Peripheral blood cell markers useful for diagnosing multiple sclerosis and methods and kits utilizing same

Abstract
Markers of multiple sclerosis and methods and kits utilizing same for diagnosing multiple sclerosis in an individual are provided.
Description
FIELD AND BACKGROUND OF THE INVENTION

The present invention relates generally to the field of diagnosis, treatment assessment and prognosis. More specifically, the present invention relates to peripheral blood cell expressed markers and kits and methods utilizing same for diagnosing, treating and assessing the state of multiple sclerosis (MS) in an individual. The present invention also provides cellular markers which are useful in distinguishing between different clinical courses of MS e.g.: probable, relapsing-remitting, secondary progressive or primary progressive as well as response to the therapy.


Multiple sclerosis is an autoimmune neurodegenerative disease, which is marked by inflammation within the central nervous system with lymphocyte attack against myelin produced by oligodendrocytes, plaque formation and demyelization with destruction of the myelin sheath of axons in the brain and spinal cord, leading to significant neurological disability over time. The disease frequently occurs in young adults between 20-40 years of age, is more prevalent in females than males (2:1), and has a characteristic geographical distribution—estimated prevalence in USA 120/100,000, (250,000 to 350,000 cases).


The annual cost of MS in USA was estimated about $34,000 per person, $2.2 million total lifetime cost per case or $6.8 billion yearly, in a conservative estimate of a national annual cost (Anderson D W, 1992; Whetten-Goldstain K., 1998).


Clinical Diagnosis and Evaluation of Stages of MS


Typically, at onset an otherwise healthy person presents with the acute or sub acute onset of neurological symptomatology (attack) manifested by unilateral loss of vision, vertigo, ataxia, dyscoordination, gait difficulties, sensory impairment characterized by paresthesia, dysesthesia, sensory loss, urinary disturbances until incontinence, diplopia, dysarthria or various degrees of motor weakness until paralysis. The symptoms are usually painless, remain for several days to a few weeks, and then partially or completely resolve. After a period of remission, a second attack will occur. During this period after the first attack, the patient is defined to suffer from probable MS. Probable MS patients may remain undiagnosed for years. When the second attack occurs the diagnosis of clinically definite MS (CDMS) is made (Poser criteria 1983; C. M. Poser et al., Ann. Neurol. 1983; 13, 227).


The clinical disease courses of MS are relapsing-remitting, primary or secondary progressive (Abramsky, 1997; Russell, 1998).


The relapsing-remitting course of MS (85% of patients) is characterized by acute attacks or relapses during which new neurological symptoms and signs appear, or worsen. Relapse develops within a period of several days, lasts for 6-8 weeks, than gradually resolves. During the acute relapse scattered inflammatory and demyelinating central nervous system (CNS) lesions produce varying combinations of motor, sensory, coordination, visual, and cognitive impairments, as well as symptoms of fatigue and urinary tract dysfunction. The outcome of a relapse is unpredictable in terms of neurological sequel but it is well established that with additional relapses, the probability of complete clinical remission decreases and neurological disability and handicap may develop. On average, about 60% of patients remain fully functional 10 years after the primary attack, and 25 to 30% remain fully functional 30 years after onset. Statistically, the disease does not greatly decrease life expectancy (mean decrease 12 years), although some patients become severely disabled and die from recurrent infections and complications.


Primary progressive MS (10% of patients) is characterized by slow, progressive neurological dysfunction usually in the form of a gradual myelopathy causing spasticity and ataxia. Treatment regimen varies greatly with different clinical course and severity of the disease.


The diagnosis of MS is still defined primary by clinical terms and relies on a combination of history, neurological examination and ancillary laboratory and neuro-imaging studies.


Laboratory tests for MS include: 1) CSF evaluation of IgG synthesis, oligoclonal bands; 2) MRI of the brain and spinal cord and; 3) exclusion of other autoimmune diseases by blood tests [e.g.; serum B12 level; HTLV 1 or HIV 1 titers; sedimentation rate or C-reactive protein; RA latex (Rheumatoid arthritis); ANA, anti-DNA antibodies (systemic lupus erythematosus)]. However, accurate diagnosis and prognosis in the “probable” stage, and early relapsing-remitting stages remains problematic. For example, it has been shown that positive MRI findings in the first demyelinating attack only provide a 50% successful prediction of development of clinically definite MS within 2-3 years (CHAMPS Study Group, Neurology 2002; 59:998-1005). Likewise, Villar et al (Neurology 2002; 59:877-83) found that detection of oligoclonal IgM bands with early symptoms were only partially predictive of development of clinically definite MS.


Other laboratory tests may provide some additional support for the diagnosis, but evidence of lesions disseminated in time and space remains a cardinal element of the diagnosis (Poser C M., 2001). In absence of definitive laboratory tests and pathognomonic clinical features, MS remains ultimately a diagnosis of exclusion.


Diseases that may be confused with MS are: 1) Acute disseminated encephalomyelitis (follows infections or vaccination mainly in children, fever, headaches, and meningitis common), 2) Lyme disease (antibodies to Borrelia species antigens in serum and CSF), 3) HIV associated myelopathy (HIV antibodies present), 4) HTLVI myelopathy (HTLVI antibodies present in serum/CSF), 5) Neurosyphilis (syphilis antibodies present in serum and/or CSF, 6) Progressive multifocal leukoencephalopathy (biopsy of lesions demonstrates virus by electron microscopy), 7) Systemic lupus erythematosus (CNS manifestations of lupus, antinuclear antibodies, anti-dsDNA), 8) Polyarteritis nodosa (systemic signs, micro-aneurysms demonstrated by angiographies, vasculitis demonstrated in biopsy of involved areas), 9) Sjogren's syndrome (dry eyes and mouth, antiRo and antiLa antibodies), 10) Behcet's disease (Oral/genital ulcers, antibodies to oral mucosa), 11) Sarcoidosis (CNS signs, increased protein in CSF, biopsy shows granuloma, 12) Paraneoplastic syndromes (older age group, antiYo antibodies), 13) Subacute combined degeneration of cord (peripheral neuropathy, vitamin B12 levels), 14) Sub acute myeloopticoneuropathy (adverse reaction to chlorhydroxyquinoline, mainly in Japanese), 15) Hereditary spastic paraparesis/primary lateral sclerosis (normal CSF, MRI and visual evoked potential studies), 16) Adrenomyeloneuropathy (adrenal dysfunction, neuropathy, increased plasma very long-chain fatty acids), 16) Spinocerebellar syndromes (familial, pes cavus scoliosis, abnormal reflexes, normal CSF IgG), 17) Miscellaneous—strokes, tumors, arteriovenous malformations, arachnoid cysts, Arnold-Chiari malformations, and cervical spondylosis all may lead to diagnostic dilemmas on occasion. Thus, detailed history and neurological examination must be complemented by specific laboratory tests for the correct diagnosis of MS. Clearly there is a long felt need for more powerful diagnostic tools for prediction and staging of MS.


Etiology of MS


The etiology of MS is unknown. It is suggested that a combination of genetic background and environmental factors and immune response are involved in the disease. A certain incidence of familial occurrence has been observed, with the concordance rate among monozygotic twins being 30%, a 10-fold increase over that in dizygotic twins or first-degree relatives (Steinman, 1966; Dyment et al Mol. Gen 1997; 6:1693-98). In addition, recent research indicates that the tissue damage in MS occurs as the result of pathological autoimmune responses to several myelin antigens following exposure to an as yet undefined environmental causal agent.


However, although some environmental factors have been statistically associated with the disease, none have provided correlations of any predictive value. Environmental factors seem to trigger MS in subjects who are already genetically susceptible to the illness. Most probably no one dominant gene determines genetic susceptibility, but rather many genes, each with different influence, are involved. Indeed, the initial pathogenic process could be caused by one group of genes, while others groups could be responsible for the development and progression of the disease (Oksenberg, 2001; Compston, 1997).


Microarray Analysis and MS


Microarray technology is based on hybridization of mRNA to high-density array of immobilized target sequences. Each sequence corresponds to a specific gene(s) of interest. The labeled pool of sample mRNA is subsequently hybridized to the array (chip). Application of this technology provides the capability of monitoring thousands of various genes simultaneously. Today commercial available DNA microarrays (Affymetrix, Santa Clara Calif., USA) contain elements representing 10,000, 20,000 or more genes that have been characterized in terms of function or disease association. The preparation and use of microarrays for diagnostics, research and drug development is disclosed in, inter alia, U.S. Pat. Nos. 6,324,497 and 6,468,476 to Friend et al and 6,410,229 to Lockhart et al; and Intnl Pat. Application WO 0053625C2 and A2.


Several application of microarrays in human disease have been reported, for example the identification (marker) genes involved in ovarian carcinogenesis (Ono K., 2000); classification of genes expression profiling of cutaneous malignant melanoma (Bitter M., 2000); and expression profile of Tangl-Rearing CA1 neurons in Alzheimer's disease (Stephen, 2000). Alizaden (2000) characterized gene expression in diffuse large B cell lymphoma, where two distinct gene expression patterns, characterized by different molecular forms of B cells lymphoma, were identified. In addition, microarray technology has also been applied to diagnosis and monitoring of such diverse diseases as cancer (U.S. Pat. No. 6,511,849 to Freuhauf et al), psoriasis (Intnl Pat. Application WO 20020027538 to Trepicchio et al), T-helper cell related diseases (Trepicchio et al, Intnl Pat Application WO 20020039734), Epstein-Barr disease (U.S. Pat. Nos. 6,506,553 and 6,468,476 to Smith and Parks), rheumatoid arthritis (Intnl Pat Application WO 0248310A2 to Trepicchio et al) and Reward Deficiency Syndrome, all of which are incorporated herein by reference.


In a recent review (Greenberg S A., 2001) the author discussed the potential application of DNA microarray technology for understanding neurological disorders. Using cDNA microarrays technology, brain tissue from pathology lesions and normal white matter of single MS patient were analyzed (Whitney L W., 1999). Blood genomic fingerprints were demonstrated after experimental strokes, seizures, hypoglycemia and hypoxia of rats (Yang Tang, 2001). Similarly, microarray analysis of gene expression in brainstem and spinal cord tissues from the animal models of MS (experimental autoimmune encephalomyelitis, EAE) has identified a number of differentially expressed genes from active-acute versus silent lesions (Lock C. et al Nat Med 2002; 8,500-504), and also suggested a role for the proinflammatory cytokine osteopontin in the development of EAE in mice (Chabas D et al Science 2001; 294:1731-34).


In another recent study, Ramanathan M et al (J of Immunology 2001; 116:213-19) used cDNA microarray technology to identify abnormal gene expression patterns in PBMC of relapsing-remitting MS patients. The study compared PBMC gene expression in 15 patients during remission (only) with that of 15 healthy controls, using a GeneFilters GF211 array (Research Genetics, Huntsville Ala., USA) having approximately 5200 human gene sequences. Groups of marker genes correlated with MS were disclosed, but the range of differences (fold changes) between level of gene expression in MS and control groups was only 13 to 35% for unregulated and from 11 to 43% for down regulated genes. Such small differences are probably due to the limited sensitivity of the technology employed in using GeneFilters arrays, and may not have any clinical or diagnostically mining significance. More significantly, the population of MS patients was limited, including only patients during clinical remission, who had not received any immunosupressive treatment for at least 3 months. Thus, the markers described do not provide a profile of expression patterns useful for diagnosing clinically defined MS in patients having probable MS, or for determining stages of the disease.


Trepicchio et al. (Intnl Pat. Application No. WO 02/079218 A1) also describe the use of microarray technology in determining characteristic gene expression in an animal model of MS (murine EAE) and in tissue samples from MS patients. The human samples were PBMC or brainstem tissue, collected from 60 patients manifesting a wide variety of symptoms, at different stages of MS including relapsing-remitting, primary and secondary progressive, and acute exacerbation. RNA probes prepared from these samples were hybridized to a human chip array containing approximately 14,000 gene sequences (MicroArray, Affymetrix, cat no. 510448, Santa Clara Calif.), and expression profiles compared with those of healthy controls. Determination of the panel of “MS-related” markers was based merely on fold change of greater than 2 fold (up- or downregulated), with a confidence level of p<0.01. No more stringent statistical criteria were applied. A “panel” of 300 differentially regulated genes was thus described in the PBMC samples, and another 100 in the brain lesion tissue. However, no classification of expression profiles characteristic to specific stages of the disease was provided, and the “class predictor model”, as described, using “neighborhood analysis”, was applied for attempted prediction of “MS-afflicted” or “non-diseased” samples only. Thus, the panel of markers described is not applicable to the diagnosis of stage of MS, in general, is unsuited for the prediction of clinically definite MS or probable MS patients, and is clearly non-predictive in monitoring response to treatment.


There is thus a widely recognized need for, and it would be highly advantageous to have gene expression profiles useful in distinguishing between different forms of MS e.g.: probable, relapsing-remitting, primary or secondary as well as response to the therapy, devoid of the above limitations.


SUMMARY OF THE INVENTION

According to one aspect of the present invention there is provided a method of diagnosing a subject with multiple sclerosis, the method comprising determining a level of expression of at least one gene selected from the group consisting of the genes listed in Tables I-V in a sample obtained from the subject, wherein a substantial difference between the level of expression of the gene in the sample obtained from the subject and a normal expression level of the gene is an indication that the subject is afflicted with multiple sclerosis.


According to further features in preferred embodiments of the invention described below a method of monitoring a state of multiple sclerosis in a subject, the method comprising monitoring a level of expression of at least one gene selected from the group consisting of the genes listed in Tables I-V over a predetermined time period, wherein substantial difference between the levels of expression of the at least one gene over the predetermined time period indicates a change in a state of the multiple sclerosis in the subject.


According to further features in preferred embodiments of the invention described below monitoring the level of expression of at least one gene over the predetermined time period is effected by periodically obtaining a sample from the individual and determining the level of expression of the at least one gene in the sample.


