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WO2011032109A1 - Biomarqueurs de l'atrophie musculaire spinale - Google Patents

Biomarqueurs de l'atrophie musculaire spinale Download PDF

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Publication number
WO2011032109A1
WO2011032109A1 PCT/US2010/048675 US2010048675W WO2011032109A1 WO 2011032109 A1 WO2011032109 A1 WO 2011032109A1 US 2010048675 W US2010048675 W US 2010048675W WO 2011032109 A1 WO2011032109 A1 WO 2011032109A1
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Prior art keywords
level
biomarkers
marker
patient
sma
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Cynthia Joyce
Karen Chen
Suzanne Forrest
Dione Kobayshi
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SMA FOUNDATION
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SMA FOUNDATION
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G01N33/6896—Neurological disorders, e.g. Alzheimer's disease
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/38—Pediatrics
    • G01N2800/385—Congenital anomalies

Definitions

  • the present invention relates generally to the fields of neurology, molecular biology, and analytical chemistry.
  • the present invention relates to the identification of biomarkers in biological samples which can predict the severity and disease progression of spinal muscular atrophy in patients.
  • the identified biomarkers are also useful for monitoring the efficacy of a therapeutic intervention in spinal muscular atrophy patients.
  • SMA Spinal muscular atrophy
  • SMA severe infantile acute SMA, or Werdnig-Hoffmann disease
  • type 11 infantile chronic SMA
  • type III juvenile SMA, or Wohlfart-Kugelberg- Welander disease
  • type IV adult-onset SMA
  • the three most severe forms manifest in children, and are divided by maximal motor function achieved: type I infants never sit, type II sit, but never walk, and type III are able to walk at least for a short time (2, 37). All types are caused by homozygous protein-null mutations (deletion, conversion, or missense) of the SMN1 gene (3).
  • Type I affects more than fifty percent of SMA patients with symptoms presenting within the first six months after birth. Death typically occurs within the first two years due to respiratory failure.
  • Type II SMA has an onset between six months and eighteen months of age, and length of survival is dependent on the severity of respiratory complications and impairment.
  • the two copies of SMN -designated SMN1 and SMN2 - differ in only one base pair, a synonymous protein-coding change in exon 7 (5).
  • Most SMN protein is derived from the SMN1 gene; the SMN2 gene contributes only a small amount of normal SMN protein due to a leaky splice site at the intron 6-exon 7 boundary. If SMN1 is lost on both alleles, the protein translated from SMN2 is sufficient to rescue embryonic lethality, but insufficient to prevent manifestation of the SMA syndrome.
  • the range of clinical severity observed in SMA varies in part as a consequence of variation in copy number of SMN2: greater copy number is correlated with, but not predictive of, a milder phenotype (6).
  • SMN is expressed in all tissues and cell types; the relative specificity of the pathogenic process for lower motor neurons is not currently understood.
  • Alpha motor neurons may have unique susceptibility to a decrement of SMN function in snRN A assembly or SMN may have accessory functions in this cell or its connections (7-9).
  • SMN protein is found in axons and growth cones (10, 1 1 , 38), and may function to transport mRNAs from the nucleus to synapse. In other models it is localized post-synaptically at the neuromuscular junction and within the Z- bands of striated muscle ( 12). Therefore the primary pathophysiology of SMA may stem not only from functions within the cell body of the lower motor neuron, but also within the axon, neuromuscular junction or even muscle.
  • a biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (39).
  • the goal in biomarker identification is an empiric interim readout that is directly related to clinical endpoints, i.e., a surrogate endpoint for disease progression and/or treatment effect.
  • biomarker of disease severity or a network of biomarkers including ( 1 ) replacement of a distal endpoint with a proximal endpoint, potentially shortening the development time of new therapeutic modalities, (2) more frequent and facile measurement, (3) increased precision, (4) increased measured dynamic range of a disease process or treatment effect compared to clinical metrics, (5) reduction in sample size requirements for clinical studies, and (6) expedited decisions concerning the efficacy and validity of therapeutic interventions.
  • the development of biomarkers will have important implications in therapeutics development timelines and more efficiently allocate patient resources into studies with the greatest probability of success.
  • the present invention is based, in part, on the discovery of a panel of biomarkers in the blood and urine from a wide range of SMA patients that segregates with measures of clinical severity, and thus can serve as a measure of disease progression and patient function.
  • the present invention provides a method of predicting the level of severity of spinal muscular atrophy or monitoring disease progression in a patient or population of patients.
  • the method comprises measuring the level of at least one biomarker described herein in a biological sample obtained from one or more patients; and comparing the measured level or ratio of measured levels to a reference value or range of reference values, wherein a change in the level of the at least one biomarker is indicative of the level of severity of spinal muscular atrophy or disease progression in the patient or population of patients.
  • the method further comprises reporting a prognosis of the patient or population of patients based on the measured levels of one or more biomarkers.
  • the relative level of the biomarker(s) is indicative of the age of onset of disease and/or the type of SMA in the patient. In other embodiments, the relative level of the biomarker(s) is indicative of a patient's motor, pulmonary, and/or feeding function.
  • novel biomarkers described herein include peptides, proteins, polynucleotides, fatty acids, lipids, amino acids, organic acids, nucleobases, nucleotides, nucleic acids, and transcripts.
  • the method comprises measuring at least one biomarker in a biological sample selected from the group consisting of plasma, urine, blood, cerebrospinal fluid, saliva, tears, nasal epithelium, skin, and skeletal muscle tissue.
  • the biological sample is plasma.
  • the biological sample is urine.
  • the present invention includes a method of predicting, evaluating, or monitoring the therapeutic efficacy of a therapeutic intervention for treating spinal muscular atrophy in a patient or population of patients.
  • the method comprises measuring the level of one or more biomarkers described herein in at least one initial biological sample obtained from a patient or patients at an initial time point, wherein the initial time point is prior to the administration of the therapeutic intervention; measuring the level of said one or more biomarkers described herein in at least one subsequent biological sample obtained from a patient or patients at subsequent time point, wherein the subsequent time point is after the administration of the therapeutic intervention; and comparing the level of said one or more biomarkers in the initial biological sample to the level of said one or more biomarkers in the subsequent biological sample, wherein a change in the level of said one or more biomarkers is indicative of the efficacy of the therapeutic intervention as a treatment for spinal muscular atrophy.
