0.3733 0.6815 0.118

AbT Parkmso 10 2. 7719 3. 0739 3.3759 0.2904 0.4222 0.7708 0.1335

AbT Diff (1-2) —3 .113 -2 .738 -2.364 0.3011 0.3985 0.5893 0.1782

T-Tests

Variable Method Variances t Value Pr > |t|

AbT Pooled Equal 18 -15.37 <.0001 AbT Satterthwaite Unequal 17.7 -15.37 <.0001

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

AbT Folded F 9 9 1.28 0.7196

Comparison in Abeam Transglutaminase 2 for Prostate and Prostati 325

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Prostate 10 0. 0132 0. 0745 0 .1358 0.059 0 .0857 0.1565 0 .0271

AbT Prostati 10 0. 0157 0. 5121 1 .0085 0 .4773 0 .6939 1.2668 0 .2194

AbT Diff (1-2) -0 .902 -0 .438 0 .0269 0 .3736 0 .4944 0.7311 0 .2211 T-Tests

Variable Method Variances DF t Value Pr > It=I

AbT Pooled Equal 18 -1.98 0 .0633

AbT Satterthwaite Unequal 9.27 -1.98 0 .0782

Equality of Variances

Variable Method Nura DP Den DP F Value Pr > F

AbT Folded F 9 9 65.52 _<.0001

Comparison in Abeam Transglutaminase 2 for Prostate and Arthriti 326

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Arthriti 10 1. .7714 2 .5635 3.3556 0 .7616 1.1073 2 .0214 0 .3501

AbT Prostate 10 0. .0132 0 .0745 0.1358 0.059 0.0857 0 .1565 0 .0271

AbT Diff (1-2) 1. .7512 2.489 3.2268 0 .5934 0.7853 1 .1613 0 .3512

T-Tests

Variable Method Variances DF t Value Pr >

AbT Pooled Equal 18 7.09 < .0001

AbT Satterthwaite Unequal 9 .11 7.09 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 166.83 <.0001 Comparison in Abeam Transglutaminase 2 for Prostate and Aortic 327

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0.155 3 .8143 7.7834 3.8164 5.5484 10.129 1.7545

AbT Prostate 10 0.0132 0 .0745 0.1358 0.059 0.0857 0.1565 0.0271

AbT Diff (1-2) 0.0532 3 .7398 7.4264 2.9648 3.9237 5.8025 1.7548

T-TeStS

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 2.13 0.0471

AbT Satterthwaite Unequal 9 2.13 0.0619

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 4188.81 <.0001

Comparison in Abeam Transglutaminase 2 for Prostate and Parkinso 328

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Parkinso 10 2.7719 3.0739 3 .3759 0 .2904 0 .4222 0 .7708 0 .1335 AbT Prostate 10 0.0132 0.0745 0 .1358 0.059 0 .0857 0 .1565 0 .0271 AbT Diff (1-2) 2.7132 2. 9994 3 .2856 0 .2302 0 .3046 0 .4505 0 .1362 T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 22.02 <.0001 AbT Satterthwaite Unequal 9.74 22.02 <.0001

Equality of Variances

Variable Method Nutn DF Den DF F Value Pr _> F

AbT Folded F 9 9 24.25 <.0001

Comparison in Abeam Transglutaminase 2 for Prostati and Arthriti 329

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Arthriti 10 1 .7714 2 .5635 3.3556 0 .7616 1.1073 2.0214 0 .3501

AbT Prostati 10 0 .0157 0 .5121 1.0085 0 .4773 0.6939 1.2668 0 .2194

AbT Diff (1-2) 1 .1832 2 .0514 2.9196 0 .6982 0.924 1.3664 0 .4132

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 4.96 0 .0001

AbT Satterthwaite Unequal 15.1 4.96 0 .0002

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F AbT Folded F 9 9 2.55 0.1801

Comparison in Abeam Transglutaminase 2 for Prostati and Aortic 330

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0.155 3 .8143 7.7834 3.8164 5.5484 10.129 1.7545

AbT Prostati 10 0.0157 0 .5121 1.0085 0.4773 0.6939 1.2668 0.2194

AbT Diff (1-2) -0.413 3 .3022 7.0171 2.9876 3.9538 5.847 1.7682

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 1.87 0.0782 AbT Satterthwaite Unequal 9.28 1.87 0.0937

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 63.93 <.0001

Comparison in Abeam Transglutaminase 2 for Prostati and Parkinso 331

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Parkinso 10 2 .7719 3 .0739 3 .3759 0.2904 0.4222 0. 7708 0.1335

AbT Prostati 10 0 .0157 0 .5121 1 .0085 0.4773 0.6939 1. 2668 0.2194

AbT Diff (1-2) 2 .0221 2 .5618 3 .1015 0.434 0.5744 0. 8494 0.2569 T-τests

Variable Method Variances DF t Value Pr > 11 J

AbT Pooled Equal 18 9.97 <.0001

AbT Satterthwaite Unequal 14.9 9.97 <=.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 2.70 0.1549 Comparison in Abeam Transglutaminase 2 for Arthriti and Aortic 332

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0 .155 3 .8143 7.7834 3.8164 5.5484 10.129 1.7545

AbT Arthriti 10 1. 7714 2 .5635 3.355S 0.7616 1.1073 2.0214 0.3501

AbT Diff (1-2) -2 .508 1 .2508 5.0096 3.0229 4.0006 5.9162 1.7891

T-Tests

Variable Method Variances DF t Value Pr > |t|

AbT Pooled Equal 18 0.70 0.4934 AbT Satterthwaite Unequal 9.72 0.70 0.5009

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 25.11 <.0001

Comparison in Abeam Transglutaminase 2 for Arthriti and Parkinso 333

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Arthriti 10 1. 7714 2 .5635 3.3556 0.7616 1.1073 2.0214 0.3501

AbT Parkinso 10 2. 7719 3 .0739 3.3759 0.2904 0.4222 0.7708 0.1335

AbT Diff (1-2) -1 .298 -0.51 0.2769 0.6332 0.8379 1.2392 0.3747

T-Tests

Variable Method Variances t Value Pr > |t|

AbT Pooled Equal 18 -1.36 0.1900 AbT Satterthwaite Unequal 11.6 -1.36 0.1991

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F AbT Folded F 9 9 6.88 0.0084 Comparison in Abeam Transglutaminase 2 for Aortic and Parkinso 334

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

AbT Aortic 10 -0.155 3.8143 7.7834 3.8164 5.5484 10.129 1.7545 AbT Parkinso 10 2.7719 3.0739 3.3759 0.2904 0.4222 0.7708 0.1335 AbT Diff (1-2) -2.956 0.7404 4.4372 2.9731 3.9346 5.8186 1.7596 T-Tests

Variable Method Variances DF t Value Pr > ItI

AbT Pooled Equal 18 0.42 0 .6789

AbT Satterthwaite Unequal 9.1 0.42 0 .5837

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

AbT Folded F 9 9 172.68 <.0001

Comparison in PGRP-I Beeta for Cstitis and KidSton 335

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Cstitis 10 102.25 190.7 279 .14 85 .043 123 .64 225. 39.098

PGRP KidSton 10 47.433 55.486 63. 539 7. 7434 11. 258 20.5 3.56

PGRP Diff (1-2) 52.728 135.21 217 .69 66 .333 87. 787 129. 39.26

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 3.44 0 .0029

PGRP Satterthwaite Unequal 9 .15 3.44 0 .0072

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 120.62 <.0001

Comparison in PGRP-I Beeta for Cstitis and Endoaden 336

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Cstitis 10 102.25 190.7 279.14 85.043 123.64 225.72 39.098 PGRP Endoaden 10 319.45 512.2 704.94 185.33 269.44 491.89 85.203 PGRP Diff (1-2) -518.5 -321.5 -124.5 158.39 209.62 309.99 93.746

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -3.43 0.0030 PGRP Satterthwaite Unequal 12.6 -3.43 0.0047

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 4.75 0.0297

Comparison in PGRP-I Beeta for Cstitis and Prostate 337

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Cstitis 10 102.25 190.7 279.14 85.043 123.64 225.72 39.098

PGRP Prostate 10 -0.141 1.0337 2.2086 1.1297 1.6424 2.9985 0.5194

PGRP Diff (1-2) 107.51 189.66 271.81 66.066 87.433 129.3 39.101 T-Tests

Variable Method Variances DP t Value Pr > |t|

PGRP Pooled Equal 18 4.85 0.0001 PGRP Satterthwaite Unequal 9 4.85 0.0009

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

PGRP Folded F 9 9 5666.64 <.0001

Comparison in PGRP-I Beeta for Cstitis and Prostati 338

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Cstitis 10 102.25 190.7 279 .14 85. 043 123 .64 225.72 39. 098

PGRP Prostati 10 195.76 387.17 578 .58 184 .05 267 .57 488.48 84. 614

PGRP Diff (1-2) -392.3 -196.5 -0. 642 157 .49 208 .42 308.22 93 .21

T-Tests

Variable Method Variances DF t Value Pr > It|

PGRP Pooled Equal 18 -2.11 0 .0493

PGRP Satterthwaite Unequal 12.7 -2.11 0 .0556

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 4.68 0.0310

Comparison in PGRP-I Beeta for Cstitis and Arthriti 339

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Arthriti 10 270.61 449.04 627 .46 171 .56 249 .42 455.34 78. 873

PGRP Cstitis 10 102.25 190.7 279. .14 85. 043 123. .64 225.72 39. 098

PGRP Diff (1-2) 73.393 258.34 443. .29 148 .74 196. .85 291.1 88. 032

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 2.93 0.0089

PGRP Satterthwaite Unequal 13 .2 2.93 0.0115

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 4.07 0.0484

Comparison in PGRP-I Beeta for Cstitis and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic 10 169.14 308.2 447 .26 133 .71 194. 39 354 .89 61.473

PGRP Cstitis 10 102.25 190.7 279 .14 85. 043 123. 64 225 .72 39.098

PGRP Diff (1-2) -35.55 117.51 270 .56 123 .09 162 .9 240 .91 72.853 T-Tests

Variable Method Variances DF t Value Pr > It]

PGRP Pooled Equal 18 1.61 0 .1242 PGRP Satterthwaite Unequal IS.3 1.Sl 0.1273

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

PGRP Folded F 9 9 2.47 0.1938

Comparison in PGRP-I Beeta for Cstitis and Parkmso 341

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean std Dev Std Dev Std Dev Std Err

PGRP Ostitis 10 102.25 190.7 279.14 85.043 123.54 225.72 39.098

PGRP Parkmso 10 79.041 83.549 88.057 4.3348 S.302 11.505 1.9929

PGRP Diff (1-2) 24.898 107.15 189.39 6S.145 87.539 129.45 39.149

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 2.74 0.0135 PGRP Satterthwaite Unequal 9.05 2.74 0.0229

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 384.90 <.0001

Comparison in PGRP-I Beeta for Kidston and Endoaden 342

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Endoaden 10 319 .45 512.2 704.94 185.33 269.44 491.89 85.203

PGRP KidSton 10 47. 433 55.486 63.539 7.7434 11.258 20.552 3.56

PGRP Diff (1-2) 277 .55 456.71 635.87 144.09 190.69 281.99 85.278

T-Tests

Variable Method Variances DF t Value Pr >

PGRP Pooled Equal 18 5.36 <.oooi PGRP Satterthwaite Unequal 9.03 5.36 0.0005

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 572.82 <.0001

Comparison in PGRP-I Beeta for Kidston and Prostate 343

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP KidSton 10 47 .433 55.486 63 .539 7 .7434 11.258 20.552 3.56

PGRP Prostate 10 -0 .141 1.0337 2. 2086 1 .1297 1.6424 2.9985 0.5194

PGRP Diff (1-2) 46 .894 54.452 62 .011 6 .0786 8.0447 11.897 3.5977 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 15.14 <.0001

