CN101563597A

CN101563597A - Compositions and methods for diagnosis and treatment of type 2 diabetes

Info

Publication number: CN101563597A
Application number: CNA200780040768XA
Authority: CN
Inventors: C·盖尔伯; L·刘
Original assignee: American Type Culture Collection ATCC
Current assignee: American Type Culture Collection ATCC
Priority date: 2006-09-01
Filing date: 2007-03-28
Publication date: 2009-10-21
Also published as: CA2661332A1; AU2007293465A1; EP2069768A4; JP2010502946A; WO2008030273A3; EP2069768A2; WO2008030273A2

Abstract

The present invention generally relates to methods of identifying biomarkers associated with an increased risk of developing diabetes, and methods of using said biomarkers in the diagnosis and prognosis of diabetes. The biomarker of the present invention provides a new therapeutic target for the treatment or prevention of diabetes and constitutes a new therapeutic drug.

Description

Be used to diagnose and treat the composition and the method for diabetes B

Invention field

The present invention relates generally to the authentication method of the relevant biomarker of diabetes dangerous development rising, and the method for using these biomarkers in diabetes diagnosis and prognosis.In addition, the selected biomarker of the present invention provides new treatment target and has constituted new medicine for treatment of diabetes or prevention.

Background of invention

Diabetes comprise with the chronic hyperglycemia being one group of disease of feature, because of health can't produce and/or utilize due to the insulin (a kind of hormone that is produced, played an important role in metabolism by pancreatic beta cell).Symptom comprises thirsty and diuresis, hunger, loses weight, chronic infection, wound healing slowly, fatigue and the dimness of vision.Yet symptom usually and not serious is not identified or asymptomatic.Diabetes can cause weak and fatal complication, comprise retinopathy, the loss of memory of blinding, the ephrosis that causes kidney failure, angiocardiopathy, neuropathy, autonomic function obstacle and amputation.In diabetes development, comprise several pathogenic courses, include but not limited to destroy the β cell of excreting insulin and, and cause the liver cell of insulin picked-up opposing and the variation of smooth muscle cell thereupon with insulinopenic process.Diabetes also can comprise because the metabolic disorder of carbohydrates, fat and protein that the insulin due to insulin insensitivity or the shortage insulin causes the effect of target tissue shortage.

Diabetes B is the most common form of diabetes, and its normally relative but not absolute insulinopenic result follows health can't suitably utilize insulin (being also referred to as " insulin resistance " in this area) simultaneously.Diabetes B takes place in overweight people (comprising children) usually, and other risk factor comprises high cholesterol, hypertension, race and gene, for example the diabetes family history.Most of diabetes B patients are overweight peoples, and obesity itself can cause insulin resistance or make its deterioration.Except that the adult, increasing children also suffer from diabetes B after diagnosing.Because should disease the characteristic of development, diabetic complication is grown up with these children usually and is developed for the adult.(American Diabetes Association, research ADA) relates to 51 children that suffered from diabetes before 17 years old after diagnosing to american diabetes association.When these children grow to 30 annual expenditure heads, suffer from kidney failures for 3,1 is blind, dies from heart attack for 2 when dialysis.This research emphasized should disease the order of severity, the grievous injury that diabetic complication causes also emphasized the needs to the disease early diagnosis.

The incidence of disease of diabetes sharply rises to warning quantity.Diabetes are involved about 1.7 hundred million people in the whole world at present, and (World Health Organization, WHO) prediction had 300,000,000 diabetes patients by 2025 in the World Health Organization (WHO).Singly just there are 2.08 thousand ten thousand people to suffer from diabetes (account for the about 6% of population, in the most common cause of death, arrange the 6th) in the U.S..Estimate the direct medical cost direct medical cost $1530-2860 hundred million of the annual diabetes of people in whole world 20-79 year, expect Sheng Zhi $2130-3960 hundred million in 2025.

Along with the increase of the diabetic population of having made a definite diagnosis, ND diabetic population is also continuing rising, mainly is that perhaps hyperglycemia seriously and not causes tangible diabetic symptom usually inadequately because diabetes B is also asymptomatic in its usual earlier.It is believed that in 2.08 thousand ten thousand diabetes patients of the U.S. and have 33% approximately not after diagnosing as yet.Because the delay in the diagnosis, so diabetic complication is shifting to an earlier date, therefore, the danger meeting of following more complication and obstacle will sharply increase.In order to eliminate complication and irreversible many organ damages, diabetes control guide is advocated at disease prognosis in early days with regard to the begin treatment intervention.

This modern popular disease needs new tool, is used for carrying out before obvious development of disease and irreversible infringement the early detection of diabetes B.In addition, need new treatment example to stop, postpone or improve the extensive deterioration of patient health, it is desirable to change disease process, reach partially or completely and cure as the alternative method of only being devoted to the current treatment of chronic control disease symptom.Can reduce the diabetic keratopathy hyperglycemia by reducing body weight, increasing sports and/or therapeutic treatment pattern.Some biological mechanisms are relevant with hyperglycemia, for example insulin resistance, insulin secretion and gluconeogenesis, and several available medicines are arranged, act on one or more such mechanism, such as but not limited to melbine, acarbose and Rosiglitazone.

Existing abundant data shows, is detecting blood sugar obstacle (for example diabetes) before, and the prediabetes illness can exist more than 10 years.With curative prediabetes (pre-diabetics) is treated, can postpone or prevent diabetes; But seldom identify and treat prediabetes.As mentioned above, a main cause is exactly: still do not have the actual danger that easy laboratory determination method can detect the individual development diabetes.Therefore, need be to not suffering from diabetes as yet but have the method that the individuality of the significant risk of development diabetes is identified and diagnosed in this area.

Summary of the invention

Prerequisite of the present invention is this discovery: before disease becomes obviously, can identify the disease association biomarker for a long time in serum or other body fluid.Whether the existence of these biomarkers is to occur in before blood-glucose control is damaged in the diabetes B patients serum fingerprint (serumfootprint), can be used as the early diagnosis instrument, can design and give therapeutic strategy to this, to prevent, to postpone, to improve or to reverse irreversible organ injury.One or more disease association biomarkers of the present invention can be used for diagnosing the patient of diabetes B or relevant disease, or preferably diagnose the asymptomatic patient of diabetes B and relevant disease.Biomarker of the present invention also can be used for designing new curative.For example, in diabetic's body, do not exist and the biomarker that exists in healthy individual can constitute new preventive medicine or curative, but in a single day such medicine gives the patient just mitigation symptoms or even reverse disease.

Therefore, on the one hand, the invention provides patient's the diabetes B or the diagnosis or the authentication method of prediabetes illness, it comprises the effective dose of measuring one or more diabetes marks (DBMARKERS) in patient's sample or its metabolin, and compare with reference value, wherein for reference value, one or more DBMARKERS content raise or reduce and show that the patient suffers from diabetes B or prediabetes illness.

In one embodiment, reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from the experimenter's who does not suffer from diabetes B or prediabetes illness numerical value, or from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness numerical value.

In another embodiment, reduction is meant than reference value and hangs down 10% at least.In other embodiments, rising is meant than reference value high at least 10%.

Sample can be urine, serum, blood plasma, haemocyte, endothelial cell, biopsy sample, pancreatic juice, ascites, marrow, interstitial fluid (interstitial fluid), tear, phlegm or saliva.

DBMARKERS of the present invention can detect by the following method: electrophoresis, immunochemistry, proteomic techniques or genome analysis.It can be radiommunoassay, immunoprecipitation, Western blotting, immunofluorescence assay or enzyme linked immunosorbent assay (ELISA) that immunochemistry detects.Proteomic techniques can comprise SELDI, MALDI, LC/MS, series LC/MS/MS, proteins/peptides array or antibody array.Genome analysis can comprise PCR (PCR), PCR in real time, microarray analysis, RNA trace or southern blotting technique.

In another embodiment, the patient before be not diagnosed as diabetes B or prediabetes illness.The patient before had been diagnosed as diabetes B or prediabetes illness.Perhaps, the patient can be the asymptomatic patient of diabetes B or prediabetes illness.

Another aspect of the present invention is provided for monitoring the method for the process of patient's diabetes B or prediabetes illness, it comprises (a) effective dose of one or more DBMARKERS in very first time period measurement patient first sample, (b) second time cycle measure the effective dose of one or more DBMARKERS in patient's second sample and the content of one or more DBMARKERS of (c) step (a) being measured and step (b) survey content or reference value compares.

In one embodiment, the patient had before accepted diabetes B or prediabetes treatment of conditions.In another embodiment, first sample picks up from and accepts diabetes B or prediabetes treatment for diseases patient before.Second sample picks up from accepts diabetes B or prediabetes treatment for diseases patient afterwards.In other embodiments, diabetes B or prediabetes treatment of conditions comprise workout scheme, meal supplement, surgical intervention, diabetes adjusting medicine or its combination.The process of diabetes B or prediabetes illness can be monitored by the variation that detects following index: body mass index (BMI), insulin level, blood glucose level, HDL level, systolic pressure and/or diastolic pressure or its combination.

In another aspect of this invention, be provided for patient's the diabetes B or the monitoring method of prediabetes treatment for diseases scheme validity, it comprises that (a) measured the effective dose of one or more DBMARKERS in patient's first sample before treatment diabetes B or prediabetes illness, (b) after treatment diabetes B or prediabetes illness, measure the effective dose of one or more DBMARKERS in patient's second sample and the content of one or more DBMARKERS of (c) step (a) being measured and step (b) survey content or reference value compares.In one embodiment, the variation of blood glucose level can be measured by oral glucose tolerance test.

Of the present invention providing on the one hand again to after diagnosing or identify the patient's who suffers from diabetes B or prediabetes illness methods of treatment, it is included in one or more DBMARKERS that exist in very first time period measurement patient first sample or the effective dose of its metabolin, and regulate medicine with one or more diabetes and treat the patient, amount up to one or more DBMARKERS or its metabolin is got back to reference value, described reference value is the value of measuring in the one or more patients that are in the low danger of development diabetes B or prediabetes illness, or the value of measuring among the one or more patients that make moderate progress on the risk of diabetes factor as regulating the result of medicines treatment with one or more diabetes.

In one embodiment, one or more diabetes are regulated cartridge bag and are drawn together sulfonylurea, biguanides, insulin, insulin analog, peroxisome proliferation-activated receptors-γ (PPAR-γ) activator, double action PPAR activator, insulin secretagogue, glucagon-like peptide-1 (GLP-1) analog, inhibitors of dipeptidyl IV, pancreatic lipase inhibitor, alpha-glucosidase restrainer or its combination.In another embodiment, as the result who regulates the medicine treatment with one or more diabetes, the improvement of the risk of diabetes factor comprises that body mass index (BMI) reduction, the reduction of blood glucose level, insulin level rising, the rising of HDL level, systolic pressure and/or diastolic pressure reduce or its combination.

In another aspect of this invention, be provided for to after diagnosing or identify that the patient suffer from diabetes B or prediabetes illness selects the method for therapeutic scheme, it comprises (a) effective dose of one or more DBMARKERS in very first time period measurement patient first sample, (b) measure the effective dose of one or more DBMARKERS in patient's second sample in second time cycle, and the content of one or more DBMARKERS that step (a) is measured and step (b) survey content or reference value compares.In one embodiment, the reference value one or more patients that make moderate progress of the risk of diabetes factor after one or more treatments of diabetes B or prediabetes illness that hang oneself.

The present invention provides the evaluation method that the patient is developed the danger variation of diabetes B or prediabetes illness on the other hand, it comprises (a) effective dose of one or more DBMARKERS in very first time period measurement patient first sample, (b) measure the effective dose of one or more DBMARKERS in patient's second sample in second time cycle, and the content of one or more DBMARKERS that step (a) is measured and step (b) survey content or reference value compares.

On the other hand, the method of one or more relevant complication of the diabetes B of identifying the patient is provided, it comprises the effective dose of measuring one or more DBMARKERS in patient's sample or its metabolin and compares with reference value, wherein for reference value, one or more DBMARKERS content raise or reduce the danger that shows that the patient suffers from the diabetes B related complication or has the described complication of development.

In one embodiment, complication comprises that retinopathy, blind, the loss of memory, ephrosis, kidney failure, angiocardiopathy, neuropathy, autonomic function obstacle, hyperglycaemia height ooze stupor or its combination.In another embodiment, reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from after diagnosing or identify the patient's suffer from diabetes B numerical value, or from the numerical value of before suffering from the patient of one or more relevant complication of diabetes B through evaluation.

The present invention provides diabetes B reference expression profile (expression profile) on the other hand, is included in the pattern of not diagnosing or identify one or more DBMARKERS expressions that detect among the one or more patients that suffer from diabetes B.On the other hand, the invention provides prediabetes illness reference expression profile, be included in the pattern of not diagnosing or identify one or more DBMARKERS expressions that detect among the one or more patients that suffer from the prediabetes illness.The present invention also provides diabetes B patient's express spectra, is included in after diagnosing or identifies to suffer from diabetes B, be in the danger of development diabetes B or treating the pattern of the expression that detects among one or more patients of diabetes B.On the other hand, the present invention also provides prediabetes illness patient's express spectra, is included in after diagnosing or identifies to suffer from the prediabetes illness, be in the danger of development prediabetes illness or treating the pattern of the expression that detects among one or more patients of prediabetes illness.

The present invention also provides kit, it comprises the DBMARKER detectable that detects one or more DBMARKERS, from sample and the optional guide for use of the experimenter with normal glucose level, the guide for use explanation uses described reagent to produce express spectra disclosed herein.Detectable can be for example one or more antibody or its fragment, one or more adaptive sons (aptamers), one or more oligonucleotides or its combination.

In another aspect of this invention, be provided for treating the pharmaceutical composition of patient's diabetes B or prediabetes illness, it comprises one or more DBMARKERS or its metabolin and the pharmaceutically acceptable carrier or the thinning agent for the treatment of effective dose.In certain embodiments, the DBMARKER metabolin comprises SEQ ID NO:1.In other embodiments, the DBMARKER metabolin comprises at least 5, at least 10, at least 15 or at least 20 continuous amino acid residues of SEQ ID NO:1.Perhaps, the DBMARKER metabolin can comprise the amino acid sequence that has at least 90% homogeneity with SEQ ID NO:1.

The present invention also provides basically the pharmaceutical composition of being made up of SEQ ID NO:1 and pharmaceutically acceptable carrier or thinning agent.

More on the one hand, offer the patient treatment diabetes B of needs or the method for prediabetes illness, it comprises the pharmaceutical composition of the present invention that gives the patient treatment effective dose.

Except as otherwise noted, otherwise all scientific and technical terminologies used herein all have the known implication of one skilled in the art of the present invention.Although can use in practice of the present invention and method as herein described and materials similar or method that is equal to and material, suitable method and material are as described below.All publications mentioned in this article, patented claim, patent and other reference all are attached to herein by reference.Under contradictory situation, be as the criterion with this instructions (comprising definition).In addition, material as herein described, method and embodiment only are illustrative, rather than restrictive.

According to following detailed description and claims, further feature of the present invention and advantage will be apparent.

The accompanying drawing summary

(be attached to herein by reference) in conjunction with the following drawings, be appreciated that with illustrative approach rather than the following detailed description that provides in the mode that limits the present invention in the described specific embodiments, wherein:

Fig. 1 represent to feed protein expression profile of glucopyron of the Cohen insulin resistance (CDr) of conventional meals (RD) or low copper high-sucrose meals (HSD) and susceptibility (CDs) rat.Under reducing condition, prepare total protein extract (5 μ g) and on the 4-12% polyacrylamide gel, run glue.

Fig. 2 A is the figure comparison of blood serum sample on the chip of SELDI Q10 anion exchange surface from CDr-RD, CDs-RD, CDr-HSD and CDs-HSD.Central peak appears at (arrow indication) among CDr-RD and the CDr-HSD, but does not appear among CDs-RD and the CDs-HSD.The protein fragments at this differential expression peak is through being accredited as the C-end fragment of Serpina 3M.

Fig. 2 B is through the MS/MS of 4.2 kilodalton fragments of SELDI evaluation spectrum.

Fig. 3 A shows 38 amino acid whose Serpina 3M (being also referred to as " D3 ") peptides and has the BLAST comparison of the protein of similar sequence homogeneity through evaluation.

Fig. 3 B shows 38 amino acid whose Serpina 3M peptides and the BLAST comparison of the nucleic acid sequences encoding proteins identified in 3A.

Fig. 3 C is the Ago-Gel photo that shows the RT-PCR experimental result, uses the degenerate primer of the conserved amino acid motif of finding in being designed for the BLAST comparison that detects Fig. 3 A and 3B.

Fig. 4 A is the two-dimensional map photo by the blood serum sample of CDr-RD, CDs-RD, CDr-HSD and the CDs-HSD of 2D/LC piece-rate system (fractionation system) analysis.The detected reactive protein content of uv absorption is passed through in the intensity representative of blue band at the 214nm place.

Fig. 4 B shows the CDr-RD (redness) of the selected first dimension isoelectric point flow point (flow point 31) and the differential second dimension reversed-phase HPLC elution profile of CDs-RD (green).In the CDs-RD sample unique protein that identifies list in figure below.

Fig. 5 A is the protein gel photo with two-dimensional gel electrophoresis (2DE), shows the different proteins spectrum of CD rat blood serum sample.The pH of the first dimension chromatofocusing is pH 5-8, and second dimension is separated the gel with 4-20%Tris-HCl SDS-PAGE.Gel is with BioSafe coomassie dyestuff (Bio-Rad) dyeing, so that observe.

Fig. 5 B is the enlarged drawing of the each point of identifying among Fig. 5 A.

Fig. 6 is included in the synoptic diagram of the differential expression protein of finding in the Cohen diabetes rat model, uses 2DE.

Fig. 7 is a histogram, shows the Cohen diabetes rat haemocyanin of the differential expression of identifying by 2DE.

Fig. 8 is the Western blotting photo, show exist in D3 hyperimmune rabbit anteserum and CDr-RD and the CDr-HSD rat blood serum～reactivity of 4kD protein fragments.In left figure, the more dual band of high molecular (in 49kD and 62kD scope) also reacts with hyper-immuneserum, show that parent's albumen (and protein complex) expressed by all strains under RD and HSD treatment modalities, and the littler derivant of size differential expression in the CDr strain only.As negative control, right figure is presented at the Western blotting film of hatching when D3 hyperimmune rabbit anteserum does not exist.

Fig. 9 shows the concentration of D3 peptide in the CDr rat blood serum of calculating by the SELDI analysis meter.

Figure 10 is the gel photograph that contains liver extract (10 μ g), it is surveyed with second goat anti-rabbit igg (1: 25000 dilution) of puting together horseradish peroxidase (HRP), at the first anti-D3 serum antibody (dilution in 1: 200) when having (right figure) or not having (left figure).

Figure 11 is the Western blotting photo with rabbit D3 hyper-immuneserum analyst serum.The 1st road is equivalent to molecular weight marker.The representative of 2-7 road is from the flow point (fraction) of the single blood serum sample of normal individual (3045NGT).The representative of 10-14 road is from the flow point of diabetes B patient's (291) single blood serum sample.

Figure 12 A and Figure 12 B show the preparation type gel that runs glue respectively with 100 μ g CDr-HSD and CDs-HSD glucopyron.Positive control dyes with 600 μ l conditioned medium supernatants with the anti-actin antibody staining of 20 μ g, subclone swimming lane.

Figure 13 shows by SELDI, people's whole serum spectrum result on anionic Q10 protein-chip.

Figure 14 is pseudo gel (pseudogel) figure, is presented at the protein peak of the differential expression of identifying in 13 T2D and 16 the normal human serum samples.For M/Z 15.2kD mark, the average peak intensity of T2D sample is 2.6, and for normal specimens, average peak intensity is 22.2.The difference of two sample rooms is about 9 times.For M/Z 14.8kD mark, the mean intensity of T2D sample is 4.4, and the mean intensity of normal specimens is 3.3.The relative intensity ratio is 1.47.

Figure 15 is pseudo gel figure, is presented at the protein peak of the differential expression of identifying in 13 T2D and 16 the normal human serum samples.The average peak intensity of T2D sample is 118, and for normal specimens, average peak intensity is 182.The relative intensity ratio is 0.65.Each point is represented the protein peak intensity of measuring in the single sample.

Figure 16 is figure, shows from the different albumin spectrums of fat T2D experimenter's sample (doctor's Cheatham sample) with non-fat T2D experimenter's sample (doctor's Dankner sample).

Figure 17 A and Figure 17 B represent the CDs-HSD that records at the O.D.450nm place by absorbance and the reactive synoptic diagram of ELISA of CDr-HSD specific hybrid knurl colony.

Figure 18 A, Figure 18 B and Figure 18 C are the Western blotting photos, show the reactivity of CDs-HSD and CDr-HSD specific hybrid knurl clone P2-10-B8-KA8, P1-14-A2-E-H8, P2-4-H5-K-B4, P1-20-B7-F-C1, P2-13-A9-P-A8 and P1-5-F11-XF5.

Figure 19 is the SDS-polyacrylamide gel of coomassie dyeing, then uses the photo that carries out immunoprecipitation from the specific hybrid knurl clone of CDs-HSD and CDr-HSD.

Figure 20 A and Figure 20 B are the screenshot captures of the MS analysis of spectrum of the below band that the SDS-PAGE gel cuts from Figure 18 (lower band).It is the positive identification of calnexin (calnexin) that the below band is made.

Figure 21 is the scatter diagram of 137 difference expression genes in the Cohen diabetes B rat pancreas.Up-regulated gene and down-regulated gene are all as shown in the figure.

Figure 22 A represents gene tree (Gene Tree) microarray analysis to 12,729 genes that exist in the Cohen diabetes B rat pancreas.

Figure 22 B represents to finding in the Cohen diabetes B rat pancreas 820 genes of 2 times of changes and the gene tree microarray analysis that 137 genes of 3 times of changes are arranged are arranged on expressing on expressing.

Figure 22 C represents that it shows 3 times change on expressing by 137 genes of the 1-5 group of K-mean cluster method (K-mean clustering) classification.

Detailed Description Of The Invention

The present invention relates to have diabetes or prediabetes illness or tend to develop the evaluation of the biomarker that the patient of diabetes or prediabetes illness is correlated with. Therefore, feature of the present invention is the diagnosis and prognosis method, is used for identifying the patient who tends to develop diabetes or prediabetes illness by biological markers detection disclosed herein, comprises the asymptomatic patient of diabetes or prediabetes illness. Preferably also can use biomarker, identify to have the diabetes B related complication or be in the patient of developing in the danger of diabetes B related complication. These biomarkers also can be used for monitoring the patient of experience diabetes or prediabetes treatment for diseases and are used for selecting the patient who suffers from diabetes or prediabetes illness is effectively treated, wherein these treatments of choice and operation can delay diabetes or prediabetes illness process, or substantially delay or prevent its outbreak. Biomarker of the present invention can be the form of pharmaceutical composition, is used for the treatment of the patient of diabetes B or associated conditions.

Except as otherwise noted, otherwise do not add before the term used herein and comprise odd number and plural form when number limits. For instance, when mentioning " activating agent " or " pharmacologically active agents ", comprise the combination of a kind of activating agent and two or more different activities agent, when mentioning " carrier ", comprise two or more carriers and a kind of carrier, etc.

" diabetes " for the present invention comprise type 1 diabetes (LADA and idiopathic) and diabetes B (being referred to as " diabetes "). World Health Organization's definition, fasting plasma glucose concentration is to be exactly the diagnostic value (whole blood 6.1mmol/l or 110mg/dl) of diabetes more than the 7.0mmol/l (126mg/dl), or 2 hours glucose level 〉=11.1mmol/L (〉=200 mg/dL). Other value of expression diabetes high-risk comprises angiosthenia rising (〉=140/90mm Hg); Plasma triglyceride rising (〉=1.7mmol/L; 150mg/dL) and/or low HDL-cholesterol (man＜0.9mmol/L, 35mg/dl; Woman＜1.0mmol/L, 39mg/dL); Abdominal obesity (man: waist-to-hipratio＞0.90; The woman: waist-to-hipratio＞0.85) and/or body mass index surpass 30kg/m² Microalbuminuria, wherein urinary albumin excretion ratio 〉=20 μ g/min or albumin: kreatinin ratio 〉=30 mg/g).

" prediabetes illness " refers to the metabolism state between normal glucose stable state, metabolism and state observed in asymptomatic (frank) diabetes. The prediabetes illness includes but not limited to that metabolic syndrome (" syndrome X "), glucose tolerance lower (IGT) and fasting blood-glucose lowers (IFG). IGT refers to the GLPP dysregulation, and that IFG refers to measure under the empty stomach state is unusual. The value of the definition IFG of the World Health Organization is above (the whole blood 5.6mmol/L of fasting plasma glucose concentration 6.1 mmol/L (100mg/dL); 100mg/dL), but less than 7.0 mmol/L (126mg/dL) (whole blood 6.1mmol/L; 110mg/dL). According to state-run cholesterol education project (National Cholesterol Education Program, NCEP) standard, metabolic syndrome is defined as at least 3 with following index: blood pressure 〉=130/85mm Hg; Fasting plasma glucose 〉=6.1mmol/L; Waistline＞102cm (man) or＞88cm (woman); Triglycerides 〉=1.7mmol/L; With HDL cholesterol＜1.0mmol/L (man) or 1.3mmol/L (woman).

" glucose tolerance attenuating " (IGT) is defined as the blood glucose level and is higher than normal but is not enough to classify as diabetes. The 2 hour glucose levels of the patient of IGT in the 75g oral glucose tolerance test are 140-199mg/dL (7.8-11.0mmol). Such glucose level is higher than normally, but is lower than the level that is diagnosed as diabetes. The patient that glucose tolerance lowers or fasting glucose lowers has the remarkable danger of development diabetes, is the important goal crowd of primary prevention therefore.

" insulin resistance " refers to that body cell has the illness of repellence to the effect of insulin, that is to say that the normal reaction to specified rate insulin reduces. The result needs higher levels of insulin, in order to allow insulin bring into play its effect.

" diabetes B related complication " or " prediabetes illness related complication " can include but not limited to diabetic retinopathy, nephrosis, blind, the loss of memory, kidney failure, angiocardiopathy (comprising coronary artery disease, peripheral arterial disease, cerebrovascular disease, atherosclerotic and hypertension), neuropathy, autonomic dysfunction, hyperglycaemia Hyperosmotic coma or its combination.

" normal glucose level " can with term " euglycemia " Alternate, refer to that limosis vein blood slurry concentration of glucose is less than 6.1mmol/L (110mg/dL). Although this numerical value is artificial definition, such numerical value is observed in the experimenter who confirms NGT, can have IGT although measure some experimenter by oral glucose tolerance test (OGTT). For the definition of the present invention and this paper, baseline value, exponential quantity or reference value for example can comprise " normal glucose level ".

The diabetic or show among the patient of symptom characteristic of prediabetes illness, identify 158 biomarkers and had content or the concentration level that changes or modify, these patients are Patients with Insulin Resistance for example, it has the β cell function of change, perhaps judges in its danger that is in the development diabetes according to following known clinical parameter or risk factor: for example the diabetes family history, activity level is low, meals are poor, overweight (especially waistline), age greater than 45 years old, hypertension, high levels of triglycerides, HDL cholesterol less than 35, before be accredited as glucose tolerance and lower, before diabetes (" gestational diabetes mellitus ") or output body weight were arranged greater than 9 pounds baby and race at pregnancy duration.

Biomarker of the present invention and method allow those skilled in the art to identify, diagnose or estimate not show any symptom of diabetes or prediabetes illness but still be in the development diabetes or the patient of the danger of experience prediabetes condition symptoms feature.

Term for the present invention " biomarker " includes but not limited to fragment, element, metabolin and other analyte of polymorphism, splicing variants, protein or the nucleic acid of protein, peptide, nucleic acid, protein and nucleic acid. Biomarker also can comprise mutain or mutant nucleic acid. Term used herein " analyte " can refer to any material to be determined is arranged and can comprise electrolyte and element, for example calcium. Finally, biomarker also can refer to comprise the non-analyte physiology mark under the health status of other Clinical symptoms, such as but not limited to age, race, diastolic pressure and systolic pressure, body mass index and static heart rate.