  • the method further comprises adjusting the type or dosage of the therapeutic intervention based on the change in the level of said at least one biomarker.
  • a change in the level of the biomarker(s) is indicative of the efficacy of the therapeutic intervention in improving motor, pulmonary, and/or feeding function of the patient.
  • the present invention includes a method of confirming or refuting a diagnosis of spinal muscular atrophy in a patient or patients comprising measuring the level of at least one marker and/or the ratio of at least two markers in a biological sample obtained from said patient or patients; and comparing the measured level or ratio to a reference value or range of reference values, wherein the diagnosis of spinal muscular atrophy in said patient or patients is confirmed or refuted based on a change in the level of the at least one marker or the ratio of at PATENT
  • the method further comprises measuring the expression level of survival motor neuron (SMN) protein in the biological sample and measuring the change in said biomarker levels with respect to SMN levels.
  • SSN survival motor neuron
  • the present invention also encompasses a method for preparing molecular profiles of patient specimens or biological samples, the profiles being indicative of the presence, progression, or state of SMA in the patient.
  • the patient can be suspected of having SMA, predisposed to SMA, diagnosed as having SMA, and/or undergoing treatment for SMA.
  • the method comprises preparing a molecular profile from a biological sample from the patient.
  • the biomarker profile comprises the level, abundance, or concentration of two or more biomarkers listed in any one of Tables 6-41 .
  • the molecular profile can be evaluated for the presence or absence of a molecular signature indicative of the presence, progression, or state of SMA in the patient.
  • kits comprising reagents for measuring one or more of the biomarkers described herein.
  • the kits further comprise instructions for measuring one or more biomarkers for diagnosing or monitoring disease progression in a SMA patient or for monitoring the efficacy of a therapeutic intervention in a SMA patient.
  • the reagents can include antibodies or fragments thereof that bind to the biomarkers described herein.
  • the reagents include components for detecting and quantitating the biomarkers using gas chromatography, liquid chromatography and/or mass spectrometry technologies.
  • Figure 1 Modified Hammersmith Functional Motor Scale versus age by SMA cohort.
  • SMA Type 1 ( ⁇ ), SMA Type II ( ⁇ ), SMA Type III (O).
  • a biomarker can be invaluable to make more efficient treatment trials at both early and late stages of clinical investigation. At present, it is possible to assess the success of an intervention only in cumbersome and expensive prolonged interventional studies.
  • a biomarker has the potential to provide a "read-out" in early proof of concept studies, permitting the allocation of limited treatment trial resources to be focused only on the most promising compounds.
  • a biomarker can help expand the potential population of patients to include those too young or old, or too severely or mildly affected, to be eligible for clinical trials as they must presently be done using clinical outcomes.
  • biomarkers may lessen the need to design trials that include frequent burdensome travel to clinical centers.
  • treatment-associated improvement with biomarkers can enhance the meaningfulness of other clinical outcomes.
  • the present invention is based, in part, on the identification of biomarkers in biological samples (e.g. , blood and urine) from a broad range of patients afflicted with SMA that segregate with various measures of clinical severity. Accordingly, the present invention provides a method of predicting or assessing the level of severity of spinal muscular atrophy or monitoring disease progression in a patient or population of patients.
  • the method comprises measuring the level of at least one biomarker in a biological sample obtained from one or more patients; and comparing the measured level to a reference value or range of reference values, wherein a change in the level of the at least one biomarker is indicative of the level of severity of spinal muscular atrophy or disease progression in the patient or population of patients.
  • the method further comprises reporting a prognosis of the patient or population of patients based on the measured levels of one or more biomarkers.
  • biomarker or “marker” refers to a biochemical molecule
  • the presence, absence, or relative amount of a biomarker can indicate the level of disease severity.
  • the presence, absence, or relative amount of a biomarker can indicate the stage of disease progression. For instance, increased levels, amounts, or concentrations of some biomarkers relative to a reference value(s) correlates with improved motor function, which reflects a more moderate or mild disease severity or an improvement in the disease condition (e.g. in response to a therapeutic intervention).
  • Such positive function biomarkers include, but are not limited to biomarkers with positive coefficients in Tables 6, 10, 13, 21 , 26, 36, 40, and 41 .
  • increased levels, amounts, or concentrations of some biomarkers relative to a reference value(s) negatively correlate with motor function, which reflects a more severe disease conditon or a worsening of the disease state (e.g. failure of therapeutic intervention).
  • Such negative function biomarkers include, but are not limited to, biomarkers with negative coefficients in Tables 6, 10, 13, 21 , 26, 36, 40, and 41 .
  • a biomarker can include, but is not limited to, a metabolite, a polypeptide, a peptide, a protein, a nucleic acid, a polynucleotide, a nucleobase, a nucleotide, a fatty acid, a lipid, an amino acid, an organic acid, a gene, a transcript, and a vitamin.
  • the biomarker can be a "surrogate marker.”
  • a surrogate marker is a characteristic, which correlates with disease pathology but is not necessarily part of the mechanistic pathway causing the disease. In such embodiments, the biomarker is a surrogate or substitute for other clinical measures of the disease.
  • Surrogate markers can be used, for example, to monitor the progression of a disease state or the efficacy of treatment regimens in place of or in addition to clinical endpoints.
  • the biomarker is component of a particular mechanistic pathway causing the disease.
  • the biomarker can be a surrogate of, or a therapeutic target itself.
  • the method comprises measuring at least one marker selected from the markers listed in Tables 6-41 . In another embodiment, the method comprises measuring at least one marker selected from the markers listed in Tables 6- 1 1. In a certain embodiment, the method comprises measuring at least one marker selected from the markers listed in Table 12.
  • At least one marker is selected from the group consisting of glutamic acid, C I 0:0 fatty acid (capric acid), aspartic acid, hydroxyproline, 1 -methylhistidine, C24:0/C24: l sphingomyelin (d 18: 1 ), and 15Me-C: 16:0.
  • the method comprises measuring at least one marker selected from the markers listed in Tables 1 3-22. In a particular embodiment, the method comprises measuring at least one marker selected from the markers listed in Table 23.
  • At least one marker is selected from the group consisting of VP9U_uk041 , pantothenic acid, VP9U_uk083, inositol, uric acid, 3-methylhistidine, 31944 uk 07, VP9U_uk045, ascorbic acid, and malic acid.