PGRP Satterthwaite unequal 9.38 15.14 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 46 98 <.0001

Comparison in PGRP-I Beeta for KidSton and Prostati 344

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP KidSton 10 47.433 55.486 63.539 7.7434 11.258 20.552 3.56 PGRP Prostati 10 195.76 387.17 578.58 184.05 267.57 488.48 84.614 PGRP Diff (1-2) -509.6 -331.7 -153.8 143.09 189.37 280.04 84.689

T-Tests

Variable Method Variances t Value Pr >

PGRP Pooled Equal 18 -3.92 0.0010 PGRP Satterthwaite Unequal 9.03 -3.92 0.0035

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 564.92 <.0001

Comparison m PGRP-I Beeta for KidSton and Arthπti 345

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Arthnti 10 270 .61 449 .04 627 .46 171.56 249.42 455.34 78.873

PGRP KidSton 10 47. 433 55. 486 63 .539 7.7434 11.258 20.552 3.56

PGRP Diff (1-2) 227 .68 393 .55 559.43 133.4 176.55 261.08 78.954

T-Tests

Variable Method Variances t Value Pr > |t|

PGRP Pooled Equal 18 4.98 <.0001 PGRP Satterthwaite Unequal 9.04 4.98 0.0007

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 490.86 <.0001

Comparison in PGRP-I Beeta for KidSton and Aortic 346

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic 10 169. .14 308.2 447 .26 133.71 194 .39 354 .89 61 .473

PGRP KidSton 10 47.433 55.486 63. 539 7.7434 11. 258 20. 552 3.56

PGRP Diff (1-2) 123, .35 252.72 382 .08 104.04 137 .69 203 .62 61 .576 T-Tests

Variable Method Variances DF t Value Pr > ItI

PGRP Pooled Equal 18 4.10 0 0007

PGRP Satterthwaite Unequal 9.06 4.10 0 .002S

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

PGRP Folded F 9 9 298.17 <.0001

Comparison in PGRP-I Beeta for KidSton and Parkmso 347

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Ston 10 47. .433 55. 486 63. 539 7 .7434 11 .258 20.552 3.56 PGRP kmso 10 79. .041 83. 549 88. 057 4 .3348 6 .302 11.505 1 .9929 PGRP f (1-2) -35.63 -28 .06 -19 .49 6 .8933 9. 1228 13.491 4 .0798

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -6.88 < .0001

PGRP Satterthwaite Unequal 14.1 -6.88 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 3.19 0.0989

Comparison m PGRP-I Beeta for Endoaden and Prostate 348

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Endoaden 10 319.45 512.2 704.94 185.33 269.44 491.89 85.203

PGRP Prostate 10 -0.141 1.0337 2.2086 1.1297 1.6424 2.9985 0.5194

PGRP Diff (1-2) 332.15 511.16 690.17 143.96 190.52 281.75 85.205

T-Tests

Variable Method Variances t Value Pr > |t|

PGRP Pooled Equal 18 6.00 <-0001 PGRP Satterthwaite Unequal 9 6.00 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 26911.4 <.0001

Comparison m PGRP-I Beeta for Endoaden and Prostati 349

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Endoaden 10 319.45 512.2 704 .94 185 .33 269 .44 491 .89 85. 203 PGRP Prostati 10 195.76 387.17 578 .58 184 .05 267 .57 488 .48 84. 614 PGRP Diff (1-2) -127.2 125.03 377 .31 202 .89 268 .51 397 .07 120 .08 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 1.04 0.3116

PGRP Satterthwaite Unequal 18 1.04 0.3116

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.01 0.9838

Comparison in PGRP-I Beeta for Endoaden and Arthriti 350

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Arthriti 10 270. 61 449. 04 627.46 171.56 249.42 455.34 78.873

PGRP Endoaden 10 319. 45 512 .2 704.94 185.33 269.44 491.89 85.203

PGRP Diff (1-2) -307 .1 -63. IS 180.77 196.17 259.62 383.93 116.11

T-Tests

Variable Method Variances t Value Pr > |t|

PGRP Pooled Equal 18 -0.54 0.5931 PGRP Satterthwaite Unequal 17.9 -0.54 0.5932

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.17 0.8219

Comparison in PGRP-I Beeta for Endoaden and Aortic 351

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic IQ 169.14 308.2 447.26 133 .71 194 .39 354.89 61. 473

PGRP Endoaden 10 319.45 512.2 704.94 185. .33 269 .44 491.89 85. 203

PGRP Diff (1-2) -424.7 -204 16.738 177. .52 234 .93 347.42 105 .06

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -1.94 0.0680

PGRP Satterthwaite Unequal 16.4 -1.94 0.0696

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.92 0.3449

Comparison in PGRP-I Beeta for Endoaden and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Endoaden 10 319.45 512.2 704.94 185.33 269.44 491.89 85.203

PGRP Parkinso 10 79.041 83.549 88.057 4.3348 6.302 11.505 1.9929

PGRP Diff (1-2) 249.59 428.65 607.7 144 190.57 281.82 85.227 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 5.03 <.0001

PGRP Satterthwaite Unequal 9.01 5.03 0 0007

Equality of Variances

Variable Method Nura DF Den DP F Value Pr > F

PGRP Folded F 9 9 1827.91 <.0001

Comparison in PGRP-I Beeta for Prostate and Prostati 353

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Stα Dev Std Dev Std Dev Std Err

PGRP Prostate 10 -0.141 1.0337 2.2086 1.1297 1.6424 2.9985 0. 5194

PGRP Prostati 10 195.76 387.17 578.58 184.05 267.57 488.48 84 .614

PGRP Diff (1-2) -563.9 -38S.1 -208.4 142.97 189.21 279.8 84 .615

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -4.56 0.0002

PGRP Satterthwaite Unequal 9 -4.56 0.0014

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 26540.1 <-0001

Comparison in PGRP-I Beeta for Prostate and Arthriti 354

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL upper CL

Variable Disease K Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Arthriti 10 270.61 449.04 627.46 171. .56 249. .42 455.34 78 .873

PGRP Prostate 10 -0.141 1.0337 2.2086 1.1297 1.6424 2.9985 0.5194

PGRP Diff (1-2) 282.29 448 613.71 133 .27 176, .37 260.82 78 .875

T-TestS

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 5.68 <.0001

PGRP Satterthwaite Unequal 9 5.68 0.0003

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PGRP Folded F 9 9 23061.1 <.0001

Comparison in PGRP-I Beeta for Prostate and Aortic 355

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic 10 169 .14 308.2 447.26 133.71 194.39 354.89 61.473

PGRP Prostate 10 -0. 141 1.0337 2.2086 1.1297 1.6424 2.9985 0.5194

PGRP Diff (1-2) 178 .01 307.17 436.32 103.87 137.46 203.28 61.475 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 5.00 <.0001

PGRP Satterthwaite Unequal 9 5.00 0.0007

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1400B.3 <.0001

Comparison in PGRP-I Beeta for Prostate and Parkmso 356

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease K Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Parkmso 10 79.041 83 .549 88. .057 4 .3348 6.302 11.505 1 .9929

PGRP Prostate 10 -0.141 1. 0337 2.2086 1 .1297 1.6424 2.9985 0 .5194

PGRP Dlff (1-2) 78.189 82 .516 86 .842 3 .4796 4.6051 6.8101 2 .0594

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 40.07 < :.0001

PGRP Satterthwaite Unequal 10.2 40.07 < :.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 14.72 0.0005

Comparison in PGRP-I Beeta for Prostati and Arthriti

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP hπti 10 270.61 449.04 627 .46 171 .56 249 .42 455. 34 78. 873 PGRP statl 10 195.76 387.17 578 .58 184 .05 267 .57 488. 48 84. 614 PGRP f (1-2) -181.2 61.872 304 .89 195 .44 258 .66 382. 51 115 .67

T-Tests

Variable Method Variances DF t Value Pr > ItI

PGRP Pooled Equal 18 0.53 0 .5993

PGRP Satterthwaite Unequal 17.9 0.53 0 .5993

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.15 0.8376

Comparison m PGRP-I Beeta for Prostati and Aortic 358

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic 10 169.14 308.2 447.26 133.71 194.39 354.89 61.473

PGRP Prostati 10 195.76 387.17 578.58 184.05 267.57 488.48 84.614

PGRP Diff (1-2) -298.7 -78.96 140.76 176.71 233.86 345.84 104.59 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -0.76 0 .4600

PGRP Satterthwaite Unequal 16.4 -0.76 0 .4609

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.89 0.35S1

Comparison in PGRP-I Beeta for Prostati and Parkinso 359

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Parkinso 10 79.041 83.549 88.057 4.3348 6.302 11.505 1.9929

PGRP Prostati 10 195.76 387.17 578.58 184.05 267.57 488.48 84.614

PGRP Diff (1-2) -481.4 -303.6 -125.8 143 189.25 279.87 84.637

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -3.59 0.0021 PGRP Satterthwaite Unequal 9.01 -3.59 0.0059

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1802.70 <.0001

Comparison in PGRP-I Beeta for Arthriti and Aortic 360

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Aortic 10 169. 14 308 .2 447.26 133.71 194.39 354.89 61.473

PGRP Arthriti 10 270. 61 449. 04 627.46 171.56 249.42 455.34 78.873

PGRP Diff (1-2) -350 .9 -140 .8 69.255 168.96 223.61 330.67 99.999

T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 -1.41 0.1761 PGRP Satterthwaite Unequal 17 -1.41 0.1771

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PGRP Folded F 9 9 1.65 0.4692

Comparison in PGRP-I Beeta for Arthriti and Parkinso 361

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PGRP Arthriti 10 270 .61 449 .04 627 .46 171.56 249.42 455.34 78.873

PGRP Parkinso 10 79. 041 83. 549 88. 057 4.3348 6.302 11.505 1.9929

PGRP Diff (1-2) 199 .73 365 .49 531 .25 133.31 176.42 260.9 78.898 T-Tests

Variable Method Variances DF t Value Pr > |t|

PGRP Pooled Equal 18 4.63 0 0002 PGRP Satterthwaite Unequal 9 01 4.63 0 0012

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PGRP Folded F 9 9 1566.39 <.0001

Comparison in PGRP-I Beeta for Aortic and Parkmso 362

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

PGRP Aortic 10 169 .14 308.2 447.26 133 .71 194 .39 354.89 61.473 PGRP Parkmso 10 79. 041 83.549 88.057 4.3348 6. 302 11.505 1.9929 PGRP Diff (1-2) 95. 435 224.65 353.87 103 .92 137 .53 203.38 61.505

T-Tests

Variable Method Variances DF t Value Pr > ]t|

PGRP Pooled Equal 18 3.65 0.0018 PGRP Satterthwaite Unequal 9.02 3.65 0.0053

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PGRP Folded F 9 9 951.49 <.0001

Comparison in PSA for Cstitis and KidSton 363

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Cstitis 10 15.23 24.02 32.809 8.4515 12 .287 22.432 3.8855 PSA KidSton 10 3.9651 4.3355 4.7059 0.3561 0.5178 0.9452 0.1637 PSA Diff (1-2) 11.514 19.684 27.854 6.5708 8.696 12.86 3.889

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 5.06 <:.0001 PSA Satterthwaite Unequal 9.03 5.06 0.0007

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 563.19 <.0001

Comparison in PSA for Cstitis and Endoaden 364

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Cstitis 10 15.23 24.02 32.809 8. 4515 12.287 22 .432 3 .8855 PSA Endoaden 10 21.459 34.504 47.55 12 .543 18.236 33 .292 5 .7667 PSA Diff (1-2) -25.09 -10.48 4.1241 11 .749 15.549 22 .994 6 .9536 T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled E Eqquuaall 18 -1 .Sl 0 .1489 PSA Satterthwaite Unequal 15.8 -1 .51 0 .1514