Diabetes or prediabetes illness patient or tend to develop in the patient body of diabetes or prediabetes illness, the protein that level can change, peptide, nucleic acid, polymorphism and metabolin are summarized in table 1, and are referred to as in this article " diabetes GAP-associated protein GAP ", " DBMARKER polypeptide " or " DBMARKER albumen " etc. The corresponding nucleic of coded polypeptide is called " diabetes associated nucleic acid ", " diabetes related gene ", " DBMARKER nucleic acid " or " DBMARKER gene ". Except as otherwise noted, otherwise " DBMARKER ", " diabetes GAP-associated protein GAP ", " diabetes associated nucleic acid " refer to any sequence disclosed herein. Also can measure the corresponding metabolin of DBMARKER albumen or nucleic acid, they are referred to herein as " DBMARKER metabolin ". By one or more, preferably the mensuration of two or more above-mentioned DBMARKERS kinds and the gauge index that obtains in conjunction with mathematical computations are called " DBMARKER index ". Protein, nucleic acid, polymorphism, mutain and mutant nucleic acid, metabolin and other analyte and conventional physiological measurement and from the constructed index of any aforementioned entity all are included among " DBMARKERS " kind of broad sense.

The about 4.2kD of the molecular weight of a kind of target DBMARKER also further is accredited as the C-end fragment of serpin Serpina 3M. In CDr-RD and CDr-HSD rat, this mark demonstrates and can be raised. The amino acid sequencing of this fragment shows that this fragment comprises amino acid sequence SGRPPMIVWFNRPFLIAVSHTHGQTILFMAKVINPVGA (SEQ ID NO:1).

DBMARKER for the present invention " metabolin " comprises the part of full-length polypeptide. Concrete length do not specified in term " part ". The length of DBMARKER metabolin can be less than 500 amino acid, and for example length is less than or equal to 400,350,300,250,200,150,100,75,50,35,26,25,15 or 10 amino acid. Exemplary DBMARKER metabolin comprises peptide, and it can comprise (all or part of) sequence of SEQ ID NO:1. Preferred DBMARKER metabolin comprises at least 5,10,15,20,25 or the more continuous amino acid of SEQ ID NO:1.

For the present invention " patient " or " experimenter " are preferably mammal. Mammal can be people, non-human primates, mouse, rat, dog, cat, horse or ox, but is not limited to these examples. Non-human mammal is preferably as the patient who represents the animal model of diabetes or prediabetes illness. The patient can be male or female. The patient can be previous after diagnosing or identify the patient who suffers from diabetes or prediabetes illness, and optional but not necessarily accepted the patient of diabetes or prediabetes treatment for diseases. The patient also can be the experimenter who does not suffer from diabetes B or prediabetes illness. The patient also can be after diagnosing or identify to suffer from diabetes B or prediabetes illness but as the patient who makes moderate progress in the result who accepts one or more diabetes Bs or prediabetes treatment for diseases and in the known risk of diabetes factor. Perhaps, the patient also can be the patient who before suffers from after diagnosing diabetes or prediabetes illness. For example, the patient can be the patient who shows one or more risk factors of diabetes or prediabetes illness, or the patient who does not show the risk of diabetes factor, or the asymptomatic patient of diabetes or prediabetes illness. The patient suffers from diabetes or prediabetes illness or is in patient in the danger of development diabetes or prediabetes illness. The patient also can be after diagnosing or differentiate the patient suffer from one or more relevant complication of diabetes B defined herein or prediabetes illness, perhaps, the patient had not before diagnosed or had identified the patient who suffers from one or more relevant complication of diabetes B or prediabetes illness.

" sample " for the present invention is the biological sample that separates from the patient, can comprise for example serum, blood plasma, haemocyte, endothelial cell, biopsy sample, lymph liquid, pancreatic juice, ascites, interstitial fluid (be also referred to as " extracellular fluid " and comprise the liquid of finding in intercellular the matter, comprise level in gingival sulcus fluid etc.), marrow, phlegm, saliva, tear or urine.

In the present invention practice, can detect one or more, preferred two or more DBMARKERS. For example can detect 1,2,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155 or more kinds of DBMARKERS. In some aspects, all 158 kinds of DBMARKERS disclosed herein can detect. Preferred detectable DBMARKERS quantitative range is included in any minimum of a value limited range of selecting between the 1-158, especially 2,5,10,15,20,25,30,40,50,60,70,80,90,100,110,120,130,140,150, with any maximum pairing of total known DBMARKERS, especially 1,2,5,10,20 and 25. Especially preferred scope comprises 1-2,1-5,1-10,1-15,1-20,1-25,1-30,1-35,1-40,1-45,1-50,1-55,1-60,1-65,1-70,1-75,1-80,1-85,1-90,1-95,1-100,1-120,1-125,1-130,1-140,1-150,1-158,2-5,2-10,2-15,2-20,2-25,2-30,2-35,2-40,2-45,2-50,2-55,2-60,2-65,2-70,2-75,2-80,2-85,2-90,2-95,2-100,2-120,2-125,2-130,2-140,2-150,2-158,5-10,5-15,5-20,5-25,5-30,5-35,5-40,5-45,5-50,5-55,5-60,5-65,5-70,5-75,5-80,5-85,5-90,5-95,5-100,5-120,5-125,5-130,5-140,5-150,5-158,10-15,10-20,10-25,10-30,10-35,10-40,10-45,10-50,10-55,10-60,10-65,10-70,10-75,10-80,10-85,10-90,10-95,10-100,10-120,10-125,10-130,10-140,10-150,10-158,20-50,20-75,20-100,20-120,20-125,20-130,20-140,20-150,20-158,50-75,50-100,50-120,50-125,50-130,50-140,50-150,50-158,100-125,125-150 and 150-158.

The diagnosis and prognosis method

Compare by " effective dose " of DBMARKER albumen, peptide, nucleic acid, polymorphism, metabolin and other analyte in the determination test sample (for example from patient sample) and with these effective dosies and reference value or exponential quantity, can measure the danger that develops diabetes or prediabetes illness. " effective dose " can be DBMARKERS total amount or the level of measuring in the sample, perhaps can be the amount of " standardization ", the DBMARKERS that for example detects in the sample and the difference between the ambient noise. Standardized method is different and different because of assay method with standardized value. Preferably can adopt mathematical algorithm, will integrate from the result's of the DBMARKERS of a plurality of individualities information and form one and detect or index. Can select arbitrarily to have through evaluation the patient of the danger increase of diabetes or prediabetes illness, the scheme of receiving treatment, for example give preventative or therapeutic compound (for example " diabetes regulating (diabetes-modulating agent) " defined herein), or perform physical exercise scheme or meal supplement, with the outbreak of prevention or delay diabetes or prediabetes illness. The sample that separates from the patient can comprise for example blood, blood plasma, haemocyte, endothelial cell, biopsy sample, lymph liquid, pancreatic juice, serum, marrow, ascites, interstitial fluid (comprising for example level in gingival sulcus fluid), urine, phlegm, saliva, tear or other body fluid.

But the content of DBMARKER albumen, peptide, nucleic acid, polymorphism, metabolin or other analyte and compare with the normal control level in the determination test sample. Term " normal control level " refers to usually do not suffering from diabetes or prediabetes illness and can not suffer from the level of one or more DBMARKER albumen, nucleic acid, polymorphism, metabolin or other analyte found among the experimenter of diabetes or prediabetes illness, or the DBMARKER index, for example with respect to the sample that gathers from young experimenter's longitudinal research: described experimenter is monitored until advanced age and discovery do not develop diabetes or prediabetes illness. " normal control level " can comprise the value that derives from the experimenter with " normal glucose level " defined herein or " NGT (normoglycemic) level ". Perhaps, the normal control level can refer to the level of common one or more DBMARKER albumen, peptide, nucleic acid, polymorphism, metabolin or other analyte of finding in the patient who suffers from diabetes or prediabetes illness. The normal control level can be a scope or index. Perhaps, the normal control level can be the database from previous tested experimenter's pattern. Compared with the normal control level, from the variation on one or more DBMARKER albumen, nucleic acid, polymorphism, metabolin or other analyte level of patient's sample, show that the experimenter suffers from diabetes or prediabetes illness or is in the danger of development diabetes or prediabetes illness. By contrast, when the method is used for prevention, with the similar level of comparing from the normal control level of one or more DBMARKER albumen, nucleic acid, polymorphism, metabolin or other analyte of patient's sample, show that the experimenter does not suffer from diabetes or prediabetes illness or is not in the danger that develops diabetes or prediabetes illness, perhaps is in the low danger of development diabetes or prediabetes illness.

Reference value can refer to derive from the value of contrast experimenter or colony, perhaps can be exponential quantity or baseline value, the diabetic disease states of described experimenter or colony is known (after diagnosing or identify to suffer from diabetes B or prediabetes illness namely, or after diagnosing or identify and do not suffer from diabetes B or prediabetes illness). Reference sample or exponential quantity or baseline value can gather from or from the one or more patients that received treatment, perhaps gather from or from the one or more patients in the low danger that is in development diabetes or prediabetes illness, perhaps gather from or from the patient who makes moderate progress as the result who receives treatment and in the risk of diabetes factor. Perhaps, reference sample or exponential quantity or baseline value can gather from or from the one or more patients that do not receive treatment. For example, sample can gather from such patient: described patient accepted the preliminary treatment of diabetes or prediabetes illness and accept diabetes or the continual cure of prediabetes illness with the monitor therapy process. Reference value also can comprise the value that derives from the risk prediction algorithm or the gauge index of studying from for example colony disclosed herein. Reference value also can be the value that derives from the patient who before suffers from after diagnosing one or more relevant complication of diabetes B or prediabetes illness, or derives from the value that not yet develops complication or before do not diagnose or identify the patient who suffers from diabetes B or prediabetes illness related complication. Reference value also can comprise corresponding to the normal control level or derive from the value of the one or more experimenters with " normal glucose level " defined herein.

The level of the DBMARKERS that detects through the inventive method or the difference of content (it can be " effective dose ") can comprise rising or the reduction of DBMARKERS level or content. For reference value, the rising of DBMARKERS content or reduction can be indicated the process of diabetes B or prediabetes illness, delay, process, development or the improvement of diabetes B or prediabetes illness related complication, increase or the reduction of the danger of development diabetes B or prediabetes illness or its related complication. Raise or reduce the indication of one or more therapeutic scheme successes that can be diabetes B or prediabetes illness, perhaps can indicate the improvement of the risk of diabetes factor or disappear. Raising or reduce can be for example at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45% or at least 50% of reference value or normal control level.

The difference of DBMARKERS level (or content) preferably has statistical significance. Alleged " statistical significance " refers to change greater than the occurrent change of expection. Can measure statistical significance by any known method in this area. For example by p value decision statistic conspicuousness. The p value is the accidental tolerance that the probability of difference occurs between each group of experimental session. (P (z＞z observes)). For example, the p value is 0.01, refers in 100 chances the result to occur 1 time accidentally. The p value is lower, more might be that group difference is to be caused by processing. When the p value was at least 0.05, change just had statistical significance. Preferred p value is 0.04,0.03,0.02,0.01,0.005, below 0.001. As described below and do not limit the present invention, reach statistical significance usually but always do not need some DBMARKERS combine in groups (in panel) used, and in conjunction with mathematical algorithm, in order to reach the DBMARKER index of statistically significant.

" diagnostic accuracy " of test, mensuration or method relate to test, mensuration or method to suffer from diabetes or prediabetes illness be in diabetes or the danger of prediabetes illness in patient's resolving ability, be according on one or more DBMARKERS levels, whether having " conspicuousness existence clinically " or " conspicuousness change clinically ".Alleged " conspicuousness existence clinically " or " conspicuousness change clinically ", be meant the existing of DBMARKER (quality (milligram for example for example, microgram) or the transcript copy number of quality of unit volume (for example milligram/decilitre) or unit volume)) or the variation of DBMARKERS content in patient's (usually at patient's sample), greater than the predetermined cut off (cut-point) (or threshold value) of DBMARKER and therefore show that the patient suffers from diabetes or prediabetes illness, its protein, peptide, nucleic acid, polymorphism, the sufficiently high content of metabolin or analyte is exactly mark.

The present invention can be used for danger classification property that is converted into diabetes B or continuity tolerance, so patient's diagnostic class definition is a prediabetes.

Under the situation of classification, method of the present invention can be used for distinguishing normal and prediabetes illness patient formation (cohort).In such classification application of the present invention, term " high diagnostic accuracy " and " very high diagnostic accuracy " are meant DBMARKERS (or the DBMARKERS index with correct (accurately) predetermined cut off of representing that whether the prediabetes illness exists; Wherein the DBMARKERS value comprises any single metric, no matter is from single DBMARKERS or from the DBMARKERS index) test or mensuration.Perfectly test will have perfect accuracy.Therefore, for the patient who suffers from the prediabetes illness, test will only be represented the positive test result and can not report any " feminine gender " (it is not " false negative ") patient.In other words, " susceptibility " of test (real positive rate) will be 100%.On the other hand, for the patient who does not suffer from the prediabetes illness, test will only be represented the negative test result and can not report any positive (it is not " false positive ") patient.In other words, " specificity " (real negative rate) will be 100%.Referring to for example O ' Marcaigh AS, Jacobson RM, " Estimating The Predictive Value Of A Diagnostic Test; How To Prevent Misleading or Confusing Results; " Clin.Ped.1993,32 (8): 485-491, wherein discuss specificity, susceptibility and the positive and the negative predictive value of testing (for example clinical diagnostic test).In other embodiments, the present invention can be used for distinguishing prediabetes illness and diabetes or diabetes and normal condition.Such purposes may need DBMARKERS (subclass among the disclosed total DBMARKERS of table 1), mathematical algorithm and/or the cut off of different subclass, but for desired use, carry out the measurement of identical above-mentioned diagnostic accuracy.

In the classification diagnosis of disease, the section (cut point) of test (or mensuration) or the change of threshold value can change susceptibility and specificity usually, but are qualitative inverse relationship (in a qualitativelyinverse relationship).For example, if reduce section, have more experimenters in the tested colony usually and have test findings above section or threshold value.Because test findings surpasses the experimenter of section and can be reported as and suffer from test disease, illness or syndrome pointed, more experimenters are reported as have positive findings (for example reporting that they suffer from diabetes or prediabetes illness) so reduce section.Therefore, test will point out that diabetes or prediabetes illness patient's ratio is higher.Therefore, testability (true positive rate) will rise.Yet meanwhile, to have more false positives, because test will point out that more diseases that do not take a disease, illness or syndromic people (for example real " feminine gender " crowd) have the DBMARKER value above section more, thereby be reported as the positive (for example suffering from disease, illness or syndrome), rather than point out correctly that through testing they are negative.Therefore, the specificity of test (true negative rate) will descend.Equally, improving section will reduce susceptibility and improve specificity.Therefore, when the accuracy of estimating proposed medical experiment, mensuration or the method that is used for the evaluate patient illness and validity, usually should consider susceptibility and specificity simultaneously and be careful section what are, susceptibility and the specificity reported when such section are because susceptibility and specificity have significant change because of section scope different.

Yet, an indicated value is arranged, allow only to represent the susceptibility and the specificity of test, mensuration or method in whole test (or mensuration) the section scope with a simple numerical value.This indicated value is used for test, mensuration or the method studied from receptacle operating characteristics (Receiver Operating Characteristics, " ROC ") curve.Referring to for example Shultz, " ClincalInterpretation Of Laboratory Procedures; " the 14th chapter, be stated from Teitz, Fundamentals of Clincal Chemistry, Burtis and Ashwood (writing), the 4th edition, 1996, W.B.Saunders Company, 192-199 page or leaf; With Zweig etc., " ROCCurve Analysis:An Example Showing The Relationships Among SerumLipid And Apolipoprotein Concentrations In Identifying Subjects WithCoronory Artery Disease; " Clin.Chem., 1992,38 (8): 1425-1428.

The ROC curve is the x-y curve map, and the y axle is a susceptibility, and scale is 0-1 (for example 100%), and the x axle is 1 to deduct specific value, and scale is 0-1 (for example 100%).In other words, this be in this test, mensuration or the method true positive rate at the curve map of false positive rate.The ROC curve of the test of studying in order to make up, mensuration or method, whether the entirely accurate of the test of studying with being independent of, mensuration or method i.e. " goldstandard " method is estimated the experimenter, be disease, illness or syndromic true positives or true negative (for example coronary angiography is exactly the goldstandard test that coronary atherosclerosis exists) to determine the experimenter.The also available test of studying, mensuration or method are tested the experimenter, and for different sections, the report experimenter is positive to test, mensuration or method or is negative.All measure susceptibility (true positive rate) and 1 for each section and deduct specific value (this value equals false positive rate), every pair of x-y value is all drawn a point on x-y figure.It is exactly the ROC curve that these points are linked to be curve.

Best single clinical ending or the treatment threshold value when ROC curve is usually used in determining susceptibility and specificity maximization; This situation is represented the point on the ROC curve, and it is described in the upper left corner of the single maximum rectangle that can draw under this curve.

Total area under curve (" AUC ") is susceptibility and the specific indicated value that allows only to represent with a simple numerical value test, mensuration or method in the whole section scope.Maximum AUC is 1 (perfect test), and minimum area is 1/2 (for example area when normal and disease indistinction).AUC is more near 1, and the accuracy of test is good more.The implication that should be noted that all ROC and AUC all is the definition of disease and the target aspect of test back time.

For " high diagnostic accuracy ", be meant such test or mensuration: wherein AUC (test or the ROC area under curve of measuring) is at least 0.70, is preferably at least 0.75, more preferably at least 0.80, preferably at least 0.85, more preferably at least 0.90, most preferably at least 0.95.

For " very high diagnostic accuracy ", be meant such test or mensuration: wherein AUC (test or the ROC area under curve of measuring) is at least 0.80, is preferably at least 0.85, more preferably at least 0.875, preferably at least 0.90, more preferably at least 0.925, most preferably at least 0.95.

Perhaps, in the tested colony of low disease popularity (being defined as annual morbidity less than 1%), ROC and AUC can make the people be misinterpreted as the clinical practice of test, can use other local defined absolute and relative level of significance of this instructions to judge the diagnostic accuracy degree.Also population of subjects to be measured can be divided into quartile, the quartile on top (account for colony 25%) comprises having development or suffer from diabetes or the prediabetes illness subject group of high relative risk, and the quartile of bottom comprises the subject group with development diabetes or the minimum relative risk of prediabetes illness.It has been generally acknowledged that, in low popular colony, from the top quartile to the quartile of bottom, in test or have the value that surpasses 2.5 times of relative risks in measuring and just have " high diagnostic accuracy ", and think have 5-7 times of relative risk in each quartile those just have very high diagnostic accuracy.Yet in each quartile, the value that only has 1.2-2.5 times of relative risk in test or mensuration still has clinical application, can be widely used as the risk factor of disease; These are the cases that have insulin level or blood glucose level for it predicts following diabetes B.

Any test desired value all depends on testability and specificity and depends on the prevalence rate of illness in accepting the colony that tests.This idea is according to Bayes' theorem (Bayes ' theorem), shows the possibility big more (prediction probability) that institute's screening conditions exist in experimenter or colony, and the big more and result of positive test validity is that the possibility of true positives is just big more.Therefore, using the problem of certain test in any colony of the low possibility of the illness that exists at present is exactly that positive findings has finite value (promptly more likely being false positive).Equally, in high danger colony, the negative test result more likely is a false negative.Qualification (being the section on the ROC curve) for diagnostic accuracy, define an acceptable AUC value and determine to constitute the tolerance interval of relative concentration of the effective dose of DBMARKERS of the present invention, can allow those skilled in the art to use DBMARKERS to diagnose or identify experimenter with predictable predeterminated level.

When relevant medical society with medical practice is clear as yet when defining classification of diseases or classification of risks (for example prediabetes illness), use the alternative method of measuring diagnostic accuracy must carry out continuous danger mensuration usually.

" danger " for the present invention is meant " definitely " danger, be meant will event in the cycle at a special time probability (%).Can be with reference to the actual observation result after the mensuration of relative time formation, or with reference to deriving from statistics goes up the benchmark index value of effective historical formation in the relative time cycle, and obtain absolute danger." relatively " danger is meant the ratio of absolute danger with the low dangerous formation or the danger of average colony of experimenter's danger, and this can be different because of the difference of the clinical risk factor of how to evaluate.Odds ratio (Odds ratio), promptly (advantage is to calculate according to following formula: p/ (1-p) for the positive events of given test findings and the ratio of negative incident, wherein p is the probability of incident, and (1-p) is the probability of no incident), also be generally used for not having and transform.The alternative METHOD FOR CONTINUOUS DETERMINATION that can estimate for the present invention comprises that diabetes transformation time and treatment diabetes transform the dangerous ratio that reduces.

For such METHOD FOR CONTINUOUS DETERMINATION, the mensuration of the diagnostic accuracy of gauge index is usually according to the successive value and the linear regression line match between the actual observation value (or history index calculated value) of prediction and utilize and to measure for example R square, p value and fiducial interval.For predicted value, formation prediction according to historical perspective, use it is reported this class algorithm that comprises fiducial interval (common 90% or 95%CI), this is not uncommon, as by Genome Health (Redwood City, California) the same in the test of commercial following breast cancer risk of relapse.

The final judgement and the goldstandard that are converted into the real hazard of diabetes are in enough large groups and the actual conversion of observing in special time length.Yet this is doubt, because need back looking forward or upwards property viewpoint, and any preventative intervention chance.As a result of, suffer from diabetes or prediabetes illness or be in patient in the danger of development diabetes or prediabetes illness normally by the means known in the art diagnosis or identify, and estimate following dangerous according to historical experience and record research.These class methods include but not limited to the mensuration of systolic pressure and diastolic pressure, the mensuration of body mass index, the external test of the T-CHOL in the blood sample, LDL, HDL, insulin and glucose level, oral glucose tolerance test, stress measure, mensuration, cardiogram (ECG), c-peptide level, anti-insulin antibody, anti-β cell-antibody and the glycosylated hemoglobin (HbA of human serum c reactive protein (hsCRP) _1c).In addition, any preceding method all can separately or be united use, whether shows " making moderate progress " with evaluate patient on the risk of diabetes factor.Such improvement includes but not limited to that body mass index (BMI) decline, the decline of blood glucose level, the rising of HDL level, systolic pressure and/or diastolic pressure descend, insulin level rises or its combination.

Oral glucose tolerance test (OGTT) is mainly used in diagnosing diabetes or prediabetes illness, when the blood glucose level is suspicious, pregnancy duration or in epidemiology research (Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications, part 1, World Health Organization, 1999).OGTT should carry out at unrestricted meals (every day is greater than the 150g carbohydrates) and common sports at least the morning after 3 days.Dusk before test should consume reasonably (30-50g) carbohydrate containing meals.Test should be carried out after 8-14 hour in the empty stomach of spending the night, and can drink water during this period.After gathering the empty stomach blood sample, under should drinking, the experimenter contains the 250-300ml water of 75g anhydrous dextrose or 82.5g Dextrose monohydrate in 5 minutes.For children, test load should be 1.75g glucose/kg body weight 75g glucose extremely altogether.Test period timing when beginning to drink.Must gather blood sample in 2 hours behind the test load.As previously mentioned, for being converted into diabetes in 7.5 years, when being used for the WHO cut off, should be noted that the diagnosis that glucose tolerance lowers (IGT) only has 50% susceptibility, and have＞10% false positive rate.This clinical use to test is major issue because even high-risk relatively race's group in such time cycle, all have only 10% to be converted into the ratio of diabetes, unless also have other risk factor; In non-selected ordinary group, the conversion ratio in such time cycle is common to be estimated at 5-6%, or less than 1% every year.

Other method of measuring blood glucose comprises reductiometric method known in the art, such as but not limited to Somogyi-Nelson method, the method for using hexokinase and glucose dehydrogenase, immobilized Glucose-oxidase Electrode, ortho-aminotoluene method, ferricyanide method and new cupferron (neocuprine) automatic analyzer method.In the patient with normal plasma cell specific volume reading, the full blood glucose value is low more about 15% than corresponding blood plasma value usually, and the artery value is usually than corresponding vein value high about 7%.Use the patient of insulin often need set up " blood sugar spectrum " by the oneself of the special time in day mensuration blood sugar." 7 point spectrum " is useful, wherein whenever before the meal and 90 minutes after the meal and go to bed before the sampling.

Suffer from diabetes or prediabetes illness or be in the development these diseases danger in the patient also can suffer from angiocardiopathy, hypertension or obesity or be in the development these diseases danger in.Diabetes B, especially have many common risk factors with angiocardiopathy, many such risk factors are height correlation each other.Relation between these risk factors is attributable to a small amount of physiological phenomenon, even may be a kind of phenomenon.Except measuring one or more DBMARKERS levels of the present invention, suffer from diabetes, angiocardiopathy, hypertension or obesity or be in the development these diseases danger in the patient can be judged by means known in the art.For example, diabetes are diagnosed by measuring fasting blood glucose level or insulin usually.The normal adult glucose level is 60-126mg/dl.Normal insulin level is 7mU/ml ± 3mU.Hypertension continues to maintain by blood pressure or surpasses 140/90 to be diagnosed.The danger of angiocardiopathy also can be diagnosed by measuring cholesterol levels.For example, the LDL cholesterol surpass 137 or T-CHOL surpass 200 and show that the danger of angiocardiopathy increases.Obesity can be diagnosed by for example body mass index.Can measure body mass index (BMI) (kg/m ²(or lb/in ²X 704.5)).Perhaps, can measure waistline (estimation Fat Distribution), waist-to-hipratio (estimation Fat Distribution), skinfold (if measure at several positions, estimate Fat Distribution) or bio-impedance (conduct electricity better principle (being fatty body weight impedance electric current) according to lean body mass than fatty body weight, estimate % fat).Normally, parameter overweight or obese individuals is as follows: underweight: BMI＜18.5; Normally: BMI 18.5-24.9; Overweight: BMI=25-29.9.The feature of overweight individuality be waistline＞94cm (man) or＞80cm (woman), waist-to-hipratio 〉=0.95 (man) and 〉=0.80 (woman).The feature of obese individuals is that BMI is 30-34.9, exceeds 20%, body fat percent＞30% (woman) and 25% (man), waistline＞102cm (40 inches) (man) or 88cm (35 inches) (woman) than " normally " body weight of same height.Feature serious or individuals with morbid obesity is BMI 〉=35.Because the mutual relationship between diabetes and the angiocardiopathy, the DBMARKERS of some or all of individualities of the present invention and DBMARKER express spectra may be overlapping, perhaps be included in the angiocardiopathy biomarker, and can be used for the danger of diagnosis of cardiovascular diseases really.

The risk prediction of diabetes or prediabetes illness also can comprise risk prediction algorithm and gauge index, and it develops the absolute danger of diabetes or prediabetes illness historical formation postevaluation of reference and estimation patient.Carry out danger evaluation with such prediction mathematical algorithm and gauge index, be attached to gradually in the guide of diagnostic test and treatment, and comprise multidate, stratification sample that derives from representative colony and the index that confirms with these samples.The wide variety of conventional risk of diabetes factor is attached in the forecast model.A remarkable example of these algorithms comprises Framingham Heart Study (Kannel, W.B. etc., Am.J.Cardiol.38:46-51) and the revision version of Framingham Study (1976), National CholesterolEducation Program Expert Panel on Detection for example, Evaluation, and Treatmentof High Blood Cholesterol in Adults (Adult Treatment Panel III), be also referred to as NCEP/ATP III, it combines patient age, total cholesterol concentration, the HDL cholesterol concentration, smoking state and systolic pressure, estimating the 10 terms danger of individual development angiocardiopathy, this is the patient who suffers from diabetes or prediabetes illness or to be among the patient in the danger of these diseases of development be often to find.Known that the Framingham algorithm suitably predicted the danger of development diabetes or prediabetes illness.