  • the method comprises measuring at least one marker selected from the markers listed in Tables 24-38. In one embodiment, the method comprises measuring at least one marker selected from the markers listed in Table 39.
  • At least one marker is selected from the group consisting of tenascin XB (TNXB), cartilage intermediate layer protein 2 (CILP2), cartilage oligomeric matrix protein (COMP), tetranectin (CLEC3B), ADAMTS-like 4 (ADAMTSL4), thrombospondin 4 (THBS4), lumican (LUM),
  • DPP4 dipeptidylpeptidase 4
  • OMD osteomodulin
  • PEPD peptidaseD
  • CDH 13 cadherin 13
  • IGFBP6 insulin-like growth factor binding protein 6
  • COV cartilage acidic protein 1
  • APOA4 apolipoprotein A-IV
  • APCS amyloid P component
  • IgG low affinity Ilia
  • receptor 1 C 1 QR 1 or CD93
  • the method comprises measuring at least one marker selected from the markers listed in Table 41.
  • at least one marker is selected from the group consisting of myoglobin (MB), osteopontin (also referred to as secreted phosphoprotein 1 (SPP 1 )), AXL receptor tyrosine kinase, calcitonin, C reactive protein (CRP), serum amyloid P component (SAP; also referred to as amyloid P component, serum (APCS)), macrophage derived chemokine (MDC),
  • thrombomodulin TM
  • creatine kinase MB CK MB
  • FBP heart fatty acid binding protein heart
  • BNP brain natriuretic peptide
  • MMP 2 matrix metal loproteinase 2
  • IL8 interleukin 8
  • CD40 L CD40 ligand
  • ACE angiotensin converting enzyme
  • MIF macrophage migration inhibitory factor
  • complement factor H fetuin A
  • ANG2 angiopoietin 2
  • the method comprises measuring at least one marker selected from the markers listed in Table 40.
  • At least one marker is selected from the group consisting of cartilage intermediate layer protein 2 (CILP2); tenascin XB (TNXB); tetranectin (CLEC3B); ADAMTS-like 4 (ADAMTSL4); thrombospondin 4 (THBS4); cartilage oligomeric matrix protein (COMP); cartilage acidic protein 1 (CRTAC 1 ); coagulation factor XIII, B polypeptide (F 13B); peptidaseD (PEPD); lumican (LUM); complement component I , q subcomponent, receptor 1 (C l QRl or CD93); dipeptidylpeptidase 4 (DPP4); mixed complement C2/B; gelsolin (GSN); vitronectin (VTN); C-reactive protein, pentraxin-related (CRP); cathepsin D (CTSD); amyloid P component, serum (APCS or SAP); apolipoprotein A-IV (APOA4); coagul
  • cadherin 1 3 (CDH 13); ceruloplasmin (CP); complement component 9 (C9); complement component 2 (C2); hemoglobin subunit alpha (HBA 1 ); serpin peptidase inhibitor, clade A, member 10 (SERPINA 10); alkaline phosphatase, liver/bone/kidney (ALPL); quiescin Q6; Fc fragment of IgG, low affinity Ilia, receptor (FCGR3A); orosomucoid 2 (ORM2); protein C (PROC); osteomodulin (OMD); protein tyrosine phosphatase, receptor type, G (PTPRG);
  • immunoglobulin kappa variable 41 amine oxidase, copper containing 3; glyceraldehyde3 phosphate dehydrogenase (GAPDH ); S I 00 calcium binding protein A9 (S 100A9); insulin-like growth factor binding protein 6 (IGFBP6); vanin 1 (VNN 1 ); vascular cell adhesion molecule 1 (VCAM 1 ); collagen VI, alpha 3 (COL6A3); endothelial protein C receptor precursor (PROCR); thrombospondin 1 ; haptoglobin (HP); collagen, type VI, alpha 1 (COL6A 1); orosomucoid 1 (ORM 1 ); pregnancyzone protein; lymphocyte cytosolic protein 1 (Lplastin); multimerin 2 (MMRN2); endoglin (ENG); carbonic anhydrase I (CA 1 ); serpin peptidase inhibitor, clade D, member 1 (SERPIND 1 ); selenium binding protein 1 ; serpin peptida
  • At least one marker is selected from the group consisting of myoglobin (MB), osteopontin (SPPl ), AXL receptor tyrosine kinase, calcitonin, C reactive protein (CRP), serum amyloid P component (SAP or APCS), macrophage derived PATENT
  • MMP 2 interleukin 8
  • CD40 L interleukin 8
  • ACE angiotensin converting enzyme
  • MIF macrophage migration inhibitory factor
  • ANG 2 pancreatic polypeptide
  • VEGF vascular endothelial growth factor
  • EGF epidermal growth factor
  • serotransferrin plasminogen activator inhibitor 1
  • PAI 1 plasminogen activator inhibitor 1
  • VTN vitronectin
  • MIP 1 beta macrophage inflammatory protein 1 beta
  • PLGF placenta growth factor
  • SOD 1 superoxide dismutase 1
  • EN RAGE glutathione S transferase alpha (GST alpha), alpha 1 antichymotrypsin (AACT), Fas ligand (FasL), macrophage colony stimulating factor 1 (MCSF), apolipoprotein A I (APOA
  • At least one marker is selected from the group consisting of ADAMTSlike 4; alpha 1 microglobulin; angiopoietin 2 (ANG2); angiotensin converting enzyme (ACE); amine oxidase, copper containing 3 (also referred to as membrane primary amine oxidase (AOC3) or vascular adhesion protein 1 ); AXL receptor tyrosine kinase; brain natriuretic peptide (BNP); C-reactive protein, pentraxin-related (CRP); complement component 9 (C9); calcitonin; CD40 Ligand (CD40 L); cluster of differentiation 93 (CD93, also referred to as complement component 1 , q subcomponent, receptor 1 (C 1 QR 1 )); cadherin- 13 (CDH 13); cofilin 1 (CFL l ); cartilage intermediate layer protein 2 (CILP2); C-type lectin domain family 3, member B (CLEC3B); carnosine dipeptidas
  • biological sample refers to any bodily fluid or tissue obtained from a patient or subject.
  • a biological sample can include, but is not limited to, whole blood, red blood cells, plasma, PBMCs, urine, saliva, tears, buccal swabs, cerebrospinal fluid (CSF), nasal epithelium, skin, and skeletal muscle tissue.