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> P

PSA Folded F 9 9 2.20 0.2551

Comparison in PSA for Ostitis and Prostate 3S5

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Ostitis 10 15.23 24.02 32.809 8.4515 12.287 22.432 3.8855

PSA Prostate 10 0.1072 0.2542 0.4012 0.1414 0.2055 0.3752 0.065

PSA Diff (1-2) 15.601 23.765 31.93 6.5659 8.6895 12.85 3.8861

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 6.12 <.0001 PSA Satterthwaite Unequal 9.01 6.12 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 3573.87 <.0001

Comparison in PSA for Ostitis and Prostati 366

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Ostitis 10 15.23 24.02 32 .809 8.4515 12 .287 22.432 3. 8855 PSA Prostati 10 38.016 40.419 42.823 2.3108 3.3595 6.1332 1.0624 PSA Diff (1-2) -24.86 -16.4 -7.937 6.806 9.0072 13.32 4.0282

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 -4.07 0.0007 PSA Satterthwaite Unequal 10.3 -4.07 0.0021

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 13.38 0.0007

Comparison in PSA for Cstitis and Arthriti 367

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13.286 24.616 35 .946 10.894 15 .838 28.915 5.0085

PSA Cstitis 10 15.23 24.02 32 .809 8.4515 12 .287 22.432 3.8855

PSA Diff (1-2) -12.72 0.5963 13 .914 10.71 14 .174 20.961 6.339 T-Tests

Variable > Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 0.09 0.92S1 PSA Satterthwaite Unequal 17 0.09 0.92S2

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 1.66 0.4611

Comparison in PSA for Ostitis and Aortic 368

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35.877 41. .647 47 .417 5 .5479 8. 0657 14.725 2 .5506

PSA Ostitis 10 15.23 24.02 32 .809 8 .4515 12 .287 22.432 3 .8855

PSA Diff (1-2) 7.8629 17. .628 27 .393 7 .8531 10 .393 15.369 4 .6479

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 3.79 0 .0013

PSA Satterthwaite Unequal 15.5 3.79 0 .0017

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 2.32 0.2258

Comparison in PSA for Ostitis and Parkinso 369

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Cstitis 10 15.23 24 .02 32.809 8.4515 12.287 22.432 3.8855

PSA Parkinso 10 11.998 12. 412 12.827 0.3985 0.5793 1.0576 0.1832

PSA Diff (1-2) 3.4351 11. 607 19.78 6.5723 8.698 12.863 3.8898

T-Tests

Variable Method Variances t Value Pr > |t|

PSA Pooled Equal 18 2.98 0.0080 PSA Satterthwaite Unequal 9.04 2.98 0.0153

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 449.84 <.0001

Comparison in PSA for KidSton and Endoaden 370

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Endoaden 10 21.459 34.504 47.55 12 .543 18 .236 33.292 5 .7667

PSA KidSton 10 3.9651 4.3355 4.7059 0. 3561 0. 5178 0.9452 0 .1637

PSA Diff (1-2) 18.049 30.169 42.289 9. 7474 12.9 19.077 5.769 T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 5.23 <.0001 PSA Satterthwaite Unequal 9.01 5.23 0.0005

Equality of Variances

Variable Method Nura DP Den DF F Value Pr > F

PSA Folded F 9 9 1240.55 c.OOOl

Comparison in PSA for KidSton and Prostate 371

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA KidSton 10 3. .9651 4.3355 4.7059 0.3561 0.5178 0.9452 0.1637 PSA Prostate 10 0. .1072 0.2542 0.4012 0.1414 0.2055 0.3752 0.065 PSA Diff (1-2) 3. .7112 4.0813 4.4514 0.2976 0.3939 0.5825 0.1762

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 23.17 <.0001 PSA Satterthwaite Unequal 11.8 23.17 <.0001

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 6.35 0.0111

Comparison in PSA for KidSton and Prostati 372

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA KidSton 10 3.9651 4.3355 4.7059 0 .3561 0.5178 0.9452 0.1637 PSA Prostati 10 38.016 40.419 42.823 2.3108 3.3595 6.1332 1.0624 PSA Diff (1-2) -38.34 -36.08 -33.83 1.8162 2.4036 3.5545 1.0749

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 -33. .57 <.0001 PSA Satterthwaite Unequal 9.43 -33..57 <.0001

Equality of Variances

Variable Method Hum DF Den DP F Value Pr > F

PSA Folded F 9 9 42.10 <:.0001

Comparison in PSA for KidSton and Arthriti 373

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13 .286 24.616 35 .946 10 .894 15.838 28.915 5.0085

PSA KidSton 10 3. 9651 4.3355 4. 7059 0. 3561 0.5178 0.9452 0.1637

PSA Diff (1-2) 9. 7522 20.28 30 .808 8. 4669 11.205 16.571 5.0112 T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 4.05 0 .0008

PSA Satterthwaite U Unneeqσuuaall 9.02 4.05 0 .0029

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

PSA Folded F 9 9 935.78 <.0001

Comparison in PSA for KidSton and Aortic 374

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35 .877 41.547 47 .417 5 .5479 8 .0657 14.725 2.5506 PSA KidSton 10 3. 9651 4.3355 4. 7059 0 .3561 0 .5178 0.9452 0.1637 PSA Diff (1-2) 31 .942 37.312 42 .681 4 .3184 5 .7151 8.4516 2.5559

T-Tests

Variable Method Variances DF t Value Pr > |t]

PSA Pooled Equal 18 14.60 <.0001

PSA Satterthwaite Unequal 9.07 14.60 <-0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 242.69 <.0001

Comparison in PSA for KidSton and Parkinso 375

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA KidSton 10 3. 9651 4.3355 4.7059 0.3561 0.5178 0.9452 0.1637

PSA Parkinso 10 11 .998 12.412 12.827 0.3985 0.5793 1.0576 0.1832

PSA Diff (1-2) -8 .593 -8.077 -7.56 0.4151 0.5494 0.8125 0.2457

T-Tests

Variable Method Variances t Value Pr > |t|

PSA Pooled Equal 18 -32.87 <.0001 PSA Satterthwaite Unequal 17.8 -32.87 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 1.25 0.7432

Comparison in PSA for Endoaden and Prostate 376

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Endoaden 10 21 .459 34.504 47.55 12 .543 18 .236 33.292 5.7667

PSA Prostate 10 0. 1072 0.2542 0.4012 0. 1414 0. 2055 0.3752 0.065

PSA Diff (1-2) 22 .134 34.25 46.366 9. 7441 12 .896 19.07 5.7671 T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 5.94 <.0001

PSA Satterthwaite Unequal 9 S.94 0.0002

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 7872.16 <.0001

Comparison m PSA for Endoaden and Prostati 377

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Endoaden 10 21. 459 34. 504 47.55 12.543 18.236 33.292 5.7667

PSA Prostati 10 38. 016 40. 419 42.823 2.3108 3.3595 6.1332 1.0S24

PSA Diff (1-2) -18 .23 -5. 915 6.4042 9.9074 13.112 19.39 5.8638

T-Tests

Variable Method Variances t Value Pr > |t|

PSA Pooled Equal 18 -1.01 0.3265 PSA Satterthwaite Unequal 9.61 -1.01 0.3378

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 29.46 <.0001

Comparison in PSA for Endoaden and Arthriti 378

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13.286 24 .616 35.946 10.894 15.838 28.915 5.0085

PSA Endoaden 10 21.459 34 .504 47.55 12.543 18.236 33.292 5.7667

PSA Diff (1-2) -25.94 -9 .889 6.1585 12 905 17.079 25.257 7.6381

T-Tests

Variable Method Variances t Value

PSA Pooled Equal 18 -1.29 0.2118 PSA Satterthwaite Unequal 17.7 -1.29 0.2121

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 1.33 0.6813

Comparison in PSA for Endoaden and Aortic 379

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35 .877 41. 647 47.417 5. 5479 8. 0657 14.725 2.5506

PSA Endoaden 10 21 .459 34. 504 47.55 12 .543 18 .236 33.292 5.7667

PSA Diff (1-2) -6 .105 7. 143 20.391 10 .654 14.1 20.851 6.3056 T-Tests

Variable Method Variances DF t Value Pr > ItI

PSA Pooled Equal 18 1 13 0 2722

PSA Satterthwaite Unequal 12 4 1 13 0 2787

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 S 11 0 0233

Comparison m PSA for Endoaden and Parkmso 380

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Endoaden 10 21 4S9 34 504 47 55 12 543 18 236 33 292 5 7667

PSA Parkmso 10 11 998 12 412 12 827 0 3985 0 5793 1 0576 0 1832

PSA Diff (1-2) 9 9707 22 092 34 214 9 7484 12 901 19 079 5 7696

T-Tests

Variable Method Variances DF t Value Pr » |t|

PSA Pooled Equal 18 3 83 0 0012

PSA Satterthwaite Unequal 9 02 3 83 0 0040

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P

PSA Folded F 9 9 990 86 < 0001

Comparison m PSA for Prostate and Prostati 381

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Prostate 10 0 1072 0 2542 0 4012 0 1414 0 2055 0 3752 0 065

PSA Prostati 10 38 016 40 419 42 823 2 3108 3 3595 6 1332 1 0624

PSA Diff (1-2) -42 4 -40 17 -37 93 1 7984 2 38 3 5196 1 0644

T Tests

Variable Method Variances t Value Pr > |t|

PSA Pooled Equal 18 37 74 0001 PSA Satterthwaite Unequal 9 07 37 74 0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 267 18 < 0001

Comparison m PSA for Prostate and Arthriti 382

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13 286 24 616 35 946 10 894 15 838 28 915 5 0085 PSA Prostate 10 0 1072 0 2542 0 4012 0 1414 0 2055 0 3752 0 065 PSA Diff (1-2) 13 838 24 362 34 885 8 4631 11 2 IS 563 5 0089 T-Tests

Variable Method Variances DF t Value Pr >

PSA Pooled Equal 18 4.86 0. 0001 PSA Satterthwaite Unequal 9 4.86 0.ooos

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 5938.19 <.0001

Comparison in PSA for Prostate and Aortic 383

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35 .877 41 .647 47.417 5 .5479 8 .0657 14.725 2.5506 PSA Prostate 10 0. 1072 0. 2542 0.4012 0 .1414 0 .2055 0.3752 0.065 PSA Diff (1-2) 35 .033 41 .393 46.753 4 .3109 5 .7052 8.437 2.5514

T-Tests

Variable Method Variances t Value Pr >

PSA Pooled Equal 18 16.22 ■c.OOOl PSA Satterthwaite Unequal 9.01 16.22 <.oooi

Equality of Variances -

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 1540.02 <.0001

Comparison in PSA for Prostate and Parkinso 384

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Parkinso 10 11.998 12.412 12.827 0.3985 0.5793 1.0576 0.1832

PSA Prostate 10 0.1072 0.2542 0.4012 0.1414 0.2055 0.3752 0.065

PSA Diff (1-2) 11.75 12.158 12.566 0.3284 0.4347 0.6428 0.1944

T-Tests

Variable Method Variances t Value Pr > |t|

PSA Pooled Equal 18 62.54 <.0001 PSA Satterthwaite Unequal 11.2 62.54 <.oooi

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 7.94 0.0050

Comparison in PSA for Prostati and Arthriti 385

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13. 286 24.616 35 .946 10.894 15 .838 28.915 5.0085

PSA Prostati 10 38. 016 40.419 42 .823 2.3108 3. 3595 6.1332 1.0624

PSA Diff (1-2) -26 .56 -15.8 -5 .047 8.6507 11 .449 16.93 5.1199 T-Tests

Variable Method Variances DF t Value Pr =. |t|

PSA Pooled Equal 18 -3.09 0.0064 PSA Satterthwaite Unequal 9.81 -3.09 0.0118

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P

PSA Folded F 9 9 22.23 <.0001

Comparison in PSA for Prostati and Aortic 386

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35 .877 41 .547 47.417 5.5479 8.0657 14.725 2.5506