Other risk of diabetes prediction algorithm includes but not limited to San Antonio cardiac studies (San Antonio Heart Study) (Stern, M.P. etc., (1984) Am.J.Epidemiol.120:834-851; Stern, M.P. etc., (1993) Diabetes 42:706-714; Burke, J.P. etc., (1999) Arch.Intern.Med.159:1450-1456), Archimedes (Archimedes) (Eddy, D.M. and Schlessinger, L. (2003) Diabetes Care 26 (11): 3093-3101; Eddy, D.M. and Schlessinger, L. (2003) Diabetes Care 26 (11): 3102-3110), based on the risk of diabetes of Finland scoring (Finnish-based Diabetes Risk Score) (

, J. and Tuomilehto, J. (2003) Diabetes Care 26 (3): 725-731) with Ely Study (Griffin, S.J. etc., (2000) Diabetes Metab.Res.Rev.16:164-171), described content all is attached to herein by reference.

Archimedes (Archimedes) is a kind of mathematical model of diabetes, the morbid state of its simulation person to person, object and object, and comprise biology details continuous in the reality, for example relevant tract, surpass 50 continuous interactional biology variablees and cardinal symptom, test, treatment and the result relevant usually with diabetes.

Archimedes comprises simultaneously and interacts in a complete physiological numerous disease, makes it can seek feature, for example is total to the incidence of disease, syndrome, treatment and other multiple effect.Archimedes's model comprises diabetes and complication thereof, for example coronary artery disease, congestive heart failure and asthma.This model can be write as the differential responses formula, with object-oriented programming and structure (being called " feature (features) ").Model comprises that (all simulation experimenters have organ to experimenter's anatomy, the heart for example, liver, pancreas, intestines and stomach, fat, muscle, kidney, eye, four limbs, the circulation system, brain, skin and peripheral nervous system), decision lysis is also represented " feature " (milligram number of glucose in one deciliter of blood plasma for example of actual physiology phenomenon, phenomenon in the behavior or notional phenomenon (for example disease " process "), risk factor, the incidence of disease and disease process, glucose metabolism, sign and test, diagnosis, symptom, the healthy result of glucose metabolism, treatment, complication is because of the death due to diabetes and the complication thereof, because of death, nursing process and the medical system resource due to other reason.Typical case for model uses, there is thousands of simulation experimenters (to have artificial anatomy and physiology separately, it will accept the simulation disease) can seek nursing in the simulation health care facility, can observe them in simulation mechanism by the simulation health care personnel, they will accept simulation test and treatment.And will have analog result.In reality, each simulated patient all is different, has different characteristic, physiology, behavior and to the reaction of treatment, all designs all with reality in observed individual difference be complementary.

Learn and pathological non-quantitation or conceptual description by the exploitation associated biomolecule, structure model-variable and relation-because they use the existing information best appreciated.Identify the research that belongs to variable and relation then, generally include fundamental research, epidemiology and clinical research, these all are that the expert of the art identifies the fundamental research of understanding as to disease itself.These information are used for the different formulas of development specification variable relation.The exploitation of any specific formulation all comprises the discovery form and the coefficient of the available information of suitable related variable in Archimedes's model, then formula is programmed for the language in the face of object.Then be a series of exercises, wherein test and adjustment model part, before this one next, be suitable combination then, with having the input of known output.Then, whole model is used for the Simulation of Complex test, not only proves the each several part of model, and proves the contact between all parts.(distributed computing technique) carries out Archimedes's calculating with the Distribution calculation machine technology.Proved that Archimedes is diabetes and complication homologic anatomy, Pathological Physiology, treatment and result's reality representative (Eddy, D.M. and Schlessinger, L. (2003) Diabetes Care 26 (11) 3102-3110).

Design is based on the scoring of the risk of diabetes of Finland, as the screening implement of identifying high-risk patient in the colony, and as the screening basis of the cognition of the increase that can change risk factor and healthy Lifestyle.With without the 35-64 of antidiabetic medicine treatment year Finland men and women random population sample as baseline, and followed the tracks of 10 years, determine the risk of diabetes scoring.Give each types of variables assignment with multivariate Logic Regression Models coefficient.Risk of diabetes scoring comprises the summation of these each scorings and is confirmed in the independent mass survey in 5 years is followed up a case by regular visits in an expection of carrying out in 1992.Fruit, berry or the vegetables selecting age, BMI, waistline, drug for hypertension treatment history and consume high blood glucose, sports and every day are as classified variable.

Based on the risk of diabetes score value of Finland from the logical model coefficient, promptly by they are fallen into 5 types.For the combination of any risk factor, can obtain 10 term estimated probabilitys (p) from following coefficient through the diabetes of drug therapy:

β wherein ₀Be intercept, β ₁, β ₂Deng representing inhomogeneity risk factor x ₁, x ₂Deng regression coefficient.

Susceptibility is meant the probability that test is positive for the patient that will obtain drug treatment of diabetic for future, and specificity reflects the probability that test is negative for the patient who does not have drug treatment of diabetic.When distinguishing the patient of developing drug treatment of diabetic and can not develop the patient of drug treatment of diabetic, all calculate the susceptibility and the specificity of 95% fiducial interval (CI) for each risk of diabetes scoring level.The ROC curve is drawn in scoring to risk of diabetes, and susceptibility is plotted on the y axle, and false positive rate (1-specificity) is plotted on the x axle.More identification exactly of test, ROC curve precipitous more to top, AUC is high more, and best section is a peak of curve.

In the risk of diabetes scoring, the statistical significance independent prediction value of future drugs treatment diabetes is age, BMI, waistline, drug for hypertension treatment and the horizontal history of high blood glucose.Risk of diabetes scoring model comprises a simplified model and the complete model with sports and fruit and vegetable consumption that these statistical significance variablees are only arranged.

San Antonio cardiac studies (San Antonio Heart Study) is the community-based long-term forecasting observational study of diabetes of carrying out in chicano and non-Hispanic Caucasian and angiocardiopathy.At first this research recruited 3,301 chicanos and 1,857 non-Hispanic Caucasia man and non-gravid woman in two cycles during 1979 and 1988.Participant's age be 25-64 year and be chosen at random the San Antonio, Texas low, in and the neighbours of booming income.About 73% survival individuality in the individuality of studying initial recruitment is carried out a 7-8 followed up a case by regular visits to test.Editor has also estimated baseline characteristic, for example treating diabetes history, age, sex, race, BMI, systolic pressure and diastolic pressure, empty stomach and 2 hours plasma glucose levels, empty stomach serum total cholesterol, LDL and HDL cholesterol levels and triglyceride levels.One have relevant diabetes as the multiple logic regression model of dependent variable and above-mentioned baseline characteristic as independent variable.Adopt this model, can be respectively to each potential danger factor of men and women with simultaneously univariate odds ratio is calculated in both sexes.For continuous risk factor, odds ratio can be the increment of 1-SD.Can adopt the stepwise logistic regression method, develop a multivariable prediction model that has both sexes simultaneously, the variable that wherein allows to demonstrate statistical significance odds ratio (when independent the detection) enters model.Then, the ROC area under curve of the 95%CI that estimates by the ROC curve with by the nonparametric algorithm of describing in the following document is for example analyzed this multivariate model: DeLong (DeLong E.R. etc., (1988) Biometrics 44:837-45).San Antonio cardiac studies result shows that the prediabetes patient has the atheroma pattern of risk factor (may be to cause because of obesity, hyperglycemia, especially hyperinsulinemia), can there be many years in this, may cause the danger of macroangiopathic, similar with the duration of clinical diabetes itself.

Estimate the danger of diabetes or prediabetes illness although used big quantity research and algorithm, but for the prediction that the short-term of diabetes or prediabetes illness and long-term danger appear in asymptomatic individuality or health volunteer, evidential many risk factors evaluation method be unique suitably accurately.Best and the DBMARKERS coupling of the present invention of such risk prediction algorithm, with the patient among the differentiation target group, thus the risk stratification of definite development diabetes or prediabetes illness.DBMARKERS disclosed herein and using method provide such instrument: described instrument can be united with these risk prediction algorithms and is used to estimate, identify or diagnose patient asymptomatic and that do not show conventional risk factor.

Can come the data of comparison by linear regression from risk prediction algorithm and the inventive method.Linear regression analysis is by having simulated linear equation and observed data fitting the relation between two variablees.Think that a variable is an explanatory variable, and another is a dependent variable.For example, the numerical value that derives from Archimedes or San Antonio heart analysis can be used as dependent variable, and analyze at one or more DBMARKERS levels of property variable as an illustration, attempt the more abundant fundamental biological knowledge meaning (referring to embodiment) that defines in the algorithm scoring of being calculated.Perhaps, such risk prediction algorithm or its each input (normally DBMARKERS itself) can directly be attached in the practice of the present invention, wherein the actual observation result in combination algorithm and the historical formation are compared.

The equation of linear regression line is Y=a+bX, and wherein X is an explanatory variable, and Y is a dependent variable.The slope of the tropic is b, and a is intercept (the y value when x=0).The quantity tolerance that concerns between two variablees be exactly " related coefficient " be R, be the numerical value between-1 and 1, the relationship strength of two observed data of variable of expression.It also often be reported as related coefficient square because " coefficient of determination " is R ²In the formula, it is the ratio of the total variance of the Y by matched curve explanation.The common methods of The regression line is exactly a least square method.This method is calculated the optimum fit curve of observed data, promptly by making each data point minimize (if point just in time just in matched curve, then its vertical missing is 0) to the quadratic sum of the vertical missing of curve.Because deviation is first square, summation again is not so positive value and negative value are all given up.

Behind one group of data computation tropic, just be called exceptional value away from the point of curve (and therefore having big residual values).Such point may be represented misdata, perhaps may indicate bad The regression line.If a point in the horizontal direction away from other data, just is called influential observation (influential observation).The reason of this differentiation is exactly that these points may have appreciable impact to the slope of the tropic.In case after regression model and the one group of data fitting, allow those skilled in the art to study the validity of the hypothesis that linear relationship exists to the inspection of residual error (deviation of matched curve and observed value).Residual error on the y axle at the mapping of the explanatory variable on the x axle, is shown any possible nonlinear relationship in the variable, but perhaps reminding technology personnel researchs " variable of hiding (lurking variable) ".When the relation between two variablees is subjected to appreciable impact because of not being included in the existence of building the 3rd variable in the work of touching, then there be " variable of hiding ".

Relation according to one or more DBMARKERS levels and actual viewed patient's clinical effectiveness in patient's sample, perhaps in conjunction with the diagnosis of the dangerous scoring of the Archimedes that for example calculated, the scoring of San Antonio cardiac risk or diabetes or prediabetes illness or predict other popular known method, especially can adopt linear regression analysis to predict the danger of development diabetes or prediabetes illness.Yet concrete the use is nonlinear equation and analysis, to judge the relation between the DBMARKERS level that is detected in known diabetes forecast model and the patient's sample.Special interest is structure and grammer (synactic) sorting algorithm and hazard index construction method, adopt the pattern-recognition feature, comprise the technology set up for example k-nearest neighbor (Kth-Nearest Neighbor), Boosting, decision tree (Decision Trees), neural network (Neural Networks), Bayesian network (Bayesian Networks), Support Vector Machine (Support Vector Machines) and hidden Markov model (Hidden MarkovModels).The most frequently used is the sorting algorithm of using logistic regression, and it is the basis of Framingham, Finnish and the scoring of San Antonio cardiac risk.In addition, the application of these technology in a plurality of DBMARKERS group comprise within the scope of the present invention, as these be combined in produce comprise single quantizing " hazard index " or " dangerous scoring " from the application in the information of a plurality of DBMARKERS inputs.

Factorial analysis is a mathematical technique, use this technology, a large amount of correlated variabless (for example risk of diabetes factor) can be reduced to less " factor ", it represents the particular feature (Hanson of the variance (variance) that accounts for vast scale in the original variable, R.L. etc., (2002) Diabetes 51:3120-3127).Therefore, factorial analysis is very suitable for identifying for example component of IGT, IFG and metabolic syndrome of diabetes and prediabetes illness.The feature of metabolic syndrome and the relation between the onset diabetes rate also can be further judged in the epidemiological study of the factor of these analyses " scoring ".Above basic factorial analysis be with the immeasurability variable of minority uniqueness promptly " factor " explain viewed relation in one group of variable.Factorial analysis comprises two programs: 1) factor is extracted, to estimate factor quantity and 2) factor rotation, to determine the formation of each factor according to original variable.

The factor is extracted and can be undertaken by principal component method.These compositions are the linear combination of original variable, and its formation makes each composition and other each composition have zero correlation.Each major component is relevant with " eigenvalue ", and this value representative is by the variance (variance) (wherein each original variable variance after standardization is 1) in the original variable of this one-tenth branch explanation.The major component quantity that can make up equals the quantity of original variable.In factorial analysis, factor quantity is normally by accounting for population variance but not the reservation of the composition of any single original variable determines (being eigenvalue＞1 of these compositions).

In case determined factor quantity, then can carry out factor rotation to determine the synthetic of the factor, it has the simplest and the clearest explanation according to original variable.In factor rotation, represent " factor loading " of the relation of each factor and original variable to change, make these factor loadings as far as possible near 0 or 1 (its restriction is to be remained unchanged by the variance total amount that the factor is explained).Developed big metering method and be used for factor rotation, can whether need last group factor to keep irrelevant each other (being also referred to as " orthogonal method ") or whether allow the factor relevant (" oblique method ") to distinguish them by them by them.In the explanation of factorial analysis, check the factor loading pattern is represented the main composition composition of each factor with definite which original variable.With regard to conventional, think that the variable of factor loading＞0.4 (or less than-0.4) of the concrete factor is exactly its main composition composition.Factorial analysis is very useful in alternative group the grouping in making up from the DBMARKER group member (panel) of its constituent and with mark.

Compare to test (" the patient ") sample of while or different time mensuration with reference to (" contrast ") sample.The latter's example is to use editor's expressing information, for example compiles the sequence library of the information of relevant DBMARKERS expression.If reference sample (for example control sample) is then similar with DBMARKERS content in the control reference sample when patient's test specimen from the experimenter who does not suffer from diabetes, show that treatment is effective.Yet the variation of one or more DBMARKERS content can reflect not too favourable clinical effectiveness or prognosis in test specimen and the reference sample." effectively " is meant that treatment causes one or more DBMARKERS content of patient to reduce or rising, or serum insulin level or the decline of blood glucose level.The available standards clinical protocol is analyzed the evaluation to serum insulin or blood glucose level.Any relevant known method of available diabetes diagnosis or treatment is determined effect.

The effective dose level of DBMARKER albumen, peptide, nucleic acid, polymorphism, metabolin or other analyte also allows to monitor diabetes or prediabetes treatment of conditions process.In the method, can provide patient's biological sample from experience treating diabetes scheme (for example drug therapy).Such therapeutic scheme can include but not limited to workout scheme, meal supplement (including but not limited to alpha-lipoic acid, chromium, Co-Q10, garlic, magnesium and omega-fatty acid), surgical intervention (such as but not limited to stomach shunting, angioplasty etc.) and treat after diagnosing or identify the patient who suffers from diabetes or prediabetes illness with curative or preventive medicine (diabetes for example defined herein are regulated medicine).If necessary, biological sample pick up from before and after the treatment or during the patient of different time points.Can measure the effective dose level of DBMARKER albumen, peptide, nucleic acid, polymorphism, metabolin or other analyte then and compare with reference value (for example the contrast experimenter or the colony of known its diabetic disease states) or exponential quantity or baseline value.Reference sample or exponential quantity or baseline value can pick up from or from the one or more patients that received treatment, perhaps can pick up from or from being in the low dangerous one or more patients of development diabetes or prediabetes illness, perhaps can pick up from or from the patient who on the risk of diabetes factor, makes moderate progress as treatment results.Perhaps, reference sample or exponential quantity or baseline value can pick up from or from untreated one or more patients.For example, sample can pick up from and accept that diabetes are tentatively treated and accepted to diabetes or prediabetes illness or the prediabetes illness continues the patient of treatment with the monitor therapy process.Reference value also can comprise from the risk prediction algorithm of for example colony disclosed herein research or the value of gauge index.

Therefore, DBMARKERS of the present invention can be used for producing " reference expression profile ", and it is included in the pattern of not suffering from diabetes or prediabetes illness (for example glucose tolerance attenuating) and will being expected to develop the DBMARKERS expression of measuring among the patient of diabetes or prediabetes illness.DBMARKERS disclosed herein also can be used for producing " patient's express spectra ", and it comprises the pattern of the DBMARKERS expression of suffering from diabetes or prediabetes illness (for example glucose tolerance attenuating) patient.Patient's express spectra and reference expression profile can be compared, be in the patient of developing in diabetes or the danger of prediabetes illness with diagnosis or evaluation, with the validity of monitoring of diseases process and disease process ratio (comprising development diabetes B or prediabetes illness related complication or its danger) and monitoring diabetes or prediabetes treatment for diseases modality.Can contain reference expression profile of the present invention and patient's express spectra in the machine readable media, such as but not limited to for example readable analog magnetic tape or digital medias such as VCR, CD-ROM, DVD-ROM, USB flash memory medium.These machine readable medias also can contain extra test findings, such as but not limited to the tolerance of the following conventional risk of diabetes factor: systolic pressure and diastolic pressure, blood glucose level, insulin level, BMI exponential sum cholesterol (LDL and HDL) level.In addition, machine readable media also can comprise patient information, for example medical history and any relevant family history.Machine readable medium also can contain other risk of diabetes algorithm for example as herein described and gauge index relevant information.

Difference in patient's genetic constitution can cause the difference on the relative capacity of the various medicines of their metabolism, the symptom or the risk factor of described medicine scalable diabetes or prediabetes illness.The patient who has diabetes or prediabetes illness or be in the danger that develops diabetes or prediabetes illness is different on following parameter: age, race, body mass index (BMI), total cholesterol level, blood glucose level, blood pressure, LDL and HDL level and other parameter.Therefore, the application of DBMARKERS disclosed herein allows predictable predeterminated level, and it is tested in selected patient infers therapeutic or preventative diabetes, prediabetes illness or its complication that will be suitable for treating or preventing the patient.

In order to identify curative or the medicine that is suitable for concrete patient, can make test specimen contact treatment medicine or medicine, and measure the level of one or more DBMARKER albumen, nucleic acid, polymorphism, metabolin or other analyte from the patient.Can with level and the treatment of one or more DBMARKERS be exposed to curative or medicine before the very first time and treatment be exposed to curative or medicine after patient's sample of second time compare, perhaps can compare with the one or more patients' that on diabetes or prediabetes illness risk factor, make moderate progress as the result of described treatment or exposure sample.The example that is usually used in this class curative for the treatment of diabetes and scalable diabetic symptom or risk factor includes but not limited to sulfonylurea, for example Glimepiride, glibenclamide, Glipizide, gliclazide; Biguanides, for example melbine; Insulin (comprise and suck formulation example such as insulin inhaled dose (Exubera)) and insulin analog, for example insulin lispro (Humalog), insulin glargine preparation (Lantus), insulin detemir and Ge Luxin insulin; Peroxisome proliferation-activated receptors-γ (PPAR-γ) activator, for example thiazolidinediones comprises troglitazone (Rezulin), Pioglitazone (Actos), Rosiglitazone (Avandia) and Netoglitazone (isaglitzone) (being also referred to as netoglitazone (netoglitazone)); Double action PPAR activator, for example BMS-298585 and for Ge Liezha (tesaglitazar); Insulin secretagogue comprises metglitinides, for example Repaglinide and Nateglinide; Glucagon-like peptide-1 (GLP-1) analog, for example Exenatide (exenatide) (AC-2993) draws glycopeptide (liraglutide) (insulinotropin (insulinotropin)) with profit; Inhibitors of dipeptidyl IV, for example LAF-237; Pancreatic lipase inhibitor, for example orlistat; Alpha-glucosidase restrainer, for example acarbose, Miglitol and voglibose; And combination, especially melbine and glibenclamide (Glucovance), melbine and Rosiglitazone (Avandamet) and melbine and Glipizide (Metaglip).These curatives or medicine are given for the patient who suffers from diabetes or prediabetes illness after diagnosing, and the symptom of scalable diabetes or prediabetes illness or risk factor (being referred to herein as " diabetes adjusting medicine ").

Patient's sample can be hatched in the presence of drug candidate, and the expression pattern of DBMARKER in the determination test sample, compares with reference spectrum (for example diabetes reference expression profile) or non-diabetic reference expression profile or exponential quantity or baseline value again.Trial drug can be any compound or composition or its combination.For example, trial drug is the medicine that is usually used in the treating diabetes scheme, is described in this paper.

Table 1 comprises 158 kinds of DBMARKERS of the present invention.Those skilled in the art will know, DBMARKERS as herein described comprises form of ownership and variant, include but not limited to that polymorphism, isoform (isoform), saltant, derivant, precursor comprise nucleic acid, acceptor (comprising soluble recepter and transmembrane receptor), part and posttranslational modification variant and any many units nucleic acid, protein and glycoprotein structure, it comprises any DBMARKERS, as the composition subunit of complete assembly structure.

Table 1:DBMARKERS

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title	1	Serpina 3M	Predicted protein C-end fragment is similar to serpin 2.4
2	Spin 2a		1	Serpina 3M	Predicted protein C-end fragment is similar to serpin 2.4
2	Spin 2a		3	Myosin β (Fetuin β)	Fetub; Myosin β (Fetuin β); Myosin B (FetuinB)
4	ApoC-III precursor	Apoc3	3	Myosin β (Fetuin β)	Fetub; Myosin β (Fetuin β); Myosin B (FetuinB)
4	ApoC-III precursor	Apoc3	5	Predicted protein is similar to apoC 2	Apoc2, prediction
6	α-2-HS-glycoprotein	α-2-HS-glycoprotein; Ahsg; Myosin α	5	Predicted protein is similar to apoC 2	Apoc2, prediction

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title			(Fetuin α); Myosin A (Fetuin A); Aa2-066
7	T-kininogen II precursor				(Fetuin α); Myosin A (Fetuin A); Aa2-066
7	T-kininogen II precursor		8	α-1-macroglobulin	α-1-macroglobulin; A2MG; Pzp; Pregnancy zone portein
9	Serpin C1	Serine/cystatin, clade C, member 1 (prediction)	8	α-1-macroglobulin	α-1-macroglobulin; A2MG; Pzp; Pregnancy zone portein
9	Serpin C1	Serine/cystatin, clade C, member 1 (prediction)	10	Clotting factor 2	F2
11	Inter-α-inhibitor H4 heavy chain	ITIH4	10	Clotting factor 2	F2
11	Inter-α-inhibitor H4 heavy chain	ITIH4	12	Vitamin D binding protein propetide (prepeptide)	Gc；VTDB
13	Low-molecular-weight T-kininogen I precursor	Kininogen; LMW T-kininogen I precursor; Main acute stage α-1 amyloid protein precursor	12	Vitamin D binding protein propetide (prepeptide)	Gc；VTDB
13	Low-molecular-weight T-kininogen I precursor		14	APoA-I	Preapoprotein A-1; ApoA1
15	Predicted protein is similar to apoC-II precursor	Apoc2	14	APoA-I	Preapoprotein A-1; ApoA1
15	Predicted protein is similar to apoC-II precursor	Apoc2	16	Fibrin ferment	The factor precursor; THRB
17	Apo E	ApoE	16	Fibrin ferment	The factor precursor; THRB
17	Apo E	ApoE	18	Liver regeneration related protein LRRG03	Tf
19	Apolipoprotein A-1 V	ApoA4	18	Liver regeneration related protein LRRG03	Tf
19	Apolipoprotein A-1 V	ApoA4	20	α-1-inhibitor 3 precursors	LOC297568
21	XP 579384		20	α-1-inhibitor 3 precursors	LOC297568
21	XP 579384		22	Be rich in the glycoprotein of histidine	Hrg
23	XP 579477		22	Be rich in the glycoprotein of histidine	Hrg
23	XP 579477		24	The complement component C9 precursor	C9
25	Apolipoprotein H	ApoH	24	The complement component C9 precursor	C9
25	Apolipoprotein H	ApoH	26	The B-factor, properdin	Cfb
27	Hemopexin	Hpx	26	The B-factor, properdin	Cfb
27	Hemopexin	Hpx	28	Calnexin	Ca (2+)-in conjunction with phosphoprotein p90
29	Reg3a	Rn.11222; Regeneration pancreas islet 3 α that derive	28	Calnexin	Ca (2+)-in conjunction with phosphoprotein p90
29	Reg3a	Rn.11222; Regeneration pancreas islet 3 α that derive	30	LOC680945	Rn.1414; Be similar to stroma cell derivative factor 2

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title			Sample 1
31	Pap	Rn.9727; Pancreatitis associated protein			Sample 1
31	Pap	Rn.9727; Pancreatitis associated protein	32	Ptf1a	Rn.10536; The pancreas idiosyncratic transcription factor, 1a
33	Mat1a	Rn.10418; Methionine adenosyltransferase I, α	32	Ptf1a
33	Mat1a	Rn.10418; Methionine adenosyltransferase I, α	34	Nupr1	Rn.11182; Nucleoprotein 1
35	Rn.128013		34	Nupr1	Rn.11182; Nucleoprotein 1
35	Rn.128013		36	Chac1 (prediction)	Rn.23367; ChaC; Cation transfer instrumentality sample 1
37	Slc7a3	Rn.9804; Solute carrier family 7 (cationic amino acid transporter, y+ system), the member 3	36	Chac1 (prediction)	Rn.23367; ChaC; Cation transfer instrumentality sample 1
37	Slc7a3		38	LOC312273	Rn.13006; Trypsase V-A
39	Rn.47821		38	LOC312273	Rn.13006; Trypsase V-A
39	Rn.47821		40	Ptger3	Rn.10361; Prostaglandin E receptor 3 (hypotype EP3
41	RGD1562451	Rn.199400; Be similar to the Pabpc4 predicted protein	40	Ptger3	Rn.10361; Prostaglandin E receptor 3 (hypotype EP3
41	RGD1562451	Rn.199400; Be similar to the Pabpc4 predicted protein	42	RGD1566242	Rn.24858; Be similar to RIKEN cDNA 1500009M05
43	Cyp2d26	Rn.91355; Cytochrome P450, family 2, subfamily d, polypeptide 26	42	RGD1566242	Rn.24858; Be similar to RIKEN cDNA 1500009M05
43	Cyp2d26		44	Rn.17900	Be similar to aldehyde dehydrogenase 1 family, member L2
45	LOC286960	Rn.10387; The former IV of protrypsin (preprotrypsinogen IV)	44	Rn.17900	Be similar to aldehyde dehydrogenase 1 family, member L2
45	LOC286960		46	Gls2	Rn.10202; Glutaminase 2 (liver, mitochondria)
47	Nme2	Rn.927; In non-transitional cell 2, express	46	Gls2	Rn.10202; Glutaminase 2 (liver, mitochondria)
47	Nme2	Rn.927; In non-transitional cell 2, express	48	Rn.165714
49	P2rx1	Rn.91176; Purinergic receptor PX2, part-gated ion channel, 1	48	Rn.165714
49	P2rx1		50	Pdk4	Rn.30070; Pyruvic dehydrogenase kinase, isodynamic enzyme 4
51	Amy1	Rn.116361; Diastase 1, saliva	50	Pdk4	Rn.30070; Pyruvic dehydrogenase kinase, isodynamic enzyme 4
51	Amy1	Rn.116361; Diastase 1, saliva	52	Cbs	Rn.87853; CBS
53	Mte1	Rn.37524; Chondriosome acyl-CoA thioesterase 1	52	Cbs	Rn.87853; CBS
53	Mte1	Rn.37524; Chondriosome acyl-CoA thioesterase 1	54	Spink1	Rn.9767; Serpin, Kazal 1