  • the biological sample is plasma.
  • the biological sample is urine.
  • the method comprises comparing the measured level of at least one biomarker to a reference value, and/or comparing a ratio of at least two biomarkers to a reference value.
  • reference value refers to a prc-determined value of the level or concentration of a biomarker ascertained from a known sample.
  • the reference value can reflect the level or concentration of a biomarker in a sample obtained from a control subject ⁇ i.e., a subject not afflicted with SMA).
  • the reference value can reflect the level or concentration of a biomarker in a sample obtained from a patient at a particular stage in the disease condition ⁇ i.e., exhibiting specific clinical criteria, such as a particular level of motor, pulmonary, or feeding function) or from a patient with a particular form of the disease ⁇ i.e. , type I, type II, or type III SMA).
  • the reference value can reflect the level or concentration of a biomarker in an initial or baseline sample ⁇ i.e., pre-treatment sample) from a patient.
  • a reference value can also be a known amount of a biomarker. Such a known amount of a biomarker may correlate with an average level of the biomarker from a population of control subjects, a population of patients with a PATENT
  • the reference value can be a range of values, which, for instance, can represent a mean plus or minus a standard deviation or confidence interval.
  • a range of reference values can also refer to individual reference values for a particular biomarker across various disease outcomes.
  • a change in the level of the one or more biomarkers and/or a change in the ratio of at least two biomarkers in the biological sample obtained from a patient is indicative of the age of onset of SMA disease.
  • at least one marker to be measured can be selected from the markers listed in Tables 9, 12, 16, 23, 29, and 39.
  • the age of onset is predictive of the level of severity of SMA disease. For instance, a younger age of onset (e.g., less than six months) can indicate a more severe form of SMA disease, while a later age of onset (e.g., greater than eighteen months) can indicate a more mild form of the disease.
  • a change in the level of the at least one marker in the biological sample obtained from a patient and/or a change in the ratio of at least two biomarkers is indicative of the type of SMA disease in the patient.
  • the at least one marker to be measured or the at least two biomarkers for ratio calculation can be selected from the markers listed in Tables 7, 8, 1 1 , 12, 14, 15, 22, 23, 24, 27, 28, 37, 38, and 39.
  • a change in the level of the at least one marker in the biological sample obtained from a patient and/or a change in the ratio of at least two biomarkers is indicative of the clinical function of the patient.
  • the relative level of the biomarker can reflect the level of motor, pulmonary, and/or feeding function of the patient.
  • the relative level of the biomarker is indicative of motor function in the patient.
  • the at least one marker to be measured can be selected from the markers listed in Tables 6, 10, 12, 13, 17, 21 , 23, 24, 26, 30, 35, 36, 39, 40, and 41.
  • the relative level of the biomarker reflects the level of motor function in the patient as measured by the Modified Hammersmith Functional Motor Scale (MHFMS).
  • MHFMS Modified Hammersmith Functional Motor Scale
  • the biomarker may be associated with positive function or negative function.
  • a "positive function" biomarker is a marker whose abundance is associated with higher scores on the MHFMS (e.g. better motor function). An increase in the abundance or concentration of a positive function biomarker relative to a reference value can indicate, inter PATENT
  • Positive function biomarkers include, but are not limited to, contactin 4 (CNTN4), colony stimulating factor 1 receptor (CSF1 R), dipeptidylpeptidase 4 (DPP4), endoglin (ENG), gelsolin (GSN), insulin-like growth factor binding protein 6 (IGFBP6), met protooncogene (MET), vascular cell adhesion molecule 1 (VCAM 1), collagen 2A 1 , 6A 1 , and 6A3 (COL2A 1 , COL6A1 , COL6A3), neogenin homolog 1 (NEOl ), type-G protein tyrosine phosphatase receptor (PTPRG), quiescin Q6 (QSOX1), sex hormone binding globulin (SHBG), osteopontin (SPP l ), caherin 13 (CD
  • a "negative function" biomarker is a marker whose abundance is associated with lower scores on the MHFMS (e.g. poor motor function). An increase in the abundance or
  • concentration of a negative function biomarker relative to a reference value can indicate, inter alia, worsening in the disease condition (e.g. poorer prognosis), a negative or neutral response to a therapeutic intervention, or a more severe form of the disease state.
  • Negative function biomarkers include, but are not limited to, catalase (CAT), C-reactive protein (CRP), cathepsin D (CTSD), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Parkinson disease 7 (PARK7), platelet factor 4 (PF4), peroxiredoxin 2 and 6 (PRDX2 and PRDX6), protein C (PROC), S I 00 calcium binding protein A4, A8 and A9 (S 100A4, S 100A8, S 100A9), superoxide dismutase 1 (SOD 1 ), superoxide dismutase 2 (SOD2), thioredoxin (TXN), vitronectin (VTN), serum amyloid P component (APCS), mixed complement C2/B, hemoglobin, beta (HBB), complement factor I (CFI), LRG 1 , RPS27A , C2, C9, INHBC, ceruloplasmin, AGA, HBA 1 , PRG4, CA2, CST6,
  • the relative level of the biomarker is indicative of pulmonary function of the patient.
  • at least one marker to be measured can be selected from the markers listed in Tables 12, 20, 23, 24, 33, 34, and 39.
  • the relative level of the biomarker is indicative of the nutritional status of the patient.
  • at least one marker to be measured can be selected from the markers listed in Tables 12, 18, 19, 23, 25, 3 1 , 32, and 39.
  • a method of predicting or assessing the level of severity of spinal muscular atrophy or disease progression in a patient or population of patients comprises measuring the level and/or ratio of two or more biomarkers described herein in a biological sample obtained from one or more patients; and comparing the measured levels to a range of reference values, wherein a change in the levels and/or ratio of the two or more biomarkers is indicative of the level of severity of spinal muscular atrophy or disease progression in the patient or population of patients.
  • the method further comprises reporting a prognosis of the patient or population of patients based on the measured levels of one or more biomarkers (e.g. , positive or negative function biomarkers).
  • a panel of biomarkers are measured in the biological sample, for instance, at least three or more, four or more, five or more, ten or more, fifteen or more, twenty or more, thirty or more, forty or more, or fifty or more biomarkers.