PSA Prostati 10 38 .016 40 .419 42.823 2.3108 3.3395 6.1332 1.0S24

PSA Diff (1-2) -4 .577 1. 2279 7.0328 4.6684 6.1783 9.1366 2.763

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 0.44 0.6620 PSA Satterthwaite Unequal 12 0.44 0.6646

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F

PSA Folded F 9 9 5.76 0.0155

Comparison in PSA for Prostati and Parkinso 387

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Parkmso 10 11 .998 12.412 12. 827 0 .3985 0.5793 1.0576 0.1832 PSA Prostati 10 38 .016 40.419 42. 823 2 .3108 3.3595 6.1332 1.0624 PSA Diff (1-2) -30.27 -28.01 -25 .74 1 .8215 2.4106 3.5649 1.0781

T-TeStS

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 -25 .98 «.0001

PSA Satterthwaite Unequal 9 .53 -25 .98 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 33.63 <.0001

Comparison in PSA for Arthriti and Aortic 388

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35.877 41.647 47.417 5. 5479 8. 0657 14.725 2.5506 PSA Arthriti 10 13.286 24.616 35.946 10 .894 15 .838 28.915 5.0085 PSA Diff (1-2) 5.2231 17.032 28.84 9. 4965 12 .568 18.586 5.6206 T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 3.03 0.0072

PSA Satterthwaite Unequal 13.4 3.03 0.0094

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

PSA Folded F 9 9 3.8S 0.0570

Comparison in PSA for Arthriti and Parkinso 389

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Arthriti 10 13 .286 24 .61S 35.946 10.894 15.838 28.915 5.0085

PSA Parkinso 10 11 .998 12 .412 12.827 0.3985 0.5793 1.0576 0.1832

PSA Diff (1-2) 1. S742 12 .204 22.733 8.468 11.207 16.573 5.0119

T-Tests

Variable Method Variances DF t Value Pr > ]t|

PSA Pooled Equal 18 2.43 0.0255 PSA Satterthwaite Unequal 9.02 2.43 0.0376

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 747.43 <.0001

Comparison in PSA for Aortic and Parkinso 390

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

PSA Aortic 10 35. .877 41 .647 47 .417 5 .5479 8.0657 14.725 2 .5506 PSA Parkinso 10 11.998 12.412 12.827 0.3985 0.5793 1.0576 0.1832 PSA Diff (1-2) 23.863 29.235 34.608 4.3206 5.718 8.456 2.5572

T-Tests

Variable Method Variances DF t Value Pr > |t|

PSA Pooled Equal 18 11. .43 < .0001 PSA Satterthwaite Unequal 9.09 11.43 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

PSA Folded F 9 9 193.84 <.0001

Comparison in Labvision Tgase 2 for Cstitis and Kidston 391

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Cstitis 10 2.0932 9 .0974 16.102 6.7347 9 .7912 17.875 3.0962

Lab KidSton 9 -0.903 2 .6482 6.1993 3.1204 4 .6197 8.8503 1.5399

Lab Diff (1-2) -1.109 6 .4492 14.008 5.8509 7 .7972 11.689 3.5826 T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 17 1.80 0 .0896 Lab Ξatterthwaite Unequal 13.1 1.86 0.0847

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Lab Folded F 9 8 4.49 0.0458

Comparison in Labvision Tgase 2 for Ostitis and Endoaden 392

The TTEST Procedure Statistics

Lab Cstitis 10 2.0932 9.0974 16.102 6.7347 9.7912 17.875 3.09S2 Lab Endoaden 10 1.1332 3.2846 5.436 2.0686 3.0074 5.4904 0.951 Lab Diff (1-2) -0.992 5.8128 12.618 5.4726 7.2426 10.711 3.239

T-Tests Variable Method Variances DF t Value Pr > 111

Lab Pooled Equal 18 1.79 0.0895

Lab Satterthwaite Unequal 10.7 1.79 0.1010

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Lab Folded F 9 9 10.60 0.0017

Comparison in Labvision Tgase 2 for Cstitis and Prostate 393

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N N M Meeaann M Meeaann Mean Std Dev std Dev Std Dev Std Err

Lab Cstitis 1 100 22.. . .00993322 9 9 . .00997744 16 .102 6 .7347 9.7912 17.8 3.0962

Lab Prostate 1 100 00 . .00228866 1 1 . .11221166 2. 2146 1.051 1.5279 2.78 0.4832

Lab Diff (1-2) 1 1.. . .33992211 7 7 . .99775588 14 .559 5 .2947 7.0072 10.3 3.1337

T-Tests

Variable Method Variances DF t Value Pr » ItI

Lab Pooled Equal 18 2.55 0 .0203

Lab Satterthwaite Unequal 9 .44 2.55 0 .0304

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 ' 41.06 <.0001

Comparison in Labvision Tgase 2 for Cstitis and Prostati 394

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Cstitis 10 2.0932 9.0974 1 166. .110022 6 .7347 9 .7912 17 .875 3 .0962

Lab Prostati 10 0.1682 0.4647 0 0..7 7661122 0 .2851 0 .4145 0. 7568 0 .1311

Lab Diff (1-2) 2.1219 8.6327 1 155. .114433 5 .2361 6 .9296 10 .248 3.099 T-Tests

Variable Method Variances DF t Value Pr > It=I

Lab Pooled Equal 18 2.79 0. 0122

Lab Satterthwaite Unequal 9.03 2.79 0.0211

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 557.92 <.0001

Comparison in Labvision Tgase 2 for Ostitis and Arthriti 395

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

Lab Arthriti 10 0.2488 0 .4395 0.S302 0.1834 0.266S 0.4868 0.0843

Lab Cstitis 10 2.0932 9 .0974 15.102 6.7347 9.7912 17.875 3.0962

Lab Diff (1-2) -15.17 _ 8.658 -2.151 5.2333 6.926 10.242 3.0974

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -2.80 0.0120 Lab Satterthwaite Unequal 9.01 -2.80 0.0208

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 1348.45 <.0001

Comparison in Labvision Tgase 2 for Cstitis and Aortic 396

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab tic 10 0.8782 1. 0367 1. 1952 0 .1524 0.2216 0.4045 0 .0701 Lab itis 10 2.0932 9. 0974 16 .102 6 .7347 9.7912 17.875 3 .0962 Lab f (1-2) -14.57 -8 .061 -1 .554 5 .2327 6.9252 10.241 3.097

T-Tests

Variable Method Variances DF t Value Pr » |t|

Lab Pooled Equal 18 -2.60 0 .0180

Lab Satterthwaite Unequal 9 .01 -2.60 0 .0286

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 1953.05 <.0001

Comparison in Labvision Tgase 2 for Cstitis and Parkinso 397

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Cstitis 10 2 .0932 9.0974 16.102 6.7347 9.7912 17.875 3.0962 Lab Parkinso 10 0. .3761 0.4616 0.5471 0.0822 0.1195 0.2182 0.0378 Lab Diff (1-2) 2 .1304 8.6358 15.141 5.2318 6.9239 10.239 3.0965 T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 2 79 0 0121

Lab Satterthwaite Unequal 9 2 79 0 0211

Equality of Variances

Variable Method Num DP Den DF F Value Pr _> F

Lab Folded F 9 9 6713 13 < 0001

Comparison in Labvision Tgase 2 for KidSton and Endoaden 398

The TTEST Piocedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Sta Dev Std Dev Std Err

Lab Endoaden 10 1 1332 3 2845 S 436 2 0686 3 0074 S 4904 0 951 Lab KidSton 9 0 903 2 6482 6 1993 3 1204 4 6197 8 8503 1 5399 Lab Diff (1-2) -3 097 0 6364 4 3697 2 8899 3 8512 S 7735 1 7695

T-Tests

Variable Method Variances DF t Value Pr > ItI

Lab Pooled Equal 17 0 36 0 7235 Lab Satterthwaite Unequal 13 5 0 35 0 7306

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 2 36 0 2228

Comparison m Labvision Tgase 2 for KidSton and Prostate 399

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab KidSton 9 -0 903 2 6482 6 1993 3 1204 4 6197 8 8503 1 5399 Lab Prostate 10 0 (3286 1 1216 2 2146 1 051 1 5279 2 7894 0 4832 Lab Diff (1-2) -1 129 1 5266 4 7823 2 5201 3 3584 5 0348 1 5431

T-Tests

Variable Method Variances DF t Value Pr > lt|

Lab Pooled Equal 17 0 99 0 3364 Lab Satterthwaite Unequal 9 57 0 95 0 3675

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 9 14 0 0032

Comparison in Labvision Tgase 2 for KidSton and Prostati 400

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab KidSton 9 -0 903 2 6482 6 1993 3 1204 4 6197 8 8503 1 5399 Lab Prostati 10 0 1682 0 4647 0 7612 0 2851 0 4145 0 7568 0 1311 Lab Diff (1-2) -0 902 2 1835 5 2695 2 3888 3 1834 4 7724 1 4627 T-Tests

Variable Method Variances DF t Value Pr > ItI

Lab Pooled Equal 17 1.49 0 .1538 Lab Satterthwaite Unequal 8.12 1.41 0.1949

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 124.20 < 0001

Comparison in Labvision Tgase 2 for KidSton and Arthriti 401

The TTEST Procedure

Statistics

Lower CL Upper CL jower CL Upper CL

Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Arthriti 10 0. 2488 0. 4395 0.6302 0.1834 0.2666 0.4868 0.0843 Lab KidSton 9 -0 .903 2. 6482 6.1993 3.1204 4.6197 8.8503 1.5399 Lab Diff (1-2) -5 .287 -2 .209 0.8691 2.3825 3.175 4.7598 1.4588

T-Tests

Variable Method Variances t Value Pr > |t|

Lab Pooled Equal 17 -1.51 0.1484 Lab Satterthwaite Unequal 8.05 -1.43 0.1898

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 300.19 <.0001

Comparison m Labvision Tgase 2 for KidSton and Aortic 402

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0. 8782 1. 0367 1.1952 0.1524 0.2216 0.4045 0.0701

Lab KidSton 9 -0 .903 2. 6482 6.1993 3.1204 4.6197 8.8503 1.5399

Lab Diff (1-2) -4 .688 -1 .612 1.4646 2.3811 3.1732 4.7571 1.458

T-Tests

Variable Method Variances t Value Pr > |t|

Lab Pooled Equal 17 -1.11 0.2844 Lab Satterthwaite Unequal 8.03 -1.05 0.3263

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 434.79 <.0001

Comparison m Labvision Tgase 2 for KidSton and Parkmso 403

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab KidSton 9 -0 .903 2 .6482 6 .1993 3 .1204 4 .6197 8.8503 1.5399

Lab Parkmso 10 0. 3761 0 .4616 0 .5471 0 .0822 0 .1195 0.2182 0.0378

Lab Diff (1-2) -0 .887 2 .1866 5 .2599 2.379 3 .1703 4.7527 1.4567 T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 17 1.50 0.1517

Lab Satterthwaite Unequal 8.01 1.42 0.1935

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 8 9 1494.48 <.0001

Comparison in Labvision Tgase 2 for Endoaden and Prostate 404

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Endoaden 10 1.1332 3.2846 5.436 2.0686 3.0074 5.4904 0.951

Lab Prostate 10 0.0286 1.1216 2.2146 1.051 1.5279 2.7894 0.4832 Lab Diff (1-2) -0.078 2.163 4.4041 1.8023 2.3853 3.5274 1.0667