According to still further features in the described preferred embodiments the at least one gene comprises at least 10, at least 50, at least 100, at least 250, at least 500, at least 750, at least 1000 or at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V.


According to another aspect of the present invention there is provided a method of diagnosing a subject with multiple sclerosis, the method comprising the step of determining a level of expression of each of the genes listed in Tables I-V in a sample obtained from the subject, wherein a substantial difference between expression levels of the genes in the sample obtained from the subject and normal expression levels of the genes is an indication that the subject is afflicted with multiple sclerosis.


According to further features in preferred embodiments of the invention described below the normal expression level of the at least one gene or genes is determined by measuring the level of expression of the gene or genes in at least one control sample obtained from at least one healthy individual.


According to still further features in the described preferred embodiments the sample includes peripheral blood mononuclear cells.


According to yet further features in the described preferred embodiments the substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.


According to further features in preferred embodiments of the invention described below the level of expression of the at least one gene or genes is determined by quantifying a level of a protein product thereof in the sample. According to still further features in the described preferred embodiments quantifying a level of the protein is effected using a reagent which specifically binds with the protein.


According to yet further features in preferred embodiments of the invention described below the reagent comprises an antibody or fragments thereof.


According to further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table I.


According to still further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table II.


According to yet further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table III.


According to further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table IV.


According to still further features in the described preferred embodiments at least one gene or genes are selected from the genes listed in Table V.


According to yet further features in preferred embodiments of the invention described below the level of expression of the at least one gene or genes in the sample is determined by detecting the presence in the sample of a transcribed polynucleotide or portion thereof. The transcribed polynucleotide can be mRNA.


According to further features in preferred embodiments of the invention described below the transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with the transcribed polynucleotide or portion thereof.


According to still further features in the described preferred embodiments the sample from a subject is T cells, the at least one gene or genes are selected from the genes listed in Table IV and the normal expression of the gene or genes is T-cell expression.


According to an additional aspect of the present invention there is provided a method of assessing the efficacy of a treatment regimen on multiple sclerosis in a subject, the method comprising determining a level of expression of at least one gene or genes selected from the group consisting of the genes listed in Tables I-V in samples obtained from the subject prior to, and following exposure to the treatment regimen, wherein a substantial difference in the expression level of at least one gene or genes between the samples is an indication that the treatment regimen is efficacious in treating multiple sclerosis in the subject.


According to further features in preferred embodiments of the invention described below the treatment regimen is administering at least one test compound for inhibiting multiple sclerosis.


According to still further features in the described preferred embodiments the treatment regimen is an environmental condition.


According to yet further features in the described preferred embodiments the substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.


According to further features in preferred embodiments of the invention described below the level of expression of the at least one gene or genes is determined by quantifying a level of a protein product thereof in the sample.


According to still further features in the described preferred embodiments quantifying a level of the protein is effected using a reagent which specifically binds with the protein.


According to yet further features in preferred embodiments of the invention described below the reagent comprises an antibody or fragments thereof.


According to further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table I.


According to still further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table II.


According to yet further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table III.


According to further features in preferred embodiments of the invention described below the at least one gene or genes are selected from the genes listed in Table IV.


According to still further features in the described preferred embodiments at least one gene or genes are selected from the genes listed in Table V.


According to yet further features in preferred embodiments of the invention described below the level of expression of the at least one gene or genes in the sample is determined by detecting the presence in the sample of a transcribed polynucleotide or portion thereof. The transcribed polynucleotide can be mRNA.


According to further features in preferred embodiments of the invention described below the transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with the transcribed polynucleotide or portion thereof.


According to still further features in the described preferred embodiments the sample from a subject is T cells, the at least one gene or genes are selected from the genes listed in Table IV and the normal expression of the gene or genes is T-cell expression.


According to still further features in the described preferred embodiments the at least one gene comprises at least 10, at least 50, at least 100, at least 250, at least 500, at least 750, at least 1000 or at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V.


According to another aspect of the present invention there is provided a kit for diagnosing multiple sclerosis in a subject, the kit comprising components suitable for determining expression levels of at least one gene selected from the group of genes listed in Tables I-V.


According to further features in the described preferred embodiments the reagents include at least one polynucleotide sequence selected capable of specifically hybridizing with an transcription product of the at least one gene and reagents for detecting and optionally quantifying a complex formed from the at least one polynucleotide sequence and said transcription product.


According to still further features in the described preferred embodiments the reagents include at least one antibody selected capable of specifically binding a polypeptide product of the at least one gene and reagents for detecting and optionally quantifying a complex formed from the at least one antibody and the polypeptide product.


According to further features in preferred embodiments of the invention described below the at least one gene is selected from the genes listed in Table I.


According to still further features in preferred embodiments of the invention described below the at least one gene is selected from the genes listed in Table II.


According to yet further features in preferred embodiments of the invention described below the at least one gene is selected from the genes listed in Table III.


According to further features in preferred embodiments of the invention described below the at least one gene is selected from the genes listed in Table IV.


According to still further features in the described preferred embodiments at least one gene is selected from the genes listed in Table V.


According to further features in preferred embodiments of the invention described below the kit further comprises packaging material identifying the kit as useful from diagnosing MS.


According to another aspect of the present invention there is provided a polynucleotide array comprising at least 10 and no more than 1500 polynucleotide sequences, wherein each of the sequences is selected capable of hybridizing with a transcription product of a polynucleotide sequence of a gene selected from the group of genes listed in Tables I-V.


According to further features in preferred embodiments of the invention described below the array is selected having polynucleotide sequences capable of diagnosing subjects suspected of suffering from multiple sclerosis. The subjects may also be suspected of suffering from probable multiple sclerosis, primary progressive multiple sclerosis, secondary progressive multiple sclerosis, and/or relapsing/remitting multiple sclerosis.


According to further features in preferred embodiments of the invention described below the gene is selected from the genes listed in Table I, II, III, IV and/or IV.


According to yet another aspect of the present invention there is provided an array comprising at least 10 and no more than 1500 antibodies or antibody fragments each capable of specifically binding a protein product of a gene selected from the group of genes listed in Tables I-V.


According to further features in preferred embodiments of the invention described below the array is selected having antibodies or antibody fragments capable of diagnosing subjects suspected of suffering from multiple sclerosis. The subjects may also be suspected of suffering from probable multiple sclerosis, primary progressive multiple sclerosis, secondary progressive multiple sclerosis, and/or relapsing/remitting multiple sclerosis.


According to further features in preferred embodiments of the invention described below the gene is selected from the genes listed in Table I, II, III, IV and/or IV.


Implementation of the method and system of the present invention involves performing or completing selected tasks or steps manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of preferred embodiments of the method and system of the present invention, several selected steps could be implemented by hardware or by software on any operating system of any firmware or a combination thereof.




BRIEF DESCRIPTION OF THE DRAWINGS

The invention is herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of the preferred embodiments of the present invention only, and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for a fundamental understanding of the invention, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice.


In the drawings:


FIGS. 1A-B are graphic representations of the differences in PMBC gene expression between MS patients and healthy subjects. RNA from Peripheral Blood Mononuclear Cells (PMBC) of 26 patients diagnosed with MS, and 18 healthy, age-matched controls was purified, labeled hybridized to a Genechip array (U95Av2, Affymetrix Inc. Santa Clara Calif., USA), scanned and analyzed according to manufacturer's recommendations. The data were normalized and fold ratios calculated for each gene of the MS samples against the geometric mean of the controls. FIG. 1A shows the number of MS specific genes detected having increased expression (fold change greater than 1.5) analyzed by t-test (red line), TNoM (green line) and INFO (blue line), compared with random occurrence (black line), at confidence levels (False Discovery Rates, FDR) of 90% (p=0.10) to 100% (p=0). Note the high level of significant MS-related gene expression at 95% FDR and above (arrows) (1249 distinguished genes). FIG. 1B is an infogram of the 1249 genes most significantly (p<0.05 on all three tests) distinguishing MS patients (MS) from (control) healthy controls, determined as above. Each spot represents expression of a specific gene; color intensity of overexpressed (green) and under-expressed (red) genes indicates fold increase as compared to controls. Gray color indicates genes showing no difference in expression between MS and controls.


FIGS. 2A-B are graphic representations of the differences in PMBC gene expression between MS patients during acute relapse, and MS patients in remission. RNA from PMBC of 12 relapsed, and 14 clinically in remission patients was purified, labeled, hybridized and analyzed as described for FIGS. 1A-B hereinabove. FIG. 2A shows the number of acute relapse-specific genes detected having increased expression in relapse, as analyzed by t-test (red line), TNoM (green line) and INFO (blue line), compared with random occurrence (black line), at confidence levels (False Discovery Rates, FDR) of 90% (p=0.10) to 100% (p=0). 735 genes were detected having significant relapsing-related gene expression at 95% FDR and above. FIG. 2B is an infogram analysis of the 735 genes most significantly (p<0.05 on all three tests) distinguishing acute relapsing MS patients (Relapse) from MS patients in remission (Remission). Note the different profiles of gene expression in patients undergoing treatment (Relapse+ and Remission+) compared with untreated patients (Relapse− and Remission−).



FIG. 3 is a pie chart diagram showing the breakdown, by functional character, of specific genes displaying up- or down-regulation in MS-derived MOG-reactive T-cell lines, as compared to normal-derived MOG-reactive T-cell lines. Significant MOG reactive MS-related genes are defined as genes with TNOM=0 and p=0.057 as compared to normal MOG-reactive T-cells.



FIG. 4 is a graphic representation of the differences in gene expression between MOG-stimulated T-cell lines from MS patients and healthy controls. RNA from MOG-stimulated T-cells of 4 MS patients and 3 matched controls was purified, labeled, hybridized and analyzed as described for FIGS. 1A-B hereinabove. Panel A shows a cluster analysis of 150 differentially expressed genes analyzed as described hereinabove (TNoM=0, p<0.05) distinguishing T-cells of MS (MS) patients from controls (Controls). Panel B shows a cluster analysis of the 43 most informative genes (TNoM=0, p<0.05, and fold change>1.5). Each row represents a gene, and each column represents a T-cell line form a different subject. Yellow color indicates genes with an increased expression relative to controls are yellow, and blue color indicates genes with relative decreased expression.




DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is of methods and kits for diagnosing multiple sclerosis in subjects, using novel gene expression profiles derived from peripheral blood cells. Specifically, the present invention can be used to diagnose MS in early stages of the disease, to determine clinical stage and predict the course of the disease in patients with a unclear diagnoses, to provide definition and prognostic information in patients with probable MS, to assess and monitor MS therapies and to screen new and established drugs and treatments for MS.


The principles and operation of the present invention may be better understood with reference to the drawings and accompanying descriptions.


Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of the components set forth in the following description or illustrated in the Examples and drawings. The invention is capable of other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting.


The present invention provides previously unavailable accuracy in predicting and staging MS, by identifying genes and groups of genes specifically over- and under-expressed in PBMC of patients at various stages of their disease.


As is further described in the Examples section which follows, the present inventors have conducted a broad scale analysis of PMBC expressed genes using hybridization of biotin-labeled PBMC mRNA to more than 12,000 human gene sequences provided on DNA chips. By utilizing specialized statistical analysis approaches, the present inventors identified in the microarray data the most highly informative expression profiles.


As mentioned hereinabove, multiple sclerosis is a chronic, multi-factorial neurodegenerative disease of unknown etiology, the diagnosis and classification of which remains largely clinical in nature. Identification of the stages and progression of the disease, particularly definition of the probable MS stage, is crucial to determination of optimal treatment regimen and development of effective therapies. However, the complexities of autoimmune interactions, and the variability of MS in different individuals have made diagnosis and subsequent prognosis using traditional methods inexact and challenging. Methods for more accurate diagnosis of MS are greatly needed.


The profiles of MS-related genetic markers listed in Table I represent genes exhibiting differential expression in PBMCs from a large sample of MS patients, compared to that of age-matched healthy controls. Abundance of specific gene transcripts, represented by the intensity of label hybridizing to individual sequence loci of the MicroArray (Affymetrix Inc, Santa Clara Calif.), was recorded and quantified according to the manufacturers recommended protocols (such as GeneChip 3.0 software from Affymetrix). However, rather than composing the profile of differentially expressed genes based on probabilities using simple distribution of mean intensities, as has been reported by Ramanathan et al (J Immunol 2001; 116:213-219), informative genes were selected based on the degree to which they were predictive of classification of the sample as “diseased” or “not diseased”. By applying the rigorous three-pronged statistical analysis described in detail hereinbelow, 1249 genes most informative in distinguishing between diseased and otherwise not diseased patients were identified (see Table I). By applying an even more restrictive analysis of the data in Table I (see Table II, Bonfferoni analysis), a subset of the 300 highest scoring genes was identified. These MS marker genes comprise both over-expressed and downregulated genes, and represent of a diverse group of functional gene categories. Additional analysis of the markers uncovered herein also led to the identification of another restricted marker set which can be accurately utilized to diagnose probable MS patients. As is further described hereinbelow, the identification of such a marker set represents a significant breakthrough since it enables to treat individuals at a much earlier stage of MS then previously possible.


Thus, according to one aspect of the present invention there is provided a method of diagnosing a subject with multiple sclerosis by determining a level of expression of at least one gene of the genes listed in Tables I-V in a sample obtained from the subject, wherein a substantial difference between the level of expression of the gene in the sample obtained from the subject and a normal expression level of the gene is an indication that the subject is afflicted with multiple sclerosis.


Normal expression levels of a marker or markers are obtained from isolated or cultured PMBCs (e.g., T-cell cultures), or samples obtained from individuals not affected with MS. A substantial difference is preferably of a magnitude that is statistically significant (see the Examples section for more detail). In particularly preferred embodiments, the marker is increased or decreased relative to control samples by at least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold or more. Similarly, one skilled in the art will be well aware of the fact that a preferred detection methodology is one in which the resulting detection values are above the minimum detection limit of the methodology utilized.