  • the method comprises measuring a first panel of biomarkers in a first biological sample and measuring a second panel of biomarkers in a second biological sample, wherein the first and second biological samples are different.
  • the first biological sample is plasma and the second biological sample is urine.
  • the first panel and second panel of biomarkers can be the same or different.
  • the method comprises measuring the level of a biomarker or panel of biomarkers of the invention alone or in combination with SMN expression and/or SMN2 copy number, i.e. , to confirm a possible diagnosis of SMA.
  • the change in the level or concentration of one or more biomarkers is measured relative to SMN levels.
  • SMN expression can be measured by assessing the level of SMN protein or SMN transcript.
  • SMN expression and SMN2 copy number can be measured by methods known in the art including, but not limited to, Northern Blot, PCR, RT-PCR, Western Blot, immunoassay (e.g. ELISA or multiplexed assays), 2D gel electrophoresis, and hybridization.
  • the biomarker or panel of biomarkers can be measured in biological samples obtained from the patient at different time points to assess disease progression or prognosis of the patient over time.
  • a biomarker or panel of biomarkers can be measured at a regular interval, such as weekly, monthly, every three months, every six months, or annually.
  • the present invention encompasses a method of diagnosing SMA in a subject or determining the susceptibility of a subject for developing SMA.
  • the method comprises measuring at least one biomarker or a panel of biomarkers described herein in a biological sample from the subject, and comparing the measured level of the at least one biomarker or panel of biomarkers to a reference value or range of reference values, wherein a difference in the level of the at least one marker or panel of biomarkers from the reference value or range of reference values is indicative of the subject having SMA or subsequently developing SMA.
  • the subject is a neonate. In another embodiment, the subject is a child less than I year old.
  • the subject is a child between the ages of 1 and 3 years old. In still another embodiment, the subject is a child between the ages of 2 and 6 years old. In yet another embodiment, the subject is a child between the ages of 6 and 12 years old.
  • the present invention also includes a method of predicting, evaluating, or monitoring the therapeutic efficacy of a therapeutic intervention for treating spinal muscular atrophy in a patient or population of patients.
  • the method comprises measuring the level of at least one biomarker described herein in at least one initial biological sample obtained from a patient or patients at an initial time point, wherein the initial time point is prior to the administration of the therapeutic intervention; measuring the level of said at least one biomarker described herein in at least one subsequent biological sample obtained from a patient or patients at subsequent time point, wherein the subsequent time point is after the administration of the therapeutic intervention; and comparing the level of the at least one biomarker or panel of biomarkers in the at least one initial biological sample to the level of the at least one biomarker or panel of biomarkers in the at least one subsequent biological sample, wherein a change in the level of the at least one biomarker or panel of biomarkers is indicative of the efficacy of the therapeutic intervention as a treatment for spinal muscular atrophy.
  • the method further comprises measuring the level of at least one bio
  • a change in the level of the at least one biomarker or panel of biomarkers is indicative of the efficacy of the therapeutic intervention in improving the patient's clinical function (e.g., motor, pulmonary, and/or feeding function).
  • the relative level of the biomarker or panel of biomarkers is indicative of the efficacy of the therapeutic intervention in improving the motor function of the patient as measured by the Modified Hammersmith Functional Motor Scale. For instance, an increase in the level of a positive function biomarker following administration of the therapeutic intervention indicates that the therapeutic intervention improves motor function.
  • a decrease in the level of a negative function biomarker following administration of the therapeutic intervention indicates that the therapeutic intervention improves motor function.
  • measurement of one or more positive and negative function biomarkers may be used before or in lieu of assessment of the patient by the MHFMS to assess disease progression and or treatment efficacy.
  • a "therapeutic intervention” is any compound, composition, biologic or treatment regimen that may be a putative therapy for treating SMA.
  • the therapeutic intervention can include, but is not limited to, proteins, peptides, polypeptides, antibodies, stem cells, nucleic acids, polynucleotides, oligonucleotides, exercise regimens, nutritional supplements, or small molecules.
  • the therapeutic intervention can be pharmaceutical compositions currently approved by the FDA for other indications or compositions comprising a new chemical entity.
  • the therapeutic intervention is a compound or biologic selected from a compound or biologic library, such as a combinatorially-generated library.
  • the therapeutic intervention increases expression of SMN protein.
  • Such therapeutic interventions can include, but are not limited to, compounds such as valproic acid, phenylbutyrate, sodium butyrate, hydroxyurea, trapoxin, and trichostatin A as well as other types of therapeutic interventions.
  • the therapeutic intervention has no effect on expression of SMN protein.
  • the present invention also provides a method of monitoring treatment of SMA in a patient in need thereof.
  • the method comprises measuring the level of at least one biomarker or panel of biomarkers as described herein in at least one initial biological sample obtained from a patient at an initial time point, wherein the initial time point is prior to the start of a therapeutic intervention protocol for SMA; measuring the level of said at least one biomarker or panel of biomarkers described herein in at least one subsequent biological sample obtained from the patient at subsequent time point, wherein the subsequent time point is after the start of the therapeutic intervention protocol; and comparing the level of the at least one biomarker or panel of biomarkers in the at least one initial biological sample to the level of the at least one biomarker or panel of biomarkers in the at least one subsequent biological sample, wherein a change in the level of the at least one biomarker or panel of biomarkers is indicative of the efficacy of the therapeutic intervention protocol.
  • the method further comprises modifying or changing the therapeutic intervention based on the measured biomark
  • the present invention provides a method of predicting therapeutic efficacy of a particular therapeutic intervention ⁇ e.g. , treatment regimen or compound) in a patient suffering from SMA.
  • the method comprises measuring at least one marker or panel of biomarkers described herein in a biological sample obtained from the patient suffering from SMA, wherein the patient is not receiving any treatment for SMA, and comparing the measured level of the at least one biomarker or panel of biomarkers to a reference value or range of reference values, wherein a difference in the level of the at least one marker or panel of biomarkers from the reference value or range of reference values predicts the therapeutic efficacy of a particular therapeutic intervention.
  • an elevated level of a biomarker relative to a reference value can indicate that a particular treatment regimen or therapeutic compound would be beneficial in the SMA patient.
  • an elevated level of a biomarker relative to a reference value can indicate that a particular treatment regimen or therapeutic compound would be contraindicated in the SMA patient.