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title			Type
55	Gatm	Rn.17661; Glycocoll amidine transferase (L-arginine: glycine amidinotransferase)			Type
55	Gatm		56	The Tmed6_ prediction	Rn.19837; Contain and stride film emp24 protein transport domain 6
57	Tff2	Rn.34367; Trefoil factor 2 (spasmolysis albumen 1)	56	The Tmed6_ prediction
57	Tff2	Rn.34367; Trefoil factor 2 (spasmolysis albumen 1)	58	Hsd17b13	Rn.25104; Hydroxy steroid (17-β) dehydrogenase 13
60	Rn.11766	Be similar to LRRGT00012	58	Hsd17b13	Rn.25104; Hydroxy steroid (17-β) dehydrogenase 13
60	Rn.11766	Be similar to LRRGT00012	61	Gnmt	Rn.11142; Glycocoll N-transmethylase
62	Pah	Rn.1652; Phenylalanine hydroxylase	61	Gnmt	Rn.11142; Glycocoll N-transmethylase
62	Pah	Rn.1652; Phenylalanine hydroxylase	63	Serpini2	Rn.54500; Serine/cystatin, clade I, the member 2
64	RGD1309615	Rn.167687	63	Serpini2	Rn.54500; Serine/cystatin, clade I, the member 2
64	RGD1309615	Rn.167687	65	LOC691307	Rn.79735; Be similar to contain and be rich in leucine repetitive sequence 39 isoforms 2 (isoforms 2)
66	Eprs	Rn.21240; Glutamy-prolyl-tRNA synthetase	65	LOC691307
66	Eprs	Rn.21240; Glutamy-prolyl-tRNA synthetase	67	The Pck2_ prediction	Rn.35508; Phosphoenolpyruvic acid carboxyl kinases 2 (mitochondria)
68	The Chd2_ prediction	Rn.162437; Enzyme dna is untwisted in conjunction with albumen 2 in Crow not domain	67	The Pck2_ prediction
68	The Chd2_ prediction		69	Rn.53085
70	Rn.12530		69	Rn.53085
70	Rn.12530		71	NIPK	Rn.22325; The tribbles homologue; CDNA clone RPCAG663 ' end, the mRNA sequence
72	Slc30a2	Rn.11135; Solute carrier family 30 (zinc transport protein), the member 2	71	NIPK
72	Slc30a2		73	Serpina10	Rn.10502; Serine/halfcystine peptidase inhibitors, clade A, the member 10
74	Cfi	Rn.7424; Complement factor I	73	Serpina10
74	Cfi	Rn.7424; Complement factor I	75	Cckar	Rn.10184; The CCK A acceptor

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title	76	LOC689755	Rn.151728；LOC689755
77	Bhlhb8	Rn.9897; Contain the bHLH domain category-B, 8	76	LOC689755	Rn.151728；LOC689755
77	Bhlhb8	Rn.9897; Contain the bHLH domain category-B, 8	78	Anpep	Rn.11132; Alanyl (film) aminopeptidase)
79	Asns	Rn.11172; Asparagine synthetase	78	Anpep	Rn.11132; Alanyl (film) aminopeptidase)
79	Asns	Rn.11172; Asparagine synthetase	80	Slc7a5	Rn.32261; Solute carrier family 7 (cationic amino acid transporter, y+ system), the member 5
81	The Usp43_ prediction	Rn.12678; Ubiquitin specific protease 43	80	Slc7a5
81	The Usp43_ prediction	Rn.12678; Ubiquitin specific protease 43	82	Csnk1a1	Rn.23810; Casein kinase 1, α 1
83	Cml2	Rn.160578; Camello sample 2	82	Csnk1a1	Rn.23810; Casein kinase 1, α 1
83	Cml2	Rn.160578; Camello sample 2	84	Pabpc4	Rn.199602
85	Gjb2	Rn.198991; Gap junctional membrane channel protein β 2	84	Pabpc4	Rn.199602
85	Gjb2	Rn.198991; Gap junctional membrane channel protein β 2	86	Ngfg	Rn.11331; Nerve growth factor, γ
87	The Clca2_ prediction	Rn.48629	86	Ngfg	Rn.11331; Nerve growth factor, γ
87	The Clca2_ prediction	Rn.48629	88	RGD1565381	Rn.16083; Be similar to RIKEN cDNA 181003M07
89	Qscn6	Rn.44920；quiescin Q6	88	RGD1565381	Rn.16083; Be similar to RIKEN cDNA 181003M07
89	Qscn6	Rn.44920；quiescin Q6	90	The Cldn10_ prediction	Rn.99994; Close protein 10 (claudin 10)
91	Spink3	Rn.144683; Serpin, Kazal 3 types	90	The Cldn10_ prediction	Rn.99994; Close protein 10 (claudin 10)
91	Spink3	Rn.144683; Serpin, Kazal 3 types	92	LOC498174	Rn.163210; Be similar to NipSnap2 albumen (spongioblastoma extension increasing sequence)
93	Rn.140163	Be similar to methionine-tRNA synzyme	92	LOC498174
93	Rn.140163	Be similar to methionine-tRNA synzyme	94	Cyr61	Rn.22129; Be rich in the albumen 61 of halfcystine
95	RGD1307736	Rn.162140; Be similar to KIAA0152	94	Cyr61	Rn.22129; Be rich in the albumen 61 of halfcystine
95	RGD1307736	Rn.162140; Be similar to KIAA0152	96	Ddit3	Rn.11183; Dna damage induction type transcript 3
97	Reg1	Rn.11332; The regeneration pancreas islet derives 1	96	Ddit3	Rn.11183; Dna damage induction type transcript 3
97	Reg1	Rn.11332; The regeneration pancreas islet derives 1	98	Eif4b	Rn.95954; Eukaryotic translation initiation factor 4B
99	Rnase4	Rn.1742; Ribonuclease, RNA enzyme A family 4	98	Eif4b	Rn.95954; Eukaryotic translation initiation factor 4B
99	Rnase4	Rn.1742; Ribonuclease, RNA enzyme A family 4	100	Cebpg	Rn.10332; CCAAT/ enhancer binding protein (C/EBP), γ

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title	101	siat7D	Rn.195322; α-2,6-sialyltransferase ST6GalNAc IV
102	Herpud1	Rn.4028; Homocysteine-induction type, ubiquitin spline structure territory member 1	101	siat7D	Rn.195322; α-2,6-sialyltransferase ST6GalNAc IV
102	Herpud1		103	Unknown rat cdna
104	Gcat	Rn.43940; Glycocoll C-acetyltransferase (2-amino-3-alpha-ketobutyric acid-CoA ligase)	103	Unknown rat cdna
104	Gcat		105	RGD1562860	Rn.75246; Be similar to RIKEN cDNA 2310045A20
106	The Hspa9a_ prediction	Rn.7535; Heat shock 70kD albumen 9A	105	RGD1562860	Rn.75246; Be similar to RIKEN cDNA 2310045A20
106	The Hspa9a_ prediction	Rn.7535; Heat shock 70kD albumen 9A	107	Dbt	Rn.198610; Dihydrolipoamide side chain acyltransferase E2
108	Bspry	Rn.53996; Contain B-box and SPRY domain	107	Dbt	Rn.198610; Dihydrolipoamide side chain acyltransferase E2
108	Bspry	Rn.53996; Contain B-box and SPRY domain	109	Fut1	Rn.11382; Fucosyltransferase 1
110	Rpl3	Rn.107726; Ribosomal protein L 3	109	Fut1	Rn.11382; Fucosyltransferase 1
110	Rpl3	Rn.107726; Ribosomal protein L 3	111	Rn.22481	Be similar to NP 083520.1 acylphosphatase 2, muscularity
112	Unknown rat cdna		111	Rn.22481	Be similar to NP 083520.1 acylphosphatase 2, muscularity
112	Unknown rat cdna		113	Vldlr	Rn.9975; Very low density lipoprotein receptor
114	RGD1311937	Rn.33652; Be similar to MGC17299	113	Vldlr	Rn.9975; Very low density lipoprotein receptor
114	RGD1311937	Rn.33652; Be similar to MGC17299	115	RGD1563144	Rn.14702; Be similar to EMeg32 albumen
116	Rn.43268		115	RGD1563144	Rn.14702; Be similar to EMeg32 albumen
116	Rn.43268		117	pre-mtHSP70	Rn.7535; 70kD heat shock protein precursor
118	Ddah1	Rn.7398; Diethylarginine dimethylamino hydrolytic enzyme 1	117	pre-mtHSP70	Rn.7535; 70kD heat shock protein precursor
118	Ddah1	Rn.7398; Diethylarginine dimethylamino hydrolytic enzyme 1	119	RAMP4	Rn.2119; Ribosomes related membrane protein 4
120	Rn.169405		119	RAMP4	Rn.2119; Ribosomes related membrane protein 4
120	Rn.169405		121	The Ccbe1_ prediction	Rn.199045; Collagen and calcium are in conjunction with EGF domain 1
122	Dnajc3	Rn.162234; DnaJ (Hsp40) homologue, subfamily C, the member 3	121	The Ccbe1_ prediction
122	Dnajc3		123	Mtac2d1	Rn.43919; Contain film target (series connection) C2 domain

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title			1
124	RGD1563461	Rn.199308			1
124	RGD1563461	Rn.199308	125	Gimap4	Rn.198155; The GTP enzyme, IMAP family member 4
126	S100b	Rn.8937; S100 albumen, beta polypeptides	125	Gimap4	Rn.198155; The GTP enzyme, IMAP family member 4
126	S100b	Rn.8937; S100 albumen, beta polypeptides	127	The Klf2_ prediction	Rn.92653; Kruppel like factor 2 (lung)
128	RGD1309561	Rn.102005; Be similar to FLH31951	127	The Klf2_ prediction	Rn.92653; Kruppel like factor 2 (lung)
128	RGD1309561	Rn.102005; Be similar to FLH31951	129	NAP22	Rn.163581
130	The Sfrs3_ prediction	Rn.9002; Splicing factor is rich in arginine/serine 3 (SRp30)	129	NAP22	Rn.163581
130	The Sfrs3_ prediction		131	Rn.6731
132	Cd53	Rn.31988; CD53 antigen	131	Rn.6731
132	Cd53	Rn.31988; CD53 antigen	133	RGD1561419	Rn.131539; Be similar to RIKEN cDNA 6030405P05 gene
134	Il2rg	Rn.14508; The interleukin-22 acceptor, γ	133	RGD1561419	Rn.131539; Be similar to RIKEN cDNA 6030405P05 gene
134	Il2rg	Rn.14508; The interleukin-22 acceptor, γ	135	LOC361346	Rn.31250; Be similar to chromosome 18 open read frames 54
136	Cd38	Rn.11414; CD38 antigen	135	LOC361346	Rn.31250; Be similar to chromosome 18 open read frames 54
136	Cd38	Rn.11414; CD38 antigen	137	The Plac8_ prediction	Rn.2649; Placenta specificity 8
138	LOC498335	Rn.6917; Be similar to little inducing cell factor B 13 precursors (CXCL13)	137	The Plac8_ prediction	Rn.2649; Placenta specificity 8
138	LOC498335		139	Igfbp3	Rn.26369; Insulin-like growth factor binding protein 3
140	Ptprc	Rn.90166; Protein-tyrosine-phosphatase, acceptor C type	139	Igfbp3	Rn.26369; Insulin-like growth factor binding protein 3
140	Ptprc	Rn.90166; Protein-tyrosine-phosphatase, acceptor C type	141	RT1-Aw2	Rn.40130; RT1 Ib class, locus Aw2
142	Rac2	Rn.2863; The RAS C3 clostridium botulinum substrate 2 of being correlated with	141	RT1-Aw2	Rn.40130; RT1 Ib class, locus Aw2
142	Rac2		143	Rn.9461
144	Fos	Rn.103750; FBJ mouse osteosarcoma virus oncogene homologue	143	Rn.9461
144	Fos	Rn.103750; FBJ mouse osteosarcoma virus oncogene homologue	145	Arhgdib	Rn.15842; Rho, GDP inhibitor (CDI) β that dissociates
146	Sgne1	Rn.6173; Secretory granules neuroendocrine albumen 1	145	Arhgdib	Rn.15842; Rho, GDP inhibitor (CDI) β that dissociates
146	Sgne1	Rn.6173; Secretory granules neuroendocrine albumen 1	147	Lck_ maps	Rn.22791; The lymphocyte protein tyrosine kinase

DBMARKER	Adopted name	Other title
DBMARKER	Adopted name	Other title			(mapping)
148	Fcgr2b	Rn.33323; The Fc acceptor, IgG, low-affinity IIb			(mapping)
148	Fcgr2b	Rn.33323; The Fc acceptor, IgG, low-affinity IIb	149	Slfn8	Rn.137139；Schlafen 8
150	Rab8b	Rn.10995; RAB8B, member RAS oncogene family	149	Slfn8	Rn.137139；Schlafen 8
150	Rab8b	Rn.10995; RAB8B, member RAS oncogene family	151	Rn.4287
152	RGD1306939	Rn.95357; Be similar to mKIAA0386 albumen	151	Rn.4287
152	RGD1306939	Rn.95357; Be similar to mKIAA0386 albumen	153	The Tnfrsf26_ prediction	Rn.162508; The Tumor Necrosis Factor Receptors subfamily, the member 26
154	The Ythdf2_ prediction	Rn.21737; YTH domain family 2	153	The Tnfrsf26_ prediction
154	The Ythdf2_ prediction	Rn.21737; YTH domain family 2	155	RGD1359202	Rn.10956; Be similar to heavy chain immunoglobulin 6 (Igh-6)
156	RGD1562855	Rn.117926; Be similar to Ig κ chain	155	RGD1359202
156	RGD1562855	Rn.117926; Be similar to Ig κ chain	157	Igha_ maps	Rn.109625; Heavy chain immunoglobulin (α polypeptide) (mapping)
158	Ccl21b	Rn.39658; Chemotactic factor (CF) (C-C motif) part 21b (serine)	157	Igha_ maps

Can adopt any known method in this area, on protein or nucleic acid level, measure the DBMARKERS level.Especially can measure DBMARKER content by the following method: electrophoresis (for example agarose gel electrophoresis, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), Tris-HCl polyacrylamide gel, non-denatured protein gel, two-dimensional gel electrophoresis (2DE) etc.), immunochemistry (being radiommunoassay, Western blotting, immunoprecipitation, immunofluorescence, enzyme linked immunosorbent assay (ELISA)), " proteomic techniques " or " genome analysis ".For example, on nucleic acid level, can adopt RNA and southern blotting technique hybridization analysis and ribonuclease protection assay to measure gene expression, use the probe of the one or more such sequences of specific recognition.Perhaps, can use based on the PCR mensuration (RT-PCR) of reverse transcription and measure expression, for example use gene order to have specific primer differential expression.Also can on protein level, measure expression, for example by peptide level or its activity of being encoded by gene outcome as herein described are measured.These class methods are well-known in the art, comprise for example according to the immunoassays of antibody at gene, adaptive son or the coded protein of molecular imprinting.Any biomaterial all can be used for detected/quantified and detects protein or its activity.Perhaps, can select appropriate method to measure the coded activity of proteins of marker gene according to each activity of proteins of being analyzed.

" proteomic techniques " include but not limited to surface-enhanced laser desorption ionization (SELDI), substance assistant laser desorpted ionized-flight time (MALDI-TOF), high performance liquid chromatography (HPLC), with or not with liquid chromatography (LC/MS), series LC/MS, protein array, peptide array and the antibody array of mass spectrometry.

" genome analysis " can comprise that for example PCR (PCR), PCR in real time (are for example passed through Light Derive from Roche Applied Sciences), serial analysis of gene expression (SAGE), rna blot analysis and southern blotting technique analysis.

Microarray technology can be used as the instrument of analyzing gene or protein expression, it comprises membranelle or solid support (such as but not limited to microslide, plastics holder, silicon chip or wafer (it has or do not have the fiber optics detection means) and film, comprising cellulose nitrate, nylon or Kynoar).Solid support can be (for example light version printing) that chemically derived (for example silane, streptavidin and various other example) or physics are derived, and makes its energy combining target analyte (normally nucleic acid, protein or its metabolin or its fragment).Can nucleic acid or protein printing (being inkjet printing), point sample (spotted) or original position is synthetic.Reach the deposition of target nucleic acid or protein by xyz microarray spotting robot (robotic microarrayer), such robot utilization has the robotization spot sample device of point-device motion control on x axle, y axle and z axle, in conjunction with pin (pin) technology, on array, provide accurate, reproducible point sample.With target analytes in order or fixed discharge on solid support, so that easily identify specific required analyte.A large amount of microarray forms are commercially available, especially can derive from Affymetrix, ArrayIt, AgilentTechnologies, Asper Biotech, BioMicro, CombiMatrix, GenePix, Nanogen and Roche Diagnostics company.

Can under nucleotide that has one or more detectable labels or occurrence of amino acid, synthesize target nucleic acid or protein.Such mark comprises for example fluorescent dye and chemiluminescent labeling.Specifically, for microarray assay, often adopt fluorescent dye, such as but not limited to rhodamine, fluorescein, phycoerythrin, cyanine dye (for example Cy3 and Cy5) and conjugate (streptavidin-phycoerythrin (when nucleic acid or protein have biotin labeling) for example.

Confocal fluorescent laser scanning or photomultiplier (its provide the nucleic acid that exists on the array or the relative signal intensity and the analyte abundance ratio of protein) usually are provided, carry out the detection of fluorescence signal and obtaining of image.Various different scanning instruments all can use, associated has various Image Acquisition and quantitatively organizes cover (package), can allow to carry out the numerical Evaluation of comprehensive selection standard, to define the optimum scanning condition, for example counting of median, interquartile range (IQR), saturated spot and the linear regression (r of scanning room in pairs ²And P).Before data analysis, can estimate optimization, background correction and the normalization of the reappearance and the condition of scanning of scanning.

Thereby normalization is meant and is used to adjust data mean value or variance influence from array, inferior array (or point sample group (print-tip groups)) a series of process with the interchannel system of dye marker abiology difference.Array is defined as the one group of complete target probe on chip or the solid support.Inferior array or point sample group are meant a subgroup of these target probes that deposit through identical point sample, and it can be accredited as the interior uniqueness of complete array and less array.The dye marker passage is meant the fluorescence frequency of target sample and chip hybridization.Two kinds of different dyes mark sample mix are called " two dyestuff experiment " together and with the experiment of same chip hybridization in the art, it is poised for battle each target that lists and all produces relative but not absolute expression values, is typically expressed as the logarithm of ratio between " red passage " and " green passage ".Can carry out normalization according to ratiometric or absolute value method.Ratiometric analyzes and is mainly used in two dyestuff experiments, thinks that wherein a passage or array are relevant with generalized reference.Each target probe of obtaining between test and reference sample is expressed ratio, again ratio is converted into log ₂(ratio) is so that representative changes relatively symmetrically.The absolute value method is generally used for two dyestuff experiments that single dyestuff experiment or one of them passage or array do not have suitable reference value." hit (hits) " accordingly and be defined as expression or the content that characterizes specific condition of experiment.Usually, these are nucleic acid or protein, wherein the expression under the different experimental conditions is obviously different, organizes the ratio of expression by nucleic acid under the different experimental conditions relatively or relative expression's (" multiple changes ") of protein expression level and analysis of nucleic acids or protein and the expression of one group sample with another usually.

Can analyze the data that derive from the microarray experiment by in the various statistical analysis any, described analysis is clustering method and methods of marking for example.Clustering method attempts to identify the similar target of behavior (for example nucleic acid and/or protein) in a series of conditioned disjunction samples.Below supposition has driven the motivation of finding these targets: these targets that show similar expression pattern are shared common trait (for example common regulating element, common function or common origin of cell).

Hierarchical clustering (hierarchical clustering) is a coacervation process, and wherein each member's cluster merges the increasing cluster of formation.This process is that paired distance matrix begins between all target molecules by calculating, and distance matrix is to study nearest gene and they are defined as cluster.After forming a new cluster, then upgrade distance matrix to reflect the distance between itself and all other clusters by the cohesion of two clusters.Then, the nearest paired cluster of this process search and with its cohesion and carry out repeatedly.This process produces level dendrogram (hierarchical dendrogram), wherein according to its similarity a plurality of clusters is fused into knot (node), obtains a hierarchical tree.The hierarchical clustering software algorithm comprises Cluster and Treeview.

K-mean cluster (K-means clustering) is an iterative process, and its search is according to its " cluster of " center " point or equal value defined.In case defined one group of cluster centre, just each target molecule be included in its immediate cluster.Then, clustering algorithm is adjusted the center of each gene cluster, make target molecule in each cluster and center apart from the sum minimum.This causes reselecting cluster centre, and target molecule is included in the cluster once more.Use such iteration till observing advolution.Self organization map (Self-organizing map, SOM also claim s self-organizing feature map) has part correlation with k-average process, wherein data is included in the predetermined clusters group.Yet different with the k-average is that what to be followed is such iterative process: wherein the expression vector in each cluster is sought the best difference between different clusters through " training ".In other words, part-structure utilizes data, according to data this structure is carried out the iteration correction again.All contain SOM in many software packages (for example GeneCluster).Other clustering method comprises graph theory clustering (graph-theoretic clustering), and it utilizes graph theory and statistical technique to discern tight group (tight group) of highly similar element (kernel), and it belongs to same true cluster probably.Then, some heuristic processes can be used for expanding kernel to complete cluster.Utilize a software instances of graph theory clustering to comprise CLICK and in conjunction with Expander visualization tool (visualization tool).

Statistical method such as operation parameter and nonparametric technique can be marked to the data that get from the high flux expression analysis.Express spectra in the parametric technique analog parameter is represented also inquires how different the parameter of experimental group is.The example of parametric technique includes but not limited to the t check, separates scoring (separation score) and Bayes t check.Nonparametric technique comprises data analysis, wherein a priori assumption (priori assumption) is not made in the distribution of express spectra in the data, but directly checks two groups of degree of expressing mensuration of difference.It is mis-classification number of threshold values (threshold number of misclassification) that another kind method is used TNOM, and it is measured the successful separation of two groups of samples by a simple threshold values that surpasses expression values.

SAGE (serial analysis of gene expression) also can be used for the level that gene expression is judged by system.In SAGE, use the short sequence label (tag) that contains the information that is enough to unique evaluation transcript at assigned address, then by label being connected into serial form.Referring to for example VelculescuV.E. etc., (1995) Science 270:484-487.Isolate poly+RNA by widow-dT initiation, then with the synthetic cDNA of biotin labeled primer.CDNA is attached to 3 '-end cDNA segment on the pearl of streptavidin bag quilt with the cutting of grappling restricted type endonuclease then.The oligonucleotide joint that will contain the marker enzyme recognition site with combine cDNA and couple together.Marker enzyme can be an II class restriction endonuclease, and it is cutting DNA on the base of recognition site 3 ' constant number, causes discharging short label and joint from globule after with this enzymic digestion.Make 3 ' end of the label that discharged and joint become flush end then and it is joined to one another, formation length is about the chain pair of label (ditag) of 100 base-pairs.Make two labels through pcr amplification again, then by releasing-joint and label with the digestion of grappling restriction endonuclease.After this, label (magnitude range is generally the 25-30 aggressiveness) is carried out gel-purified, connect and be cloned in the sequence carrier.To the concatermer order-checking, make each label can be identified and can measure the transcript abundance of specific cells or types of organization.

Can adopt any way well known by persons skilled in the art to measure DBMARKER albumen, polypeptide, sudden change and polymorphism thereof.Especially adopt two-dimensional gel electrophoresis, wherein first dimension is according to isoelectric point (for example the pH scope is 5-8), and second dimension is according to molecular weight, comes isolated protein potpourri (for example protein in the biological sample such as serum).Two-dimensional liquid chromatography preferably also can be used for identifying or detecting DBMARKER albumen of the present invention, polypeptide, sudden change and polymorphism, and an instantiation, and ProteomeLab PF 2D Separation of Proteins system sees embodiment for details.First dimension of PF 2D system isolated protein is according to isoelectric point, and second dimension is according to hydrophobicity.Another favorable method that detects protein, polypeptide, sudden change and polymorphism comprises SELDI (disclosed herein) and other high throughput protein group array.

Usually can adopt following method to detect DBMARKER albumen, polypeptide, sudden change and polymorphism: promptly by with patient's sample with can contact in conjunction with the antibody of DBMARKER albumen, polypeptide, sudden change or polymorphism, whether the detection reaction product exists then.Antibody can be monoclonal antibody, polyclonal antibody, chimeric antibody or aforesaid fragment, and as detailed above, the step of assaying reaction product can be carried out with any suitable method of immunity.The normally aforesaid biological fluid of patient's sample, and can be the same body fluid example that is used to carry out said method.

The immunoassays of carrying out according to the present invention can be homogeneous determination or heterogeneous assays.In homogeneous determination, immune response generally includes the analyte and the target sample of specific antibody (for example anti-DBMARKER protein antibodies), tape label.In case antibody with after the analyte of tape label combines, has just directly or indirectly changed the signal from mark.The mensuration of immune response and scope thereof all can be carried out in homogeneous phase solution.Operable immuno-chemical marker comprises free radical, radioactive isotope, fluorescent dye, enzyme, bacteriophage or coenzyme.

In the heterogeneous assays method, reagent is sample, antibody and be used to produce the instrument of detectable signal normally.Can use aforesaid sample.Antibody can be fixed on the holders such as pearl (for example albumin A agarose, Protein G agarose, latex, polystyrene, magnetic bead or paramagnetic beads), flat board or slide, and in liquid phase, contact with sample that suspection contains antigen.Again with holder and liquid phase separation, and utilize the method that produces detectable signal, detect holder mutually or the described signal in the liquid phase.Signal is relevant with the existence of analyte in the sample.The instrument that produces detectable signal comprises use radioactive label, fluorescence labeling or enzyme mark.For example, if antigen to be detected contains second binding site, but the antibody that can combine and detection moiety with this site put together, and join in the liquid-phase reaction solution, carry out separating step then.But the existence of detection moiety shows and has antigen in the test specimen on the solid support.The example of suitable immunoassays is oligonucleotides, Western blotting, immunoprecipitation, immunofluorescence method, chemiluminescence method, electrogenerated chemiluminescence or enzyme-linked immunoassay.

Those skilled in the art will be familiar with various concrete immunoassays form and modification thereof, and it can be used for realizing method disclosed herein.General document is referring to E.Maggio, Enzyme-Immunoassay, (1980) (CRC Press, Inc., Boca Raton, Fla.); Other sees U.S. Patent number 4,727,022 (Skold etc., name is called " Methods for ModulatingLigand-Receptor Interactions and their Application "), U.S. Patent number 4,659,678 (Forrest etc., name is called " Immunoassay of Antigens "), U.S. Patent number 4,376,110 (David etc., name is called " Immunometric Assays UsingMonoclonal Antibodies "), U.S. Patent number 4,275,149 (Litman etc., name is called " Macromolecular Environment Control in Specific Receptor Assays "), U.S. Patent number 4,233,402 (Maggio etc., name is called " Reagents and MethodEmploying Channeling ") and U.S. Patent numbers 4,230,767 (Boguslaski etc., name is called " Heterogenous Specific Binding Assay Employing a Coenzyme asLabel ").

Can be according to known technologies such as passive combinations, antibody is conjugated on the solid support that is suitable for diagnostic assay (pearl (for example albumin A or Protein G agarose) for example, microsphere, flat board, slide or the aperture made by materials such as latex or polystyrene).Equally, also can be according to known technique for example radioactive label is (for example with antibody as herein described and detectable label or group ³⁵S, ¹²⁵I, ¹³¹I), enzyme mark (for example horseradish peroxidase, alkaline phosphatase) and fluorescence labeling (for example fluorescein, Alexa, green fluorescent protein) are puted together.

Antibody also can be used for detecting the posttranslational modification of DBMARKER albumen, polypeptide, sudden change and polymorphism, for example tyrosine phosphorylation, threonine phosphorylation, serine phosphorylation, glycosylation (for example O-GlcNAc).Phosphorylated amino acid in these one or more target proteins of antibody-like specific detection, and can be used for Western blotting as herein described, immunofluorescence and ELISA mensuration.These antibody are that those skilled in the art are well-known, are commercially available.Metastable state ion in also available reverberator matrix assisted laser desorption ionisation-flight time tandem mass spectrum (MALDI-TOF) is measured posttranslational modification (Wirth, U. etc. (2002) Proteomics 2 (10): 1445-51).