As is further described in the Examples section which follows, the marker listed in Tables I-V were identified in peripheral blood cells. As such, the sample obtained from the individual is preferably a peripheral blood sample or any sample which includes blood cells such as T-cells. In a preferred embodiment, the sample is blood, thymus, spleen, lymph, pus, or bone marrow. However, it will be apparent to one skilled in the art that PMBCs may be present as an infiltrate in many other tissues, and that such tissues may also serve as samples in which the presence, activity, and/or quantity of the markers of the invention may be assessed. The tissue samples containing one or more of the markers themselves may be useful in the methods of the invention, and one skilled in the art will be well aware of methods by which such samples may be conveniently obtained, stored, preserved and processed. For further description relating to collection and processing of blood samples please see the Examples section which follows.


As is detailed in the Examples section below, analysis of PBMC genes differentially expressed in MS, according to the methods described herein, revealed groups of genes of specific interest in MS. Genes that are most significantly over expressed, or downregulated in MS can indicate members of pathways important to disease development or pathology. Strongly overexpressed genes, according to Tables I and II, include SLAM (signaling lymphocyte activation molecule, GenBank Accession No. U33017), LEF1 (lymphoid enhancer-binding factor 1, GenBank Accession No. AL099409), LRP5 (low density lipoprotein receptor-related protein 5, GenBank Accession No. AF077820), LILRB (leukocyte immunoglobulin-like receptor, GenBank Accession No. AF004230), LY75 (lymphocyte antigen 75, GenBank Accession No. AF011333), CDW52 (GenBank Accession No. N90866), PIP5K1-gamma (Phosphatidylinositol-4-phosphate 5-kinase, type 1, gamma, GenBank Accession No. AB011161), MAP4 (Microtubule-associated protein 4, GenBank Accession No. M64571), CTSK (Cathepsin K, GenBank Accession No. X82153) and CTSB (Cathepsin B, GenBank Accession No. L22507). Strongly down-regulated genes include IL1B (Interleukin 1 beta, GenBank Accession No. M15330), TRAF6 (GenBank Accession No. U78798), SCYA20 (GenBank Accession No. U64197), IL1R (type1 receptor, GenBank Accession No. M27492), IL1RAP (receptor accessory protein, GenBank Accession No. AB006537) and IL1RN (receptor antagonist, GenBank Accession No. X52015), TGFB1 (Transforming growth Factor beta. 1, GenBank Accession No. X05839), SKI (v-ski sarcoma viral oncogene homologue, GenBank Accession No. X15218), VEGF (Vascular endothelial growth factor, GenBank Accession No. M63978), IGFBP4 (Insulin-like growth factor binding protein 4, GenBank Accession No. U20982), EREG (epiregulin, GenBank Accession No. NM001432.1), and NR4A1, NR4A2, NR4A3 (nuclear receptor family genes, GenBank Accession Nos. NM002135.1, X75918 and U12767, respectively).


Functional groups of genes strongly represented in the profile of most significantly differentially regulated genes in MS include, inter alia, apoptosis-related genes, T-cell activation and expansion related genes, cell proliferation related genes and epidermal growth factor genes. Many of the marker genes identified are associated with other MS-related genes, according to Tables I-V.


It will be appreciated that although a single marker can be used for diagnosis, diagnostic accuracy typically increases with an increase in the number of markers utilized.


As such, the diagnostic method of the present invention preferably utilizes a marker set that can range anywhere from 2 genes to 1200 genes. For example, the present method can utilize at least 10, at least 50, at least 100, at least 250, at least 500, at least 750, at least 1000 or at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V. Most preferably the markers utilized are selected from the sequences listed in Table II.


The markers sets utilized can be selected according to a statistical significance or fold change thereof (provided for each marker in Tables I-V), a higher significance and higher fold change indicating higher probability of marker accuracy. For example, a selected marker set can encompass markers displaying a high statistical significance (low P-value), preferably a P-value lower than 5.0E-02, more preferably lower than 5.0E-04, most preferably, lower than 5.0E-06. Alternatively, markers can be selected according to shared features of the marker gene. For example, gene markers of similar cellular function (e.g., genes of a signaling pathway such as apoptosis) or markers displaying similar activity (e.g., enzymes of the same enzyme family) can be grouped into specific marker sets.


Each marker set may be considered individually, although it is within the scope of the invention to provide combinations of two or more marker sets for use in the methods and compositions of the invention to increase the confidence of the analysis.


As used herein, the terms “polynucleotide” and “oligonucleotide” are used interchangeably, and include polymeric forms of nucleotides of any length, either deoxyribonucleotides or ribonucleotides, or analogs thereof. Polynucleotides may have any three-dimensional structure, and may perform any function, known or unknown. The following are non-limiting examples of polynucleotides: a gene or gene fragment, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers. A polynucleotide may comprise modified nucleotides, such as methylated nucleotides and nucleotide analogs. If present, modifications to the nucleotide structure may be imparted before or after assembly of the polymer. The sequence of nucleotides may be interrupted by non-nucleotide components. A polynucleotide may be further modified after polymerization, such as by conjugation with a labeling component. The term also includes both double- and single-stranded molecules. Unless otherwise specified or required, any embodiment of this invention that is a polynucleotide encompasses both the double-stranded form and each of two complementary single-stranded forms known or predicted to make up the double-stranded form.


As used herein, a “gene” includes a polynucleotide containing at least one open reading frame that is capable of encoding a particular polypeptide or protein after being transcribed and translated. Any of the polynucleotide sequences described herein may be used to identify larger fragments or full-length coding sequences of the gene with which they are associated. Methods of isolating larger fragment sequences are known to those of skill in the art, some of which are described herein. A “gene product” includes an amino acid (e.g., peptide or polypeptide) generated when a gene is transcribed and translated.


As used herein, a “probe” is defined as an oligonucleotide that is provided as a reagent to detect a target present in a sample of interest by hybridizing with the target. Usually, a probe will comprise a label or a means by which a label can be attached, either before or subsequent to the hybridization reaction. Suitable labels include, but are not limited to radioisotopes, fluorochromes, chemiluminescent compounds, dyes, and proteins, including enzymes.


As used herein, “expression” includes the process by which polynucleotides are transcribed into mRNA and translated into peptides, polypeptides, or proteins. “Differentially expressed”, as applied to a gene, includes the differential production of mRNA transcribed from a gene or a protein product encoded by the gene. A differentially expressed gene may be overexpressed or underexpressed as compared to the expression level of a normal or control cell. In one aspect, it includes a differential that is 2.5 times, preferably 5 times or preferably 10 times higher or lower than the expression level detected in a control sample. The term “differentially expressed” also includes nucleotide sequences in a cell or tissue which are expressed where silent in a control cell or not expressed where expressed in a control cell.


As used herein, the term “polypeptide” is defined as a compound of two or more subunit amino acids, amino acid analogs, or peptidomimetics. The subunits may be linked by peptide bonds. In another embodiment, the subunit may be linked by other bonds, e.g., ester, ether, etc. As used herein the term “amino acid” includes either natural and/or unnatural or synthetic amino acids, including glycine and both the D or L optical isomers, and amino acid analogs and peptidomimetics. A peptide of three or more amino acids is commonly referred to as an oligopeptide. Peptide chains of greater than three or more amino acids are referred to as a polypeptide or a protein.


As used herein, the term “marker” is defined as a polynucleotide or polypeptide molecule which is present or absent, or increased or decreased in quantity or activity in subjects afflicted with multiple sclerosis, or in cells involved in multiple sclerosis. The relative change in quantity or activity of the marker is correlated with the incidence or risk of incidence of multiple sclerosis or progression from one stage of the disease to another.


Although all of the markers listed in Tables I-V can be used in diagnosis of MS, an additional object of the present invention was to identify those markers which can be utilized to diagnose specific clinical forms and/or stages of MS.


Accurate clinical tools for specific diagnosis of disease stages in MS are presently unavailable.


As a result of comprehensive studies conducted in efforts to evaluate specific gene expression in relation to clinical disease phases, the present invention provides, for the first time, specific markers sets which can be utilized in accurate diagnosis of specific forms and stages of MS


As is illustrated in Example II of the Examples section which follows, the present invention provides marker sets which can be accurately utilized to diagnose acute relapse, remission and probable stages of MS (Tables III-V).


Of particular importance is the marker set provided in Table V. As is described in the Examples section which follows, the present inventors also uncovered cellular markers which distinct between disease-related and non-disease related T-cell myelin reactivity. Although MS appears to be caused by autoimmune T-cells activated against myelin self-antigens, myelin-reactive T-cells have been demonstrated in healthy subjects as well. Thus, distinction between disease-related and non-disease related T-cell myelin reactivity is of great clinical and investigational importance.


Cellular markers which distinct between disease-related and non-disease related T-cell myelin reactivity include down-regulating apoptosis associated genes, up regulating anti-apoptotic genes and genes responsible for increased expansion capability of autoreactive T cells and enhanced ability to penetrate the CNS. Thus, the markers of Table V include genes involved in perpetuating pathologic cellular proliferation and tissue destruction within the CNS characteristic of MS, along with increased resistance to regulation. This marker set accurately defines the requirements for an individual to develop MS, and thus has important predictive value, especially in diagnosing individuals having MS in the “probable” stage.


The identification of these markers significantly advances the field of MS diagnosis and treatment as well as provides tools which will enable elucidation of the mechanisms underlying MS formation and progression, ultimately leading to formulation of efficient, stage specific, treatment regimens.


The markers of the invention may be nucleic acid molecules (e.g., DNA, cDNA, or RNA) or the polypeptides encoded thereby. As such, detection of markers in a sample obtained from an individual can be effected using various detection methods well known to the ordinary skilled artisan.


Briefly, measurement of the relative amount of nucleic acid or polypeptide molecules can be effected by any method known in the art (see, e.g., Sambrook, J., Fritsh, E. F., and Maniatis, T. Molecular Cloning: A Laboratory Manual. 2nd, ed, Cold Spring Harbor Laboratory, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., 1989; and Current Protocols in Molecular Biology, eds. Ausubel et al. John Wiley & Sons: 1992). Typical methodologies for RNA detection include RNA extraction from a cell or tissue sample, followed by hybridization of a labeled probe (e.g., a complementary nucleic acid molecule) specific for the target RNA to the extracted RNA, and detection of the probe (e.g., Northern blotting). Typical methodologies for polypeptide detection include activity assays in cases of known enzymes, protein extraction from a cell or tissue sample, followed by hybridization of a labeled probe (e.g., an antibody) specific for the target protein to the protein sample, and detection of the probe. The label group can be a radioisotope, a fluorescent compound, an enzyme, or an enzyme co-factor. Detection of specific polypeptide and nucleic acid molecules may also be assessed by gel electrophoresis, column chromatography, direct sequencing, or quantitative PCR (in the case of nucleic acid molecules) among many other techniques well known to those skilled in the art.


Probes based on the nucleotide sequence of a marker gene or of a nucleic acid molecule encoding a marker polypeptide of the invention can be used to detect transcripts or genomic sequences corresponding to the marker gene(s) and/or marker polypeptide(s) of the invention. In preferred embodiments, the probe comprises a label group attached thereto, e.g., the label group can be a radioisotope, a fluorescent compound, an enzyme, or an enzyme co-factor. Such probes can be used as a part of a diagnostic test kit for identifying cells or tissue which misexpress (e.g., over- or under-express) a marker polypeptide of the invention, or which have greater or fewer copies of a marker gene of the invention. For example, a level of a marker polypeptide-encoding nucleic acid in a sample of cells from a subject may be detected, the amount of mRNA transcript of a gene encoding a marker polypeptide may be determined, or the presence of mutations or deletions of a marker gene of the invention may be assessed. The invention further encompasses nucleic acid molecules that differ from the nucleic acid sequences of the genes set forth in Tables I-V, due to degeneracy of the genetic code and which thus encode the same proteins as those encoded by the genes shown in Tables I-V.


An isolated marker protein, or a portion or fragment thereof, can be used as an immunogen to generate antibodies that bind marker proteins using standard techniques for polyclonal and monoclonal antibody preparation. A full-length marker protein can be used or, alternatively, the invention provides antigenic peptide fragments of these proteins for use as immunogens. The antigenic peptide of a marker protein comprises at least 8 amino acid residues of an amino acid sequence encoded by a gene set forth in Tables I-V, and encompasses an epitope of a marker protein such that an antibody raised against the peptide forms a specific immune complex with the marker protein. Preferably, the antigenic peptide comprises at least 10 amino acid residues, more preferably at least 15 amino acid residues, even more preferably at least 20 amino acid residues, and most preferably at least 30 amino acid residues. Preferred epitopes encompassed by the antigenic peptide are regions of the marker protein that are located on the surface of the protein, e.g., hydrophilic regions, as well as regions with high antigenicity.


An anti-marker protein antibody (e.g., monoclonal antibody) can be used to isolate a marker protein of the invention by standard techniques, such as affinity chromatography or immunoprecipitation. An anti-marker protein antibody can facilitate the purification of natural marker proteins from cells and of recombinantly produced marker proteins expressed in host cells. Moreover, an anti-marker protein antibody can be used to detect marker protein (e.g., in a cellular lysate or cell supernatant) in order to evaluate the abundance and pattern of expression of the marker protein. Anti-marker protein antibodies can be used diagnostically to monitor protein levels in tissue as part of a clinical testing procedure, e.g., to, for example, determine the efficacy of a given treatment regimen. Detection can be facilitated by coupling (i.e., physically linking) the antibody to a detectable substance. Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, -galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include 125I, 131I, 35S or 3H.