  • a reduced level of a biomarker relative to a reference value can indicate that a particular treatment regimen or therapeutic compound would be beneficial in the SMA patient.
  • a reduced level of a biomarker relative to a reference value can indicate that a particular treatment regimen or therapeutic compound would be contraindicated in PATENT
  • a treating physician or neurologist may prescribe a particular therapeutic compound or treatment regimen for the SMA patient based on the measured levels of one or more biomarkers or a panel of biomarkers thereby tailoring the treatment for SMA to a particular patient.
  • the present invention provides a method for preparing molecular profiles of patient specimens or biological samples, the profiles being indicative of the presence, progression, or state of SMA in the patient.
  • the patient can be suspected of having SMA, predisposed to SMA, diagnosed as having SMA, and/or undergoing treatment for SMA.
  • the method comprises preparing a molecular profile from a biological sample from the patient.
  • the biomarker profile comprises the level, abundance, or concentration of two or more biomarkers listed in any one of Tables 6-41.
  • the molecular profile can be evaluated for the presence or absence of a molecular signature indicative of the presence, progression, or state of SMA in the patient.
  • the patient may have one or more presumptive signs of SMA.
  • Presumptive signs of SMA include for example, muscle weakness, muscle atrophy, motor neuron loss, decreased life expectancy, poor muscle tone, decreased or absent deep tendon reflexes, twitching of leg, arm or tongue muscles, abnormal gait, and difficulty breathing.
  • the patient may have a reduced level of expression of SMN protein relative to age-matched control subjects.
  • the invention provides a method for preparing a biomarker profile indicative of the presence or absence of SMA.
  • the method comprises preparing a biomarker profile from a biological sample, such as a plasma or urine sample of a patient suspected of having SMA.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 6-41 .
  • the biomarker profile comprises the level, abundance, or concentration of at least four, or at least six, or at least eight, or at least ten, or at least twenty biomarkers listed in any one of Tables 6-41.
  • the biomarker profile comprises the level, abundance, or concentration of at least four, or at least six, or at least eight, or at least ten, or at least twenty biomarkers listed in any one of Tables 12, 23, 24, 39, and 41.
  • the biomarker profile may be prepared with the use of a custom kit or array, e.g. , to allow particularly for the profiling of biomarkers associated with SMA.
  • the biomarker profile includes the level, abundance, or concentration of biomarkers associated with the age of onset of SMA disease.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 9, 12, 16, 23, 29, and 39.
  • the age of onset is predictive of the level of severity of SMA disease. For instance, a younger age of onset (e.g., less than six months) can indicate a more severe form of SMA disease, while a later age of onset (e.g., greater than eighteen months) can indicate a more mild form of the disease.
  • the biomarker profile includes the level, abundance, or concentration of biomarkers associated with the type of SMA disease in the patient.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 7, 8, 1 1 , 12, 14, 15, 22, 23, 24, 27, 28, 37, 38, and 39.
  • the biomarker profile includes the level, abundance, or concentration of biomarkers associated with the clinical function of the patient.
  • the biomarker profile is indicative of the level of motor, pulmonary, and/or feeding function of the patient.
  • the biomarker profile is indicative of motor function in the patient.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 6, 10, 12, 13, 17, 21 , 23, 24, 26, 30, 35, 36, 39, 40, and 41 .
  • the biomarker profile includes the level, abundance, or concentration of at least two positive function biomarkers as described herein.
  • the biomarker profile includes includes the level, abundance, or concentration of at least two negative function biomarkers as described herein.
  • the biomarker profile includes the level, abundance, or concentration of biomarkers associated with pulmonary function of the patient.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 12, 20, 23, 24, 33, 34, and 39.
  • the biomarker profile includes the level, abundance, or concentration of biomarkers associated with the nutritional status of the patient.
  • the biomarker profile includes the level, abundance, or concentration of at least two biomarkers listed in any one of Tables 12, 1 8, 19, 23, 25, 3 1 , 32, and 39.
  • biomarkers of the invention can be measured in a biological sample by various methods known to those skilled in the art.
  • metabolites and macromolecules can be PATENT
  • kits for measuring at least one biomarker of the invention include reagents and optionally instructions for measuring panels of two or more, three or more, four or more, five , or more, ten or more, twenty or more, thirty or more, forty or more, or fifty or more biomarkers of the invention.
  • reagents refers to the components necessary for detecting or quantitating one or more biomarkers by any one of the methods described herein.
  • kits for measuring metabolite and macromolecule biomarkers can include reagents for performing amino acid analysis, free fatty acid analysis, liquid or gas chromatography, and mass spectrometry.
  • kits for measuring protein biomarkers can include reagents for performing immunoassays, electrophoresis, or mass spectrometiy.
  • the reagents include one or more binding partners that specifically bind to a biomarker, including but not limited to antibodies and fragments thereof, aptamers, carbohydrates, and the like.
  • the reagents include one or more oligonucleotides or polynucleotides that specifically bind to nucleic acid biomarkers or nucleic acids encoding protein biomarkers.
  • the kit includes reagents for measuring one or more biomarkers, two or more, three or more, four or more, five or more, ten or more, twenty or more, thirty or more, forty or more, or fifty or more biomarkers listed in any one of Tables 6-41.
  • the kit includes reagents for measuring one or more biomarkers, two or more, three or more, four or more, five or more, ten or more, twenty or more, thirty or more, forty or more, or fifty or more biomarkers listed in Tables 12, 23, 24, 39, and 41 .
  • the kit can include reagents for measuring one or more biomarkers in plasma or urine samples. In some embodiments, can include reagents for measuring one or more biomarkers in plasma or urine samples.
  • kits can include reagents for measuring one or more biomarkers in other patient samples including skin, skeletal muscle tissue, blood, cerebrospinal fluid, saliva, tears, PATENT
  • kits further comprise a set of reference values to which the levels of the one or more biomarkers can be compared.
  • the second is prospective recruitment of a well-characterized disease cohort that is free of many potential confounders, in a design intended to account for the singular characteristics of SMA variability and clinical course.
  • An age-matched normal control cohort is included for secondary class- specific comparisons.
  • the third is use of sophisticated bioinformatics methodologies, including pathway and con-elation network approaches (24).
  • n 6 Females age 2-5.
  • n 6 Females age 6- 12.