For known DBMARKER albumen, polypeptide, sudden change and polymorphism, can use enzymatic determination known in the art, in its activity of external test with enzymatic activity.These mensuration include but not limited to kinase assays, phosphatase mensuration, reductase mensuration etc.Can use algorithm known, by the measuring rate constant K _MMeasure the dynamic (dynamical) adjusting of enzymatic activity, described algorithm is Xi Er mapping (Hill plot), rice-Man equation (Michaelis-Menten equation), linear regression mapping (for example Lineweaver-Burk analyzes) and Scatchard mapping for example.

The sequence information that use is provided by DBMARKERS sequence library entry, and use the well-known technology of those of ordinary skills, can detect the expression (if any) of DBMARKER sequence.For example, corresponding to the sequence in the sequence library entry of DBMARKERS sequence, or the sequence in the sequence disclosed herein, all can be used for making up probe, be used for detecting DBMARKER RNA sequence in the method for for example RNA blot hybridization analysis or especially preferred quantitative amplification specific nucleic acid sequence.As another example, can use these sequences to make up primer, be used for for example based on the detection method of amplification for example based on PCR (RT-PCR) the specific amplification DBMARKER sequence of reverse transcription.When the variation in the gene expression is relevant with gene magnification, disappearance, polymorphism and sudden change, can come the sequence among comparison test and the reference group by comparison test with reference to the relative content of the dna sequence dna of measuring in the cell colony.

Can use any known method in this area, on rna level, measure expression of gene disclosed herein.For example, can use RNA hybridization analysis (with one or more the probe in these sequences of specific recognition) to measure gene expression.Perhaps, can use PCR (RT-PCR) to measure expression, for example use the differential expression sequence is had specific primer based on reverse transcription.

Perhaps, can measure the metabolin or the fragment of DBMARKER albumen and nucleic acid.Term " metabolin " comprises any chemistry or the biochemical product of metabolic process, for example through processing, cutting or the consumption of biomolecule (for example protein, nucleic acid, carbohydrates or lipid) and any compound that produces.Can detect metabolin according to the whole bag of tricks well known by persons skilled in the art, comprise refractive index spectra (RI), ultraviolet spectrophotometry (UV), fluorescence analysis, radiochemicak analysis, near infrared spectrum (near-IR), NMR (Nuclear Magnetic Resonance) spectrum (NMR), light-scattering analysis (LS), mass spectrum, the thermal cracking mass spectrum, turbidimetry, the distributing Raman spectrum, gas chromatography, the liquid chromatography/mass spectrometry coupling, substance assistant laser desorpted ionized-flight time (MALDI-TOF)/mass spectrometry, surface-enhanced laser desorption ionization (SELDI), ion sprays spectrum/mass spectrometry, Capillary Electrophoresis, NMR and IR detect.(, all being attached to herein by reference respectively) referring to WO 04/056456 and WO 04/088309.Therefore, available above-mentioned detection method or other method well known by persons skilled in the art are measured other DBMARKER analyte.

Kit

The present invention also comprises with kit form DBMARKER detectable packaging together, for example nucleic acid or antibody, described nucleic acid by having with the homologous nucleotide sequence (for example oligonucleotide sequence) of DBMARKER nucleic acid moiety complementation and but specificity is identified one or more DBMARKER nucleic acid, and described antibody is at the antibody by the protein of DBMARKERS nucleic acid coding.Oligonucleotides can be the fragment of DBMARKER gene.For example oligonucleotides length can be 200,150,100,50,25,10 or Oligonucleotide more.The DBMARKER detectable also can comprise antibody or antibody fragment and adaptive son etc.Kit can contain nucleic acid or antibody (its be combined on the solid matrix or be used for its reagent that combines with matrix is packed separately), control formulation (positive and/or feminine gender) and/or detectable label in independent container.The guide for use (for example literal, tape, VCR, CD-ROM etc.) that is used to measure can be housed in the kit.Mensuration can adopt the form of RNA blot hybridization for example known in the art or sandwich ELISA.Perhaps, kit can adopt the form of microarray known in the art.

Can produce the diagnostic kit that is used to realize the inventive method in many ways.Preferred kit of the present invention comprises contrast (or reference) sample from the experimenter with normal glucose level.Perhaps, kit can comprise from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness control sample.In one embodiment, diagnostic kit comprise antibody (for example fibrinogen α C-structure territory peptide) that (a) and solid support are puted together but and (b) and the detection moiety second antibody of the present invention of puting together.Reagent also can comprise assistant, for example buffering agent and protein stabilizing agent (for example polysaccharide) etc.If necessary, diagnostic kit also can comprise other member (but detection moiety is exactly a member (a for example zymolyte) in described system) of signal generation system, the reagent that reduces the test background interference, contrast agents, the equipment tested etc.Perhaps, test kit contain (a) but antibody and (b) and the specific binding partner of the antibody puted together of detection moiety.Test kit can be packed by any suitable method, normally all elements is contained in the container, and the operation instructions of an optional subsidiary printing are used to test.

For example, the DBMARKER detectable can be fixed on the solid matrix (for example porous bar (strip)), form at least one DBMARKER detection site.The measurement of porous bar or detection zone can comprise a plurality of sites of containing nucleic acid.Test bar also can contain the site of negative control and/or positive control.Perhaps, control site can be positioned at independent strips but not on the test bar.Optional different detection site can contain the immobilized nucleic acids of different amounts, and for example content is higher in first detection site, and content is lower in site subsequently.After the test specimen adding, the number of loci that presents detectable signal provides the quantizating index of the DBMARKERS content that exists in the sample.Detection site can be set at any suitable detected shape, general shape is to cross over the clavate or the some shape of test bar width.

Perhaps, kit contains the nucleic acid matrix array (substrate array) that comprises one or more nucleotide sequences.Nucleic acid specificity on the array identifies with DBMARKERS 1-158 to be one or more nucleotide sequences of representative.In different embodiments, can by with the combining of array, identify 2,3,4,5,6,7,8,9,10,15,20,25,30,40,50 or more a plurality of expression among the DBMARKERS 1-158.The matrix array can be on for example following document of for example solid matrix described " chip ": U.S. Patent number 5,744,305.Perhaps, the matrix array can be the solution array, for example xMAP (Luminex, Austin, TX), Cyvera (Illumina, San Diego, CA), CellCard (Vitra Bioscience, Mountain View, CA) and Quantum Dots ' Mosaic (Invitrogen, Carlsbad, CA).

The technician can conventionally prepare antibody, nucleic acid probe (for example oligonucleotides), adaptive son, siRNA, antisense oligonucleotides, and it is at any DBMARKERS in the table 1.The given embodiment of this paper has described and produced monoclonal antibody in mouse, and produces the polyclone hyper-immuneserum in rabbit.These technology all are that those of ordinary skills are well-known.

Pharmaceutical composition and methods of treatment

Be meant prevention (being chemoprophylaxis), cure, reverse, slow down, alleviate, minimize, suppress or end the ill-effect of morbid state, disease process, the disease cause of disease (for example bacterium or virus) or other unusual illness with its different grammatical forms term related to the present invention " treatment ".For example, treatment can comprise the symptom that palliates a disease (promptly not necessarily all symptoms) or slow down disease process.

Term used herein " treatment effective dose " is meant that qualification can reach the DBMARKERS of required biologically or the amount that other diabetes are regulated medicine.For the present invention, required biologically can be part or all of inhibition, delay or prevention patient's (for example people) diabetes B, prediabetes illness and the diabetes B or the process of prediabetes illness related complication; Suppress, postpone or prevent the recurrence of diabetes B, prediabetes illness or diabetes B or prediabetes illness related complication; The perhaps outbreak or the development of prevention (chemoprophylaxis) diabetes B, prediabetes illness or diabetes B or prediabetes illness related complication.

Preferably the DBMARKERS as the ingredient of pharmaceutical composition can give by any known medication well known by persons skilled in the art.That the example of method of administration includes but not limited to is oral, stomach and intestine outer, in the peritonaeum, intravenous, intra-arterial, in skin, part, hypogloeeis, intramuscular, rectum, per os, nose, liposome, by suction, vagina, intraocular, by in conduit or support local delivery, subcutaneous, the fat, in the joint, in the sheath or the employing slow release formulation.Can give DBMARKERS or contain the pharmaceutical composition of DBMARKERS according to any dosage that reaches treatment disease effective dose and administration time table.

As an example, DBMARKERS of the present invention or the pharmaceutical composition that contains DBMARKERS can following oral form give: tablet, capsule (it comprises sustained release preparation or controlled release preparation separately), pill, pulvis, granule, elixir, tincture, supensoid agent, syrup and emulsion.Equally, DBMARKERS or the pharmaceutical composition that contains DBMARKERS can adopt pharmaceutical field those of ordinary skill well-known form, give in the following manner: intravenous (for example injecting or infusion), peritonaeum are interior, subcutaneous, intramuscular or other approach.

DBMARKERS also can form slow-release injected or implantation preparation give with the pharmaceutical composition that contains DBMARKERS, can prepare described preparation, and its mode makes active component slowly to discharge.Active component can be pressed into sheet or roundlet column and implant through subcutaneous or intramuscular with slow-release injected or implant form.Implant can use inert material, biological example degradable polymer or synthetic silicone, for example silicone (Silastic), silicon rubber (silicone rubber) or other polymkeric substance of being produced by Dow-Corning Corporation.

DBMARKERS or the pharmaceutical composition that contains DBMARKERS also can liposome delivery system form give, for example small unilamellar vesicle, big unilamellar liposome and multilamellar liposome.Liposome can be made of various phosphatide such as cholesterol, octadecylamine or phosphatid ylcholines.The Liposomal formulation that diabetes are regulated medicine also can be used for method of the present invention.

Also can be by using monoclonal antibody as single carrier (coupling compound molecule on it), send DBMARKERS or contain the pharmaceutical composition of DBMARKERS.

DBMARKERS or the pharmaceutical composition that contains DBMARKERS also can be prepared into target medicine carrier with soluble polymer.Such polymkeric substance can comprise polyvinylpyrrolidone, pyran co-polymer, poly-hydroxypropyl-Methacrylamide-phenol, poly-hydroxyethyl-asparagine-phenol or the polyoxyethylene-polylysine that is replaced by palmitin acyl residue.In addition, DBMARKERS or the pharmaceutical composition that contains DBMARKERS can prepare with biodegradable polymer, be used to reach controlled delivery of pharmaceutical agents and discharge, described polymkeric substance is the crosslinked or amphiphilic block copolymer of PLA, polyglycolic acid, PLA and co-glycolic acid, poly epsilon caprolactone lactone, poly butyric, poe, polyacetal, poly-dihydropyrane, polybutylcyanoacrylate and hydrogel for example.

DBMARKERS or the pharmaceutical composition that contains DBMARKERS also can use so that form in the nose is local by solvent in the suitable nose, or by through the skin approach, use those of ordinary skills well-known through skin skin patch form.For with through skin delivery system form administration, in whole dosage regimen, dosage will be continuous but not intermittence gives.

As herein described and be applicable to that the suitable pharmaceutically acceptable salt of the reagent of the inventive method is conventional nontoxic salts, can comprise base addition salts or acid-addition salts, the for example salt that forms with inorganic base, for example alkali metal salt (for example lithium salts, sodium salt, sylvite etc.), alkali salt (for example calcium salt, magnesium salts etc.), ammonium salt; The salt that forms with organic base, for example organic amine salt (for example triethylamine salt, pyridiniujm, picoline salt, ethanolamine salt, triethanolamine salt, dicyclohexyl amine salt, N, N '-dibenzyl ethylenediamine salt etc.) etc.; Inorganic acid addition salt (for example hydrochloride, hydrobromate, sulfate, phosphate etc.); The addition salts of organic carboxyl acid or sulfonic acid (for example formates, acetate, trifluoroacetate, maleate, tartrate, mesylate, benzene sulfonate, tosilate etc.); The salt (for example arginine salt, aspartate, glutamate etc.) that forms with alkalescence or acidic amino acid etc.

In addition, the present invention also comprises any solid that contains one or more DBMARKERS of the present invention or the pharmaceutical composition of liquid physical form.For example, DBMARKERS can be crystal, amorphous form, and can have any particle diameter.Can or make it be condensed into granule, pulvis, finish, the solid that contains oil suspension or any other form or liquid physical form with the micronization of DBMARKER particle.

For oral administration, pharmaceutical composition can be a liquid or solid.Suitable solid orally ingestible comprises tablet, capsule, pill, granule, pilule etc.Suitable liquid oral medicine comprises solution, supensoid agent, spreading agent, emulsion, finish etc.

Any inert excipient that is conventionally used as carrier or thinning agent all can be used for preparation of the present invention, for example natural gum, starch, sugar, cellulosic material, acrylate or its potpourri.Composition also can comprise disintegrant and lubricant, can comprise one or more in addition and be selected from following adjuvant: bonding agent, buffering agent, protease inhibitors, surfactant, solubilizer, plastifier, emulsifying agent, stabilizing agent, viscosity increasing agent, sweetener, film forming agent or its any combination.In addition, composition of the present invention can be the form of controlled release or immediate release formulations.

For predetermined form of medication, DBMARKERS can be used as active component to be mixed with suitable drug thinning agent, excipient or the carrier (being referred to as " carrier " material or " pharmaceutically acceptable carrier " in this article) suitably selected and gives." pharmaceutically acceptable carrier or thinning agent " used herein comprises any and all solvents, dispersion medium, coating material, antiseptic and antifungal agent, isotonic agent and the absorption delay agent etc. compatible with administration.Usually, suitable carriers can be referring to latest edition " Remington ' s Pharmaceutical Sciences ", and this book is this area canonical reference teaching material, is attached to herein by reference.

For liquid preparation, pharmaceutically acceptable carrier can be water-based or non-aqueous solution, suspension, emulsion or oil.The example of non-aqueous solution is propylene glycol, polyglycol and injection organic ester, for example ethyl oleate.Aqueous carrier comprises water, alcohol/aqueous solution, emulsion or suspension, comprises salt solution and buffering medium.The example of oil is the oil in oil, animal oil, vegetable oil or synthetic source, for example peanut oil, soybean oil, mineral oil, olive oil, sunflower oil and cod-liver oil.Solution or suspension also can comprise following composition: sterile diluent is water for injection, brine solution, fixing oil, polyglycol, glycerine, propylene glycol or other synthetic for example; Antibacterials are phenmethylol or methyl p-hydroxybenzoate for example; Antioxidant is ascorbic acid or sodium bisulfite for example; Sequestrant is ethylenediamine tetraacetic acid (EDTA) for example; Buffering agent is acetate (salt), citric acid (salt) or phosphoric acid (salt) for example, and the reagent of adjustment of tonicity for example sodium chloride or glucose.Usable acid or alkali is hydrochloric acid or NaOH adjusting pH for example.

Liposome and non-water-soluble matchmaker for example fixedly oil also can use.Such medium and the reagent purposes in pharmaceutically active substance is well-known in the art.Except with inconsistent any conventional media of reactive compound or reagent, comprise its purposes in composition.The reactive compound that replenishes also can be incorporated in the composition.

Solid carrier/thinning agent includes but not limited to natural gum, starch (for example cornstarch, pregelatinized starch), carbohydrate (for example lactose, sweet mellow wine, sucrose, glucose), cellulosic material (for example microcrystalline cellulose), acrylate (for example polymethacrylate), lime carbonate, magnesium oxide, talcum powder or its potpourri.

In addition, composition also can comprise bonding agent (Arabic gum for example, cornstarch, gelatin, carbomer, ethyl cellulose, guar gum, hydroxypropyl cellulose, hydroxypropyl methylcellulose, polyvidone), disintegrant (cornstarch for example, farina, alginic acid, silicon dioxide, Ac-Di-Sol, polyvinylpolypyrrolidone, guar gum, primojel, Primogel), the buffering agent of different pH and ionic strength (tris-HCl for example, acetate (salt), phosphoric acid (salt)), adjuvant for example prevents to be adsorbed onto the albumin or the gelatin on surface, scaling agent (polysorbas20 for example, Tween 80, Pluronic F68, bile salt), protease inhibitors, surfactant (for example NaLS), penetration enhancers, solubilizer (glycerine for example, polyglycol), glidant (for example colloidal silica), antioxidant (ascorbic acid for example, sodium metabisulfite, butylated hydroxy anisole), stabilizing agent (hydroxypropyl cellulose for example, hydroxypropyl methylcellulose), viscosity increasing agent (carbomer for example, colloidal silica, ethyl cellulose, guar gum), sweetener (sucrose for example, aspartame (aspartame), citric acid), flavouring (peppermint for example, gaultherolin or orange flavor spices), antiseptic (thimerosal for example, phenmethylol, parabens), lubricant (stearic acid for example, dolomol, polyglycol, NaLS), glidant (for example colloidal silica), plastifier (diethyl phthalate for example, triethyl citrate), emulsifying agent (carbomer for example, hydroxypropyl cellulose, NaLS), polymeric coatings material (for example poloxamer or poloxamines), coating material and film forming agent (ethyl cellulose for example, acrylate, polymethacrylate) and/or adjuvant.

In one embodiment, reactive compound can prepare with carrier, and described carrier can be protected compound in order to avoid eliminate fast from body, and for example controlled release preparation comprises implant and microencapsulation delivery system.Can use biodegradable, biocompatible polymer, for example ethylene vinyl acetate, polyanhydrides, polyglycolic acid, collagen, poe and PLA.The preparation method of these preparations it will be apparent to those skilled in the art that.Material can be available from Alza Corporation and Nova Pharmaceuticals, Inc.Also can use liposome supensoid agent (comprise and have) as pharmaceutically acceptable carrier at the monoclonal antibody of viral antigen and the liposome of target infected cell.Can prepare them according to those skilled in the art's known method, for example referring to U.S. Patent number 4,522,811.

Especially advantageously with dosage unit form preparation Orally administered composition, make things convenient for administration and make the dosage unanimity.Dosage unit form used herein is meant the physically separated unit of the unit dose that is applicable to the patient that treats; Per unit contains the reactive compound of the scheduled volume that can produce required curative effect as calculated and required pharmaceutical carrier.The unique property of reactive compound and the curative effect that specifically will reach and be used for the treatment of inherent limitations in the individual field at this class reactive compound of preparation all stipulates also directly to have determined the specification of dosage unit form of the present invention.Pharmaceutical composition can be contained in container, packing or the divider, has the instructions of administration simultaneously.

The preparation of drug combination method that contains active component is well-known in the art, for example by mixing, granulation or film-making process.Usually together with active treatment composition and pharmaceutically acceptable and compatible mixed with excipients with this active component.For oral administration, the adjuvant (for example solvent, stabilizing agent or inert diluent) that activating agent and this purpose is commonly used mixes, and is transformed into suitable form of medication (for example above tablet, coated tablet, hard or soft gelatin capsule agent, water-based, alcohol or the oily solution agent of describing in detail etc.) by conventional method.

For the IV administration, have intravenous administration glucuronic acid, L-lactic acid, acetate, citric acid or any pharmaceutically acceptable acid/put together matrix of receptible reasonable buffer capacity and pH scope all can be used as buffering agent.Also can use sodium chloride solution with acid-alkali accommodation pH such as hydrochloric acid or NaOH.Usually, the pH scope of iv formulation can be about 5 to about 12.The concrete pH scope that contains the iv formulation (wherein hdac inhibitor has the hydroxamic acid part) of hdac inhibitor is about 9 to about 12.

Can prepare the pH scope between about 5 to about 12 subcutaneous preparations according to method well-known in the art, it comprises suitable buffering agent and isotonic agent.They can be mixed with can one or more every days, the subcutaneous administration form be sent the activating agent consumption per day.Those of ordinary skills can easily select the suitable buffering agent and the pH of preparation, and this depends on the solubleness of one or more DBMARKERS that given.Also can use in the subcutaneous preparations with the sodium chloride solution of acid-alkali accommodation pH such as hydrochloric acid or NaOH to required scope.Usually, the pH scope of subcutaneous preparations can be about 5 to about 12.

Composition of the present invention also can use so that form in the nose is local by solvent in the suitable nose, or by through the skin approach, uses that those of ordinary skills are well-known to be given through skin skin patch form.For with through skin delivery system form administration, in whole dosage regimen, dosage will be continuous but not intermittence gives.

Embodiment

The evaluation of biomarker in the Cohen rat model of embodiment 1:2 type diabetes

Cohen diabetes (CD) rat is well-known general diabetes B animal model, forms by showing 2 kinds of rodent strains that have many common traits with people's diabetes B (T2D).When keeping high-sucrose/low copper diet (HSD), sensitive strain (CDs) developed into diabetes in 30 days, and resistant strain (CDr) keeps normal blood glucose level.When the conventional rodent meals of long term maintenance (RD), these two kinds of strains can not develop the T2D symptom.

Specimen preparation

30 days CDr rat of RD or HSD and CDs rat are gathered serum, urine and tissue sample (comprising spleen tissue, pancreas tissue and hepatic tissue) from feeding.With the sample quick-frozen and be stored in-80 ℃.

Each of 4 kinds of experiment conditions is all prepared the holoprotein extract, and every group with 10 organs.Handle the pancreas tissue with mechanical shearing device (Polytron).In order in handling sample, to keep the integrality of protein, tissue is kept in the dry ice up to beginning handles, all damping fluids and instrument are all wanted precooling.Sample also will be kept on ice in the homogenate process.

T-Per damping fluid (Pierce) in precooling on ice, before the use, is added 2 adequate proteins enzyme inhibitors (Roche Applied Sciences) in every 50ml damping fluid.In case behind the adding protease inhibitors, discard the damping fluid of any not usefulness.The consumption of T-Per damping fluid is a 20ml/ gram tissue.For each group, give the pancreas samples weighing, calculate the consumption of required lysis buffer and join in each tissue sample in the 50ml pipe.In 10 seconds of homogenate on ice, then is leaving standstill the phase of 30 seconds with each sample, allows the sample cooling.If coarse fragments is still significantly talked about, repeat this circulation till homogenate evenly.The homogenate probe is inserted into the generation of sentencing the minimizing foam in the sample apart from the pipe about 1cm in the end.After finishing homogenate, with extract 4 ℃ in 10, centrifugal 15 minutes of 000x g.

After centrifugal, the results supernatant, (bicinchoninic acid BCA) measures to measure total protein content to carry out two quinoline dicarboxylic acids.Table 2 provides the average protein content corresponding to the sample of the CDs rat of the CDr rat of feed RD or HSD and feed RD or HSD.

The total protein content of table 2:Cohen diabetes rat glucopyron

Supernatant is divided into aliquot and is stored in-80 ℃.Sediment also keeps and is stored in-80 ℃.

Use one dimension SDS-PAGE, glucopyron is carried out the protein expression analysis of spectrum of CDr phenotype and CDs phenotype.The sample ligand that will contain each extract of 6 μ g total proteins is also gone up sample to the 4-12% acrylamide gel in sample buffer.After electrophoresis runs glue and finishes, gel is immersed in the coomassie dyestuff 1 hour, in distilled water, decolour and spend the night.The gained protein expression profile can be estimated comparison (Fig. 1) to each extract by rule of thumb.Again these glucopyrons are used for two-way immunity contrast disclosed herein (Bi-DirectionalImmunological Contrasting).

Because albumin, immunoglobulin (Ig) and other abundant protein account for about 95-97% of total serum protein, so, then can shelter lower protein of abundance and peptide-labeled detection if directly analysis of whole blood is clear.Therefore, be necessary the separation of serum sample, to reduce the quantity of sheltering and increase the peak that can be used for analyzing to low abundance proteins.

In order to increase the detection at a large amount of peaks and to alleviate the signal reptation behavior of high-abundance proteins matter (for example albumin, immunoglobulin (Ig) etc.), will be separated into 6 flow points from the CDr rat of feed RD or HSD and the rough blood serum sample of CDs rat to low abundance proteins.(purchase in Ciphergen, Fremont CA) separates to use serum separating kit based on the anion exchange pearl.In brief, blood serum sample dilutes with the urea-denatured liquid of 9M; Again sample on the dilute sample is filtered on the micro plate (filter microplate) to pre-96 holes of filling the anion exchange adsorbent.Adopt this method, allow sample combine, after 30 minutes, use progressively pH gradient buffering liquid elution samples 4 ℃ of insulations with the active surface of pearl.This process is collected 6 flow points, comprises pH 9, pH 7, pH 5, pH 4, pH 3 and machine eluate is arranged.After the separation, in such a way, serum analysis sample on the SELDI chip.

SELDI (surface-enhanced laser desorption ionization)

SELDI

Technology (Ciphergen) is the technology of the protein mixture that is retained on the chromatogram chip surface being carried out mass spectrophotometry through being designed for.The SELDI mass spectrum according to the matter of protein in the potpourri/lotus than and the binding ability of they and chip surface, obtain the spectrogram of complex proteins potpourri.By comparison peak intensity, measure the protein of differential expression by these protein spectrums.This technology adopts holder or the chip based on aluminium, and it uses surface (hydrophilic, hydrophobic, pre-activation, positive, immobilization metal affinity, kation or negative ion) or biology (antibody, Fab (for example scFv), DNA, enzyme or acceptor) bait surface (bait surface) through chemical modification to transform.Different proteins can be caught according to protein self intrinsic characteristic in chemistry that these are different and biological chemistry surface.Few tissue extract or the body fluid to 1 μ l of volume can be directly used in these surfaces, wherein to the bait surface have affinity protein will with surface combination.Through series washing with remove nonspecific proteins or weak in conjunction with albumen after,, be used for MS and analyze through laser desorption and ionization in conjunction with albumen.Measurement range is the protein molecular weight of (1000 dalton are to 200kD) from little peptide to protein.Use these mass spectrum patterns that a sample and other sample are made a distinction then, and identify leading candidate's mark, be used for further analysis.People identify candidate's mark by comparison condition to the protein spectrum of condition stem cell media (conditioned versusconditioned stem cell culture medium) always.In case identify candidate's mark, can be purified and check order.

The blood serum sample that separates is added on the surperficial chip (cation exchange, anion exchange, metal-affinity combination, hydrophobic and positive) of different chemical modification, and its distribution is analyzed by SELDI, two-dimentional PAGE (2DE) and two-dimensional liquid chromatography (2D/LC).

Two-dimensional liquid chromatography (2D/LC)

ProteomeLab PF 2D Separation of Proteins system is full-automatic, two dimensional separation system (in liquid phase), and protein is differentiated and collected in this system by the isoelectric point (pI) of first dimension and the hydrophobicity of second dimension.This system displays complex patterns with two-dimentional protein profiling, thus the direct protein spectrum of more different sample rooms.Because all the components is all in liquid phase separation and collection, so be desirable for the downstream identification of proteins of using mass spectrum and/or Protein Extraction (being used for antibody producing).

PF 2D system can be used for solving the relevant many problems of traditional proteomics research, the reappearance of for example detection of low abundance proteins, each batch (run-to-run), quantitatively, the detection of the protein of the detection of the detection of film or hydrophobic protein, alkaline protein and very low and very high molecular weight.Because the dynamic range of protein is crossed over 10 orders of magnitude in the serum, and a few abundant protein accounts for more than 95% of total protein content relatively, this is very difficult for the detection as the low abundance proteins of candidate's mark.For enrichment and the more low-abundance protein of evaluation, distribute blood serum sample with IgY-R7 rodent optimized distribution post, so that 7 kinds of abundant proteins (albumin, IgG, transferrins, fibrinogen, IgM, alpha1-antitrypsin, haptoglobin) and more low-abundance Separation of Proteins are opened.

To distribute on the serum sample to PF-2D.On the HPCF post, use the linear pH gradient that produces by initial damping fluid (pH 8.5) and elution buffer (pH 4.0), carry out the first dimension chromatofocusing.According to the pI isolated protein.Collect flow point and go up sample, carry out second dimension and separate to anti-phase HPRP post.The 2D collection of illustrative plates that relatively each sample produced is identified different peaks pattern then.Select flow point then, carry out trypsinization.With LC/MS sample digestion is checked order, be used for the evaluation of protein.

The 2-D gel electrophoresis

Two dimensional electrophoresis just can be differentiated thousands of kinds of protein in the complex mixture simultaneously on a clotting glue.In first dimension,, be by the molecular weight isolated protein and tie up second by the pI isolated protein.The application of 2D gel electrophoresis comprises the mensuration of protein group (proteome) analysis, cell differentiation, disease marker, to the monitoring etc. of the reaction of treatment.