The nucleic acid and protein sequences of the present invention can further be used as a “query sequence” to perform a search against public databases to, for example, identify other family members or related sequences. Such searches can be performed using the NBLAST and XBLAST programs (version 2.0) of Altschul, et al. (J. Mol. Biol. 1990; 215:403-10). BLAST nucleotide searches can be performed with the NBLAST program, score=100, wordlength=12 to obtain nucleotide sequences homologous to nucleic acid molecules of the invention. BLAST protein searches can be performed with the XBLAST program, score=50, wordlength=3 to obtain amino acid sequences homologous to marker protein molecules of the invention. To obtain gapped alignments for comparison purposes, Gapped BLAST can be utilized as described in Altschul et al., (1997) Nucleic Acids Res. 25(17):3389-3402. When utilizing BLAST and Gapped BLAST programs, the default parameters of the respective programs (e.g., XBLAST and NBLAST) can be used. See http://www.ncbi.nlm.nih.gov.


It will be appreciated that non-coding sequences, such as promoter or other regulatory sequences of marker genes may be used as probes in the context of the present invention. Thus, the expression of groups of functionally related genes, responsive to similar signals important to the pathogenesis or progression of multiple sclerosis, may be assessed.


It will be appreciated that in certain cases the genes themselves can serve as markers. For example, mutations in the nucleic acid sequence of a gene (e.g., non-sense, mis-sense deletion and the like) which result in lower expression levels of the gene or lower activity of the gene product may be correlated with MS. Similarly, a duplication of the gene, which can result in higher expression levels or mutations which result in higher activity can also be correlated with MS.


Detection of the presence or number of copies of all or a part of a marker gene of the invention may be performed using any method known in the art. Typically, it is convenient to assess the presence, quantity and quality of genomic DNA by Southern analysis, in which total DNA from a cell or tissue sample is extracted, is hybridized with a labeled probe (e.g., a complementary DNA molecule), and the probe is detected. The label group can be a radioisotope, a fluorescent compound, an enzyme, or an enzyme co-factor. Other useful methods of DNA detection and/or quantification include direct sequencing, gel electrophoresis, column chromatography, and quantitative PCR, as is known by one skilled in the art.


In cases where detection involves discrete marker sets, the detection method of the present invention preferably employs marker probes which are conjugated to a solid support. For example, polynucleotide probes capable of specifically hybridizing with polynucleotide markers of the present invention (e.g., mRNA) may be coupled to an array (e.g., a GeneChip array for hybridization analysis), to a resin (e.g., a resin which can be packed into a column for column chromatography), or a matrix (e.g., a nitrocellulose matrix for northern blot analysis). The immobilization of molecules complementary to the marker(s), either covalently or noncovalently, permits a discrete analysis of the presence or activity of each marker in a sample. In an array, for example, polynucleotides complementary to each member of a marker set may individually be attached to different, known locations on the array (region-specific arrays). The array may be hybridized with, for example, polynucleotides extracted from a blood sample obtained from a subject. The hybridization of polynucleotides extracted from the sample with the array at any location on the array can be detected, and thus the presence or quantity of the marker in the sample can be ascertained. In a preferred embodiment, a “GeneChip” array is employed (e.g., an Affymetrix type array). Similarly, Western analyses may be performed on immobilized antibodies specific for different polypeptide markers hybridized to a protein sample from a subject.


It will also be apparent to one skilled in the art that the probes of the array need not bind with the entire marker molecule. A probe designed to bind a portion of the marker of sufficient length for detection purposes (e.g., for hybridization), for example, a portion of the marker which is 7, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 100 or more nucleotides or amino acids in length may be sufficient for detection purposes.


Polynucleotide probes can be synthesized using any known synthesis method. Preferably, synthesis is effected using on-chip lithography methodology in a manner similar to that utilized for the synthesis of Affymetrix chips (www.affymetrix.com). Additional methods of array production and methodology are described in detail in the U.S. patent applications cited in the Background section hereinabove.


Antibody probes useful for detecting polypeptide markers can be generated using various well known techniques. For example, monoclonal antibodies which can be used per se or as a basis for antibody fragments (scFv, Fab etc) can be synthesized using isolated Hybridomas. In such an approach, a protein corresponding to a marker of the invention is isolated (e.g., by purification from a cell in which it is expressed or by transcription and translation of a nucleic acid encoding the protein in vivo or in vitro using known methods. A vertebrate, preferably a mammal such as a mouse, rat, rabbit, or sheep, is immunized using the isolated protein or protein fragment. The vertebrate may optionally (and preferably) be immunized at least one additional time with the isolated protein or protein fragment, so that the vertebrate exhibits a robust immune response to the protein or protein fragment. Splenocytes are isolated from the immunized vertebrate and fused with an immortalized cell line to form hybridomas, using any of a variety of methods well known in the art. Hybridomas formed in this manner are then screened using standard methods to identify one or more hybridomas which produce an antibody which specifically binds with the protein or protein fragment.


The invention also includes an array comprising a marker(s) of the present invention. The array can be used to assay expression of one or more genes in the array.


In one embodiment, the array can be used to assay gene expression in a tissue of multiple sclerosis patients at different stages of the disease to ascertain stage specificity of genes in the array. In this manner, more than about 30,000 genes can be simultaneously assayed for expression. This allows a profile to be developed showing a battery of genes specifically expressed in one or more stages of the disease.


In addition to such qualitative determination, the invention allows the quantitation of gene expression. Thus, not only stage specificity, but also the level of expression of a battery of stage specific genes is ascertainable. Thus, genes can be grouped on the basis of their expression per se, and level of expression in that stage of the disease.


The detection arrays described herein are preferably packaged in kits identified for use in detecting MS in general or for detecting specific stages of MS. The kit can further include reagents suitable for the detection of polynucleotide hybridization or antibody binding and instructions for effecting diagnosis using the kit components and suitable detection hardware (e.g., detection microscope) and software (e.g., detection and analysis software). For further description of such hardware and software and detection reagents please see www.affymetrix.com.


Thus, the present invention provides methods useful for diagnosing MS including specific stages or states of the disease and also a risk of developing the disease.


These methods involve isolating a sample from a subject (e.g., a sample containing T-cells), detecting the presence, quantity, and/or activity of one or more markers of the invention in the sample relative to a normal sample. Observing a significant increase or decrease in one or more markers in the test sample indicates the presence or risk of presence of MS.


Using specific marker sets, the present invention also provides methods of assessing the severity or stage of MS in a subject.


As detailed hereinabove, a major concern in treatment of multiple sclerosis is accurate early diagnosis following the first acute attack. At present, clinical studies indicate that only 40-50% of individuals suffering a first acute attack will progress to clinically definite MS. Thus, treatment protocols most commonly suspend treatment of these patients defined as probable MS, until the appearance of a second attack, which may entail years of waiting and uncertainty. It will be appreciated that early and accurate detection of the portion of probable MS patients likely to progress to further stages of the disease can save undue suffering and expense, and, more importantly, provide early treatment and a better prognosis for the portion of probable MS patients likely to progress to more severe stages. The present invention provides, for the first time, marker genes for probable MS, as well as for relapsing vs. remitting MS.


The present invention also provides methodology which can be used to assess the efficacy of an MS treatment regimen and/or the effect of environmental factors or diet on the progression of MS.


These methods involve isolating a sample from a subject (e.g., a sample containing T-cells) suffering from MS who is undergoing treatment which includes drug therapy, exposure to a predetermined environmental condition and/or a specific diet, detecting the presence, quantity, and/or activity of one or more markers of the invention in test samples obtained from the subject prior to and following treatment or in a test sample obtained from the subject relative to a sample obtained from an individual suffering from MS who is not undergoing any treatment and/or relative to a sample obtained from an individual not suffering from MS and undergoing treatment. The levels of markers in the samples are compared, and significant increases or decreases in one or more markers in the test sample following treatment relative to the other samples are observed, and correlated with the severity or stage of MS. By assessing whether MS has been lessened or alleviated, the ability of the treatment or therapy to treat MS is also determined.


It will be appreciated that the present invention also provides methods of treating (e.g., inhibiting) the formation or progression of MS. These methods involve isolating a sample from a subject (e.g., a sample containing PMBCs such as T-cells), detecting the presence, quantity, and/or activity of one or more markers of the invention in the sample relative to a normal sample and observing significant increases or decreases in one or more markers in the test sample. For markers that are significantly decreased in expression or activity, the subject may be administered that expressed marker protein, or may be treated by the introduction of mRNA or DNA corresponding to the decreased marker (e.g., by gene therapy), to thereby increase the levels of the marker protein in the subject. For markers that are significantly increased in expression or activity, the subject may be administered mRNA or DNA antisense to the increased marker (e.g., by gene therapy), or may be administered antibodies specific for the marker protein, to thereby decrease the levels of the marker protein in the subject. In this manner, the subject may be treated for MS or MS related condition.


In another embodiment, the methods further involve obtaining a control biological sample (e.g., nondiseased tissue) from a control subject, contacting the control sample with a compound or agent capable of detecting marker protein, mRNA, or genomic DNA, such that the presence of marker protein, mRNA or genomic DNA is detected in the biological sample, and comparing the presence of marker protein, mRNA or genomic DNA in the control sample with the presence of marker protein, mRNA or genomic DNA in the test sample.


The invention also provides methods for identifying modulators, i.e., candidate or test compounds or agents (e.g., peptides, peptidomimetics, peptoids, small molecules or other drugs) which (a) bind to the marker, or (b) have a modulatory (e.g., stimulatory or inhibitory) effect on the activity of the marker or, more specifically, (c) have a modulatory effect on the interactions of the marker with one or more of its natural substrates (e.g., peptide, protein, hormone, co-factor, or nucleic acid), or (d) have a modulatory effect on the expression of the marker. Such assays typically comprise a reaction between the marker and one or more assay components. The other components may be either the test compound itself, or a combination of test compound and a natural binding partner of the marker. The test compounds of the present invention may be obtained from any available source, including systematic libraries of natural and/or synthetic compounds. Test compounds may also be obtained by any of the numerous approaches in combinatorial library methods known in the art, including: biological libraries; peptoid libraries (libraries of molecules having the functionalities of peptides, but with a novel, non-peptide backbone which are resistant to enzymatic degradation but which nevertheless remain bioactive; (see, e.g., Zuckermann et al., 1994, J. Med. Chem. 37:2678-85); spatially addressable parallel solid phase or solution phase libraries; synthetic library methods requiring deconvolution; the ‘one-bead one-compound’ library method; and synthetic library methods using affinity chromatography selection. The biological library and peptoid library approaches are limited to peptide libraries, while the other four approaches are applicable to peptide, non-peptide oligomer or small molecule libraries of compounds (Lam, 1997, Anticancer Drug Des. 12:145).


Additional objects, advantages, and novel features of the present invention will become apparent to one ordinarily skilled in the art upon examination of the following examples, which are not intended to be limiting. Additionally, each of the various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below finds experimental support in the following examples.


EXAMPLES

Reference is now made to the following examples, which together with the above descriptions, illustrate the invention in a non limiting fashion.


Generally, the nomenclature used herein and the laboratory procedures utilized in the present invention include molecular, biochemical, microbiological and recombinant DNA techniques. Such techniques are thoroughly explained in the literature. See, for example, “Molecular Cloning: A laboratory Manual” Sambrook et al., (1989); “Current Protocols in Molecular Biology” Volumes I-III Ausubel, R. M., ed. (1994); Ausubel et al., “Current Protocols in Molecular Biology”, John Wiley and Sons, Baltimore, Md. (1989); Perbal, “A Practical Guide to Molecular Cloning”, John Wiley & Sons, New York (1988); Watson et al., “Recombinant DNA”, Scientific American Books, New York; Birren et al. (eds) “Genome Analysis: A Laboratory Manual Series”, Vols. 1-4, Cold Spring Harbor Laboratory Press, New York (1998); methodologies as set forth in U.S. Pat. Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and 5,272,057; “Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis, J. E., ed. (1994); “Culture of Animal Cells—A Manual of Basic Technique” by Freshney, Wiley-Liss, N.Y. (1994), Third Edition; “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds), “Basic and Clinical Immunology” (8th Edition), Appleton & Lange, Norwalk, Conn. (1994); Mishell and Shiigi (eds), “Selected Methods in Cellular Immunology”, W. H. Freeman and Co., New York (1980); available immunoassays are extensively described in the patent and scientific literature, see, for example, U.S. Pat. Nos. 3,791,932; 3,839,153; 3,850,752; 3,850,578; 3,853,987; 3,867,517; 3,879,262; 3,901,654; 3,935,074; 3,984,533; 3,996,345; 4,034,074; 4,098,876; 4,879,219; 5,011,771 and 5,281,521; “Oligonucleotide Synthesis” Gait, M. J., ed. (1984); “Nucleic Acid Hybridization” Hames, B. D., and Higgins S. J., eds. (1985); “Transcription and Translation” Hames, B. D., and Higgins S. J., eds. (1984); “Animal Cell Culture” Freshney, R. I., ed. (1986); “Immobilized Cells and Enzymes” IRL Press, (1986); “A Practical Guide to Molecular Cloning” Perbal, B., (1984) and “Methods in Enzymology” Vol. 1-317, Academic Press; “PCR Protocols: A Guide To Methods And Applications”, Academic Press, San Diego, Calif. (1990); Marshak et al., “Strategies for Protein Purification and Characterization—A Laboratory Course Manual” CSHL Press (1996); all of which are incorporated by reference as if fully set forth herein. Other general references are provided throughout this document. The procedures therein are believed to be well known in the art and are provided for the convenience of the reader. All the information contained therein is incorporated herein by reference.