T-Tests

Variable Method Variances DP t Value Pr > |t|

Lab Pooled Equal 18 2.03 0.0577 Lab Satterthwaite Unequal 13.4 2.03 0.0630

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 3.87 0.0562

Comparison in Labvision Tgase 2 for Endoaden and Prostati 405

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev- Std Dev Std Dev Std Err

Lab Endoaden 10 1 .1332 3 .2846 5.436 2 .0686 3.0074 5. .4904 0.951

Lab Prostati 10 0 .1682 0 .4647 0.7612 0 .2851 0.4145 0 .7568 0.1311

Lab Diff (1-2) 0.803 2 .8199 4.8368 1 .6221 2.1467 3 .1745 0.96

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 2.94 0 .0088

Lab Satterthwaite Unequal 9 .34 2.94 0 .0159

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P

Lab Folded F 9 9 52.64 <.0001

Comparison in Labvision Tgase 2 for Endoaden and Arthriti 406

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Arthriti 10 0.2488 0.4395 0.6302 0 .1834 0 .2666 0 .4868 0.0843 Lab Endoaden 10 1.1332 3.2846 5.436 2 .0686 3 .0074 5 .4904 0.951 Lab Diff (1-2) -4.851 -2.845 -0.839 1 .6132 2 .1349 3 .1572 0.9548 T-Tests

Variable Method Variances DF t Value Pr > 111

Lab Pooled Equal 18 -2.98 0 0080 Lab Satterthwaite Unequal 9.14 -2.98 0 0152

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

Lab Folded F 9 9 127.22 <.0001

Comparison m Labvision Tgase 2 for Endoaden and Aortic 407

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0.8782 1.03S7 1.1952 0.1524 0.2216 0.4045 0.0701

Lab Endoaden 10 1.1332 3.2846 5.436 2.0686 3.0074 5.4904 0.951

Lab Diff (1-2) -4.251 -2.248 -0.244 1.6112 2.1323 3.1533 0.9536

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -2.36 0.0299 Lab Satterthwaite Unequal 9.1 -2.36 0.0425

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 184.26 <.0001

Comparison in Labvision Tgase 2 for Endoaden and Parkmso 408

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab oaden 10 1 .1332 3 .2846 5.436 2 .0586 3.0074 5.4904 0 .951 Lab kmso 10 0 .3761 0 .4616 0.5471 0 .0822 0.1195 0.2182 0. 0378 Lab f (1-2) 0 .8234 2.823 4.8226 1 .6081 2.1282 3.1473 0. 9518

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 2 .97 0 .0083

Lab Satterthwaite Unequal 9 .03 2 .97 0 .0158

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 633.35 <.0001

Comparison m Labvision Tgase 2 for Prostate and Prostati 409

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Prostate 10 0. 0286 1 .1216 2 .2146 1.051 1 .5279 2 .7894 0 .4832

Lab Prostati 10 0. 1682 0 .4647 0 .7612 0 .2851 0 .4145 0 .7568 0 .1311

Lab Diff (1-2) -0 .395 0 .6569 1 .7087 0 .8459 1 .1195 1 .6555 0 .5006 T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 1.31 0.2060

Lab Satterthwaite Unequal 10.3 1.31 0.2179

Equality of Variances

Variable Method Num DF Den DF F Value Pr _> F

Lab Folded F 9 9 13.59 0.0006

Comparison in Labvision Tgase 2 for Prostate and Arthriti 410

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab hriti 10 0.2488 0. 4395 0.6302 0 .1834 0.2666 0.4868 0 .0843 Lab ■state 10 0.0286 1. 1216 2.2146 1.051 1.5279 2.7894 0 .4832 Lab f (1-2) -1.713 -0 .682 0.3483 0 .8287 1.0967 1.6219 0 .4905

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -1.39 0 .1813

Lab Satterthwaite Unequal 9 .55 -1.39 0 .1959

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 32.84 <.0001

Comparison in Labvision Tgase 2 for Prostate and Aortic 411

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0.8782 1.0367 1.1952 0.1524 0.2216 0.4045 0.0701

Lab Prostate 10 0.0286 1.1216 2.2146 1.051 1.5279 2.7894 0.4832

Lab Diff (1-2) -1.111 -0.085 0.9408 0.8249 1.0917 1.6144 0.4882

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -0.17 0.8639 Lab Satterthwaite Unequal 9.38 -0.17 0.8656

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 47.56 <.0001

Comparison in Labvision Tgase 2 for Prostate and Parkinso 412

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Parkinso 10 0. 3761 0 .4616 0 .5471 0.0822 0 .1195 0 .2182 0 .0378

Lab Prostate 10 0. 0286 1 .1216 2 .2146 1.051 1 .5279 2 .7894 0 .4832

Lab Diff (1-2) -1 .678 -0.66 0 .3582 0.8189 1 .0837 1 .6026 0 .4846 T Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -1 36 0 1901

Lab Satterthwaite Unequal 9 11 -1 36 0 2060

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

Lab Folded F 9 9 163 48 < 0001

Comparison m Labvision Tgase 2 for Prostati and Arthnti 413

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Arthnti 10 0 2488 0 4395 0 6302 0 1834 0 2666 0 4868 0 0843

Lab Prostati 10 0 1682 0 4647 0 7612 0 2851 0 4145 0 7568 0 1311

Lab Diff (1-2) -0 353 -0 025 0 3022 0 2633 0 3485 0 5154 0 1559

T-Tests

Variable Method Variances DF t Value Pr > ]t|

Lab Pooled Equal 18 -0 16 0 8734 Lab Satterthwaite Unequal 15 4 -0 16 0 8737

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 2 42 0 2048

Comparison m Labvision Tgase 2 for Prostati and Aortic

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0 8782 1 0367 1 1952 0 1524 0 2216 0 4045 0 0701 Lab Prostati 10 0 1682 0 4647 0 7612 0 2851 0 4145 0 7568 0 1311 Lab DiEf (1-2) 0 2597 0 572 0 8843 0 2511 0 3324 0 4915 0 1486

T-Tests

Variable Method Variances DF t Value Pr > t

Lab Pooled Equal 18 3 85 0 0012 Lab Satterthwaite Unequal 13 8 3 85 0 0018

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 3 50 0 0760

Comparison in Labvision Tgase 2 for Prostati and Parkmso 415

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Parkmso 10 0 3761 0 4616 0 5471 0 0822 0 1195 0 2182 0 0378

Lab Prostati 10 0 1682 0 4647 0 7612 0 2851 0 4145 0 7568 0 1311

Lab Diff (1-2) -0 29 -0 003 0 2835 0 2305 0 305 0 4511 0 1364 T-Tests

Variable Method Variances DF t Value Pr _> |t|

Lab Pooled Equal 18 -0.02 0.9821

Lab Satterthwaite Unequal 10.5 -0.02 0.9823

Equality of Variances

Variable Method Num DP Den DF F Value Pr > F

Lab Folded F 9 9 12.03 0.0010

Comparison in Labvision Tgase 2 for Arthriti and Aortic 41S

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0 .8782 1 .0367 1 .1952 0 .1524 0 .2216 0.4045 0.0701 Lab Arthriti 10 0 .2488 0 .4395 0 .6302 0 .1834 0 .2666 0.4868 0.0843 Lab Diff (1-2) 0 .3669 0 .5972 0 .8275 0 .1852 0 .2451 0.3625 0.1096

T-Tests

Variable Method Variances t Value Pr > |t|

Lab Pooled Equal 18 5.45 <.oooi Lab Satterthwaite Unequal 17.4 5.45 <.0001

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F

Lab Folded F 9 9 1.45 0.5899

Comparison in Labvision Tgase 2 for Arthriti and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Arthriti 10 0.2488 0. 4395 0.6302 0. .1834 0.2666 0.4868 0. 0843 Lab Parkinso 10 0.3761 0.4616 0.5471 0..0822 0.1195 0.2182 0.0378 Lab Diff (1-2) -0.216 -0.022 0.172 0..1561 0.2066 0.3055 0.0924

T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 -0.24 0.8137 Lab Satterthwaite Unequal 12.5 -0.24 0.8148

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 4.98 0.0254

Comparison in Labvision Tgase 2 for Aortic and Parkinso 418

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Lab Aortic 10 0 .8782 1 .0367 1 .1952 0 .1524 0 .2216 0 .4045 0 .0701

Lab Parkinso 10 0 .3761 0 .4616 0 .5471 0 .0822 0 .1195 0 .2182 0 .0378

Lab Diff (1-2) 0 .4079 0 .5751 0 .7423 0 .1345 0.178 0 .2632 0 .0796 T-Tests

Variable Method Variances DF t Value Pr > |t|

Lab Pooled Equal 18 7.22 < .0001

Lab Satterthwaite Unequal 13.8 7.22 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Lab Folded F 9 9 3.44 0.0801

Comparison in Aquaponn-4 for Cstitis and Kidston 419

The TTEST Procedure Statistics

Lower CL Upper CL Lower CIJ Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Cstitis 9 75.34 285.87 496.4 185 273 .89 524.71 91.297

Aqua KidSton 10 46.678 54.239 61.799 7.2697 10. 569 19.295 3.3422

Aqua Diff (1-2) 49.343 231.63 413.92 141.11 188 .04 281.91 86.4

T-Tests

Variable Method Variances t Value Pr >

Aqua Pooled Equal 17 2.68 0.0158 Aqua Satterthwaite Unequal 8.02 2.54 0.0349

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 8 9 671.57 <.0001

Comparison in Aquapoπn-4 for Cstitis and Endoaden 420

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Cstitis 75.34 285.87 496.4 185 273.89 524.71 91.297 Aqua Endoaden 232.32 480 727.68 195.88 296.26 602.97 104.74 Aqua Diff (1-2) -488.8 -194.1 100.58 210.2 284.55 440.39 138.27

T-Tests

Variable Method Variances t Value Pr > |t|

Aqua Pooled Equal 15 -1.40 0.1807 Aqua Satterthwaite Unequal 14.4 -1.40 0.1835

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 7 8 1.17 0.8225

Comparison in Aquaporin-4 for Cstitis and Prostate 421

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Cstitis 9 75.34 285 .87 496.4 185 273 .89 524.71 91.297

Aqua Prostate 10 0.1329 0. 492 0.8511 0.3453 0. 502 0.9164 0.1587

Aqua Diff (1-2) 103.24 285 .38 467.51 140.99 187 .89 281.67 86.328 T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 17 3 31 0 0042 Aqua Satterthwaite Unequal 8 3 13 0 0141

Equality of Variances

Variable Method Mum DF Den DF F Value Pr _> F

Aqua Folded F 8 9 297721 <.0001

Comparison m Aquaporm-4 for Ostitis and Prostati

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev std Dev Std Dev Std Err

Aqua Ostitis 9 75.34 285 87 496 4 185 273.89 524 71 91 297

Aqua Prostati 10 238.33 413.84 589.35 168.76 245 35 447.92 77 587

Aqua Diff (1-2) -379.2 -128 123 27 194.48 259 17 388.54 119.08

T-Tests

Variable Method Variances t Value Pr > |t|

Aqua Pooled Equal 17 -1.07 0 2976 Aqua Satterthwaite Unequal 16.2 -1.07 0.3011

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 8 9 1.25 0 7452

Comparison in Aquaporm-4 for Cstitis and Arthriti 423

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Arthriti 10 363.49 506 92 650 35 137.91 200.5 366.04 63.404 Aqua Ostitis 9 75.34 285.87 496.4 185 273 89 524.71 91.297 Aqua Diff (1-2) -9.546 221.05 451.64 178.5 237.87 356.61 109.3

T-Tests

Variable Method Variances t Value Pr > |t|

Aqua Pooled Equal 17 2.02 0.0592 Aqua Satterthwaite Unequal 14.6 1.99 0 0659

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 8 9 1.87 0.3715

Comparison m Aquaporm-4 for Cstitis and Aortic 424

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344 .57 523.75 172.28 250 .47 457.26 79.206