Sample is to the band of immobilization pH gradient (IPG) on the blood serum sample that IgY is distributed, and wherein different pH gradients are pH 3-10, pH 3-6 and pH 5-8.After first dimension is run through, ipg strip is placed on 8-16% or 4-20%SDS-PAGE gradient gel top, is used for second dimension and separates.

The result

About 4200 daltonian peak albumen are present in the serum of CDr-RD and CDr-HSD, but do not exist in the serum of CDs-RD or CDs-HSD, see Fig. 2 A.Fig. 2 B is the MS/MS spectrogram of 4200 dalton's fragments.This protein is checked order, carry out the mass data library searching then, find that this protein is a kind of new protein.This peptide called after " D3 " finds that its sequence is SGRPP MIVWF NRPFL IAVSH THGQT ILFMA KVINPVGA (SEQ ID NO:1).The D3 peptide is the peptide sequence of 38 aggressiveness, corresponding to first biomarker of finding in the Cohen diabetes rat.(derive from state-run biotechnology (the National Center for Biotechnology Information of information center with the BLAST algorithm, NCBI)) carry out sequence alignment, find that these 38 amino acid whose fragments and at least 10 kinds of different aminoacids sequences have sequence homogeneity.It should be noted that BLAST comparison shows, these 38 amino acid whose D3 peptides contain the conservative motif corresponding to " FNRPFL " and " FMS/GKVT/VNP ".Fig. 3 A shows the BLAST comparison result of D3 fragments of peptides related amino acid sequence, and Fig. 3 B shows the nucleic acid sequence encoding of D3 peptide and the BLAST comparison result of the nucleic acid sequence encoding of the peptide identified through PROTEIN B LAST.5 '-TTC AAC MRR CCYTTY ST-3 ' (SEQ ID NO:2)) and reverse primer ((the target practice district that contains sequence " FMS/GKVT/VNP ": 5 '-YVA CYT TKC YMA KRA AGA-3 ' (SEQ ID NO:3)) degenerate primer should conservative motif and comprise following sequence through the design target: forward primer (the target practice district that contains amino acid sequence " FNRPFL ":; Wherein M=A or C; R=A or G; Y=C or T; S=C or G; K=G or T; With V=A, C or G.These degenerate primers are used for reverse transcriptase polymerase chain reaction (RT-PCR), with the people SERPINA 3 in amplification liver and the pancreas.In people liver and pancreas, identify the 1.3Kb fragment, seen Fig. 3 C.

Table 3: expression is analyzed extra candidate's mark of identifying by SELDI.

Difference in the Cohen diabetes rat is seen Fig. 4 A and Fig. 4 B, shows the figure of the wash-out profile that obtains through the gel of the biomarker of LC/MS technical appraisement with through differential two dimension reversed-phase HPLC or the CDr-RD (red) and CDs-RD (green) of the selected first dimension pI flow point (flow point 31).Fig. 5 A shows from each the 2DE gel of sample in 4 kinds of Cohen diabetes rat models, and Fig. 5 B is the enlarged drawing of the each point of identifying among Fig. 4 A, is accredited as apo E, liver regeneration related protein and a kind of previous unidentified protein.Fig. 6 is a synoptic diagram, is illustrated in the differential expression protein that uses the 2DE scientific discovery in 4 kinds of Cohen diabetes rat models.Fig. 7 is a histogram, shows the Cohen diabetes rat haemocyanin of the differential expression of identifying by 2DE.

In rabbit, produce hyper-immuneserum with the D3 peptide.Fig. 8 shows Western blotting, show D3 hyperimmune rabbit anteserum with in CDr-RD and CDr-HSD rat blood serum flow point 6, separate～reactivity of 4kD albumen.The CD rat blood serum sample that separates is run glue on the 10%SDS-PAGE gel, transfer on the pvdf membrane then.(scope is 49kD～62kD) also react with hyper-immuneserum for higher molecular weight bimodal, showing that all product tie up to all expresses parent's albumen under treatment modalities RD or the HSD, yet, corresponding to the less derivant of D3 fragment (～4kD) but differential expression in the CDr strain only.These results be consistent by the resulting result of SELDI analysis of spectrum.Analyze the concentration of D3 fragment in the CDr rat blood serum then by SELDI.With the CDr-serum of a series of synthetic D3 poly saccharide peptide standard products (0.1mg/ml, 0.033mg/ml, 0.011mg/ml, 0.0037mg/ml, 0.0012mg/ml and 0mg/ml) and 10 times of dilutions in duplicate point sample on Q10 protein-chip array.Peak intensity is at the concentration mapping of D3 poly saccharide peptide standard product.According to the figure that has done (Fig. 9), the range of linearity that is used for the concentration judgement is 0-0.01mg/ml.Therefore, according to the peak intensity of CDr-RD blood serum sample, the D3 concentration in the CDr-RD serum is about 0.04mg/ml.

With anti-D3 rabbit anteserum (1: 200) and second goat anti-rabbit igg puted together with HRP (1: 25,000 dilution), in Cohen rats'liver extract, carry out the analysis that Serpina expresses by western blot analysis.To the second goat anti-rabbit igg antibody that contains liver extract (10 μ g) and put together (1: 25,000 dilution) but the contrast that does not contain first antibody has also carried out analyzing (Figure 10) with HRP.After liver extract and D3 hyper-immuneserum reacted, cluster protein (41kD, 45kD and 47kD) displayed.The expression of 41kD and 45kD albumen is roughly the same, and does not detect 47kD albumen in diabetes rat (being CDs-HSD (diabetes)).

Table 4 contains the biomarkcr data that derives from CD rat blood serum sample and gathers.

Embodiment 2: the evaluation of biomarker in the human serum

With D3 hyper-immuneserum (rabbit; Figure 11) human serum is analyzed.Used first antibody is the rabbit polyclonal antibody that produces with after the immunity of D3 peptide.The patient compares with diabetes B, and the protein expression intensity that the middle molecular weight of normal individual serum (people) is 20kD (between 14kD and 28kD mark) is higher.In two kinds of (normal and diabetes) samples, molecular weight is that it seems that a pair of protein of 60-80kD all exist.What is interesting is that the protein intensity in both can transform; Use from the monoclonal antibody of the CDr-HSD pancreas of subduing immunization and CDs-HSD pancreas and observe.Figure 12 A and Figure 12 B represent to contain the preparation type gel of 100 μ gCDr-HSD or CDs-HSD glucopyron.Positive control is with the anti-actin antibody staining of 20 μ g, and the subclone swimming lane is with 600 μ l condition culture supernatant dyeing (referring to the other parts of this instructions).

The human serum sample who picks up from normal subjects, diabetic and insulin resistance patient carries out SELDI and analyzes: Itamar doctor Raz, doctor WendellCheatham and Rachel doctor Dankner from following 3 separate sources.Doctor's Raz sample (being called " Raz sample " hereinafter) comprises 11 T2D human serums and plasma sample and 9 normal human serums and plasma sample.The Cheatham sample comprises altogether 51 blood serum samples and urine samples, and wherein 12 from the type 1 diabetes individuality, and 13 from the T2D individuality, and 10 from the insulin resistance patient, and 16 from the normal subjects.The Dankner sample comprises 23 T2D human serum samples and 25 normal human serum samples.SELDI analyze to show the important peak of Raz sample and Dankner sample, sees the following form 5 and table 6.Figure 13 is the example of composing by the human whole serum that SELDI distributes on anionic Q10 chip.

The selected important peak that exists in the table 5:Raz sample

Sample number into spectrum	Peak (M/Z)	The P value	Change multiple (T2D/N)
Sample number into spectrum	Peak (M/Z)	The P value	Change multiple (T2D/N)	1	12900	9.90E-07	3.24
2	134500	4.75E-06	0.55	1	12900	9.90E-07	3.24
2	134500	4.75E-06	0.55	3	44500	1.75E-05	2.21
4	4260	1.84E-05	0.4	3	44500	1.75E-05	2.21
4	4260	1.84E-05	0.4	5	4260	2.13E-05	0.49
6	56500	2.84E-05	0.55	5	4260	2.13E-05	0.49
6	56500	2.84E-05	0.55	7	6640	8.08E-05	2.14
8	12600	1.96E-04	2.64	7	6640	8.08E-05	2.14
8	12600	1.96E-04	2.64	9	2505	2.09E-04	1.71
10	29000	2.46E-04	0.63	9	2505	2.09E-04	1.71
10	29000	2.46E-04	0.63	11	3300	3.44E-04	0.65
12	14070	3.58E-04	0.69	11	3300	3.44E-04	0.65
12	14070	3.58E-04	0.69	13	11750	5.22E-04	2.81
14	6875	7.49E-04	2.2	13	11750	5.22E-04	2.81
14	6875	7.49E-04	2.2	15	13750	1.05E-03	0.66
16	9715	2.69E-03	1.89	15	13750	1.05E-03	0.66
16	9715	2.69E-03	1.89	17	9375	3.88E-03	1.61
18	6440	6.04E-03	2.1	17	9375	3.88E-03	1.61

The selected important peak that exists in the table 6:Dankner sample

Sample number into spectrum	Peak (M/Z)	The P value	Change multiple (T2D/N)
Sample number into spectrum	Peak (M/Z)	The P value	Change multiple (T2D/N)	1	10075	4.81E-04	3.63
2	9310	1.87E-03	1.9	1	10075	4.81E-04	3.63
2	9310	1.87E-03	1.9	3	4160	3.68E-03	1.74
4	6450	1.59E-04	0.76	3	4160	3.68E-03	1.74
4	6450	1.59E-04	0.76	5	9310	8.25E-04	1.36
6	7770	8.25E-04	0.66	5	9310	8.25E-04	1.36
6	7770	8.25E-04	0.66	7	6430	1.32E-05	0.7
8	10650	2.25E-04	2.58	7	6430	1.32E-05	0.7

SELDI analyzes the protein peak be disclosed in the differential expression of identifying in 13 T2D human samples and 16 the normal person's samples.Figure 14 describes the pseudo gel figure of the SELDI analysis of sample flow point 1.Every swimming lane is represented the spectrogram of the single sample of M/Z 14.0kD to 16.0kD.The M/Z of protein band is about 15.2kD, 14.8kD and 14.5kD respectively.Figure 15 is that the SELDI that carries out on 13 T2D and 16 normal separation blood serum samples (flow point 3) analyzes another width of cloth pseudo gel figure of (distributing) on the Q10 protein-chip.Each swimming lane is represented the spectrogram of the single sample of M/Z 8.0kD to 10.0kD.The M/Z of protein labeling is about 9.3kD.Figure among Figure 15 is a kind of mark (M/Z～6430) synoptic diagram, and this is marked in the T2D sample and is reduced.Analyze with SELDI distribution to albumin level on the Cheatham sample, and compare, see Figure 16 with the Dankner sample.

Embodiment 3: the generation of two-way immunity contrast and monoclonal antibody

According to the glucopyron protein spectrum that SDS-PAGE obtained, notice the notable difference (Fig. 1) of CDr-HSD sample and CDs-HSD sample room banding pattern.Carried out two-way immunity contrast at these two sample rooms.This technology comprises the foot pad that two kinds of glucopyrons from the Cohen diabetes rat that will contrast is expelled to animal used as test (for example Balb/c mouse) respectively.After injection site picked-up and process antigen, activation APC is moved to the (of regional nodes popliteal nest (popliteal) by antigen presenting cell (APC)) and cause immune response.Because these lymph nodes are positioned on every leg, they are separated from one another on dissecting, and prevent that the antigentic specificity lymphocyte from mixing at this position.After the immune response, these activated lymphocytes are moved to spleen from regional nodes, and they mix and from then on can be in systemic circulation at this.

Foot pad injection 2 weeks of back, used with in the past identical antigen and inject each foot pad, give the animal booster immunization.Such booster immunization is recalled the injection site with the antigentic specificity lymphocyte, and subsequently Yin Liu Dao popliteal nest lymph node.This technology uses natural propagation and cell migration process as filtering mechanism, so that separate and enrichment specificity lymphocyte in each lymph node that on dissecting, separates, thereby reduce the mixing of cell as far as possible, and described antigen is only expressed in a kind of extract with antigentic specificity.Behind the booster immunization 3 days, get out popliteal nest lymph node and put into merging thing respectively from each side of animal.During booster immunization, imperative is not changed antigen-like material, otherwise will cause that the specificity lymphocyte moves to Liang Ce popliteal nest lymph node and cause that specific cell separates on dissecting, thereby loses the advantage of this technology.

Ordered female Balb/c mouse in all ages of 15 6-8 from Harlan.Inject 25 μ g CDr-HSD glucopyrons at its left hind foot pad for every mouse, and at its right back foot pad injection 25 μ g CDs-HSD glucopyrons.Preparation antigen is as follows in the 20%Ribi adjuvant, cumulative volume 50 μ l:

Table 7:

	Right foot pad	Left side foot pad
	Right foot pad	Left side foot pad	375mg CDs-HSD	110μl	-----------
375mg CDr-HSD	-----------	62μl	375mg CDs-HSD	110μl	-----------
375mg CDr-HSD	-----------	62μl	PBS	490μl	538μl
The Ribi adjuvant	150μl	150μl	PBS	490μl	538μl

The Ribi adjuvant is heated to 37 ℃ also with the aseptic PBS reprovision of 1ml.With bottle vortex at least 1 minute, abundant composite material.Ribi adjuvant with correct volume joins in the antigen preparation thing again, and the gained potpourri is vortex 1 minute again.Abandon its preparing materials of any not usefulness, the Ribi adjuvant of any not usefulness is stored in 4 ℃ and be used to prepare the booster immunization injection.Animal is at the 1st day initial immunity, at the 14th day booster immunization.At the 17th angel's animal euthanasia, after death (post mortem) Qie Qu popliteal nest lymph node is also transported the laboratory back and is handled.

The generation of hybridoma

Basically according to Kohler and the described method of Milstein (1975), created hybridoma cell line.By hatching, will merge from lymphocyte and the rat bone marrow tumour cell system (Sp2/0) of immune animal with polyglycol (PEG).After the fusion, cell is maintained in the selective medium (HAT nutrient culture media) that contains hypoxanthine, aminopterin and thymidine, this nutrient culture media only allows chimeric fused cell grow.

Merge the previous day, fusion partner (be in the Sp2/0x Ag14 cell of division stage, viablity surpasses 95%) is divided into 1 * 10 ⁵Living cells/ml, in fusion preceding 24 hours.Merge the same day, put to death mouse, cut lymph node and put into double dish, wherein contain the DMEM of 10% hyclone of interpolation (FBS) that is preheated to room temperature.Use aseptic microslide, lymph node is placed between 2 Fu Shi sides (frosty sides) of slide and is squeezed into single cell suspension.Again cell suspension is transferred in the 15ml pipe and centrifugal 1 minute in 1000rpm.Supernatant is removed in suction, cell precipitation carefully is resuspended among the 12ml serum-free DMEM in 1000rpm centrifugal once more 10 minutes then.Repeat this process more than 2 times, be removed fully to guarantee serum.After the washing, cell is resuspended among the 5ml serum-free DMEM, counts at microscopically.

By collecting fusion partner in centrifugal 10 minutes in 1000rpm.Cell is washed 3 times in serum-free DMEM, be resuspended among the serum-free DMEM at last and counting.Calculate the number of fusion partner cell according to the lymph-node cell number.For each myeloma cell (fusion partner), (ratio of myeloma and lymph-node cell is 1: 2 to need 2 lymph-node cell; For example for 10 * 10 ⁶Lymph-node cell needs 5 * 10 ⁶The fusion partner cell).Add the myeloma cell and the LN cell of suitable quantity, the cell cumulative volume is adjusted to 25ml, again 25ml 3% glucosan is joined in the cell with serum-free DMEM.With potpourri centrifugal 10 minutes, inhale from cell precipitation as far as possible and remove supernatant in 1000rpm.Lid covered the Guan Shanghou of cell is being housed, carefully at the bottom of the tapping pipe, re-suspended cell, PEG joins in the pipe with 1ml preheating 50% (volume).Allow the cell of aggegation leave standstill 1 minute, add 20ml serum-free DMEM then, add 25ml 20%FBS again, contain the DMEM of 25mM Hepes.Pipe upset is mixed once centrifugal 10 minutes then in 1000rpm.Nutrient culture media is removed in suction, and the tapping cell makes it resuspended.Add HAT and select nutrient culture media, making cell suspension is 0.125 * 10 ⁶Cell/ml or 0.0625 * 10 ⁶Cell/ml.Every hole adds 100 μ l cells in 96 hole flat undersides, and at 37 ℃/CO ₂Hatch under/8.5% condition.After 2 days, in cell, add the fresh HAT of 100 μ l and select nutrient culture media.Check the colony growing state of cell after 7 days.

The screening of hybridoma

When in 96 orifice plates, observing visible colony, gather in the crops 100 μ l condition supernatants from each colony, be used for the ELISA screening.The screening supernatant, but the antigentic specificity IgG that whether exists at the detection level of CDr-HSD extract and CDs-HSD extract seen.Only select the colony that is positive ELISA reaction and has 2 times of differences at least at one of two kinds of extracts, increase and further characterize.

The concentration that to test is that the glucopyron of 25 μ g/ml dilutes with carbonate-bicarbonate buffer (1 carbonate-supercarbonate capsule is dissolved in the 100ml deionized water).2 additional bore that keep in 96 orifice plates are used for positive control, and 2 additional bore are used for negative control.With bonding film covering plank and 4 ℃ of overnight incubation.

Wash plate 1 time with 200 μ l PBS/ tweens.By plank is flicked to tank, remove the hole content, more carefully with plank to the thieving paper tapping, remove residual liquid.Add about 200 μ l lavation buffer solutions (PBS/ tween), discard as previously mentioned then.At 37 ℃, in 200 μ l, 5% milk powder/PBS/ tween, whole plate was sealed 1 hour.Preceding for another example described, wash plate 3 times with the PBS/ tween.

To merge culture supernatant and in 0.5% milk/PBS/ tween, carry out dilution in 1: 1, each sample will be joined (50 μ l in the hole; Every hole final volume is 100 μ l), wherein the 50 μ l anti-actin Ab of 20 μ g/ml (Sigma) join in the hole that contains 50 μ l damping fluids.50 μ l damping fluids are joined in the negative control hole.Cover plank, 4 ℃ of overnight incubation.Wash plate 3 times with the PBS/ tween as previously mentioned, will resist the 0.5% milk/PBS/ tween of the anti-mouse IgG of HRP to join in each hole again by 1: 20000 (100 μ l).Cover plank, hatched 2 hours at 37 ℃.

After hatching with second antibody, wash plate 4-5 time as previously mentioned.During last the washing, lavation buffer solution is stayed a few minutes onboard, and then abandon.100 μ l are preheated to the TMB (VWR of room temperature; Lucifuge is stored) join in each hole, avoid bubble simultaneously, up to colour developing (20-30 minute) as far as possible.Add 50 μ l 2M sulfuric acid cessation reactions.Read plate with spectrophotometer at the 450nm place.

13 clones that produce monoclonal antibodies (mAb) satisfy above-mentioned experimental standard, and 9 at CDs-HSD, and 4 at CDr-HSD.The ELISA data of these colonies are summarized in table 5, and histogram is seen Figure 17 A and Figure 17 B.Table 8 shows the ELISA garbled data of monospecific CDr-HSD and CDs-HSD hybridoma.Show absolute absorption value and the difference multiple of each colony at OD 450nm place.In order to confirm first garbled data, some clones during increasing, have been tested again, to confirm the experimental observation result of first screening.

Table 8

In order to obtain monoclonal hybridoma system, make all subclones of each colony by limiting dilution.Again screen DCRP system of institute, and clone to judge the best by the O.D.450nm classification from each parent's colony.Increase preceding 10 secretory antibodies the clone and be stored in the liquid nitrogen.Give cell count and guarantee that vigor is at least 80%.Prepare cell in the subclone nutrient culture media of the DMEM that contains 10%FBS and 10% hybridoma clone's factor (bioVeris), concentration is 5 cell/ml (about 60ml is for 3 plates).Preparation concentration be about 1.6 cells/ml (about 60ml is for 3 plates) another organize same like cell.Inoculation 200 μ l cells in every hole of 96 hole circle base plates.1 cell is contained in one group 3 the every holes of plate, and 1 cell is contained in average per 3 holes of another group.After 10 days, as seen cell measures the specificity of these subclones.10%FBS is being housed and is containing the target cell that increases in 24 orifice plates of DMEM of the 5% hybridoma clone factor.

The heavy chain by measuring each composition and the type and the molecular weight of light chain define the composition of every kind of mAb.Use Immunopure monoclonal antibody isotype kit I (Pierce),, carry out the isotype somatotype according to the guide for use of manufacturer.With the Experion autophoresis system measurement heavy chain of Bio-Rad and the molecular weight of light chain.The Experion system carries out the electrophoresis of multistep based on gel automatically: separation, dyeing, decolouring, band detection, imaging and data analysis.These analyses the results are shown in following table 9, shown that the physics of the monoclonal antibody specific of CDr-HSD and CDs-HSD characterizes.Carried out the evaluation of heavy chain and light chain with Immunopure monoclonal antibody isotype kit I (Pierce), measured molecular weight (kD of unit) with Experion autophoresis system (Bio-Rad).

Table 9

In order to determine each clone's specific antigen, measure each mAb by Western blotting, to determine the molecular weight of corresponding antigens.The data that derive from reactive clone are seen Figure 18 A-18C.

For purifying has specific antigen to P2-10-B8-KA8, carry out immunoprecipitation.Specific antibody is attached on the Protein G pearl, is used for from containing the CDr-HSD glucopyron elutriation antigen of 6mg total protein.In the Eppendorf pipe, in 13, centrifugal 5 minutes of 000rpm takes out the sediment at extract top with the CDR-HSD glucopyron.Do not take out any precipitation, the 6mg extract is transferred in 3 clean centrifuge tubes, volume is adjusted to 1ml by adding the T-per damping fluid.In pipe 1,100 μ g purifying P2-10-B8-KA8 are joined in the dilute sample, 200 μ g purifying P2-10-B8-KA8 are joined in the pipe 2,300 μ g purifying P2-10-B8-KA8 are joined in the pipe 3.Pipe is spent the night 4 ℃ of rotations.

With Protein G pearl slurries (1ml) on the Eppendorf hydro-extractor centrifugal 3 minutes in 500x g, by with damping fluid dilution in 1: 1 pearl with precooling T-per damping fluid washing 2 times.(200 μ l) transfers in each pipe that contains antibody-antigen mixture with slurries.Prepare pipe by 1ml T-Per damping fluid and 300 μ g antibody, set up control tube with 200 μ l slurries.Each pipe was rotated 2 hours at 4 ℃.Then, with precooling T-per damping fluid washing pearl 2 times (centrifugal 3 minutes of 500x g), keep supernatant.In cold PBS, after the washing for the last time, remove supernatant as much as possible, add 100 μ l 2X sample buffers (Pierce 5X sample-loading buffer: 200 μ l sample-loading buffers, 100 μ l reductive agents, additional 200 μ l water).Sample was boiled 5 minutes at 95 ℃, then cooled on ice 5 minutes.Sample after centrifugal 3 minutes, is carried out electrophoresis according to sample on the consumption in 20 μ l/ roads with each sample to the little gel of 4-12%SDS-PAGE.

Post precipitation, total protein can be seen several strips after dyeing with coomassie on gel.Between the 70-80kD molecular weight ranges, can be observed faint two bands (referring to Figure 19).By detecting Western blotting, confirm that two bands are target stripe (data not shown) with the similar gels preparation of identical mAb.Downcut two bands from the SDS-PAGE gel respectively, identify by mass spectrum.The below band is made the positive identification of calnexin.Calnexin is the chaperone that associates with endoplasmic reticulum.

Calnexin is endoplasmic reticulum (ER) integral protein of 90kD.It is made up of the acid kytoplasm tail of big (50kD) N-end calcium binding cavity intracellular domain (lumenal domain), single span film spiral and weak point (90 residues).Calnexin is under the jurisdiction of the protein families that is called " chaperone ", it is characterized in that auxilin folds and the major function of quality control, guarantees to have only protein suitably folding and assembling just can enter secretory pathway.The function of calnexin is to keep folding or not unassembled N-connection glycoprotein in endoplasmic reticulum.Calnexin only combines with the N-glycoprotein with GlcNAc2Man9Glc1 compound sugar.In ER, the compound sugar with 3 continuous glucose residues adds on the asparagine residue of nascent protein.The glucosyl compound sugar that calnexin is discerned comes free two glucuroide (I and II) continuous actions and to the pruning of 2 glucose residues.Glucuroide II also can remove the 3rd and last glucose residue.If glycoprotein is suitably not folding, the enzyme of a kind of UGGT of being called can be added back to glucose residue on the compound sugar, thereby generation can be in conjunction with the glycoprotein of calnexin.Therefore, dissociate in ER because of certain reason is difficult to suitably folding glycoprotein chains, take a risk to run into MNS1 (alpha-Mannosidase), this finally makes this class bad luck glycoprotein be degraded because of removing its mannose residue.ATP and Ca ²⁺Be two co-factors that participate in the combination of calnexin substrate.Figure 20 A and Figure 20 B are screenshot captures, and the MS spectrogram that target protein is accredited as calnexin is read in demonstration.

The microarray analysis of gene expression in the embodiment 2:Cohen diabetes B rat tissue

By Phase I and Phase II analysis microarray data is analyzed.Phase I is according to the process data from Gene Logic.Phase II is equivalent to use the data analysis of GeneSpringGX.Additional criteria (comprising statistics, signal transduction pathway and cluster) is used for analyzing.

Use Affymetrix, the MAS5.0 software of Inc. is analyzed and to be derived from Cohen diabetes B rat (CDs-HSD, CDr-HSD) microarray results of the total RNA contrast of pancreas from Gene Logic (Phase I).Overall gene expression analysis shows, compares with CDs-HSD, has 1178 genes to raise in CDr-HSD, 803 gene downward modulations.Many such transcripts participate in relating to some signal transduction pathways of diabetes B, for example insulin signaling transduction, β cell dysfunction and lipid and glucose metabolism.In addition, some serpin family members (serpin) differential expression in 2 kinds of models.

Table 10 provides the data general introduction from Gene Logic, wherein observes the change greater than 3 times.

Signal transduction pathway	Up-regulated gene CDR-HS and CDS-HS	Down-regulated gene CDR-HS and CDS-HS
Signal transduction pathway	Up-regulated gene CDR-HS and CDS-HS	Down-regulated gene CDR-HS and CDS-HS	The insulin signaling transduction	39	41
β cell dysfunction (Apoptosis, survival)	17	6	The insulin signaling transduction	39	41
β cell dysfunction (Apoptosis, survival)	17	6	Inflammation and immune system	5	92
Mitochondria dysfunction and reactive oxygen species	20	8	Inflammation and immune system	5	92
Mitochondria dysfunction and reactive oxygen species	20	8	Lipid and glucose metabolism	17	13
Proteinase and protease inhibitors	28	17	Lipid and glucose metabolism	17	13
Proteinase and protease inhibitors	28	17	Amino acid, nucleic acid delivery albumen and metabolism	13	9
Potassium channel	3	6	Amino acid, nucleic acid delivery albumen and metabolism	13	9
Potassium channel	3	6	ER and golgiosome related gene	8	8
Other unfiled gene	1028	603	ER and golgiosome related gene	8	8
Other unfiled gene	1028	603	Amount to	1178	803

Carry out Phase II data analysis with GeneSpring GX, it is used to make data normalization (ratio=transcribe signal/control signal), to improve the comparison of chip chamber.GeneSpring GX allows according to show the gene of 2 times or 3 times changes on expression, to list of genes to be filtered is arranged.GeneSpring GX also comprises statistic algorithm, for example ANOVA, check (Post-Hoc Test) and Cross-Gene Error Modeling afterwards, and gene clustering algorithm for example gene tree, K-mean cluster and self organization map (SOM) cluster.GeneSpring GX also has the ability that this area has been announced approach of integrating, for example capital of a country gene and genome encyclopedia (Kyoto Encyclopedia of Genes and Genomes, " KEGG approach ") and Gen MapAnnotator and Pathway Profiler (GenMAPP).