Materials and Methods

Subjects—Blood was obtained from patients or controls after written informed consent. For comparison of healthy controls and MS patients, and between MS patients in acute relapse or remission: Gene expression profiles of 26 patients (20 females, mean age 41.0±2.5 years) with definite diagnosis of MS according to Poser criteria (8), a relapsing-remitting disease course, and brain magnetic resonance imaging ascertaining the diagnosis (9) were compared with eighteen (18) age-matched healthy subjects (16 females). For comparison of transcriptional profiles in MOG-reactive T-cells: Four MS female patients (mean age 38±4.2 years, mean disease duration 9.3±3.3 years) having a definite MS according to Poser criteria (10), a relapsing-remitting disease course, neurological disability evaluated by the expanded disability status scale (EDSS, 11) between 2 to 5.0, and brain MRI supporting the diagnosis of MS, and three age- and sex-matched healthy controls were included in the study. None of the patients received immunomodulatory drugs or steroid treatment for at least three months prior to when blood was drawn. The studies were approved by the institutional review board and the Israel Ministry of Health.


mRNA preparation—Total RNA was isolated from Ficoll™ isolated Peripheral Blood. Mononuclear Cells (PBMC) or from MOG-stimulated T cell lines (2×107 cells) by ice-cold TRIZOL Reagent (Gibco, BRL). Poly-A mRNA was isolated using a mini-kit (Oligotex, Qiagen) and used as a template for double-stranded cDNA synthesis using oligo (dT)-24 primers containing a T7 RNA polymerase promoter site added to the 3′-end (Genset). After phenol/chloroform extraction cDNA was used as a template for in vitro transcription (Ambion T7 Megascript system) with biotin labeled nucleotides (Enzo Diagnostics). Labeled cRNA was fragmented, quantified by spectrophotometer, and hybridized to the microarrays.


Microarray gene analysis—Each Genechip (U95Av2) which carries probes for 12,625 (or U133A with 22,000 for patients with probable MS diagnosis) transcripts was hybridized with 10 μg/200 μl hybridization mix, stained and scanned (Hewlett Packard, GeneArray™ scanner G2500A) according to manufacturer protocol (Affymetrix Inc, Santa Clara, Calif.). Scaling procedure was performed to an average intensity of 600 per gene. A value of 20 was assigned to all measurements lower then 20. For comparison of healthy controls and MS patients, and between MS patients in acute relapse or remission: All data was normalized by dChip software and fold ratios were calculated for each gene of the samples against geometric means of the matched controls. For comparison of transcriptional profiles in MOG-reactive T-cells: Genes that did not have at least one average difference intensity value≧100 or were present at least once by Affymetrix criteria, were not included in the analysis.


Data analysis—The analysis was performed according to the analytical approach as previously described (24-26). Genechip 4 software (Affymetrix Inc, Santa Clara, Calif.) was used for analysis of the scanned arrays. Fold ratios were calculated for each gene of the samples against the geometric mean of matched controls. For comparison of transcriptional profiles in MOG-reactive T-cells: To determine the most informative genes threshold number of misclassifications (TNoM) score was applied. This score counts the number of classification errors that occur between compared groups for each gene of the dataset. The best threshold (TNoM=0) implies that no errors have been counted and the distinction between the two groups in relation to the expression level of a specific gene is maximal. To select a group of strongly differential expression, t-test p-value (comparing expression levels of genes from MS patients vs. healthy controls) were also computed. Genes with TNoM=0, fold-change>1.5 (either up or down regulated) and corresponded t-test P value<0.05, were designated as most informative. For comparison of healthy controls and MS patients, and between MS patients in acute relapse or remission: The data was analyzed by the classic parametric t-test, and the following non-parametric tests: (i) Threshold number of misclassifications (TNoM) method and (ii) INFO score that measures the misclassifications made by a simple threshold in terms of the information lost. Analysis was performed between MS patients and the control group for each gene of the dataset as well as between subgroups of patients. Only informative MS related genes (p<0.05 in all three statistical tests) were included. To retrieve the most informative genes, the False Discovery Rate (FDR) method (14) that ranks and tests all “P” values against different thresholds was used. The degree of significance by the Bonferroni threshold method, which evaluates the allowed error probability divided by the number of genes measured, and ensures that each and every validated scoring event is indeed a significant event, was also calculated.


Validation Strategy—To further assess the predictive power of the data sets, computerized analysis by the Leave-One-Out-Cross-Validation (LOOCV) statistical method was performed. The method simulates removal of a single sample every trial and trains on the rest. The procedure is repeated until each sample is left out once and the number of correct and incorrect predictions is counted.


Example I
Accurate Gene Expression Profiles of MS

In order to provide an accurate, reliable profile of gene markers for diagnosis and evaluation of MS, DNA chip analysis was used to compare multiple gene expression patterns of PBMCs from patients with different clinical forms of MS. After informed consent blood was obtained from 26 patients (20 females, mean age 41.0±2.5 years) with definite diagnosis of MS according to Poser criteria, a relapsing-remitting disease course, and brain magnetic resonance imaging ascertaining the diagnosis. Eighteen age-matched healthy subjects (16 females) served as controls. PBMC gene expression of 12,625 human genes was analyzed as described hereinabove, using Ficoll™ for preparation of PBMCs and total RNA purification and sample preparation according to the instructions of Affymetrix, Inc (Affymetrix, Santa Clara Calif., USA). In order to determine the most informative genes, unique computerized scoring methods, as yet not applied to analysis of data regarding MS, were employed. In brief, a gene is designated as informative based on the degree to which its tissue expression level is predictive of an independent classification of the tissue sample as “diseased” or “not diseased”, as previously described by Ben-Dor et al (J Comput Biol 2000; 7:559-63) and applied to the analysis of breast cancer and melanoma using cDNA arrays (for review see Freidman N et al Ernst Schering Res Found Wkshp 2002; 38:109-31). The scores used in this study were:


TNoM (Total Number of Misclassifications)—the number of classification errors committed when using the best simple threshold to distinguish between two classes (diseased or not diseased) based on the expression levels of a specific gene.


INFO—an estimate of the uncertainty remaining about accuracy of a sample classification (diseased or not diseased) after the incorporation of predictions based on expression of an individual gene is given (a lower “INFO” score indicates a higher predictive value for a given gene).


Gaussian (t-test)—The overlap between distributions of expression levels for genes in two classes. The score is based on normality assumptions.


One of the advantages of the analytic methods used here is their amenability to rigorous statistical benchmarking. Using this unique analysis, the number of informative genes per score expected in a random classification can be calculated, and then this estimated number of high scoring (or informative) genes can be compared to the actual number of informative genes (per score) measured in a dataset.


Comparison of the gene expression profiles shows that gene expression of PBMC in MS patients is significantly different from that in healthy subjects. Under the null-hypotheses that the separation of the samples is random despite genetic heterogeneity between tested groups, observed significant overabundance of informative genes was observed (FIG. 1A). The difference between expected and observed number of genes with significant p value in all 3 statistical tests (t-test, TNoM, INFO) performed, indicates that the diversity in gene expression observed in PBMC is biologically significant.


The predictive power of the data sets results was assessed by performing computerized error estimates based on leave-one-out cross validation (LOOCV) trials. The results disclosed only 3 classification errors. This low rate of error estimates suggest that the gene expression signature in MS is reliable for the diagnosis of the disease using peripheral blood and confirms that the patterns we observed accurately represent significant biologic phenomena associated with MS. The false discovery rate (FDR) method distinguished 1249 most informative genes that pass 95% FDR on all three statistical tests (t-test, TNoM, INFO) at p<0.05 (FIG. 1B and Table I).


Confirmation of gene microarray expression findings was performed by RT-PCR for the following five randomly selected genes: EGFL5, P44, GS3686, MX1 and CCR2. Significant correlations (coefficients ranged from 0.76 to 0.98) were found between the relative number of expression genes analysis and the RT-PCR profile. The data from microarray hybridizations was further tested against the strict Bonferroni threshold method from all three statistical tests, as described hereinabove, resulting in 300 top scoring genes that distinguish between MS and healthy subjects. (Table II).


The 1249 most informative genes (681 up-regulated, 569 down-regulated, Table I) consist of inflammatory, apoptosis and cell signaling pathways components, cytokines, antigen presentation molecules and chemokines as well as number of expressed sequence tags (ESTs).


Over-expressed genes in MS—The most abundant over-expressed transcripts unique to MS include: (i) SLAM (signaling lymphocyte activation molecule) a member of the immunoglobulin gene superfamily that is involved in T-cell stimulation. SLAM potentiates T-cell expansion and was described as CD28 independent co-stimulatory molecule, selectively increasing interferon gamma production and dysregulating type 1 and type 2 cytokine production in MS upon T-cell receptor activation. The surprising observation of SLAM upregulation suggests an enhanced proliferation of autoreactive T cells in MS patients; (ii) LEF1 (lymphoid enhancer-binding factor 1) one of the transcriptional factors expressed in pre-B and T cells, and known to be associated with T cell receptor (TCR) stimulation and apoptosis survival of pro-B cells (19); (iii) LRP5 (low density lipoprotein receptor-related protein 5) a of cell receptor protein required for LEF1 activation; (iv) LILRB (leukocyte immunoglobulin-like receptor), a protein that binds MHC class I molecules and delivers a negative signal inhibiting killing by natural killer and regulatory T cells; (v) LY75 (lymphocyte antigen 75) an endocytotic receptor used by dendritic cells to direct captured antigens from the extracellular space to a specialized antigen-processing compartment; and (vi) CDW52, a 21-28 kDa glycopeptide antigen expressed on lymphocytes and macrophages known to be a target for complement-mediated insult, inducing pro-inflammatory cytokine (e.g. TNF alpha and interferon gamma) production. Other up-regulated genes are members of the anti-apoptotic pathways, and include PIP5K1-gamma (Phosphatidylinositol-4-phosphate 5-kinase, type 1, gamma) and MAP4 (Microtubule-associated protein 4). Over-expression of transcripts belonging to the papain cysteine proteinase family CTSK (Cathepsin K) and CTSB (Cathepsin B) was also observed.


Down-regulated genes in MS—Abundant down-regulated transcripts unique to MS that were identified include IL1B (Interleukin 1 beta), an important inflammatory cytokine; TRAF6, which is essential for IL1 signaling; and SCYA20, known to be mediated by IL1B. Decreased mRNA expression of IL1B was strengthened by the down regulation of IL1R (type1 receptor), IL1RAP (receptor accessory protein) and IL1RN (receptor antagonist).


Other important down-regulated genes include TGFB1 (Transforming growth Factor beta 1) and SKI (v-ski sarcoma viral oncogene homologue) a component of TGFB signaling pathway, both known to inhibit cell proliferation. Thus, their under expression may contribute to autoreactive T cell expansion. Members of epidermal growth factor family such as VEGF (Vascular endothelial growth factor), IGFBP4 (Insulin-like growth factor binding protein 4) and EREG (epiregulin) were also down regulated. Additionally, mRNA expression of members of the steroid-thyroid receptors family including nuclear receptor subfamily 4, group A members 1, 2 and 3 (NR4A1, NR4A2, NR4A3) were significantly reduced. Down regulation of these genes may inhibit apoptosis through Fas ligand and tumor necrosis factor alpha or through early response of T-cell receptor induced apoptosis of thymocytes, thus mimicking positive selection.


Taken together, the identification of profiles of up- (overexpressed) and down regulated genes specific to MS indicates the suitability of the methods of the present invention for identifying validated and significant molecular signatures of PBMC gene expression in MS. While reducing the present invention to practice, it was observed that the specific disease related genes include transcripts involved in T cell activation and expansion and anti-apoptotic mediators, indicating failure of apoptosis-related elimination of autoreactive T cells.


Example II
Stage Specific Gene Expression Profiles of MS

Accurate clinical tools for specific diagnosis of disease stages in MS are presently unavailable. In order to provide a useful profile of the clinically defined stages of MS, specific gene expression was evaluated in relation to clinical disease phases. Significant overabundance was found between the number of observed and expected genes expressed in MS patients during an acute relapse and in remission (FIG. 2A). Using the methods described hereinabove, the 743 most informative genes (302 up-regulated and 441 down-regulated) with p-value<0.05 in all three scores (t-test, TNoM, INFO) that differentiated relapse from remission (FIG. 2B, Table III) were identified.


Over-expressed genes in acute relapse of MS, compared to patients in remission—The most informative over-expressed genes included CTSL (Lysosomal cystein protease L, cathepsin L) known to play a role in MHC class II antigen presentation, responsible for quantitative and qualitative difference in peptide repertoires displayed by MHC class II molecules, and having a regulatory role in epitope generation for antigens subsets. Moreover, in vitro, proteolytic CTSL processed myelin basic protein into more then 60 different 20-40-mers species, and myelin-associated glycoprotein was described as a substrate for CTSL like proteases. These data, taken together with our observation that CTSL mRNA was over expressed in the active stage of MS, offer a biochemical basis for the immunodominant epitope spreading implicated in the pathogenesis of MS. Also up-regulated is SCYA2 (Monocyte specific chemoattractant protein, MCP1), essential for monocyte and NK cells recruitment to site of inflammatory injury. Augmented SCYA2 expression level in the CNS has been identified at the onset of EAE. Other abundant up-regulated transcripts identified by the method of the present invention include CD79A, DDIT3 (DNA-damage inducible transcript 3); E2-EPF (Ubiquitin carrier protein) and COX6.


Downregulated genes in acute relapse of MS, compared to patients in remission—From the downregulated gene transcripts in acute relapse vs. remission it is important to note several programmed cell death-related genes like CCNG1 (Cyclin G1) identified as p53 dependent apoptosis; PDCD2 (Programmed cell death 2) expressed in immature thymocytes; and CTLA1 (Cytotoxic T lymphocyte associated serine esterase 1), crucial for the rapid induction of apoptosis by cytotoxic cells. Also prominently down-regulated during acute relapse was JAK1 (Janus kinase 1), a protein tyrosine kinase reported to be obligatory for several cytokines receptors, important for regulation of acute cellular response.