Aqua Cstitis 9 75.34 285 .87 496.4 185 273 .89 524.71 91.297

Aqua Diff (1-2) -195 58. 702 312.44 196.42 261 .75 392.41 120.27 T Tests

Variable Method Variances DF t Value Pr » ItI

Aqua Pooled Equal 17 0 49 0 S317 Aqua Satterthwaite Unequal 16 3 0 49 0 S336

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 8 9 1 20 0 7898

Comparison m Aquaporm-4 for Ostitis and Parkmso 425

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Cstitis 9 75 34 285 87 496 4 185 273 89 524 71 91 297

Aqua Parkmso 10 85 402 88 731 92 061 3 2016 4 6546 8 4974 1 4719

Aqua Diff (1-2) 14 973 197 14 379 3 141 01 187 92 281 72 86 342

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 17 2 28 0 0356 Aqua Satterthwaite Unequal 2 16 0 0S29

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 8 9 3462 53 < 0001

Comparison in Aquaponn 4 for KidSton and Endoaden 426

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Endoaden 8 232 32 480 727 68 195 88 296 26 602 97 104 74 Aqua KidSton 10 46 678 54 239 61 799 7 2697 10 569 19 295 3 3422 Aqua Diff (1-2) 228 55 425 76 622 97 146 06 196 12 298 48 93 028

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 16 4 58 0 0003 Aqua Satterthwaite Unequal 7 01 4 06 0 0048

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 7 9 785 77 < 0001

Comparison in Aquaporm-4 for KidSton and Prostate 427

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua KidSton 10 46 678 54 239 61 799 7 2697 10 569 19 295 3 3422

Aqua Prostate 10 0 1329 0 492 0 8511 0 3453 0 502 0 9164 0 1587

Aqua Diff (1-2) 46 717 53 747 60 776 5 6533 7 4818 11 064 3 3459 T-Tests

Variable Method Variances DF t Value Pr >

Aqua Pooled Equal 18 16.06 «.0001 Aqua Satterthwaite Unequal 9.04 16.06 <.oooi

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 443.32 <.0001

Comparison in Aquaponn-4 for KidSton and Prostati 42S

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua KidSton 10 46.678 54.239 61.799 7.2697 10. 569 19.295 3. 3422 Aqua Prostati 10 238.33 413.84 589 35 168.76 245 .35 447.92 77 .587 Aqua Diff (1-2) -522.8 -359.6 -196.4 131.21 173 .65 256.8 77 .659

T-Tests

Variable Method Variances DF t Value Pr > ItI

Aqua Pooled Equal 18 -4.63 0 .0002 Aqua Satterthwaite Unequal 9 .03 -4.63 0 .0012

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 538.92 <.0001

Comparison m Aquaponn-4 for KidSton and Arthriti 429 ^r r

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Arthriti 10 363.49 506 .92 650.35 137.91 200.5 366.04 63.404

Aqua KidSton 10 46.678 54. 239 61.799 7.2697 10.569 19.295 3.3422

Aqua Diff (1-2) 319.29 452 .68 586.07 107.28 141.97 209.95 63.492

T-Tests

Variable Method Variances DF t Value Pr > |t]

Aqua Pooled Equal 18 7.13 <.0001 Aqua Satterthwaite Unequal 9.05 7.13 <.0001

Equality of Variances

Variable Method Num DF Den DP F Value Pr > F

Aqua Folded F 9 9 359.89 <.0001

Comparison m Aquaporm-4 for KidSton and Aortic 430

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344.57 523 .75 172.28 250.47 457 .26 79 .206 Aqua KidSton 10 46.678 54.239 61. 799 7.2697 10.569 19. 295 3. 3422 Aqua Diff (1-2) 123.78 290.33 456 .89 133.95 177.27 262 .15 79 .277 T-Tests

Variable Method Variances DF t Value Pr > |t]

Aqua Pooled Equal 18 3.66 0.0018 Aqua Satterthwaite Unequal 9.03 3.66 0.0052

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 561.64 <.0001

Comparison in Aquaporin-4 for KidSton and Parkinso 431

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua KidSton 10 46.678 54.239 61.799 7.2697 10.569 19.295 3.3422

Aqua Parkinso 10 85.402 88.731 92.061 3.2016 4.6546 8.4974 1.4719

Aqua Diff (1-2) -42.16 -34.49 -26.82 6.1703 8.166 12.076 3.6519

T-Tests

Variable Method Variances t Value Pr > |t|

Aqua Pooled Equal 18 -9.44 <.0001 Aqua Satterthwaite Unequal 12.4 -9.44 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 5.16 0.0226

Comparison in Aquaporin-4 for Endoaden and Prostate 432

The TTEST Procedure

Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Endoaden 8 8 223322..3322 4 48800 772277. .6688 1 19955.. .8888 2 29966 . .2266 602.97 104.74

Aqua Prostate 1 100 00..11332299 0 0..449922 00..88551111 0 0..33445533 0 0.. 5 50022 0.9164 0.1587

Aqua Diff (1-2) 2 28822..4466 4 47799..5511 667766. .5566 1 14455., .9944 1 19955 . .9966 298.24 92.952

T-Tests

Variable M Meetthhoodd VVaarriiaanncceess DDFF tt VVaalluuee Pr > |t|

Aqua PPoooolleedd EEqquuaall 1166 55..1166 <.0001

Aqua SSaatttteerrtthhwwaaiittee UUnneeqquuaall 77 44..5588 0.0026

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Aqua Folded F 7 9 348347 <.0001

Comparison in Aquaporin-4 for Endoaden and Prostati 433

The TTEST Procedure Statistics

Aqua Endoaden 8 232.32 480 727.68 195. 88 296 .26 602 .97 104 .74 Aqua Prostati 10 238.33 413.84 589.35 168. 76 245 .35 447 .92 77. 587 Aqua Diff (1-2) -204.1 66.16 336.47 200 .2 268 .81 409 .12 127 .51 T Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 16 0 52 0 6110 Aqua Satterthwaxte Unequal 13 6 0 51 0 6199

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F Aqua Folded F 7 9 1 46 0 5854

Comparison m Aquaporm 4 for Endoaden and Arthriti 434

The TTEST Procedure Statistics

Aqua Arthriti 10 363 49 506 92 650 35 137 91 200 5 366 04 63 404 Aqua Endoaden 8 232 32 480 727 68 195 88 296 26 602 97 104 74 Aqua Dlff (1-2) -221 5 26 918 275 3 183 96 247 01 375 93 117 17

T Tests Variable Method Variances DF t Value Pr > 111

Aqua Pooled Equal 16 0 23 0 8212 Aqua Satterthwaite Unequal 11 8 0 22 0 8297

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Aqua Folded F 7 9 2 18 0 2731

Comparison in Aquapoπn-4 for Endoaden and Aortic 435

The TTEST Procedure Statistics

Aqua Aortic 10 165 4 344 57 523 75 172 28 250 47 457 26 79 206 Aqua Endoaden 8 232 32 480 727 68 195 88 296 26 602 97 104 74 Aqua Dlff (1-2) 408 4 -135 4 137 54 202 17 271 46 413 14 128 76

T-Tests Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 16 -1 OS 0 3085

Aqua Satterthwaite Unequal 13 8 -1 03 0 3202

Equality of Variances

Variable Method Nura DF Den DF F Value Pr > F Aqua Folded F 7 9 1 40 0 6249

Comparison in Aquaporm-4 for Endoaden and Parkmso 436

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Endoaden 8 232 32 480 727 68 195 88 296 26 602 97 104 74 Aqua Parkmso 10 85 402 88 731 92 061 3 2016 4 6546 8 4974 1 4719 Aqua Dlff (1-2) 194 19 391 27 588 35 145 97 195 99 298 28 92 966 T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 16 4.21 0 0007 Aqua Satterthwaite Unequal 7 3 74 0 0073

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 7 9 4051 31 < 0001

Comparison m Aquaponn-4 for Prostate and Prostati 437

The TTEST Procedure Statistics

Lower CL Upper CL Lower CD Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Prostate 10 0.1329 0.492 0.8511 0.3453 0.502 0.9164 0.1587 Aqua Prostati 10 238.33 413 84 589.35 168 76 245.35 447.92 77.587 Aqua Diff (1-2) -576.4 -413 3 -250.3 131.09 173.49 256.56 77.587

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 -5.33 <.0001 Aqua Satterthwaite Unequal 9 -5 33 0.0005

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 238912 <.0001

Comparison m Aquapoπn-4 for Prostate and Arthriti 438

The TTEST Procedure Statistics

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Arthriti 10 363.49 506.92 650.35 137.91 200 5 356 04 63.404 Aqua Prostate 10 0.1329 0.492 0 8511 0.3453 0.502 0.9164 0.1587 Aqua Diff (1-2) 373.22 506.43 639.63 107.13 141.78 209.66 63 404

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 7.99 < 0001 Aqua Satterthwaite Unequal 9 7.99 < .0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 159547 <.0001

Comparison in Aquaponn-4 for Prostate and Aortic 439

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344 .57 523.75 172.28 250 .47 457.26 79.206

Aqua Prostate 10 0.1329 0. 492 0.8511 0.3453 0. 502 0.9164 0.1587

Aqua Diff (1-2) 177.67 344 .08 510.49 133.83 177 .11 261 92 79.206 T-Tests

Variable Method Variances DF t Value Pr > 1t1

Aqua Pooled Equal 18 4.34 0.0004 Aqua Satterthwaite Unequal 9 4.34 0.0019

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 248988 <.0001

Comparison in Aquaporin-4 for Prostate and Parkinso

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Parkinso 10 85.402 88 .731 92 .061 3 .2016 4.6S46 8.4974 1.4719 Aqua Prostate 10 0.1329 0.492 0.8511 0.3453 0.502 0.9164 0.1587 Aqua Diff (1-2) 85.129 88.239 91.349 2.5013 3.3104 4.8954 1.4804

T-Tests

Variable Method Variances DF t Value Pr ^ |t|

Aqua Pooled Equal 18 59.60 <.0001 Aqua Satterthwaite Unequal 9.21 59.60 <.0001

Equality of Variances

Variable Method Num DF Den DF ' F Value Pr > F

Aqua Folded F 9 9 85.98 <.0001

Comparison in Aquaporin-4 for Prostati and Arthriti 441

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std En

Aqua Arthriti 10 3S3.49 506.92 650. .35 137.91 200 .5 366.04 63.404 Aqua Prostati 10 238.33 413.84 589..35 168.76 245.35 447.92 77.587 Aqua Diff (1-2) -117.4 93.078 303..59 169.3 224.05 331.33 100.2

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 0.93 0.3652 Aqua Satterthwaite Unequal 17.3 0.93 0.3657

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 1.50 0.5571

Comparison in Aquaporin-4 for Prostati and Aortic 442

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344.57 523 .75 172 .28 250 .47 457 .26 79. 206

Aqua Prostati 10 238.33 413.84 589 .35 168 .7S 245 .35 447 .92 77. 587

Aqua Diff (1-2) -302.2 -69.27 163 .67 187 .34 247 .93 366 .64 110 .88 T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 -0 62 0.5400

Aqua Satterthwaite Unequal 18 -0.S2 0.S400

Equality of Variances

Variable Method Num DF Den DF P Value Pr > F Aqua Folded F 9 9 1.04 0.9519

Comparison in Aquaponn-4 for Prostati and Parkmso 443

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Parkmso 10 85.402 88.731 92.061 3.2016 4.6546 8.4974 1.4719 Aqua Prostati 10 238.33 413.84 589.35 168.76 245.35 447.92 77.587 Aqua Dlff (1-2) -488.1 -325.1 -162.1 131.12 173.52 256.61 77.601