  • the number of subjects was selected based on clinical and statistical considerations. An unbalanced number of subjects from the three types of SMA was selected in part out of concern that rapid recruitment of eligible patients with SMA I across the full age range would be difficult, and in part because SMA 1 patients provide categorical data but not continuous data for the primary outcome because of floor effects of the MHFMS.
  • the sample size for the SMA subjects was selected to achieve 83% power for the primary outcome of MHFMS to detect a univariate biomarker associated with motor function using an elastic net regression analysis, assuming a 0.75 correlation between the observed and theoretical outcomes (26). The power estimate is based on an average of 100 simulated datasets using data available from the original Hammersmith Scale (27).
  • the sample size of 20 control subjects was selected to achieve at least 90% power to detect a univariate biomarker with a mean-fold change (MFC) of 1.5 when the false discovery rate (28) is controlled at 0.05. In both power calculations it was assumed that 10% of profiled analytes are true biomarkers, and that variance of analytes is equal to 0.2.
  • Systemic or specific-organ illness including renal, hepatic, cardiac, pulmonary, significant gastrointestinal illness, hematologic or rheumatic disorders requiring ongoing treatment or chronic medication use.
  • anti-reflux medications e.g., rantidine
  • constipation or stool softening medications e.g., polyethylene glycol 3350
  • stool bulking agents e.g., stool bulking agents
  • inhaled bronchodilator medications and nebulizers e.g., albuterol
  • a standardized general physical examination was performed including vital signs, inspection and evaluation of nutritional balance, pulmonary function and neurological examination.
  • Pulmonary assessment consisted of:
  • the Modified Hammersmith Functional Motor Scale (25) provides a tool for evaluation of motor function in pediatric subjects with SMA type II and type III.
  • the Modified Hammersmith Functional Motor Scale was performed according to the Study Manual of Operations. A score of "0" is acceptable for those unable to perform any of the measurements ⁇ e.g., type I SMA subjects). In this study, both control subjects and SMA subjects underwent the assessment as the scale was used as the primary outcome.
  • a 10-meter Timed Walk Test was performed on all ambulatory SMA subjects and controls according to the Study Manual of Operations. This test compares higher functioning subjects with SMA and control subjects in their ability to walk 10 meters (30-32).
  • the BMI Z Scale was used to determine a child's body mass index (BMI).
  • BMI percentile-for-age calculator automatically adjusts for differences in height, age and gender, making it one of the best tools for evaluating a growing child's weight.
  • Many SMA children have a higher average BMI related to their lack of motor activity.
  • the BMI Z Score was automatically calculated upon data entering the height, weight, and ulnar length.
  • MHFMS was obtained for controls and all subjects with SMA types II and III, and 10 meter walk time for controls and all type III subjects able to walk. Forced vital capacity was available for all subjects over age 5. As expected, none of the Type I subjects were able to complete the motor or pulmonary function measures. All measures of function, present functional state, and the historical age of disease onset were spread over a wide range, though each of these, as expected, correlated with SMA type and MHFMS. (Table 4)
  • Biomarkers identified in this study have the advantage of being independent of specific hypotheses about pathophysiology. Only a portion of SMA variability is due to identified factors such as SMN2 copy number, partially functional SMN1 missense mutation, or specific SMN2 mutations (34).
  • Plasma samples obtained from the SMA patient and control populations described in Example 1 were subject to a metabolomics analysis consisting of four separate platforms as described in Table 5 below.
  • the objective from this set of analyses was to identify a biomarker in blood that segregates with measures of clinical severity of SMA.
  • comparison of biomarkers between SMA and control cases were performed using regression analysis, controlling for sex and age. Correlations of biomarkers with outcomes were conducted within SMA cases, as well as in the combined population of SMA and control cases.
  • i denotes the i category
  • j denotes the j subject in the i category
  • x is the anaiyte intensity
  • the anaiyte was declared a marker if both the overall test for mean level differences and one of the pairwise comparisons across all categories were significant.
  • HMDBID is the identifier from the human metabolome database (41 ).
  • STD is the Standard Deviation: Estimated standard error for regression coefficient.
  • the Lower Confidence Limit (LCL) is the lower 95% confidence interval for regression coefficient, while the Upper Confidence Limit (UCL) is the upper 95% confidence interval for regression coefficient.
  • HMDBID is the identifier from the human metabolome database (41) while type comparisons show estimated MFC values. Grey color denotes fold changes for analytes which were not declared markers in a given test. One hundred and four (104) plasma metabolites were statistically significant markers by univariate analysis.
  • elastic net multivariate regression (26) was used to find a composite set of biomarkers that correlates with outcome.
  • Elastic net multivariate regression was also used for continuous secondary outcomes (e.g., age of disease onset, height, weight).
  • the following elastic net model was used for continuous outcome variables:
  • Elastic net puts a constraint on the coefficients and has the following features:
  • Unconditional P-value raw p-value for hypothesis testing (null hypothesis: regression coefficient for this analyte is 0) PATENT
  • MHFMS denotes marker status vs. MHFMS.
  • SMA types, Disease Onset, Current Level of Function and Respiratory Support denote multiple categorical outcomes (the number of outcomes is in parentheses), and total denotes the sum of all outcomes for which the analyte is a marker.
  • Urine samples ( 100 ⁇ ) obtained from the SMA patient and control populations described in Example 1 were subject to a metabolomics analysis consisting of a GC/MS platform in which extracted and derivatized analytes are quantified by gas chromatography coupled with mass spectrometry.
  • Typical analyte classes in this platform include organic acids, mono- & di- saccharides, fatty acids, amino acids, alcohols, nucleobases, and nucleotides.
  • HMDBID is the identifier from the human metabolome database (41 ).
  • STD is the Standard Deviation: Estimated standard error for regression coefficient.
  • the Lower Confidence Limit (LCL) is the lower 95% confidence interval for regression coefficient, while the Upper Confidence Limit (UCL) is the upper 95% confidence interval for regression coefficient.
  • P-value represents the raw p-value for hypothesis testing: ⁇ 1
  • HMDBID is the identifier from the human metabolome database (41 ) while type comparisons show estimated MFC values. Grey color denotes fold changes for analytes which were not declared markers in a given test. Fifty-six (56) urine metabolites were statistically significant markers by univariate analysis.
  • Each numeric entiy indicates the number of statistical tests in which an analyte was found to be a statistically significant biomarker, for a given outcome measure.