The results of the functional annotation of the transcriptional motifs that distinguish between acute MS relapse and remission suggest that many of the genes are involved in cellular recruitment and epitope spreading, as well as important to immunologic mechanisms related to escape from regulatory surveillance and augmentation of cell survival potential. Thus, it can be suggested that during the acute inflammatory process of the disease there is a failure of the immune regulatory cells to inhibit autoreactivity and the self-expansion of the non-restrained autoreactive T cells further lead to a vicious cycle of on going inflammatory activity.


It is evident from the gene-clustering map (FIG. 2B) that during an acute relapse no significant differences are found between relapse treated vs. relapse untreated patients. Such a result is of great clinical significance, since this may indicate that during an acute MS exacerbation the major gene expression transcripts are related to relapse associated genes and the effect of therapy is negligible. However, during remission treatment effect was more pronounced and this effect on gene suppression in treated patients was evident.


Of even greater significance is the demonstration, for the first time, of a specific gene expression profile of the “probable” stage of MS. As described hereinabove, “probable” MS precedes definitive clinical diagnosis, and is characterized by diverse neurological symptoms including unilateral loss of vision, true vertigo, ataxia, paresthesia, incontinence, diplopia, dysarthria or paralysis. Probable MS patients may suffer undiagnosed for years. In order to provide a method for accurate diagnosis of probable MS, in advance of onset of clinical symptoms, gene expression in PBMC samples of 13 probable MS patients were compared with that of samples from 5 age-matched healthy controls. RNA preparation, hybridization to MicroArray and analysis of results was performed as described for Examples 1 and 2, and in the Material and Methods section hereinabove.


As is shown in Table V, a specific “probable” MS profile of gene expression distinguishes PBMCs of diseased and healthy individuals.


Thus, there is demonstrated, for the first time, gene expression profiles providing criteria for distinguishing between stages of MS in humans, for example, between relapsing and remitting MS, probable MS and healthy individuals. Further, the groups of up- and down-regulated genes identified herein may be used for investigation of mechanisms of disease and disease progression in MS.


Example III
Gene Expression Profiles in Treatment of MS

The effect of immunomodulatory treatment on gene expression in MS patients was investigated by comparison analysis of gene transcripts between treated and untreated patients. Suprisingly, despite the variety of immunomodulatory treatments and differences between patients in relation to treatment duration, the microarray methods described herein, treatment-related gene transcripts that differentiated between treated and untreated patients were detected. Treatment-specific gene expression is mainly associated with phosphorylation and signal transduction. Thus, gene microarray technology can be a powerful tool in evaluating and monitoring clinical correlations of effects of treatment, and determining prognosis.


Thus, data presented herein demonstrate for the first time distinct and significant fingerprint cluster in MS patients that differentiates them from healthy subjects. Moreover, the stringent and specific fingerprint is predictive for the diagnosis of MS and is suitable for guiding the selection of patients for early treatment. Additionally, separate gene expression patterns were identified between acute MS relapse and remission, and treatment effects could also be identified. The methods described herein may also be used to offer superior insight into the biological mechanisms involved in the disease as well as improving functional gene characterization and transcription sites detection, important for identification of new targets for treatment and drug identification, such as T cell activation and expansion and anti-apoptotic genes like SLAM, PIP5K1-g and the NR4A1-3 steroid-thyroid receptors subfamily.


Example IV

Gene Expression Profiles of MOG-Reactive T-Cells from MS Patients


Although MS appears to be caused by autoimmune T cells activated against myelin self-antigens, myelin-reactive T-cells have been demonstrated in healthy subjects as well. Thus, distinction between disease-related and non-disease related T-cell myelin reactivity is of great clinical and investigational importance. In order to determine a profile of MS-related T-cell genes, gene expression in MOG-reactive T-cells from 4 MS patients having relapsing-remitting disease course, positive Poser criteria, and neurological disability, and 3 healthy age-matched controls was compared.


Using the microarray methods described herein, gene expression patterns obtained in MOG reactive T cell lines from MS patients detected 150 transcripts with TNoM=0, p=0.057 compared to healthy subjects (FIG. 4). These high scoring gene transcripts were defined as significant MOG reactive MS-related genes. Hierarchical clustering of gene expression patterns from MS patients and healthy controls is presented in FIG. 2, panel A. From the 150 genes with absolutely different expression levels, 43 most informative genes were further identified and clustered. These include 18 up-regulated and 25 down-regulated genes (FIG. 2, panel B).


Investigation of the known biological function of these genes (Table V) shows a great diversity of activity (A Pie-chart diagram showing the functional groups of genes included in this evaluation is presented in FIG. 3). Included are genes coding for proteins involved in the regulation and execution of apoptosis, growth factors, mediators of signal transduction pathways, molecules that participate in inflammation and also genes encoding heat shock proteins, transcription factors and components of different biochemical pathways.


Upregulated Genes in MS-Derived T-cells—Up-regulated in MS patient-derived T-cell lines are several anti-apoptotic genes such as BCL2, lifeguard, and the MAP-activated kinase MAP3K12. The BCL2 gene product is an important member of the anti-apoptotic proteins. Lifeguard (LFG), is a molecule that inhibits cell death mediated by the Fas (CD95) receptor through a unique mechanism that down regulates apoptotic signals from Fas and is associated with human autoimmune lymphoproliferative syndrome (ALPS) and in lymphoproliferative lupus-like syndrome in mice.


The MAP3K12 gene is associated with programmed cell death and encodes a polypeptide that catalyzes the phosphorylation of BAD, a member of the BCL2 anti-apoptosis protein family. Increased expression of IGFBP3 and VEGF was also demonstrated in MS-derived T cells. IGFBP-3 has been implicated in the expansion of disease related T-cell, associated with acute brain lesions of MS patients. Thus, in addition to increased survival potential, our findings suggest that autoreactive T cells in MS also have an expansion advantage compared with T cells from healthy individuals.


Furthermore, migration of autoimmune T cells into the brain would be expected to be assisted by over-expression of transcripts encoding for vascular endothelial growth factor (VEGF) in lines from MS patients. VEGF enhances vascular permeability and may facilitate migration of lymphocytes into the CNS and induction of inflammatory reactions in the brain.


Downregulated Genes in MS-Derived T-cells—The profile of gene expression in MS-derived T-cells (FIG. 4, and Table V) indicates a suppression of apoptosis-related functions in the diseased state. One aspect of failure to induce apoptosis in the MS-derived T cell lines is the significant down-regulation of the gene encoding for the pro-apoptotic molecule TNF. A reduction in TNF could also contribute to a reduction in the ratio of pro- and anti-apoptotic transcript expression in the anti-MOG T cell lines from MS patients compared to healthy controls. Indeed, inadequate apoptosis present in MS autoreactive T cell lines could lead to insufficient deletion of autoimmune activated T cell clones and increase susceptibility to autoimmunity.


In addition, effectors of MHC class I presentation were revealed to be down-regulated in MS patients' cells. Such down-regulated expression includes the transcript for the proteasome PA28 complex, known to be a principal provider of MHC class I-presented peptides in antigen presenting cells, and HSP70 1A and 1B variants. TNF is also known to stimulate MHC class I presentation in addition to induction of apoptosis. The findings presented herein indicate that a weaker antigenic MHC class I presenting capability might distinguish MS-patient derived T cell lines from their healthy counterparts, and providing powerful diagnostic tools. It is conceivable that a lower expression of MHC class-I on CD4 autoimmune T cells might enable them to escape regulation by CD8 cells that recognize autoimmune idiotypes.


Taken together the combined effects of down-regulation of apoptosis associated genes, up regulation of anti-apoptotic genes, increased expansion capability by autoreactive T cells and enhanced ability to penetrate the CNS may lead to perpetuated pathologic cellular proliferation and tissue destruction within the CNS characteristic of MS, along with increased resistance to regulation. The specific gene expression profiles described herein can define some of the requirements for an individual to develop MS, and thus have important predictive value, especially in determining MS in the “probable” stage. It is noteworthy that despite activation in vitro with the same MOG epitope, anti-MOG T cells from healthy subjects did not attain the gene expression profile that characterized the MS patient-derived cells. The findings support the concept that not all autoimmune T cells are equal; autoimmune T cells from MS patients follow a unique pattern of T cell activation that appears to be more resilient to apoptosis and can support long term survival. Although T cell lines derived from MS patients and healthy donors responded to the same autoantigen, were both activated T cell populations that proliferated extensively in the presence of IL-2, the gene expression imprints that are unique to each group were preserved. These findings indicate the existence of different T-cell activation mechanisms. The nature of the stimuli that generate aberrant autoimmune T-cell gene expression has yet to be identified in order to determine whether their formation is merely the result of the chronic immune stimulation driven by other factors in MS, or whether such T cells function as primary drivers of the MS process. Characterization of such driver T cells, dictating the state of immunity/autoimmunity can also greatly contribute to understanding autoimmunity and possibly also for designing effective treatments for MS.