T-Tests Variable Method Variances DF t Value Pr > | t |

Aqua Pooled Equal 18 -4.19 0.0006

Aqua Satterthwaite Unequal 9.01 -4.19 0.0023

Equality of Variances

Variable Method Hum DF Den DF F Value Pr > F Aqua Folded F 9 9 2778.58 -=.0001

Comparison in Aquapoπn-4 for Arthπti and Aortic 444

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344.57 523.75 172.28 250.47 457.26 79.206 Aqua Arthritl 10 363.49 506.92 650.35 137.91 200.5 366.04 63.404 Aqua Dlff (1-2) -375.5 -162.3 50.809 171.42 226.87 335.5 101.46

T-Tests Variable Method Variances DF t Value Pr > \t\

Aqua Pooled Equal 18 -1.60 0.1270

Aqua Satterthwaite Unequal 17.2 -1.60 0.1278

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F Aqua Folded F 9 9 1.56 0.5178

Comparison m Aquaporm-4 for Arthπti and Parkmso 445

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N N M Meeaann M Meeaann Mean Std Dev Std Dev Std Dev Std Err

Aqua Arthriti 10 363.49 506 .92 650.35 137 .91 200.5 366 .04 63 .404 Aqua Parkmso 10 85.402 88. 731 92.061 3.2016 4.6546 8.4974 1. 4719 Aqua Diff (1-2) 284.94 418 .19 551.43 107 .16 141.81 209 .72 63 .421 T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 6.59 <.0001 Aqua Satterthwaite Unequal 9.01 6.59 <.0001

Equality of Variances

Variable Method Num DF Den DF F Value Pr > F

Aqua Folded F 9 9 1855.55 <.0001

Comparison in Aquaporm-4 for Aortic and Parkmso 446

The TTEST Procedure Statistics

Lower CL Upper CL Lower CL Upper CL

Variable Disease N Mean Mean Mean Std Dev Std Dev Std Dev Std Err

Aqua Aortic 10 165.4 344 .57 523 .75 172.28 250.47 457.26 79.206

Aqua Parkmso 10 85.402 88. 731 92.061 3.2016 4.6546 8.4974 1.4719

Aqua Diff (1-2) 89.406 255 84 422 .28 133.85 177.14 261.96 79.22

T-Tests

Variable Method Variances DF t Value Pr > |t|

Aqua Pooled Equal 18 3.23 0.0047 Aqua Satterthwaite Unequal 9.01 3.23 0.0103

Equality of Variances

Variable Method Num DF Den DF F Value Pr > P Aqua Folded F 9 9 2895.75 <.0001

It is understood that the disclosed method and compositions are not limited to the particular methodology, protocols, and reagents described as these may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention which will be limited only by the appended claims.

It must be noted that as used herein and in the appended claims, the singular forms "a ", "an", and "the" include plural reference unless the context clearly dictates otherwise. Thus, for example, reference to "a calcifying nano-particle" includes a plurality of such calcifying nano-particles, reference to "the calcifying nano-particle" is a reference to one or more calcifying nano-particles and equivalents thereof known to those skilled in the art, and so forth.

"Optional" or "optionally" means that the subsequently described event, circumstance, or material may or may not occur or be present, and that the description includes instances where the event, circumstance, or material occurs or is present and instances where it does not occur or is not present.

Ranges may be expressed herein as from "about" one particular value, and/or to "about" another particular value. When such a range is expressed, also specifically contemplated and considered disclosed is the range from the one particular value and/or to the other particular value unless the context specifically indicates otherwise. Similarly, when values are expressed as approximations, by use of the antecedent "about," it will be understood that the particular value forms another, specifically contemplated embodiment that should be considered disclosed unless the context specifically indicates otherwise. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint unless the context specifically indicates otherwise. Finally, it should be understood that all of the individual values and sub-ranges of yalues contained within an explicitly disclosed range are also specifically contemplated and should be considered disclosed unless the context specifically indicates otherwise. The foregoing applies regardless of whether in particular cases some or all of these embodiments are explicitly disclosed. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed method and compositions belong. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present method and compositions, the particularly useful methods, devices, and materials are as^' described. Publications cited herein and the material for which they are cited are hereby specifically incorporated by reference. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such disclosure by virtue of prior invention. No admission is made that any reference constitutes prior art. The discussion of references states what their authors assert, and applicants reserve the right to challenge the accuracy and pertinency of the cited documents. It will be clearly understood that, although a number of publications are referred to herein, such reference does not constitute an admission that any of these documents forms part of the common general knowledge in the art.

Throughout the description and claims of this specification, the word "comprise" and variations of the word, such as "comprising" and "comprises," means "including but not limited to," and is not intended to exclude, for example, other additives, components, integers or steps. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the method and compositions described herein. Such equivalents are intended to be encompassed by the following claims.

Claims

CLAIMSWe claim: '

1. A method for detecting calcifying nano-particles, the method comprising detecting calcifying nano-particles by detecting one or more proteins or components on the calcifying nano-particle.

2. The method of claim 1, wherein the calcifying nano-particles are detected by detecting one or more of the proteins selected from the group consisting of the proteins anti- Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF-kappa B₅ osteopontin, Factor X/Xa, CD 14, prothrombine, Factor DC, Fetuin B, CD40, anti-myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA₅ CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 micro gl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D-Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

3. The method of claim 1, wherein the calcifying nano-particles are detected by detecting two or more proteins or components on the calcifying nano-particle.

4. The method of claim 1, wherein the calcifying nano-particles are detected by detecting one or more proteins or components with a GLA-containing domain.

5. The method of claim 1, wherein the calcifying nano-particles are detected by detecting one or more proteins or components with a calcium binding domain.

6. The method of claim 1, wherein the calcifying nano-particle is captured, identified, or both prior to, simultaneous with, or following detection of one or more of the proteins or components.

7. The method of claim 6, wherein capture or identification of the calcifying nano- particle indicates that the detected proteins or components are on the calcifying nano-particle.

8. The method of claim 6, wherein the calcifying nano-particle is captured by binding at least one compound to one or more of the proteins or components, wherein the compound is or becomes immobilized.

9. The method of claim 6, wherein the calcifying nano-particle is identified by binding at least one compound to one or more of the proteins or components, wherein the calcifying nano-particle is separated based on the compound.

10. The method of claim 9, wherein the calcifying nano-particle is separated by fluorescence activated sorting.

11. The method of claim 1 , wherein one or more of the proteins are detected by binding at least one compound to the protein and detecting the bound compound.

12. The method of claim 11, wherein detection of two or more bound compounds indicates that the proteins to which the compounds are bound are on the calcifying nano- particle.

13. The method of claim 12, wherein the two or more compounds are detected in the same location or at the same time.

14. The method of claim 11, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the protein.

15. The method of claim 1, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins.

16. The method of claim 1, wherein the proteins are detected by detecting any combination of 100 or fewer of the proteins selected from the group consisting of proteins with a GLA-containing domain, clotting factor V, clotting factor VII, clotting factor IX, clotting factor X, tissue factor-clotting factor Vila complex, fibrin, fibrinogen, factor XIIIa, fragments of factor II, thrombin, prothrombin Fragment 1, matrix GLA-protein and osteocalcin on the calcifying nano-particle.

17. The method of claim 16, wherein the proteins are detected by detecting any combination of 75 or fewer of the proteins.

18. The method of claim 17, wherein the proteins are detected by detecting any combination of 50 or fewer of the proteins.

19. The method of claim 18, wherein the proteins are detected by detecting any combination of 10 or fewer of the proteins.

• 20. The method of claim 16, wherein the combination of proteins is detected in the same assay.

21. The method of claim 16, wherein the combination of proteins is detected simultaneously.

22. The method of claim 16, wherein the combination of proteins is detected on the same calcifying nano-particle.

23. The method of claim 16, wherein the combination of proteins is detected on or within the same device.

24. The method of claim 16, wherein the combination of proteins detected constitutes a pattern of proteins.

25. The method of claim 24, wherein the pattern indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination.

26. The method of claim 24, wherein the pattern indicates or identifies a treatment to inhibit, remove or prevent the calcifying nano-particles.

27. The method of claim 24, wherein the pattern identifies the type of calcifying nano- particles detected.

28. The method of claim 1, wherein the proteins are detected by detecting the presence or absence of any combination of 10 or fewer of the proteins selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor X/Xa, CD 14, prothrombine, Factor DC, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

29. The method of claim 28, wherein the pattern of the presence or absence of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination.

30. The method of claim 28, wherein the pattern of the presence or absence of the proteins indicates or identifies a treatment to inhibit, remove or prevent the calcifying nano- particles.

31. The method of claim 28, wherein the pattern of the presence or absence of the proteins identifies the type of calcifying nano-particles detected.

32. The method of claim 28, wherein the presence of one or more of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination.

33. The method of claim 28, wherein the presence of one or more of the proteins indicates or identifies a treatment to inhibit, remove or prevent the calcifying nano-particles.

34. The method of claim 28, wherein the presence of one or more of the proteins identifies the type of calcifying nano-particles detected.

35. The method of claim 28, wherein the absence of one or more of the proteins indicates or identifies a disease or condition, a risk of a disease or condition, the severity of a disease or condition, or a combination.

36. The method of claim 28, wherein the absence of one or more of the proteins indicates or identifies a treatment to inhibit, remove or prevent the calcifying nano-particles.

37. The method of claim 28, wherein the absence of one or more of the proteins identifies the type of calcifying nano-particles detected.

38. The method of claim 1, wherein at least one of the proteins is detected using a microarray, coded beads, coated beads, flow cytometry, ELISA, mass spectrometry, fluorescence, chemiluminescence, spectrophotometry, chromatography, electrophoresis, or a combination.

39. The method of claim 1, wherein the proteins on the calcifying nano-particle are detected by

(a) capturing the calcifying nano-particle,

(b) binding a detection compound to one or more of the proteins or components of said particle, and

(c) detecting the detection compound.

40. The method of 39, wherein the calcifying nano-particle is captured by binding a capture compound to one or more of the proteins or components of said particle, wherein the capture compound is or becomes immobilized.

41. The method of claim 40, wherein the proteins to which capture compounds bind mediate capture, wherein the detection compound is bound to one of the proteins or components of said particle, wherein the calcifying nano-particle is characterized by determining which proteins mediate capture of the calcifying nano-particle to which the detected detection compound is bound.

42. The method of claim 40, wherein the capture compound is bound to one of the proteins or components of said particle, wherein the detection compounds detected indicate which of the proteins is present on the calcifying nano-particle, wherein the calcifying nano- particle is characterized by which proteins are present on the calcifying nano-particle.

43. The method of claim 1, wherein the proteins on the calcifying nano-particle are detected by

(a) binding a detection compound to one or more of the proteins,

(b) capturing the calcifying nano-particle, and

(c) detecting the detection compound.

44. A method for detecting one or more proteins, the method comprising detecting one or more proteins on a calcifying nano-particle.

45. The method of claim 44, wherein the proteins are selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor X/Xa, CD 14, prothrombine, Factor DC, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, JunB, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

46. The method of claim 44, wherein two or more proteins are detected on the calcifying nano-particle.

47. The method of claim 44, wherein one or more of the proteins are detected by binding at least one compound to the protein and detecting the bound compound.

48. The method of claim 47, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the protein.

49. The method of claim 44, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins.

50. A method of characterizing a calcifying nano-particle, the method comprising identifying one or more proteins on a calcifying nano-particle.

51. The method of claim 50, wherein the proteins are selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor XIXa, CD14, prothrombine, Factor IX, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, larninin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII₅ heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, JunB, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

52. The method of claim 50, wherein the calcifying nano-particles are characterized by identifying two or more proteins on the calcifying nano-particle.

53. The method of claim 50, wherein the identified proteins identify the type of calcifying nano-particle.

54. The method of claim 53, wherein the identified type of calcifying nano-particle is related to or associated with a disease or condition.

55. The method of claim 50, wherein the identified proteins identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated.