Be presented at through the microarray results that GeneSpring GX analyzes and change greater than 3 times transcript in 2 groups, the p value of 137 transcripts is less than 0.05.These genes participate in some signal transduction pathways, for example insulin signaling transduction pathway, serpin protein family, basic metabolism, pancreas function and inflammation.Figure 21 shows the scatter diagram of difference expression gene.Its level changes sees Figure 22 B at 137 transcripts more than 3 times, also ranges following table 11 and 12.

Table 11: up-regulated gene (transcript altogether=101)

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	Reg3a	Rn.11222	Regeneration pancreas islet 3 α that derive
LOC680945	Rn.1414	Be similar to stroma cell derivative factor 2 samples 1	Reg3a	Rn.11222	Regeneration pancreas islet 3 α that derive
LOC680945	Rn.1414	Be similar to stroma cell derivative factor 2 samples 1	Pap	Rn.9727	Pancreatitis associated protein
Ptf1a	Rn.10536	The pancreas idiosyncratic transcription factor, 1a	Pap	Rn.9727	Pancreatitis associated protein
Ptf1a	Rn.10536	The pancreas idiosyncratic transcription factor, 1a	Mat1a	Rn.10418	Methionine adenosyltransferase I, α
Nupr1	Rn.11182	Nucleoprotein 1	Mat1a	Rn.10418	Methionine adenosyltransferase I, α
Nupr1	Rn.11182	Nucleoprotein 1		Rn.128013	Unknown cDNA
The Chac1_ prediction	Rn.23367	ChaC, cation transfer instrumentality sample 1 (Escherichia coli) (prediction)		Rn.128013	Unknown cDNA
The Chac1_ prediction	Rn.23367		Slc7a3	Rn.9804	Solute carrier family 7 (cationic amino acid transporter, y+ system), the member 3
LOC312273	Rn.13006	Trypsase V-A	Slc7a3	Rn.9804
LOC312273	Rn.13006	Trypsase V-A		Rn.47821	The open gene seat
Ptger3	Rn.10361	Prostaglandin E receptor 3 (hypotype EP3)		Rn.47821	The open gene seat
Ptger3	Rn.10361	Prostaglandin E receptor 3 (hypotype EP3)	The RGD1562451_ prediction	Rn.199400	Be similar to Pabpc4_ predicted protein (prediction)
The RGD1566242_ prediction	Rn.24858	Be similar to RIKEN cDNA 1500009M05 (prediction)	The RGD1562451_ prediction	Rn.199400	Be similar to Pabpc4_ predicted protein (prediction)
The RGD1566242_ prediction	Rn.24858	Be similar to RIKEN cDNA 1500009M05 (prediction)	Cyp2d26	Rn.91355	Cytochrome P450, family 2, subfamily d, polypeptide 26
	Rn.17900	Be similar to aldehyde dehydrogenase 1 family, member L2	Cyp2d26	Rn.91355	Cytochrome P450, family 2, subfamily d, polypeptide 26
	Rn.17900	Be similar to aldehyde dehydrogenase 1 family, member L2	LOC286960	Rn.10387	The former IV of protrypsin
Gls2	Rn.10202	Glutaminase 2 (liver, mitochondria)	LOC286960	Rn.10387	The former IV of protrypsin
Gls2	Rn.10202	Glutaminase 2 (liver, mitochondria)	Nme2	Rn.927	In non-metastatic cell 2, express
	Rn.165714	The open gene seat	Nme2	Rn.927	In non-metastatic cell 2, express
	Rn.165714	The open gene seat	P2rx1	Rn.91176	Purinergic receptor P2X, part-gated ion channel, 1
Pdk4	Pn.30070	Pyruvic dehydrogenase kinase, isodynamic enzyme 4	P2rx1	Rn.91176	Purinergic receptor P2X, part-gated ion channel, 1
Pdk4	Pn.30070	Pyruvic dehydrogenase kinase, isodynamic enzyme 4	Amy1	Pn.116361	Diastase 1, saliva
Cbs	Pn.87853	CBS	Amy1	Pn.116361	Diastase 1, saliva
Cbs	Pn.87853	CBS	Mte1	Rn.37524	Chondriosome acyl-CoA thioesterase 1
Spink1	Rn.9767	Serpin, Kazal 1 type	Mte1	Rn.37524	Chondriosome acyl-CoA thioesterase 1
Spink1	Rn.9767	Serpin, Kazal 1 type	Gatm	Pn.17661	Glycine amidinotransferase (L-arginine: glycine amidinotransferase)

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	The Tmed6_ prediction	Rn.19837	Contain and stride 6 (predictions) of film emp24 protein transport domain
Tff2	Rn.34367	Trefoil factor 2 (spasmolysis albumen 1)	The Tmed6_ prediction	Rn.19837
Tff2	Rn.34367	Trefoil factor 2 (spasmolysis albumen 1)	Hsd17b13	Rn.25104	Hydroxy steroid (17-β) dehydrogenase 13
	Rn.11766	Be similar to LRRGT00012[Rattus norvegicus (Rattus norvegicus)]	Hsd17b13	Rn.25104	Hydroxy steroid (17-β) dehydrogenase 13
	Rn.11766		Gnmt	Rn.11142	Glycocoll N-transmethylase
Pah	Rn.1652	Phenylalanine hydroxylase	Gnmt	Rn.11142	Glycocoll N-transmethylase
Pah	Rn.1652	Phenylalanine hydroxylase	Serpini2	Rn.54500	Serine (or halfcystine) protease inhibitors, clade I, the member 2
RGD1309615	Rn.167687	Unknown cDNA	Serpini2	Rn.54500
RGD1309615	Rn.167687	Unknown cDNA	LOC691307	Rn.79735	Be similar to contain and be rich in leucine repetitive sequence 39 isoforms 2
Eprs	Rn.21240	Glutamy-prolyl-tRNA synthetase	LOC691307	Rn.79735
Eprs	Rn.21240	Glutamy-prolyl-tRNA synthetase	The Pck2_ prediction	Rn.35508	Phosphoenolpyruvic acid carboxyl kinases 2 (mitochondria) (prediction)
The Chd2_ prediction	Rn.162437	Enzyme dna is untwisted in conjunction with albumen 2 (prediction) in Crow not domain	The Pck2_ prediction	Rn.35508
The Chd2_ prediction	Rn.162437			Rn.53085	The open gene seat
	Rn.12530	The open gene seat		Rn.53085	The open gene seat
	Rn.12530	The open gene seat	NIPK	Rn.22325	Tribbles homologue 3 (Drosophila (Drosophila))
Slc30a2	Rn.11135	Solute carrier family 30 (zinc transport protein), the member 2	NIPK	Rn.22325	Tribbles homologue 3 (Drosophila (Drosophila))
Slc30a2	Rn.11135		Serpina10	Rn.10502	Serine (or halfcystine) peptidase inhibitors, clade A, the member 10
Cfi	Rn.7424	Complement factor I	Serpina10	Rn.10502
Cfi	Rn.7424	Complement factor I	Cckar	Rn.10184	The CCK A acceptor
LOC689755	Rn.151728	Infer albumen LOC689755	Cckar	Rn.10184	The CCK A acceptor
LOC689755	Rn.151728	Infer albumen LOC689755	Bhlhb8	Rn.9897	The category-B that contains bHLH domain, 8
Anpep	Rn.11132	Alanyl (film) aminopeptidase	Bhlhb8	Rn.9897	The category-B that contains bHLH domain, 8
Anpep	Rn.11132	Alanyl (film) aminopeptidase	Asns	Rn.11172	Asparagine synthetase
Slc7a5	Rn.32261	Solute carrier family 7 (cationic amino acid transporter, y+ system), the member 5	Asns	Rn.11172	Asparagine synthetase

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	The Usp43_ prediction	Rn.12678	Ubiquitin specific protease 43 (prediction)
Csnk1a1	Rn.23810	Casein kinase 1, α 1	The Usp43_ prediction	Rn.12678	Ubiquitin specific protease 43 (prediction)
Csnk1a1	Rn.23810	Casein kinase 1, α 1	The Pck2_ prediction	Rn.35508	Phosphoenolpyruvic acid carboxyl kinases 2 (mitochondria) (prediction)
Spink1	Rn.9767	Serpin, Kazal 1 type	The Pck2_ prediction	Rn.35508
Spink1	Rn.9767	Serpin, Kazal 1 type	Cml2	Rn.160578	Camello sample 2
Pabpc4	Rn.199602	The open gene seat	Cml2	Rn.160578	Camello sample 2
Pabpc4	Rn.199602	The open gene seat	Gjb2	Rn.198991	Gap junctional membrane channel protein β 2
Ngfg	Rn.11331	Nerve growth factor, γ	Gjb2	Rn.198991	Gap junctional membrane channel protein β 2
Ngfg	Rn.11331	Nerve growth factor, γ	The Clca2_ prediction	Rn.48629	The open gene seat
The RGD1565381_ prediction	Rn.16083	Be similar to RIKEN cDNA 1810033M07 (prediction)	The Clca2_ prediction	Rn.48629	The open gene seat
The RGD1565381_ prediction	Rn.16083	Be similar to RIKEN cDNA 1810033M07 (prediction)	Qscn6	Rn.44920	Quiescin Q6
The Cldn10_ prediction	Rn.99994	Close protein 10 (Claudin 10) (prediction)	Qscn6	Rn.44920	Quiescin Q6
The Cldn10_ prediction	Rn.99994	Close protein 10 (Claudin 10) (prediction)	Spink3	Rn.144683	Serpin, Kazal 3 types
LOC498174	Rn.163210	Be similar to NipSnap2 albumen (spongioblastoma extension increasing sequence)	Spink3	Rn.144683	Serpin, Kazal 3 types
LOC498174	Rn.163210			Rn.140163	Be similar to methionine-tRNA synzyme [Rattus norvegicus (Rattus norvegicus)]
Cyr61	Rn.22129	Be rich in the albumen 61 of halfcystine		Rn.140163
Cyr61	Rn.22129	Be rich in the albumen 61 of halfcystine	RGD1307736	Rn.162140	Be similar to and infer albumen KIAA0152
Ddit3	Rn.11183	DNA-damage induction type transcript 3	RGD1307736	Rn.162140	Be similar to and infer albumen KIAA0152
Ddit3	Rn.11183	DNA-damage induction type transcript 3	Reg1	Rn.11332	Regeneration pancreas islet derive 1
Eprs	Rn.21240	Glutamy-prolyl-tRNA synthetase	Reg1	Rn.11332	Regeneration pancreas islet derive 1
Eprs	Rn.21240	Glutamy-prolyl-tRNA synthetase	NIPK	Rn.22325	CDNA clone RPCAG663 ' end, the mRNA sequence.
Eif4b	Rn.95954	Eukaryotic translation initiation factor 4B	NIPK	Rn.22325	CDNA clone RPCAG663 ' end, the mRNA sequence.
Eif4b	Rn.95954	Eukaryotic translation initiation factor 4B	Spink1	Rn.9767	Serpin, Kazal 1 type
Rnase4	Rn.1742	Ribonuclease, RNA enzyme A family 4	Spink1	Rn.9767	Serpin, Kazal 1 type
Rnase4	Rn.1742	Ribonuclease, RNA enzyme A family 4	Cebpg	Rn.10332	CCAAT/ enhancer binding protein (C/EBP), γ
siat7D	Rn.195322	α-2,6-sialyltransferase ST6GalNAc IV	Cebpg	Rn.10332	CCAAT/ enhancer binding protein (C/EBP), γ
siat7D	Rn.195322	α-2,6-sialyltransferase ST6GalNAc IV	Herpud1	Rn.4028	The homocysteine induction type, ubiquitin spline structure territory member 1
		Unknown rat cdna	Herpud1	Rn.4028

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	Gcat	Rn.43940	Glycocoll C-acetyltransferase (2-amino-3-alpha-ketobutyric acid-CoA ligase)
The RGD1562860_ prediction	Rn.75246	Be similar to RIKEN cDNA 2310045A20 (prediction)	Gcat	Rn.43940
The RGD1562860_ prediction	Rn.75246	Be similar to RIKEN cDNA 2310045A20 (prediction)	The Hspa9a_ prediction	Rn.7535	Heat shock 70kD albumen 9A (prediction)
Dbt	Rn.198610	Dihydrolipoamide side chain acyltransferase E2	The Hspa9a_ prediction	Rn.7535	Heat shock 70kD albumen 9A (prediction)
Dbt	Rn.198610	Dihydrolipoamide side chain acyltransferase E2	Bspry	Rn.53996	Contain B-box and SPRY domain
Fut1	Rn.11382	Fucosyltransferase 1	Bspry	Rn.53996	Contain B-box and SPRY domain
Fut1	Rn.11382	Fucosyltransferase 1	Rpl3	Rn.107726	Ribosomal protein L 3
	Rn.22481	Be similar to NP 083620.1 acylphosphatase 2, muscularity [house mouse (Mus musculus)]	Rpl3	Rn.107726	Ribosomal protein L 3
	Rn.22481				Unknown rat cdna
Vldlr	Rn.9975	Very low density lipoprotein receptor			Unknown rat cdna
Vldlr	Rn.9975	Very low density lipoprotein receptor	The RGD1311937_ prediction	Rn.33652	Be similar to and infer albumen MGC17299 (prediction)
The RGD1563144_ prediction	Rn.14702	Be similar to EMeg32 albumen (prediction)	The RGD1311937_ prediction	Rn.33652	Be similar to and infer albumen MGC17299 (prediction)
The RGD1563144_ prediction	Rn.14702	Be similar to EMeg32 albumen (prediction)		Rn.43268	The open gene seat
pre-mtHSP70	Rn.7535	70kD heat shock protein precursor;		Rn.43268	The open gene seat
pre-mtHSP70	Rn.7535	70kD heat shock protein precursor;	Ddah1	Rn.7398	Diethylarginine dimethylamino hydrolytic enzyme 1
RGD1307736	Rn.162140	Be similar to and infer albumen KIAA0152	Ddah1	Rn.7398	Diethylarginine dimethylamino hydrolytic enzyme 1
RGD1307736	Rn.162140	Be similar to and infer albumen KIAA0152	RAMP4	Rn.2119	Ribosomes related membrane protein 4
Ptger3	Rn.10361	Prostaglandin E receptor 3 (hypotype EP3)	RAMP4	Rn.2119	Ribosomes related membrane protein 4
Ptger3	Rn.10361	Prostaglandin E receptor 3 (hypotype EP3)		Rn.169405	The open gene seat
The Ccbe1_ prediction	Rn.199045	Collagen and calcium are in conjunction with EGF domain 1 (prediction)		Rn.169405	The open gene seat
The Ccbe1_ prediction	Rn.199045		Dnajc3	Rn.162234	DnaJ (Hsp40) homologue, subfamily C, the member 3
Mtac2d1	Rn.43919	Contain film target (series connection) C2 domain 1	Dnajc3	Rn.162234	DnaJ (Hsp40) homologue, subfamily C, the member 3

Table 12: down-regulated gene (transcript altogether=36)

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	The RGD1563461_ prediction	Rn.199308	The open gene seat
Gimap4	Rn.198155	The GTP enzyme, IMAP family member 4	The RGD1563461_ prediction	Rn.199308	The open gene seat
Gimap4	Rn.198155	The GTP enzyme, IMAP family member 4	S100b	Rn.8937	S100 albumen, beta polypeptides
The Klf2_ prediction	Rn.92653	Kruppel like factor 2 (lung) (prediction)	S100b	Rn.8937	S100 albumen, beta polypeptides

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	The RGD1309561_ prediction	Rn.102005	Be similar to and infer albumen FLJ31951 (prediction)
NAP22	Rn.163581	The open gene seat	The RGD1309561_ prediction	Rn.102005	Be similar to and infer albumen FLJ31951 (prediction)
NAP22	Rn.163581	The open gene seat	The Sfrs3_ prediction	Rn.9002	Splicing factor is rich in arginine/serine-3 (SRp20) (prediction)
	Rn.6731	The open gene seat	The Sfrs3_ prediction	Rn.9002
	Rn.6731	The open gene seat	Cd53	Rn.31988	CD53 antigen
The RGD1561419_ prediction	Rn.131539	Be similar to RIKEN cDNA 6030405P05 gene (prediction)	Cd53	Rn.31988	CD53 antigen
The RGD1561419_ prediction	Rn.131539	Be similar to RIKEN cDNA 6030405P05 gene (prediction)	Il2rg	Rn.14508	The interleukin-22 acceptor, γ
LOC361346	Rn.31250	Be similar to chromosome 18 open read frames 54	Il2rg	Rn.14508	The interleukin-22 acceptor, γ
LOC361346	Rn.31250	Be similar to chromosome 18 open read frames 54	Cd38	Rn.11414	CD38 antigen
The Klf2_ prediction	Rn.92653	Kruppel like factor 2 (lung) (prediction)	Cd38	Rn.11414	CD38 antigen
The Klf2_ prediction	Rn.92653	Kruppel like factor 2 (lung) (prediction)	The Plac8_ prediction	Rn.2649	Placenta specificity 8 (prediction)
LOC498335	Rn.6917	Be similar to little inducing cell factor B 13 precursors (CXCL13)	The Plac8_ prediction	Rn.2649	Placenta specificity 8 (prediction)
LOC498335	Rn.6917		Igfbp3	Rn.26369	Insulin-like growth factor binding protein 3
Ptprc	Rn.90166	Protein-tyrosine-phosphatase, receptor type, C	Igfbp3	Rn.26369	Insulin-like growth factor binding protein 3
Ptprc	Rn.90166	Protein-tyrosine-phosphatase, receptor type, C	RT1-Aw2	Rn.40130	The RT1Ib class, locus Aw2
Rac2	Rn.2863	The RAS C3 clostridium botulinum substrate 2 of being correlated with	RT1-Aw2	Rn.40130	The RT1Ib class, locus Aw2
Rac2	Rn.2863			Rn.9461	The open gene seat
Fos	Rn.103750	FBJ mouse osteosarcoma virus oncogene homologue		Rn.9461	The open gene seat
Fos	Rn.103750	FBJ mouse osteosarcoma virus oncogene homologue	Arhgdib	Rn.15842	Rho, GDP inhibitor (GDI) β that dissociates
Sgne1	Rn.6173	Secretory granules neuroendocrine albumen 1	Arhgdib	Rn.15842	Rho, GDP inhibitor (GDI) β that dissociates
Sgne1	Rn.6173	Secretory granules neuroendocrine albumen 1	Lck_ maps	Rn.22791	Lymphocyte protein tyrosine kinase (mapping)
Fcgr2b	Rn.33323	The Fc acceptor, IgG, low-affinity IIb	Lck_ maps	Rn.22791	Lymphocyte protein tyrosine kinase (mapping)
Fcgr2b	Rn.33323	The Fc acceptor, IgG, low-affinity IIb	Slfn8	Rn.137139	Schlafen 8
Rab8b	Rn.10995	RAB8B, member RAS oncogene family	Slfn8	Rn.137139	Schlafen 8
Rab8b	Rn.10995	RAB8B, member RAS oncogene family		Rn.4287	Unknown cDNA
RGD1306939	Rn.95357	Be similar to mKIAA0386 albumen		Rn.4287	Unknown cDNA
RGD1306939	Rn.95357	Be similar to mKIAA0386 albumen	The Tnfrsf26_ prediction	Rn.162508	The Tumor Necrosis Factor Receptors subfamily, member 26 (prediction)
The Ythdf2_ prediction	Rn.21737	YTH domain family 2 (prediction)	The Tnfrsf26_ prediction	Rn.162508
The Ythdf2_ prediction	Rn.21737	YTH domain family 2 (prediction)	RGD1359202	Rn.10956	Be similar to heavy chain immunoglobulin 6 (Igh-6)

Adopted name	UniGene	Describe
Adopted name	UniGene	Describe	The RGD1562855_ prediction	Rn.117926	Be similar to Ig κ chain (prediction)
Igha_ maps	Rn.109625	Heavy chain immunoglobulin (α polypeptide) (mapping)	The RGD1562855_ prediction	Rn.117926	Be similar to Ig κ chain (prediction)
Igha_ maps	Rn.109625	Heavy chain immunoglobulin (α polypeptide) (mapping)	Ccl21b	Rn.39658	Chemotactic factor (CF) (C-C motif) part 21b (serine)

Gene tree gene cluster analysis shown in Figure 22 A shows 12,729 genes that all exist in all 6 samples.As mentioned above, 820 genes demonstrate 2 times change on expressing, and 137 genes demonstrate 3 times of changes on expressing, and gene tree represents to see Figure 22 B.In demonstrating 137 genes of 3 times of changes, according to maximum comparability between the interior gene of group, the K-mean cluster analysis further is divided into 5 groups (Figure 21 C) with these 137 genes.These 5 groups are called " Up-1 ", " Up-2 ", " Up-3 ", " Up-4 " and " Up-5 ", are summarized in following table 13-17.

Table 13:Up-1

Total gene: 91		Multiple
Total gene: 91		Multiple	Adopted name	Describe	Change
Reg3a	Regeneration pancreas islet 3 α that derive	75.08	Adopted name	Describe	Change
Reg3a	Regeneration pancreas islet 3 α that derive	75.08	LOC680945	Be similar to stroma cell derivative factor 2 samples 1	32.31
Pap	Pancreatitis associated protein	19.53	LOC680945	Be similar to stroma cell derivative factor 2 samples 1	32.31
Pap	Pancreatitis associated protein	19.53	Ptf1a	The pancreas idiosyncratic transcription factor, 1a	11.59
Mat1a	Methionine adenosyltransferase I, α	8.67	Ptf1a	The pancreas idiosyncratic transcription factor, 1a	11.59
Mat1a	Methionine adenosyltransferase I, α	8.67	Nupr1	Nucleoprotein	1	7.53
	Unknown cDNA	7.52	Nupr1	Nucleoprotein	1	7.53
	Unknown cDNA	7.52	The Chac1_ prediction	ChaC, cation transfer instrumentality sample 1 (Escherichia coli) (prediction)	7.41
Slc7a3	Solute carrier family 7 (cationic amino acid transporter albumen, y+ system), the member 3	6.68	The Chac1_ prediction		7.41
Slc7a3		6.68	LOC312273	Trypsase V-A	6.38
	The open gene seat	6.08	LOC312273	Trypsase V-A	6.38
	The open gene seat	6.08	Ptger3	Prostaglandin E receptor 3 (hypotype EP3)	6.01
The RGD1562451_ prediction	Be similar to Pabpc4_ predicted protein (prediction)	5.88	Ptger3	Prostaglandin E receptor 3 (hypotype EP3)	6.01
The RGD1562451_ prediction	Be similar to Pabpc4_ predicted protein (prediction)	5.88	The RGD1566242_ prediction	Be similar to RIKEN cDNA 1500009M05 (prediction)	5.62
Cyp2d26	Cytochrome P450, family 2, subfamily d, polypeptide 26	5.59	The RGD1566242_ prediction	Be similar to RIKEN cDNA 1500009M05 (prediction)	5.62

	Be similar to aldehyde dehydrogenase 1 family, member L2[domesticated dog (Canis familiaris)]	5.37
		5.37	LOC286960	The former IV of protrypsin	5.19
Gls2	Glutaminase 2 (liver, mitochondria)	5.10	LOC286960	The former IV of protrypsin	5.19

Table 14:Up-2

Total gene: 91		Multiple
Total gene: 91		Multiple	Adopted name	Describe	Change
	The open gene seat	4.92	Adopted name	Describe	Change
	The open gene seat	4.92	P2rx1	Purinergic receptor P2X, part-gated ion channel, 1	4.85
Pdk4	Pyruvic dehydrogenase kinase, isodynamic enzyme 4	4.72	P2rx1	Purinergic receptor P2X, part-gated ion channel, 1	4.85
Pdk4	Pyruvic dehydrogenase kinase, isodynamic enzyme 4	4.72	Amy1	Diastase	1, saliva	4.70
Cbs	CBS	4.67	Amy1	Diastase	1, saliva	4.70
Cbs	CBS	4.67	Mte1	Chondriosome acyl-CoA thioesterase 1	4.49
Spink1	Serpin, Kazal 1 type	4.43	Mte1	Chondriosome acyl-CoA thioesterase 1	4.49
Spink1	Serpin, Kazal 1 type	4.43	Gatm	Glycine amidinotransferase (L-arginine: glycine amidinotransferase)	4.40
The Tmed6_ prediction	Contain and stride 6 (predictions) of film emp24 protein transport domain	4.38	Gatm		4.40
The Tmed6_ prediction		4.38	Tff2	Trefoil factor 2 (spasmolysis albumen 1)	4.36
Hsd17b13	Hydroxy steroid (17-β) dehydrogenase 13	4.34	Tff2	Trefoil factor 2 (spasmolysis albumen 1)	4.36
Hsd17b13	Hydroxy steroid (17-β) dehydrogenase 13	4.34		Be similar to the LRRGT00012[Rattus norvegicus]	4.30
Gnmt	Glycocoll N-transmethylase	4.30		Be similar to the LRRGT00012[Rattus norvegicus]	4.30
Gnmt	Glycocoll N-transmethylase	4.30	Pah	Phenylalanine hydroxylase	4.29
Serpini2	Serine (or halfcystine) protease inhibitors, clade I, the member 2	4.28	Pah	Phenylalanine hydroxylase	4.29
Serpini2		4.28	RGD1309615	Unknown cDNA	4.16
LOC691307	Be similar to contain and be rich in leucine repetitive sequence 39 isoforms 2	4.12	RGD1309615	Unknown cDNA	4.16
LOC691307		4.12	Eprs	Glutamy-prolyl-tRNA synthetase	4.03
The Pck2_ prediction	Phosphoenolpyruvic acid carboxyl kinases 2 (mitochondria) (prediction)	4.01	Eprs	Glutamy-prolyl-tRNA synthetase	4.03

Table 15:Up-3

Total gene: 91		Multiple
Total gene: 91		Multiple	Adopted name	Describe	Change
	The open gene seat	3.97	Adopted name	Describe	Change
	The open gene seat	3.97		The open gene seat	3.96
Slc30a2	Solute carrier family 30 (zinc transport protein), the member 2	3.77		The open gene seat	3.96
Slc30a2		3.77	Serpina10	Serine (or halfcystine) peptidase inhibitors, clade A, the member 10	3.77
Cfi	Complement factor I	3.69	Serpina10		3.77

Cckar	The CCK A acceptor	3.68
Cckar	The CCK A acceptor	3.68	LOC689755	Infer albumen LOC689755	3.68
Bhlhb8	Contain bHLH domain, category-B, 8	3.66	LOC689755	Infer albumen LOC689755	3.68
Bhlhb8	Contain bHLH domain, category-B, 8	3.66	Anpep	Alanyl (film) aminopeptidase	3.65
Asns	Asparagine synthetase	3.65	Anpep	Alanyl (film) aminopeptidase	3.65
Asns	Asparagine synthetase	3.65	The Usp43_ prediction	Ubiquitin specific protease 43 (prediction)	3.62
Slc7a5	Solute carrier family 7 (cationic amino acid transporter albumen, y+ system), the member 5	3.62	The Usp43_ prediction	Ubiquitin specific protease 43 (prediction)	3.62
Slc7a5		3.62	Csnk1a1	Casein kinase	1, α 1	3.58
Cml2	Camello sample	2	Csnk1a1	Casein kinase	1, α 1	3.58	3.51
Cml2	Camello sample	2	Pabpc4	The open gene seat	3.50		3.51
Gjb2	Gap junctional membrane channel protein β 2	3.49	Pabpc4	The open gene seat	3.50
Gjb2	Gap junctional membrane channel protein β 2	3.49	Ngfg	Nerve growth factor, γ	3.47
The Clca2_ prediction	The open gene seat	3.46	Ngfg	Nerve growth factor, γ	3.47
The Clca2_ prediction	The open gene seat	3.46	The RGD1565381_ prediction	Be similar to RIKEN cDNA 1810033M07 (prediction)	3.42
Qscn6	Quiescin Q6	3.41	The RGD1565381_ prediction	Be similar to RIKEN cDNA 1810033M07 (prediction)	3.42