TABLE IGene Expression Profile from PBMCs of MS vs. HealthyInfot-TestLog FoldIdentifierTNOM PValuePValuePValueChangeSymbolU781078.55E−111.94E−114.04E−12−0.43769NAPGM153308.55E−118.55E−112.49E−12−2.13825IL1BX152188.55E−118.55E−11 1.4E−10−1.41501SKIAF0247108.55E−118.55E−111.13E−12−1.95537VEGFU099371.84E−094.16E−102.04E−09−1.21578HSUROKR7AB0183431.84E−094.16E−109.05E−120.383078KIAA0800X740391.84E−094.16E−101.51E−10−0.67381PLAURM645711.84E−091.84E−092.41E−110.416659MAP4U641971.84E−091.84E−092.95E−10−0.62373SCYA20X684522.57E−082.93E−099.12E−11−0.26618CCND2AB0111612.57E−082.93E−099.64E−110.63432PIP5K1CL477382.57E−082.93E−097.54E−090.31646PIR121U787982.57E−082.93E−091.11E−06−0.3172TRAF6M639042.57E−087.16E−095.38E−09−0.59612GNA15U720662.57E−087.16E−094.33E−08−0.34482RBBP8AI1848022.64E−071.61E−082.67E−09−0.21576HPRP4PAF0778202.64E−071.61E−082.91E−080.656852LRP5L137402.64E−071.61E−085.83E−08−1.45891NR4A1AL0085832.64E−071.61E−081.12E−080.250082Z247242.64E−071.61E−085.96E−09−1.10426D307832.57E−082.19E−088.95E−10−1.65011EREGU479272.57E−082.19E−085.53E−090.545592USP5AI5608902.57E−082.19E−08 1.8E−070.179028Y006302.57E−083.69E−086.65E−09−2.38485SERPINB2N908662.64E−078.23E−082.76E−080.304525CDW52AF0223752.64E−078.23E−081.87E−11−1.35847VEGFM248952.11E−061.08E−071.72E−080.476779AMY2BAF0541762.11E−061.08E−076.47E−09−0.58138C1orf7L209412.64E−071.08E−071.78E−06−0.58618FTH1L054242.11E−061.08E−072.27E−09−0.58081HUMSCG19AB0023472.11E−061.08E−077.19E−100.371731KIAA0349AB0231532.11E−061.08E−071.82E−080.895842KIAA0936AF0695172.11E−061.08E−074.91E−070.399638RBM6X693922.64E−071.08E−07 1.1E−080.297444RPL26U519202.11E−061.08E−077.01E−08−0.28142SRP54L220752.64E−071.71E−07 1.1E−08−0.55736GNA13X045002.64E−071.71E−073.43E−10−2.12121IL1BAB0289512.64E−071.71E−078.78E−090.543028KIAA1028AF0042302.64E−071.71E−073.06E−070.349166LILRB1AF0705822.64E−071.71E−073.23E−08−0.19773MGC13033X663632.64E−071.71E−076.53E−07−0.24505PCTK1L338812.64E−071.71E−075.06E−08−0.59585PRKCIU330172.64E−071.71E−07 5.2E−070.373581SLAMAJ0070422.64E−071.71E−07 2.1E−070.170935WHSC1Z939302.64E−071.71E−072.42E−05−0.39839XBP1AF0791672.64E−071.71E−077.37E−10−1.93249AF0986412.64E−071.71E−071.56E−07−0.41172HG3227-HT34042.64E−071.71E−071.68E−08−0.25361U783022.64E−071.71E−072.41E−080.329878U915432.64E−072.49E−072.01E−070.478678CHD3M229192.64E−072.49E−079.52E−08−0.81053MYL6AB0290152.64E−072.49E−075.37E−090.695063PLCE2Z116971.37E−054.08E−073.55E−06−1.21033CD83AL0967801.37E−054.08E−072.13E−060.34487CHKLU512051.37E−054.08E−072.65E−07−0.76279COP9Y086831.37E−054.08E−074.71E−060.492738CPT1BS520282.11E−064.08E−079.62E−08−0.81662CTHX633682.11E−064.08E−07 2.3E−08−0.55432DNAJB2M844431.37E−054.08E−074.08E−070.303567GALK2U323241.37E−054.08E−073.21E−080.334966IL11RAAB0111151.37E−054.08E−073.39E−070.382809KIAA0543AB0145351.37E−054.08E−071.04E−060.285282KIAA0635X021521.37E−054.08E−074.63E−08−0.75601LDHAAF0071302.11E−064.08E−072.51E−060.391811LOC54104AF0071511.37E−054.08E−073.25E−060.468343MMS19LX822092.11E−064.08E−071.37E−09−0.45281MN1X798821.37E−054.08E−071.78E−070.520965MVPU916161.37E−054.08E−071.27E−07−0.80419NFKBIEU418151.37E−054.08E−072.16E−07−0.96931NUP98AB0111081.37E−054.08E−074.39E−070.453498PRP4L403771.37E−054.08E−073.49E−07−0.79409SERPINB8X996561.37E−054.08E−071.68E−06−0.23553SH3GL1AJ0100592.11E−064.08E−072.95E−060.2235SITJ029731.37E−054.08E−072.93E−07−1.30804THBDN908621.37E−054.08E−073.28E−080.43576VAMP8Y147681.37E−054.08E−077.26E−080.248383U474142.11E−067.73E−072.31E−060.370736CCNG2AB0023862.11E−067.73E−075.34E−090.586117EZH1U293442.11E−067.73E−072.35E−07−0.43842FASNAF0155532.11E−067.73E−072.61E−070.61214GTF2IAB0289812.11E−067.73E−075.34E−070.282288KIAA1058U296562.11E−067.73E−077.52E−080.353186NME3X007372.11E−067.73E−075.21E−08−0.67074NPU291852.11E−067.73E−071.56E−07−1.08006PRNPAB0079602.11E−067.73E−077.96E−060.447772SH3GLB1U448392.11E−067.73E−072.54E−07−0.97008USP11U840077.44E−051.28E−060.0002350.236422AGLS781877.44E−051.28E−061.95E−050.203265CDC25BX821537.44E−051.28E−062.27E−060.47844CTSKAL0500847.44E−051.28E−065.26E−050.509331DC8X625351.37E−051.28E−065.68E−070.243937DGKAAB0264367.44E−051.28E−060.000219−0.7589DUSP10M988337.44E−051.28E−061.52E−060.434288FL11AW0515791.37E−051.28E−067.58E−070.593476FLJ10512X167067.44E−051.28E−061.23E−06−1.09747FOSL2U909171.37E−051.28E−063.89E−070.433406FOXM1M241947.44E−051.28E−064.38E−060.560895GNB2L1AJ0021907.44E−051.28E−062.17E−080.33775GNPATX879497.44E−051.28E−064.05E−07−0.54468HSPA5U968767.44E−051.28E−063.54E−06−0.45317INSIG1AF0385641.37E−051.28E−062.05E−07−0.40446ITCHD800117.44E−051.28E−06 4.2E−07−0.35073KIAA0189AI9503821.37E−051.28E−061.63E−07−0.74128KIAA0585AB0232357.44E−051.28E−061.43E−050.311216KIAA1018AB0290387.44E−051.28E−067.62E−050.364386KIAA1115U241667.44E−051.28E−067.52E−06−0.45293MAPRE1X614987.44E−051.28E−06 8.8E−07−0.49884NFKB2U127677.44E−051.28E−062.84E−07−1.23483NR4A3U852457.44E−051.28E−064.57E−070.365266PIP5K2BU509287.44E−051.28E−064.72E−060.302213PKD2U136957.44E−051.28E−061.11E−050.805607PMS1AA2035271.37E−051.28E−061.18E−070.281992RPP20J029397.44E−051.28E−062.16E−07−0.87844SLC3A2N301517.44E−051.28E−065.05E−050.393521STX16U529602.11E−061.28E−061.51E−07−0.84863SURB7AF0302491.37E−051.28E−061.98E−070.534547AL0223987.44E−051.28E−068.09E−080.919627HG1103-HT11031.37E−051.28E−061.16E−07−0.39165D307582.11E−06 1.8E−061.58E−050.27738CENTB1U759682.11E−06 1.8E−064.36E−060.139542DDX11M691992.11E−06 1.8E−061.45E−07−1.9021G0S2U209822.11E−06 1.8E−06 1.2E−08−0.67125IGFBP4AF0407072.11E−06 1.8E−063.57E−070.289845NPR2LAB0079272.11E−06 1.8E−062.12E−070.323787REREAA9027132.11E−06 1.8E−061.44E−060.474378U660632.11E−062.24E−06 4.7E−070.277185CAMK2GD138912.11E−062.24E−064.57E−05−0.20577ID2AL0500872.11E−062.24E−061.27E−07−0.31279KIAA1785N231372.11E−062.24E−062.06E−070.247311MPHOSPH9N420072.11E−062.24E−069.19E−050.167986NUP50M745252.11E−062.24E−06 3.5E−07−0.61792UBE2BAF0352812.11E−062.24E−064.87E−070.472445U117321.37E−053.17E−063.04E−07−0.22574ETV6AB0023481.37E−053.17E−062.49E−070.576346KIAA0350AB0078911.37E−053.17E−063.99E−050.196376KIAA0431AI7543911.37E−053.17E−061.72E−06−0.27657KLF12D504061.37E−053.17E−062.65E−050.461907RECKAF0706171.37E−053.17E−063.23E−070.323494M231142.11E−064.08E−061.59E−07−0.96141ATP2A2AF0149582.11E−064.08E−061.05E−07−0.42152CCRL2AF0678531.37E−054.31E−065.02E−060.361707ADSLM735471.37E−054.31E−06 9.2E−080.438897D5S346W283191.37E−054.31E−06 1.5E−050.294631FBLN1AB0078951.37E−054.31E−069.61E−070.186643KIAA0435AB0145791.37E−054.31E−066.08E−080.367966MGEA5AF0190831.37E−054.31E−068.34E−070.17011PTENP1AL0801411.37E−054.31E−062.42E−070.330868SEC31B-1AF1103771.37E−054.31E−063.05E−050.361232TRRAPAB0024481.37E−054.31E−062.45E−070.468926AL0497871.37E−054.31E−067.11E−060.311278U505271.37E−054.31E−065.11E−060.416543Z328601.37E−054.31E−067.81E−060.133192AF0944811.37E−055.01E−062.74E−07−0.29045CGGBP1U291711.37E−055.01E−06 1.1E−06−0.6032CSNK1DAL0501961.37E−055.01E−06  2E−05−0.24688DKFZP586D2223U488071.37E−055.01E−064.97E−08−0.93178DUSP4U155521.37E−055.01E−061.67E−05−0.68094HSU15552L137401.37E−055.01E−06 9.1E−08−0.61928NR4A1AF0103091.37E−055.01E−067.36E−07−0.28533PIG3Y180041.37E−055.01E−064.19E−07−0.9465SCML2R909421.37E−055.01E−061.05E−05−0.17696ST6GALNACIVW286121.37E−055.01E−06 1.7E−06−0.25519X643307.44E−056.03E−062.27E−060.297851ACLYU498447.44E−056.03E−063.67E−070.47168ATRAB0150197.44E−056.03E−062.75E−07−0.24515BAIAP2AF0065130.0003446.03E−064.48E−05−1.45973CHD1U569980.0003446.03E−06 3.7E−06−0.74294CNKS681340.0003446.03E−068.37E−07−1.64652CREMS681340.0003446.03E−064.35E−06−2.47105CREMS682710.0003446.03E−063.03E−06−2.07185CREMAF0218190.0003446.03E−064.41E−050.298771DJ-1AF0297771.37E−056.03E−068.27E−070.290159GCN5L2U288110.0003446.03E−061.33E−060.32855GLG1S819140.0003446.03E−064.18E−07−1.59146IER3X808210.0003446.03E−068.51E−05−0.5606KIAA0874L068957.44E−056.03E−061.12E−05−0.1928MADD785791.37E−056.03E−064.25E−07−1.65638NR4A3D785797.44E−056.03E−069.62E−07−1.61438NR4A3U127670.0003446.03E−062.55E−07−2.13744NR4A3M956780.0003446.03E−06  2E−060.432923PLCB2X518040.0003446.03E−067.23E−05−0.19283PMIW287430.0003446.03E−062.78E−06−0.28926PP1628X170427.44E−056.03E−066.64E−06−0.36481PRG1M802440.0003446.03E−062.72E−06−0.8522SLC7A5AF0012941.37E−056.03E−061.23E−06−0.76359TSSC3D496777.44E−056.03E−064.18E−060.198707U2AF1RS2AB0110040.0003446.03E−061.41E−06−1.34073UAP1AB0111131.37E−056.03E−063.74E−070.444795WDR7AC0023940.0003446.03E−060.0014730.17105AL0217070.0003446.03E−064.95E−06−2.21462AL0223987.44E−056.03E−06 1.1E−070.79713AL0494420.0003446.03E−068.09E−060.621935U177600.0003446.03E−064.25E−06−0.84472L225691.37E−058.66E−061.52E−060.318129CTSBAL0310581.37E−058.66E−060.0003750.149046DSPAL0801721.37E−058.66E−061.89E−050.098968FLJ21919M368211.37E−058.66E−062.21E−07−0.36334GRO3U066311.37E−058.66E−061.31E−050.486332H326L164991.37E−058.66E−065.12E−060.374296HHEXX535861.37E−058.66E−06 3.4E−070.51291ITGA6D874661.37E−058.66E−061.49E−070.466046KIAA0276N986671.37E−058.66E−063.38E−070.367127KIAA1696X991421.37E−058.66E−061.24E−06−0.29773KRTHB6AF0113331.37E−058.66E−061.55E−050.342503LY75U707351.37E−058.66E−061.82E−060.249185MOV34-34KDU020201.37E−058.66E−061.37E−06−1.13863PBEFM317241.37E−058.66E−060.000172−0.2601PTPN1U291751.37E−058.66E−06 1.9E−060.266342SMARCA4AL0318461.37E−058.66E−060.0004180.38404Y120597.44E−051.51E−055.64E−06−0.46008BRD4U491877.44E−051.51E−051.48E−060.671467C6orf32X669457.44E−051.51E−051.91E−07−0.35494FGFR1M609227.44E−051.51E−054.47E−080.39657FLOT2AL0494097.44E−051.51E−05 1.1E−060.714173LEF1L167947.44E−051.51E−052.23E−05−0.27553MEF2DU777357.44E−051.51E−055.66E−060.574142PIM2U101177.44E−051.51E−054.07E−060.563673SCYE1AF0236141.37E−051.51E−054.79E−07−0.20744TACIS735911.37E−051.51E−054.68E−060.414777VDUP1AF0521607.44E−051.51E−051.67E−060.623021L765287.44E−051.51E−056.14E−06−0.39652U510077.44E−051.51E−051.49E−060.309996D107041.37E−051.75E−054.69E−07−0.36791CHKU971051.37E−051.75E−056.56E−071.00615DPYSL2U036341.37E−051.75E−05  1E−06−0.21467LBCL137731.37E−051.75E−056.44E−070.247919MLLT2M315231.37E−051.75E−052.09E−060.36898TCF3AL0235531.37E−051.75E−052.51E−060.226635W259847.44E−052.35E−051.42E−050.482493ACTA1U785210.0003442.35E−052.53E−050.320909AIPM307040.0003442.35E−051.65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40.349997DUTAI9519460.004820.0044678.71E−050.401112HBOAAB0023540.004820.0044670.001517−0.13368KIAA0356M360670.004820.0044678.15E−050.277858LIG1J027830.004820.0044670.002151−0.21979P4HBM372380.004820.0044670.005333−0.15474PLCG2M994380.004820.004467 6.2E−05−0.36844TLE3Z976300.004820.0044670.0027940.217849D148740.004820.0056080.000611−0.55358ADML081770.004820.0056080.000434−0.49252EBI2U095100.004820.0056085.27E−05−0.57567GARSL054240.004820.0056080.000114−0.39048HUMSCG19X139560.004820.0056080.0040980.187622MGC10471U886200.004820.0056080.000740.345628OGG1M295510.004820.0056080.0004710.319301PPP3CBAF0688360.004820.0056080.000323−0.23628PSCDBPU083160.004820.0056080.00060.205899RPS6KA3J029660.004820.0056080.000498−0.11291SLC25A4AF1074630.004820.0056080.002824−0.36924SPF30AB0004500.004820.0056080.000256−0.24717VRK2AF0705900.004820.0056080.0008340.127523AF0013830.004820.0060650.0020750.16512BIN1AF0262910.004820.0060650.000385−0.16859CCT4D638770.004820.0060650.005226−0.13956KIAA0157U143830.004820.0060650.002623−0.18669MUC8U681400.004820.0060650.0006770.172443NVLL254410.004820.0060650.000613−0.17207PGGT1BU467510.004820.0060650.000578−0.38675SQSTM1HG4740-HT51870.004820.0060650.008670.146562W268510.004820.0060650.0020520.312992U787350.004820.0063470.000529−0.09197ABCA3Y122260.004820.0063470.000397−0.21303AP1G1D382930.004820.0063470.002894−0.24373AP3M2X140460.004820.0063470.0010840.134786CD37AF0260040.004820.0063470.008622−0.07494CLCN2U460230.004820.0063470.000273−0.17969CXorf6AL0801780.004820.0063470.0006830.260343DKFZP434K171AL0801180.004820.0063470.001904−0.28696DKFZP564F1123AL0501970.004820.0063470.0042940.233045DKFZP586D0623X682770.004820.0063470.011411−0.42385DUSP1X036740.004820.0063470.0084780.174463G6PDY132860.004820.0063470.0040680.134985GDI2U192470.004820.0063470.000589−0.29688HSINFGRA7AB0231630.004820.0063470.0025370.194491HYPHL368180.004820.0063470.0071820.204818INPPL1U511270.004820.0063470.0039520.108702IRF5M153950.004820.0063470.0018630.402323ITGB2U513360.004820.0063470.0086150.336527ITPK1AJ0000080.004820.0063470.000256−0.14181PIK3C2GAI1260040.004820.0063470.0009540.262925SAS10AF0513250.004820.0063470.000144−0.43952SH2D2AU795280.004820.0063470.0025180.158101SR-BP1U524260.004820.0063479.31E−050.411984STIM1AB0183390.004820.0063470.0007510.199758SYNE-1BD436420.004820.0063470.00050.305805TCFL1D297670.004820.0063470.003934−0.09702TECM923830.004820.0063470.0014660.219769TMSB10AA1923590.004820.0063470.000280.17619TRN-SRAC0044720.004820.0063470.002169−0.15115AF0521380.004820.0063470.0001890.441167X156740.004820.0063470.007899−0.10738Z822150.004820.0063470.0025270.153792AF0705230.004820.0066340.000370.437983JWAD136410.004820.0066340.0007760.275308KIAA0016X792040.004820.0066340.0001820.256049SCA1AB0157180.004820.0066340.0011720.202412STK10AF0595750.004820.0066340.000563−0.18074M740890.004820.0066340.000760.187888U441110.004820.0066340.0038450.105361AJ2433100.004820.0069210.000945−0.97643C14orf3W268540.004820.0069210.011098−0.13774DKFZP434D156U886290.004820.0069210.001778−0.16763ELL2M598300.004820.0069210.000221−1.12882HSPA1BM959290.004820.0069210.004606−0.34536PMX1M573990.004820.0069210.010231−0.14331PTNN251170.004820.0069210.002068−0.16335RPS26AL0499400.004820.0069210.001149−0.42489RYBPU393180.004820.0069210.001097−0.24533UBE2D3Z293310.004820.0069210.000193−0.15851UBE2HM556820.004820.0069210.010264−0.10921S585440.004820.0069210.005501−0.11193L136870.004820.0073110.0021850.114008ARL2M887140.004820.0073110.0020750.114833BDKRB2AL0501730.004820.0073110.0018660.128954C21orf25M336800.004820.0073110.0026120.134487CD81X052990.004820.0073110.0038370.171613CENPBX168320.004820.0073110.0005780.177395CTSHU834100.004820.0073110.0052070.219569CUL2AL0500180.004820.0073110.0039380.220539DKFZP564B116AL0800630.004820.0073110.0065620.186332DKFZP564I052AL0502860.004820.0073110.0007670.221397DKFZP586A011X636920.004820.0073110.0031740.172997DNMT1AA5225370.004820.0073110.0027620.113812ELAC2AI1834170.004820.0073110.0061670.101739GABPB1X625340.004820.0073110.0009730.195089HMG2D505320.004820.0073110.0012680.159735HML2AJ0065910.004820.0073110.0013790.1682HSA6591Y007960.004820.0073110.0004380.386166ITGALAB0183010.004820.0073110.0087010.138344KIAA0758AB0206940.004820.0073110.0025260.205561KIAA0887AB0231980.004820.0073110.0004090.275051KIAA0981AB0289580.004820.0073110.0015330.117614KIAA1035U667110.004820.0073110.0065670.260368LY6EL137440.004820.0073110.0076580.19599MLLT3Y096310.004820.0073110.0007690.309898PIBF1L772130.004820.0073110.0011220.247214PMVKX734780.004820.0073110.0006810.242238PPP2R4U943190.004820.0073110.0006880.337656PSIP2U275160.004820.0073110.0002220.194938RAD52W257930.004820.0073110.0004380.258505RNF3X066170.004820.0073110.0025810.116631RPS11Z257490.004820.0073110.0014190.123333RPS7U807600.004820.0073110.0073710.161214TNRC1L270710.004820.0073110.0006380.372837TXKAL0314270.004820.0073110.0005410.367004L1097220.004820.0073110.001870.134304X156750.004820.0073110.0111650.131908AL0500890.004820.0078520.001906−0.23061BAZ1AL220050.004820.0078520.002439−0.22532CDC34AB0146790.004820.0078520.003059−0.13664CHST2X779560.004820.0078520.000689−0.22743ID1AI8144660.004820.0078520.001127−0.1955VAMP5HG4074-HT43440.004820.0078520.000964−0.17461AF0050500.004820.0080590.0017610.230395DNPEPJ039090.004820.0080590.000125−0.18353IFI30X598410.004820.0080590.0002260.265756PBX3AI8199420.004820.0093140.0022860.3261152-SepD869810.004820.0093140.0034410.319525APPBP2Y108050.004820.0093140.0025830.183496HRMT1L2U511270.004820.0093140.002120.282678IRF5U149700.004820.0093140.0005610.144991RPS5AI8135320.004820.0093140.00037−0.41933TNFRSF1BY152280.004820.0103630.002026−0.17032DLEU2AA9269570.004820.0103630.000909−0.22483FLJ10534AA5549450.004820.0103630.001827−0.14301FLJ10803AJ0013830.004820.0103630.001968−0.3226LY94M976760.004820.0103630.010011−0.16313MSX1AF0020200.004820.0103630.001278−0.1736NPC1U259750.004820.0103630.000764−0.24651PAK2X663630.004820.0103630.000837−0.4179PCTK1D879570.004820.0103630.004418−0.14751RQCD1AI6104670.004820.0103630.000699−0.17683SMG1AJ0120080.004820.0103630.002571−0.32997AJ0120080.004820.0103630.001638−0.16204