56. The method of claim 50, wherein one or more of the proteins are identified by binding at least one compound to the proteins or components of said particle and detecting the bound compound.

57. The method of claim 56, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the proteins or components of said particle.

58. The method of claim 50, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins or components of said particle.

59. A method of diagnosing a disease or condition, the method comprising identifying one or more proteins or components on a calcifying nano-particle from a subject, wherein the identified proteins identify a disease or condition with which calcifying nano-particles having the identified proteins are related or associated.

60. The method of claim 59, wherein the proteins are selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor X/Xa, CD 14, prothrombine, Factor DC, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

61. The method of claim 59, wherein the disease or condition is diagnosed by identifying two or more proteins or components on the calcifying nano-particle.

62. The method of claim 59, wherein the identified proteins identify a disease or condition that is caused by calcifying nano-particles having the identified proteins or components of said particle.

63. The method of claim 59, wherein the identified proteins identify a disease or condition in which calcifying nano-particles having the identified proteins or components of said particle are produced.

64. The method of claim 59, wherein one or more of the proteins are identified by binding at least one compound to the proteins or components of said particle and detecting the bound proteins or components therein.

65. The method of claim 64, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the protein.

66. The method of claim 59, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins or components of said particle.

67. A method of assessing the prognosis of a disease or condition, the method comprising identifying one or more proteins or components on a calcifying nano-particle from a subject, wherein the identified proteins identify calcifying nano-particles that are related to or associated with the prognosis of the disease or condition.

68. The method of claim 67, wherein the proteins are selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor X/Xa, CD 14, prothrombine, Factor IX, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillm-l, B2 microgl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S₅ BAFF on the calcifying nano-particle.

69. The method of claim 67, wherein the prognosis of a disease or condition is assessed by identifying two or more proteins or components on the calcifying nano-particle.

70. The method of claim 67, wherein one or more of the proteins or components of said particle are identified by binding at least one compound to said proteins or components and detecting the bound compound.

71. The method of claim 70, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the proteins or components of said particle.

72. The method of claim 67, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins or components of said particle.

73. A method of identifying a subject at risk of a disease or condition, the method comprising identifying one or more proteins or components on a calcifying nano-particle from a subject, wherein the identified proteins or components identify calcifying nano-particles that are related to or associated with a risk of developing a disease or condition.

74. The method of claim 73, wherein the proteins are selected from the group consisting of proteins anti-Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF- kappa B, osteopontin, Factor XfXa, CD 14, prothrombine, Factor IX, Fetuin B, CD40, anti- myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, laminin, trypsin, Notch-1, BSA, LBP, PTX3, complement C5, fibrinogen, D- Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c-Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin-1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

75. The method of claim 73, wherein the subject is identified by identifying two or more proteins on the calcifying nano-particle.

76. The method of claim 73, wherein one or more of the proteins or components are identified by binding at least one compound to the proteins or component and detecting the bound compound.

77. The method of claim 76, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the protein or component.

78. The method of claim 73, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the protein or components of said particle.

79. An isolated calcifying nano-particle, wherein the calcifying nano-particle comprises one or more of the proteins selected from the group consisting of proteins anti- Fetuin A, calmodulin, Tgase II, MMP-9, MMP-3, CD 42b, NF-kappa B, osteopontin, Factor X/Xa, CD 14, prothrombine, Factor DC, Fetuin B, CD40, anti-myeloperoxidase, Fibronectin, Factor VII, tissue factor, human complement 5b-9, human CRP, matrix GLA, CD61, Kappa Light Chain, Macrophage, factor XIIIA, hsp 60, fibrillin- 1, B2 microgl, CD 18, laminin, trypsin, Notch- 1, BSA, LBP, PTX3, complement C5, fibrinogen, D-Dimer, factor V, human gamma-Gla, TF-VIIa, complement C3c, Complement C4, antichymotrypsin, Annexin V, Lipid A, isopeptide bond, vitronectin, thrombin, osteocalcin, Troponin T, vimentin, tropomyosin, HAS, Troponin I cardiac, Apo Al, MHC class I, Amyloid P protein, sCD40 L, kallikrein, Prothr Fl, goat- ATIII, Thrombin, Factor VIII, heparan Sulph, Factor XI, c-jun, Fra-2, Fra-1, Jun B, P-c- Jun, TGase3, alpha fetoprotein, PSA, erbB2, VEGF, alpha synuclein, mucin- 1, Cystatin A, Cystatin S, Prostein, Aquaporin 4, Trypsin, Osteonectin, RAGE, PGRP-I Beeta, PGRP-S, Gram positive bacteria, Troponin C Cardiac, Protein C, Macrophage Scavenger Receptor Type I, anti-Thrombin, Protein S, BAFF on the calcifying nano-particle.

80. A composition comprising a calcifying nano-particle and one or more compounds bound to one or more proteins or components on the calcifying nano-particle.

81. The composition of claim 80, wherein the composition comprises a calcifying nano-particle and one or more compounds bound to two or more proteins or components on the calcifying nano-particle.

82. The composition of claim 80, wherein at least one of the compounds is an antibody, wherein the antibody is specific for the protein or components.

83. The composition of claim 80, wherein the calcifying nano-particles comprise calcium phosphate and one or more of the proteins or components.

84. The composition of claim 80, wherein at least one of the compounds blocks the calcifying nano-particle.

85. A method of detecting a particle wherein proteins on the particle are detected by (a) capturing the particle, (b) binding a detection compound to one or more of the proteins or components of said particle, and

(c) detecting the detection compound.

86. The method of claim 85, wherein said particle is a stable particle, such as a microparticle, virus, spore, bacteria, prion, mineral, metal, or synthetic particle as introduced into the circulation of an animal.

87. The method of claim 85 wherein said proteins or compounds are quantitated using a single standard curve.

88. The method of claim 87, wherein said curve is created by including, as the standard, at least one protein or other component of said particle as a standard for the assay

89. The method of claim 87, wherein said curve is created by including various concentrations of CNPs or at least one of the CNP antigen into the assay format.

90. The method of claim 1, wherein said proteins or components may be any of those that adhere to the surface of said particle.

91. The method of claim 1 , wherein said proteins may be any calcium binding protein.

92. The method of claim 1, wherein said proteins may be any proteins that bind to calcium binding proteins.

93. The method of claim 39, wherein said detector antibody is directed against conformationally changed or chemically modified epitope.

94. The method of claim 39, wherein said proteins or compounds are quantitated using a single standard curve.

95. The method of claim 39, wherein said curve is created by including various concentrations of CNPs or at least one of the CNP antigen into the assay format.

96. The method of claim 39, wherein said proteins or components may be any of those that adhere to the surface of said particle.

97. The method of claim 39, wherein said proteins may be any calcium binding protein.

98. The method of claim 39, wherein said proteins may be any proteins that bind to calcium binding proteins.

99. A kit comprising one or more detection compounds, one or more capture compounds, and one or more solid supports for the detection of calcifying nanoparticles and assessment or quantification of the proteins or components associated thereupon.

100. The method of claim 59, wherein said pattern of said proteins indicate or identify a disease or condition, or a combination of said diseases or conditions including but not limited to heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Scleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Mercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofilms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease.

101. The method of claim 67, wherein said pattern of said proteins indicate prognosis of a disease or condition including, but not limited to heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Scleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyreoidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Intercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofilms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease.

102. The method of claim 73, wherein said pattern of said proteins indicates risk of a disease or condition, or combination of diseases or conditions, including but not limited to heart or circulatory diseases such as Arteriosclerosis, Atherosclerosis, Coronary Heart Disease, Chronic Heart Failure, Valve Calcifications, Arterial Aneurysms, Calcific Aortic Stenosis, Transient Cerebral Ischemia, Stroke, Peripheral Vascular Disease, Monckeberg's Disease, Vascular Thrombosis; Dental Diseases such as Dental Plaque, Gum Disease (dental pulp stones), calcification of the dentinal papilla, and Salivary Gland Stones; Chronic Infection Syndromes such as Chronic Fatigue Syndrome; Kidney and Bladder Stones, Gall Stones, Pancreas and Bowel Diseases such as Pancreatic Duct Stones, Crohn's Disease, Colitis Ulcerosa; Blood disorders; Adrenal Calcification; Liver Diseases such as Liver Cirrhosis and Liver Cysts; Testicular Microliths, Chronic Calculous Prostatitis, Prostate Calcification, Calcification in Hemodialysis Patients, Malacoplakia; Autoimmune Diseases such as Lupus Erythematosous, Schleroderma, Dermatomyositis, Cutaneous polyarteritis, Panniculitis (Septal and Lobular), Antiphospholipid Syndrome, Arteritis Nodosa, Thrombocytopenia, Hemolytic Anemia, Myelitis, Livedo Reticularis, Chorea, Migraine, Junvenile Dermatomyositis, Graves Disease, Chronic Thyroiditis, Hypothyroidism, Type 1 Diabetes Mellitis, Addison's Disease, and Hypopituitarism; Placental and Fetal Disorders, Polycystic Kidney Disease, Glomerulopathies; Eye Diseases such as Corneal Calcifications, Cataracts, Macular Degeneration and Retinal Vasculature-derived Processes and other Retinal Degenerations; Retinal Nerve Degeneration, Retinitis, and Iritis; Ear Diseases such as Otosclerosis, Degeneration of Otoliths and Symptoms from the Vestibular Organ and Inner Ear (Vertigo and Tinnitus); Thyroglossal cysts, Thyroid Cysts, Ovarian Cysts; Cancer such as Meningiomas, Breast Cancer, Prostate Cancer, Thyroid Cancer, Serous Ovarian Adenocarcinoma; Skin diseases such as Calcinosis Cutis, Skin Stones, Calciphylaxis, Psoriasis, Eczema, Lichen Ruber Planus or Lichen Simple Cysts;, Choroid Plexus Calcification, Neuronal Calcification, Calcification of the FaIx Cerebri, Calcification of the Intervertebral Cartilage or Disc, Intercranial or Cerebral Calcification, Rheumatoid Arthritis, Calcific Tenditis, Oseoarthritis, Fibromyalgia, Bone Spurs, Diffuse Interstitial Skeletal Hyperostosis, Intracranial Calcifications such as Degenerative Disease Processes and Dementia; Erythrocyte-Related Diseases involving Anemia, Intraerythrocytic Nanobacterial Infection and Splenci Calcifications; Chronic Obstructive Pulmonary Disease, Broncholiths, Bronchial Stones, Neuropathy, Calcifications and Encrustations of Implants, Mixed Calcified Biofϊlms, and Myelodegenerative Disorders such as Multiple Sclerosis, Lou Gehrig's, and Alzheimer's Disease.

103. A method of identifying a treatment to inhibit, remove or prevent the calcifying nano-particles or monitor response to said treatment, the method comprising identifying one or more proteins or components on a calcifying nano-particle from a subject, wherein the identified proteins are related to or associated with the selection of therapy or for predicting response to treatment.

104. A method for detecting calcifying nanoparticles on or in foreign devices implanted or to be implanted, or introduced into body cavities including, but not limited to stents, scopes, tubes, endoscopes, catheters, pumps, pace makers, dental appliances, and other implants by detecting one ore more proteins or components on the calcifying nano-particle.

105. A method for detecting calcifying nano-particles in biological materials or donors thereof including, but not limited to blood, tissues, organs, cells, and biopharmaceutical products by detecting one ore more proteins or components on the calcifying nano-particle.

106. A method for detecting calcifying nano-particles in biological materials or donors thereof including but not limited to dairy products, meats, water, and other food stuffs by detecting one or more proteins or components on the calcifying nano-particle.

107. A method for determining risk of future severe adverse health events for individuals to be placed in extreme, demanding, or solitary environments including, but not limited to astronauts, military personnel, and explorers or for aiding in the determination of insurance risk by detecting one ore more proteins or components, or patterns thereof, on the calcifying nano-particle.