  • MHFMS denotes marker status vs. MHFMS. SMA types, Disease Onset, Current Level of Function and
  • Respiratory Support denote multiple categorical outcomes (the number of outcomes is in parentheses), and total denotes the sum of all outcomes for which the analyte is a marker.
  • RNA isolated from blood samples from the SMA patient and control populations described in Example 1 was subject to transcript profiling using the human exon microarray available from Affymetrix (Human Exon 1.0 ST array). Samples from 105 SMA patients and 21 controls were anlayzed. The children in the control group matched the gender and age distribution expected in the SMA cohorts. A total of 807,038 analytes were present in the final data sets, which were subject to a univariate analysis for each functional outcome.
  • Blood plasma samples 100 ⁇ l obtained from the SMA patient and control populations described in Example 1 were subject to a proteomics analysis consisting of a LC-MALDI- MS/MS platform.
  • Example 2 The same univariate and multivariate analyses as described for the plasma metabolomics biomarkers in Example 2 were also used to identify biomarkers for the proteomics analysis of plasma samples. Samples from 106 SMA patients and 22 controls were analyzed. The children in the control group matched the gender and age distribution expected in the SMA cohorts. There were a total of 701 proteins in the final data sets.
  • Identifier is the identifier from the International Protein Index database (42) while type comparisons show estimated MFC values. Red color denotes upregulated proteins in a given comparison, green denotes downregulated proteins and grey denotes fold changes for analytes which were not declared markers in a given test. Hemoglobin beta (HBB) was also found to be a signficant marker. Sixty-seven (67) proteins were statistically significant markers by univariate analysis.
  • Each numeric entry indicates the number of statistical tests in which a protein analyte was found to be a statistically significant biomarker, for a given outcome measure.
  • MHFMS denotes marker status vs. MHFMS.
  • SMA types, Disease Onset, Current Level of Function and Respiratory Support denote multiple categorical outcomes (the number of outcomes is in parentheses), and total denotes the sum of all outcomes for which the protein is a marker. Only analytes with 20 or more marker outcomes are shown.
  • iTRAQ proteomics analysis
  • AAA amino acid analysis: FFA: free fatty acid analysis
  • GC/MS gas chromatography/mass spectrometry analysis
  • Lipid LC/MS liquid chromatography/mass spectrometry analysis of plasma lipids.
  • the first group contains analytes that are markers of positive function while the second contains analytes that are markers of negative function.
  • the positive function group included primarily proteins and metabolites associated with cellular differentiation [contactin 4 (CNTN4), colony stimulating factor 1 receptor (CSF I R), dipeptidylpeptidase 4 (DPP4), endoglin (ENG), PATENT
  • the positive function group also included other analytes associated with cell growth and development, such as CILP2, COMP, TNXB, tetranectin (CLEC3B), osteomodulin (OMD), and alkaline phosphatase (ALPL).
  • CILP2 CILP2
  • COMP TNXB
  • CLEC3B tetranectin
  • OMD osteomodulin
  • ALPL alkaline phosphatase
  • the vast majority of these proteins are expressed extracellularly (e.g. found in extracellular matrix or secreted) or are embedded in the plasma membrane. Hydroxyproline is a metabolite in this set, perhaps denoting near-normal utilization of collagens.
  • the negative function group included primarily proteins and metabolites associated with cell death [catalase (CAT), C-reactive protein (CRP), cathepsin D (CTSD), glyceraldehyde- 3-phosphate dehydrogenase (GAPDH), Parkinson disease 7 (PARK7), platelet factor 4 (PF4), peroxiredoxin 2 and 6 (PRDX2 and PRDX6), protein C (PROC), S I 00 calcium binding protein A4, A8 and A9 (S 100A4, S 100A8, S 100A9), superoxide dismutase 1 (SOD 1 ), superoxide dismutase 2 (SOD2), thioredoxin (TXN), and vitronectin (VTN)] and free radical scavenging [CAT, PARK7, serum amyloid P component (APCS), and CRP].
  • CAT catalase
  • CRP C-reactive protein
  • CSD cathepsin D
  • GPDH glyceraldehyde
  • Metabolites in this group include known markers of muscle damage, such as 3- methylhistidine and myoinositol.
  • markers may have clinical utility as surrogates of clinical function. Further, depending on relative stability and their relevance to disease progression, some of these markers may have utility in longitudinal measurements of current function. This is of special value among patients with extreme MHFMS scores, i.e., "0" or "40"; where the score cannot separate patient function but the biomarker may have this ability. Additionally, changes in the relative abundance levels of these markers in a therapeutic setting may denote drug response in advance of, or complementary to, tests of motor function. PATENT
  • the blood plasma samples obtained from the SMA patient and control populations described in Example 5 were subject to an immunoassay analysis using multi-analyte profiling (MAP) technology (Human DiscoveryMAP® v 1 .0, Rules Based Medicine, Austin, TX).
  • MAP multi-analyte profiling
  • the data comprised clinical information for 129 subjects and DiscoveryMAP protein measurements for 190 proteins for each subject.
  • a variety of statistical methods were used, as described below, ' to identify associations between the DiscoveryMAP protein levels and clinical variables including the Hammersmith score and several secondary measures.
  • the relationships between the DiscoveryMAP protein levels and potential confounding variables such as age, gender, medications, etc, were also examined.
  • the analyte data were log transformed to produce distributions closer to normal. Most statistical analyses were performed with both linear and log scaled values.
  • neuron function in motor axons is independent of functions required for small
  • Axonal-SMN (a-SMN), a protein isoform of the survival motor neuron gene, is

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Abstract

La présente invention a pour objet de nouveaux biomarqueurs qui distinguent, à l'aide de mesures, la gravité clinique de l'atrophie musculaire spinale. En particulier, la présente invention concerne des biomarqueurs du plasma et de l'urine qui peuvent être utilisés pour prédire ou évaluer la gravité de l'AMS ou confirmer le diagnostic d'AMS chez un patient. La présente invention concerne également des méthodes d'utilisation de tels biomarqueurs pour sélectionner une thérapeutique potentielle et surveiller l'efficacité d'une intervention thérapeutique chez un patient.
PCT/US2010/048675 2009-09-11 2010-09-13 Biomarqueurs de l'atrophie musculaire spinale Ceased WO2011032109A1 (fr)

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