Table 16:Up-4

Total gene: 91		Multiple
Total gene: 91		Multiple	Adopted name	Describe	Change
The Cldn10_ prediction	Close protein 10 (Claudin 10) (prediction)	3.40	Adopted name	Describe	Change
The Cldn10_ prediction	Close protein 10 (Claudin 10) (prediction)	3.40	Spink3	Serpin, Kazal 3 types	3.38
LOC498174	Be similar to NipSnap2 albumen (spongioblastoma extension increasing sequence)	3.36	Spink3	Serpin, Kazal 3 types	3.38
LOC498174		3.36		Be similar to methionine-tRNA synzyme [Rattus norvegicus]	3.35
Cyr61	Be rich in cysteine protein 61	3.33		Be similar to methionine-tRNA synzyme [Rattus norvegicus]	3.35
Cyr61	Be rich in cysteine protein 61	3.33	RGD1307736	Be similar to and infer albumen KIAA0152	3.32
Ddit3	DNA-damage inducible transcription thing 3	3.32	RGD1307736	Be similar to and infer albumen KIAA0152	3.32
Ddit3	DNA-damage inducible transcription thing 3	3.32	Reg1	The regeneration pancreas islet derives 1	3.22
NIPK	Unknown cDNA	3.19	Reg1	The regeneration pancreas islet derives 1	3.22
NIPK	Unknown cDNA	3.19	Eif4b	Eukaryotic translation initiation factor 4B	3.17
Rnase4	Ribonuclease, RNA enzyme A family 4	3.16	Eif4b	Eukaryotic translation initiation factor 4B	3.17
Rnase4	Ribonuclease, RNA enzyme A family 4	3.16	Cebpg	CCAAT/ enhancer binding protein (C/EBP), γ	3.16
siat7D	α-2,6-sialyltransferase ST6GalNAc IV	3.15	Cebpg	CCAAT/ enhancer binding protein (C/EBP), γ	3.16
siat7D	α-2,6-sialyltransferase ST6GalNAc IV	3.15	Herpud1	The homocysteine induction type, ubiquitin spline structure territory member 1	3.15
Gcat	Glycocoll C-transacetylase (2-amino-3-alpha-ketobutyric acid-CoA ligase)	3.13	Herpud1		3.15

The RGD1562860_ prediction	Be similar to RIKEN cDNA 2310045A20 (prediction)	3.11
The RGD1562860_ prediction	Be similar to RIKEN cDNA 2310045A20 (prediction)	3.11	The Hspa9a_ prediction	Heat shock 70kDa albumen 9A (prediction)	3.10
Dbt	Dihydrolipoamide side chain acyltransferase E2	3.10	The Hspa9a_ prediction	Heat shock 70kDa albumen 9A (prediction)	3.10
Dbt	Dihydrolipoamide side chain acyltransferase E2	3.10	Bspry	Contain B-box and SPRY domain	3.10

Table 17:Up-5

Total gene: 91		Multiple
Total gene: 91		Multiple	Adopted name	Describe	Change
Fut1	Fucosyltransferase		Adopted name	Describe	Change
Fut1	Fucosyltransferase	1	3.09
Rpl3	Ribosomal protein L 3	1	3.09	3.08
Rpl3	Ribosomal protein L 3		Be similar to NP 083620.1 acylphosphatase 2 strongly, muscularity [house mouse]	3.08	3.08
Vldlr	Very low density lipoprotein receptor			3.07	3.08
Vldlr	Very low density lipoprotein receptor	The RGD1311937_ prediction	Be similar to and infer albumen MGC17299 (prediction)	3.07	3.04
The RGD1563144_ prediction	Be similar to EMeg32 albumen (prediction)	The RGD1311937_ prediction	Be similar to and infer albumen MGC17299 (prediction)	3.04	3.04
The RGD1563144_ prediction	Be similar to EMeg32 albumen (prediction)		The open gene seat	3.04	3.04
Ddah1	Diethylarginine dimethylamino base hydrolase 1		The open gene seat	3.03	3.04
Ddah1	Diethylarginine dimethylamino base hydrolase 1	RAMP4	Ribosomes related membrane protein 4	3.03	3.01
	The open gene seat	RAMP4	Ribosomes related membrane protein 4	3.01	3.01
	The open gene seat	The Ccbe1_ prediction	Collagen and calcium are in conjunction with EGF domain 1 (prediction)	3.01	3.01
Dnajc3	DnaJ (Hsp40) homologue, subfamily C, the member 3	The Ccbe1_ prediction		3.00	3.01
Dnajc3	DnaJ (Hsp40) homologue, subfamily C, the member 3	Mtac2d1	Contain film target practice (series connection) C2 domain 1	3.00	3.00

The gene of finding of reducing is analyzed in 2 additional set (being called " Down-1 " and " Down-2 ") representative in Cohen diabetes rat sample through GeneSpring GX.The result who obtains in following table 18 and table 19 general introduction " Down-1 " and " Down-2 " group.

Table 18:Down-1

Total gene: 35 genes		Multiple
Total gene: 35 genes		Multiple	Adopted name	Describe	Change
Ccl21b	Chemotactic factor (CF) (C-C motif) part 21b (serine)	11.33	Adopted name	Describe	Change
Ccl21b	Chemotactic factor (CF) (C-C motif) part 21b (serine)	11.33	Igha_ maps	Heavy chain immunoglobulin (α polypeptide) (mapping)	7.63
The RGD1562855_ prediction	Be similar to Ig κ chain (prediction)	4.98	Igha_ maps	Heavy chain immunoglobulin (α polypeptide) (mapping)	7.63
The RGD1562855_ prediction	Be similar to Ig κ chain (prediction)	4.98	RGD1359202	Be similar to heavy chain immunoglobulin 6 (Igh-6)	4.78
The Ythdf2_ prediction	YTH domain family 2 (prediction)	4.63	RGD1359202	Be similar to heavy chain immunoglobulin 6 (Igh-6)	4.78
The Ythdf2_ prediction	YTH domain family 2 (prediction)	4.63	The Tnfrsf26_ prediction	Tumor necrosis factor receptor super family, member 26 (prediction)	4.37
RGD1306939	Be similar to mKIAA0386 albumen	4.33	The Tnfrsf26_ prediction		4.37
RGD1306939	Be similar to mKIAA0386 albumen	4.33		Unknown cDNA	4.24
Rab8b	RAB8B, member RAS oncogene family	4.10		Unknown cDNA	4.24
Rab8b	RAB8B, member RAS oncogene family	4.10	Slfn8	Schlafen	8	3.91
Fcgr2b	The Fc acceptor, IgG, low compatibility IIb	3.79	Slfn8	Schlafen	8	3.91
Fcgr2b	The Fc acceptor, IgG, low compatibility IIb	3.79	Lck_ maps	Lymphocyte protein tyrosine kinase (mapping)	3.66
Sgne1	Secretory granules neuroendocrine albumen 1	3.56	Lck_ maps	Lymphocyte protein tyrosine kinase (mapping)	3.66
Sgne1	Secretory granules neuroendocrine albumen 1	3.56	Fos	FBJ mouse osteosarcoma virus oncogene homologue	3.55
Arhgdib	Rho, GDP inhibitor (GDI) β that dissociates	3.55	Fos	FBJ mouse osteosarcoma virus oncogene homologue	3.55
Arhgdib	Rho, GDP inhibitor (GDI) β that dissociates	3.55		The open gene seat	3.51
Rac2	The RAS C3 clostridium botulinum substrate 2 of being correlated with	3.42		The open gene seat	3.51

Table 19:Down-2

Total gene: 35 genes		Multiple
Total gene: 35 genes		Multiple	Adopted name	Describe	Change
RT1-Aw2	The RT1Ib class, locus Aw2	3.39	Adopted name	Describe	Change
RT1-Aw2	The RT1Ib class, locus Aw2	3.39	Ptprc	Protein-tyrosine-phosphatase, receptor type, C	3.39
Igfbp3	Insulin-like growth factor binding protein 3	3.37	Ptprc	Protein-tyrosine-phosphatase, receptor type, C	3.39
Igfbp3	Insulin-like growth factor binding protein 3	3.37	LOC498335	Be similar to little induction type cell factor B13 precursor (CXCL13)	3.27
The Plac8_ prediction	Placenta specificity 8 (prediction)	3.25	LOC498335		3.27
The Plac8_ prediction	Placenta specificity 8 (prediction)	3.25	Cd38	CD38 antigen	3.24
LOC361346	Be similar to chromosome 18 open reading frame 54	3.24	Cd38	CD38 antigen	3.24
LOC361346	Be similar to chromosome 18 open reading frame 54	3.24	The RGD1561419_ prediction	Be similar to RIKEN cDNA 6030405P05 gene (prediction)	3.19
Il2rg	The interleukin-22 acceptor, γ (Reconstruction in Sever Combined Immunodeciency)	3.19	The RGD1561419_ prediction	Be similar to RIKEN cDNA 6030405P05 gene (prediction)	3.19

Cd53	CD53 antigen	3.18
Cd53	CD53 antigen	3.18		The open gene seat	3.16
The Sfrs3_ prediction	Splicing factor is rich in arginine/serine 3 (SRp20) (prediction)	3.15		The open gene seat	3.16
The Sfrs3_ prediction		3.15	The RGD1309561_ prediction	Be similar to and infer albumen FLJ31951 (prediction)	3.13
NAP22	The open gene seat	3.13	The RGD1309561_ prediction	Be similar to and infer albumen FLJ31951 (prediction)	3.13
NAP22	The open gene seat	3.13	The Klf2_ prediction	Kruppel like factor 2 (lung) (prediction)	3.11
S100b	S100 albumen, beta polypeptides	3.08	The Klf2_ prediction	Kruppel like factor 2 (lung) (prediction)	3.11
S100b	S100 albumen, beta polypeptides	3.08	Gimap4	The GTP enzyme, IMAP family member 4	3.07
The RGD1563461_ prediction	The open gene seat	3.07	Gimap4	The GTP enzyme, IMAP family member 4	3.07

Finally, adopt quantitative RT-PCR,, confirm the gene expression analysis that obtains through microarray according to standard method.Following table provides the general introduction of the target gene of identifying through microarray analysis, and the multiple change on it is expressed confirms with Q-RT-PCR.

Table 20: to the quantitative RT-PCR analysis of selected gene

				Downward modulation	ABI， $
				Downward modulation	ABI， $	Adopted name	Genbank	UniGene	Describe	Multiple changes
Ccl21b	BI282920	Rn.39658	Chemotactic factor (CF) (C-C motif) part 21b (serine)	11.33	250	Adopted name	Genbank	UniGene	Describe	Multiple changes
Ccl21b	BI282920	Rn.39658	Chemotactic factor (CF) (C-C motif) part 21b (serine)	11.33	250	The Tnfrsf26_ prediction	BE098317	Rn.162508	Tumor necrosis factor receptor super family, member 26 (prediction)	4.37	250
Igfbp3	NM_012588	Rn.26369	Insulin-like growth factor binding protein 3	3.37	150	The Tnfrsf26_ prediction	BE098317	Rn.162508		4.37	250
Igfbp3	NM_012588	Rn.26369	Insulin-like growth factor binding protein 3	3.37	150	Il2rg	AI178808	Rn.14508	The interleukin-22 acceptor, γ (Reconstruction in Sever Combined Immunodeciency)	3.19	250
						Il2rg	AI178808	Rn.14508		3.19	250
										Raise
Adopted name	Genbank	UniGene	Describe	Multiple changes						Raise
Adopted name	Genbank	UniGene	Describe	Multiple changes		Reg3a	L10229	Rn.11222	Regeneration pancreas islet 3 α that derive	75.08	250
LOC680945	BI275923	Rn.1414	Be similar to stroma cell derivative factor 2 samples 1	32.31	250	Reg3a	L10229	Rn.11222	Regeneration pancreas islet 3 α that derive	75.08	250
LOC680945	BI275923	Rn.1414	Be similar to stroma cell derivative factor 2 samples 1	32.31	250	Ptf1a	NM_053964	Rn.10536	The pancreas idiosyncratic transcription factor, 1a	11.59	150
LOC312273	AI178581	Rn.13006	Trypsase V-A	6.38	250	Ptf1a	NM_053964	Rn.10536	The pancreas idiosyncratic transcription factor, 1a	11.59	150
LOC312273	AI178581	Rn.13006	Trypsase V-A	6.38	250	LOC286960	X15679	Rn.10387	The former IV of protrypsin	5.19	250
Spink1	NM_012674	Rn.9767	Serpin, Kazal 1 type	4.43	150	LOC286960	X15679	Rn.10387	The former IV of protrypsin	5.19	250

Serpini2	NM_133612	Rn.54500	Serine (or halfcystine) protease inhibitors, clade I, the member 2	4.28	250
Serpini2	NM_133612	Rn.54500		4.28	250	Serpina10	NM_133617	Rn.10502	Serine (or halfcystine) peptidase inhibitors, clade A, the member 10	3.77	250
Spink3	M27883	Rn.144683	Serpin, Kazal 3 types	3.38	150	Serpina10	NM_133617	Rn.10502		3.77	250
Spink3	M27883	Rn.144683	Serpin, Kazal 3 types	3.38	150	Reg1	NM_012641	Rn.11332	The regeneration pancreas islet derives 1	3.22	250
Eif4b	BI278814	Rn.95954	Eukaryotic translation initiation factor 4B	3.17	250	Reg1	NM_012641	Rn.11332	The regeneration pancreas islet derives 1	3.22	250
Eif4b	BI278814	Rn.95954	Eukaryotic translation initiation factor 4B	3.17	250	Rpl3	BG057530	Rn.107726	Ribosomal protein L 3	3.08	250
RAMP4	AI103695	Rn.2119	Ribosomes related membrane protein 4	3.01	250	Rpl3	BG057530	Rn.107726	Ribosomal protein L 3	3.08	250
RAMP4	AI103695	Rn.2119	Ribosomes related membrane protein 4	3.01	250
The rat contrast	4352338E		GAPDH									450
The rat contrast	4352338E		GAPDH				4352340E		ACTIN，β		450	450
					4750		4352340E		ACTIN，β		450

Protein by the CD53 gene code is to stride film 4 superfamilies (being also referred to as tetraspanin family) member.Great majority among these members are to be the cell surface protein of feature there to be 4 hydrophobic structure territories.This protein mediated signal transduction incident that in regulating cell development, activation, growth and motion, works.This encoded protein matter is the known cell surface glycoprotein that associates with integrin.It helps CD2 to produce the transduction of signal in T cell and natural killer cell, and thinks and work in growth regulating.It is relevant with the immunodeficiency of the recurrent infection disease association that is caused by bacterium, fungi and virus that the familial of this gene lacks.Alternative splicing produces the multiple transcript variant of coding same protein.CD38 is a kind of new multi-functional ectoenzyme of wide expression in cell and tissue (especially lymphocyte).CD38 also works in cell adhesion, signal transduction and calcium signal transduction.

Although should be known in conjunction with detailed Description Of The Invention and introduced the present invention, foregoing description all is in order to illustrate rather than limit the scope of the invention that scope defined by appended claims.Others, advantage and modification all fall within the scope of appended claims.

Claims

1. diagnose or evaluation patient's the diabetes B or the method for prediabetes illness for one kind, described method comprises:

A. measure the effective dose of one or more DBMARKERS in described patient's sample or its metabolin; With

B. described amount and reference value are compared, wherein for described reference value, one or more DBMARKERS content raise or reduce and show that described patient suffers from diabetes B or prediabetes illness.

2. the method for claim 1, wherein said reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from the experimenter's who does not suffer from diabetes B or prediabetes illness numerical value, or from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness numerical value.

3. the process of claim 1 wherein that described reduction is to hang down 10% at least than described reference value.

4. the process of claim 1 wherein that described rising is than described reference value high at least 10%.

5. the process of claim 1 wherein that described sample is urine, serum, blood plasma, haemocyte, endothelial cell, biopsy sample, pancreatic juice, ascites, marrow, interstitial fluid, tear, phlegm or saliva.

6. the process of claim 1 wherein that described DBMARKER detects by the following method: electrophoresis, immunochemistry, proteomic techniques or genome analysis.

7. the method for claim 6, wherein said immunochemistry detect and comprise radiommunoassay, immunoprecipitation, Western blotting, immunofluorescence assay or enzyme linked immunosorbent assay (ELISA).

8. the method for claim 6, wherein said proteomic techniques comprises SELDI, MALDI, LC/MS, series LC/MS/MS, proteins/peptides array or antibody array.

9. the method for claim 6, wherein said genome analysis comprises PCR (PCR), PCR in real time, microarray analysis, RNA trace or southern blotting technique.

10. the process of claim 1 wherein that described patient before be not diagnosed as diabetes B or prediabetes illness.

11. the process of claim 1 wherein that described patient before had been diagnosed as diabetes B or prediabetes illness.

12. the process of claim 1 wherein that described patient is the asymptomatic patient of diabetes B or prediabetes illness.

13. a method that is used to monitor the process of patient's diabetes B or prediabetes illness, described method comprises:

A. the effective dose of one or more DBMARKERS in described patient's first sample of very first time period measurement;

B. measure the effective dose of one or more DBMARKERS in described patient's second sample in second time cycle; With

C. the content of one or more DBMARKERS that step (a) is measured and step (b) survey content or reference value compares.

14. the method for claim 13, wherein said patient had before accepted diabetes B or prediabetes treatment of conditions.

15. the method for claim 13, wherein first sample picks up from and accepts diabetes B or prediabetes treatment for diseases described patient before.

16. the method for claim 13, wherein second sample picks up from and accepts diabetes B or prediabetes treatment for diseases described patient afterwards.

17. each method among the claim 14-16, wherein said diabetes B or prediabetes treatment of conditions comprise workout scheme, meal supplement, surgical intervention, diabetes adjusting medicine or its combination.

18. the method for claim 13, wherein said process also can be monitored by the variation that detects following index: body mass index (BMI), insulin level, blood glucose level, HDL level, systolic pressure and/or diastolic pressure or its combination.

19. the method for claim 13, wherein said sample are urine, serum, blood plasma, haemocyte, endothelial cell, biopsy sample, pancreatic juice, ascites, marrow, interstitial fluid, tear, phlegm or saliva.

20. the method for claim 13, wherein said reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from the experimenter's who does not suffer from diabetes B or prediabetes illness numerical value, or from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness numerical value.

21. one kind is used to monitor patient's the diabetes B or the method for prediabetes treatment for diseases scheme validity, described method comprises:

A. before treatment diabetes B or prediabetes illness, measure the effective dose of one or more DBMARKERS in described patient's first sample;

B. after treatment diabetes B or prediabetes illness, measure the effective dose of one or more DBMARKERS in described patient's second sample; With

22. the method for claim 21, wherein said diabetes B or prediabetes treatment of conditions scheme comprise workout scheme, meal supplement, surgical intervention, diabetes adjusting medicine or its combination.

23. the method for claim 21, wherein said validity also can be monitored by the variation that detects following index: body mass index (BMI), insulin level, blood glucose level, HDL level, systolic pressure and/or diastolic pressure or its combination.

24. the method for claim 23, the variation of wherein said blood glucose level is measured by oral glucose tolerance test.

25. the method for claim 21, wherein said sample are urine, serum, blood plasma, haemocyte, endothelial cell, biopsy sample, pancreatic juice, ascites, marrow, interstitial fluid, tear, phlegm or saliva.

26. the method for claim 21, wherein said patient had before accepted diabetes B or prediabetes treatment of conditions.

27. the method for claim 21, wherein said reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from the experimenter's who does not suffer from diabetes B or prediabetes illness numerical value, or from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness numerical value.

28. a treatment is after diagnosing or identify the patient's who suffers from diabetes B or prediabetes illness method, described method comprises:

A. the effective dose of one or more DBMARKERS that in described patient's first sample of very first time period measurement, exist; With

B. regulate medicine with one or more diabetes and treat described patient, amount up to one or more DBMARKERS or its metabolin is got back to reference value, described reference value is the value of measuring in being in one or more patients of developing in diabetes B or the low danger of prediabetes illness, or the value of measuring among the one or more patients that make moderate progress on the risk of diabetes factor as regulating the result of medicines treatment with one or more diabetes.

29. the method for claim 28, wherein said one or more diabetes are regulated cartridge bag and are drawn together sulfonylurea, biguanides, insulin, insulin analog, peroxisome proliferation-activated receptors-γ (PPAR-γ) activator, double action PPAR activator, insulin secretagogue, glucagon-like peptide-1 (GLP-1) analog, inhibitors of dipeptidyl IV, pancreatic lipase inhibitor, alpha-glucosidase restrainer or its combination.

30. the method for claim 28 wherein saidly comprises body mass index (BMI) reductions, the reduction of blood glucose level, insulin level rising, the rising of HDL level, systolic pressure and/or diastolic pressure reduction or its combination as the improvement of regulating the risk of diabetes factor of medicine treatment results with one or more diabetes.

31. a method that is used to after diagnosing or identifies the patient who suffers from diabetes B or prediabetes illness to select therapeutic scheme, described method comprises:

32. the method for claim 31, wherein said patient suffers from diabetes B or prediabetes illness.

33. the method for claim 31, wherein said patient had before accepted diabetes B or prediabetes treatment of conditions.

34. the method for claim 31, wherein said patient had not before diagnosed or identified suffers from diabetes B or prediabetes illness.

35. picking up from, the method for claim 31, wherein said first sample accept diabetes B or prediabetes treatment for diseases described patient before.

36. picking up from, the method for claim 31, wherein said second sample accept diabetes B or prediabetes treatment for diseases described patient afterwards.

37. the method for claim 31, wherein said diabetes B or prediabetes treatment of conditions comprise workout scheme, meal supplement, surgical intervention, diabetes adjusting medicine or its combination.

One or more patients that the risk of diabetes factor makes moderate progress after one or more treatments of diabetes B or prediabetes illness 38. the method for claim 31, wherein said reference value are hung oneself.

39. the method for claim 38, the improvement of the wherein said risk of diabetes factor comprise that body mass index (BMI) reduction, the reduction of blood glucose level, insulin level rising, the rising of HDL level, systolic pressure and/or diastolic pressure reduce or its combination.

40. the method for claim 39, the reduction of wherein said blood glucose level is measured by oral glucose tolerance test.

41. one kind develops the evaluation method that the danger of diabetes B or prediabetes illness changes to the patient, described method comprises:

42. the method for claim 41, wherein said patient suffers from diabetes B or prediabetes illness.

43. the method for claim 41, wherein said patient had before accepted diabetes B or prediabetes treatment of conditions.

44. the method for claim 41, wherein said patient had not before diagnosed or identified suffers from diabetes B or prediabetes illness.

45. the method for claim 41, wherein said patient is the asymptomatic patient of diabetes B or prediabetes illness.

46. picking up from, the method for claim 41, wherein said first sample accept diabetes B or prediabetes treatment for diseases described patient before.

47. picking up from, the method for claim 41, wherein said second sample accept diabetes B or prediabetes treatment for diseases described patient afterwards.

48. the method for claim 41, wherein said diabetes B or prediabetes treatment of conditions comprise workout scheme, meal supplement, surgical intervention, diabetes adjusting medicine or its combination.

49. the method for claim 41, wherein said reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from the experimenter's who does not suffer from diabetes B or prediabetes illness numerical value, or from after diagnosing or identify the patient's suffer from diabetes B or prediabetes illness numerical value.

50. the method for one or more complication that a diabetes B of identifying the patient is relevant, described method comprises:

B. described amount and reference value are compared, wherein for described reference value, one or more DBMARKERS content raise or reduce and show that described patient suffers from the diabetes B related complication or is in the danger of the described diabetes B related complication of development.

51. the method for claim 50, wherein said complication comprise that retinopathy, blind, the loss of memory, ephrosis, kidney failure, angiocardiopathy, neuropathy, autonomic function obstacle, hyperglycaemia height ooze stupor or its combination.

52. the method for claim 50, wherein said reference value comprises exponential quantity, numerical value from one or more risk of diabetes prediction algorithms or gauge index, from after diagnosing or identify the patient's suffer from diabetes B numerical value, or from the numerical value of before suffering from the patient of one or more relevant complication of diabetes B through evaluation.

53. the method for claim 50, wherein said reduction are to hang down 10% at least than described reference value.

54. the method for claim 50, wherein said rising are than described reference value high at least 10%.

55. the method for claim 50, wherein said sample are urine, serum, blood plasma, haemocyte, endothelial cell, biopsy sample, pancreatic juice, ascites, marrow, interstitial fluid, tear, phlegm or saliva.

56. the method for claim 50, wherein said DBMARKER detects by the following method: electrophoresis, immunochemistry, proteomic techniques or genome analysis.

57. the method for claim 56, wherein said immunochemistry detect and comprise radiommunoassay, immunoprecipitation, Western blotting, immunofluorescence assay or enzyme linked immunosorbent assay (ELISA).

58. the method for claim 56, wherein said proteomic techniques comprise SELDI, MALDI, LC/MS, series LC/MS/MS, proteins/peptides array or antibody array.

59. the method for claim 56, wherein said genome analysis comprise PCR (PCR), PCR in real time, microarray analysis, RNA trace or southern blotting technique.

60. the method for claim 50, wherein said patient had not before identified suffers from diabetes B.

61. the method for claim 50, wherein said patient had before identified suffers from diabetes B.

62. the method for claim 50, wherein said patient had not before identified suffers from one or more relevant complication of diabetes B.

63. the method for claim 50, wherein said patient had before identified suffers from one or more relevant complication of diabetes B.

64. a diabetes B reference expression profile, described express spectra are included in the pattern of the expression of not diagnosing or identify one or more DBMARKERS that detect among the one or more patients that suffer from diabetes B.

65. a prediabetes illness reference expression profile, described express spectra is included in the pattern of the expression of not diagnosing or identify one or more DBMARKERS that detect among the one or more patients that suffer from the prediabetes illness.

Suffer from diabetes B, be in the danger of development diabetes B or treating the pattern of the expression that detects among one or more patients of diabetes B 66. a diabetes B patient express spectra, described express spectra are included in after diagnosing or identify.

Suffer from the prediabetes illness, be in the danger of development prediabetes illness or treating the pattern of the expression that detects among one or more patients of prediabetes illness 67. a prediabetes illness patient express spectra, described express spectra are included in after diagnosing or identify.

68. kit, described kit comprises the DBMARKER detectable that detects one or more DBMARKERS, from sample and the optional guide for use of the experimenter with normal glucose level, the guide for use explanation uses described reagent to produce among the claim 64-67 each express spectra.

69. the kit of claim 68, wherein said detectable comprise one or more antibody or its fragment, one or more adaptive sons, one or more oligonucleotides or its combination.

70. one kind is used for the treatment of patient's the diabetes B or the pharmaceutical composition of prediabetes illness, described composition comprises one or more DBMARKERS or its metabolin and the pharmaceutically acceptable carrier or the thinning agent for the treatment of effective dose.

71. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprises SEQ ID NO:1.

72. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprise at least 5 continuous amino acid residues of SEQ ID NO:1.

73. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprise at least 10 continuous amino acid residues of SEQ ID NO:1.

74. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprise at least 15 continuous amino acid residues of SEQ ID NO:1.

75. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprise at least 20 continuous amino acid residues of SEQ ID NO:1.

76. the pharmaceutical composition of claim 70, wherein said DBMARKER metabolin comprises the amino acid sequence that has at least 90% homogeneity with SEQ ID NO:1.

77. a pharmaceutical composition, described composition are made up of SEQ ID NO:1 and pharmaceutically acceptable carrier or thinning agent basically.

78. a treatment has the patient's who needs the diabetes B or the method for prediabetes illness, described method comprises the claim 70 that gives described patient treatment effective dose or the pharmaceutical composition of claim 77.

79. the method for claim 78, wherein said patient had before accepted diabetes B or prediabetes treatment of conditions.

80. the method for claim 78, wherein said patient had not before accepted diabetes B or prediabetes treatment of conditions.