TABLE II










Gene Expression Profile from PBMCs of MS vs. Healthy-Highest


Scoring Genes (Bonfferoni analysis)













TNOM
Info
t-Test
Log



Identifier
PValue
PValue
PValue
FoldChange
Symbol















AA203527
1.37131E−05
1.613E−06
1.18E−07
0.281992
RPP20


AA780049
7.44428E−05
 2.35E−05
7.39E−07
0.54912
FLJ21439


AA845349
7.44428E−05
0.0001187
7.78E−07
0.457176
TRIP7


AA902713
2.10971E−06
1.993E−06
1.44E−06
0.474378


AB002344
7.44428E−05
5.915E−05
8.48E−07
−1.00068
KIAA0346


AB002347
2.10971E−06
1.329E−07
7.19E−10
0.371731
KIAA0349


AB002348
1.37131E−05
3.861E−06
2.49E−07
0.576346
KIAA0350


AB002386
2.10971E−06
7.732E−07
5.34E−09
0.586117
EZH1


AB002448
1.37131E−05
5.009E−06
2.45E−07
0.468926


AB007891
1.37131E−05
3.861E−06
3.99E−05
0.196376
KIAA0431


AB007895
1.37131E−05
5.009E−06
9.61E−07
0.186643
KIAA0435


AB007927
2.10971E−06
1.993E−06
2.12E−07
0.323787
RERE


AB007960
2.10971E−06
9.536E−07
7.96E−06
0.447772
SH3GLB1


AB008775
0.000344298
0.0003041
1.88E−06
−0.80745
AQP9


AB011004
0.000344298
7.048E−06
1.41E−06
−1.34073
UAP1


AB011108
1.37131E−05
5.045E−07
4.39E−07
0.453498
PRP4


AB011113
1.37131E−05
7.048E−06
3.74E−07
0.444795
WDR7


AB011115
1.37131E−05
5.045E−07
3.39E−07
0.382809
KIAA0543


AB011161
2.57282E−08
4.013E−09
9.64E−11
0.63432
PIP5K1C


AB014535
1.37131E−05
5.045E−07
1.04E−06
0.285282
KIAA0635


AB014538
0.000344298
 4.67E−05
1.98E−06
−0.63923
KIAA0638


AB014579
1.37131E−05
5.009E−06
6.08E−08
0.367966
MGEA5


AB014608
7.44428E−05
9.644E−05
4.59E−06
0.41494
KIAA0708


AB015019
7.44428E−05
7.048E−06
2.75E−07
−0.24515
BAIAP2


AB018343
1.83773E−09
4.157E−10
9.05E−12
0.383078
KIAA0800


AB023153
2.10971E−06
1.329E−07
1.82E−08
0.895842
KIAA0936


AB023235
7.44428E−05
1.613E−06
1.43E−05
0.311216
KIAA1018


AB026118
0.00137719
0.0001897
4.47E−06
−0.24886
MALT1


AB026436
7.44428E−05
1.613E−06
0.000219
−0.7589
DUSP10


AB028951
2.63714E−07
1.715E−07
8.78E−09
0.543028
KIAA1028


AB028981
2.10971E−06
7.732E−07
5.34E−07
0.282288
KIAA1058


AB029015
2.63714E−07
2.488E−07
5.37E−09
0.695063
PLCE2


AB029038
7.44428E−05
1.613E−06
7.62E−05
0.364386
KIAA1115


AC002400
1.37131E−05
 3.06E−05
2.28E−06
−0.25834
UBPH


AF000545
7.44428E−05
5.226E−05
3.48E−06
−0.85393
P2Y10


AF001294
1.37131E−05
7.048E−06
1.23E−06
−0.76359
TSSC3


AF004230
2.63714E−07
1.715E−07
3.06E−07
0.349166
LILRB1


AF005043
7.44428E−05
5.226E−05
 2.7E−06
0.408592
PARG


AF007130
2.10971E−06
5.045E−07
2.51E−06
0.391811
LOC54104


AF007142
0.000344298
0.0004443
3.15E−06
0.678734


AF007151
1.37131E−05
5.045E−07
3.25E−06
0.468343
MMS19L


AF010193
7.44428E−05
 2.35E−05
1.26E−07
−1.4705
MADH7


AF010309
1.37131E−05
5.009E−06
7.36E−07
−0.28533
PIG3


AF012023
7.44428E−05
5.915E−05
1.02E−06
0.50623
ICAP-1A


AF014958
2.10971E−06
4.309E−06
1.05E−07
−0.42152
CCRL2


AF015553
2.10971E−06
9.536E−07
2.61E−07
0.61214
GTF2I


AF019083
1.37131E−05
5.009E−06
8.34E−07
0.17011
PTENP1


AF022375
2.63714E−07
8.227E−08
1.87E−11
−1.35847
VEGF


AF023614
1.37131E−05
1.511E−05
4.79E−07
−0.20744
TACI


AF024710
8.54758E−11
8.548E−11
1.13E−12
−1.95537
VEGF


AF026086
0.000344298
 4.67E−05
2.66E−06
0.297942
PEX1


AF029777
1.37131E−05
7.048E−06
8.27E−07
0.290159
GCN5L2


AF030249
1.37131E−05
1.613E−06
1.98E−07
0.534547
ECH1


AF035281
2.10971E−06
2.484E−06
4.87E−07
0.472445


AF038564
1.37131E−05
1.613E−06
2.05E−07
−0.40446
ITCH


AF040707
2.10971E−06
1.993E−06
3.57E−07
0.289845
NPR2L


AF042386
1.37131E−05
5.009E−06
0.000107
0.137192
PPIE


AF052160
7.44428E−05
1.511E−05
1.67E−06
0.623021


AF054176
2.10971E−06
1.329E−07
6.47E−09
−0.58138
C1orf7


AF054589
0.000344298
 2.35E−05
1.98E−06
0.945394


AF061258
7.44428E−05
9.644E−05
1.58E−06
0.622201
LIM


AF067853
1.37131E−05
5.009E−06
5.02E−06
0.361707
ADSL


AF069517
2.10971E−06
1.329E−07
4.91E−07
0.399638
RBM6


AF070582
2.63714E−07
1.715E−07
3.23E−08
−0.19773
MGC13033


AF070606
1.37131E−05
 3.06E−05
1.48E−06
−0.89337


AF070617
1.37131E−05
3.861E−06
3.23E−07
0.323494


AF077820
2.63714E−07
2.188E−08
2.91E−08
0.656852
LRP5


AF079167
2.63714E−07
2.488E−07
7.37E−10
−1.93249
OLR1


AF082557
0.00137719
 4.67E−05
2.23E−06
0.226994
TNKS


AF094481
1.37131E−05
5.009E−06
2.74E−07
−0.29045
CGGBP1


AF098641
2.63714E−07
1.715E−07
1.56E−07
−0.41172


AF110377
1.37131E−05
5.009E−06
3.05E−05
0.361232
TRRAP


AF117829
7.44428E−05
0.000129
2.61E−06
−0.57516
RIPK2


AI133727
7.44428E−05
0.0001187
1.43E−06
0.181464
FLB6421


AI141670
0.000344298
0.0003041
 1.6E−06
−0.2494
CLCN2


AI148772
0.000344298
 4.67E−05
4.18E−06
−1.02619
KYNU


AI184802
2.63714E−07
2.188E−08
2.67E−09
−0.21576
HPRP4P


AI560890
2.57282E−08
2.829E−08
 1.8E−07
0.179028


AI670100
7.44428E−05
2.577E−05
 7.7E−07
0.22677
GRLF1


AI754391
1.37131E−05
3.861E−06
1.72E−06
−0.27657
KLF12


AI935146
0.000344298
 2.35E−05
2.05E−06
−0.46726
GALNT3


AI950382
1.37131E−05
1.613E−06
1.63E−07
−0.74128
KIAA0585


AI970189
0.000344298
 2.35E−05
6.16E−07
−0.75934
KIAA0997


AJ002190
7.44428E−05
1.613E−06
2.17E−08
0.33775
GNPAT


AJ007042
2.63714E−07
1.715E−07
 2.1E−07
0.170935
WHSC1


AJ010059
2.10971E−06
5.045E−07
2.95E−06
0.2235
SIT


AL008583
2.63714E−07
2.188E−08
1.12E−08
0.250082
CBX6


AL021154
0.000344298
 4.67E−05
2.19E−06
−0.82935
ID3


AL021707
0.000344298
7.048E−06
4.95E−06
−2.21462


AL022398
7.44428E−05
1.613E−06
8.09E−08
0.919627


AL022398
7.44428E−05
7.048E−06
 1.1E−07
0.79713
DJ434O14.3


AL022398
7.44428E−05
2.577E−05
 2.4E−06
0.493166


AL023553
1.37131E−05
1.753E−05
2.51E−06
0.226635
PMM1


AL049387
0.00137719
0.0001897
5.12E−06
0.379296


AL049409
7.44428E−05
1.511E−05
 1.1E−06
0.714173
LEF1


AL049782
7.44428E−05
2.577E−05
7.66E−07
0.237794


AL049787
1.37131E−05
5.009E−06
7.11E−06
0.311278


AL049963
0.000344298
 4.67E−05
8.36E−07
−0.74421
LOC64116


AL050084
7.44428E−05
1.613E−06
5.26E−05
0.509331
DC8


AL050087
2.10971E−06
2.484E−06
1.27E−07
−0.31279
KIAA1785


AL050196
1.37131E−05
5.009E−06
  2E−05
−0.24688
DKFZP586D2223


AL050281
0.000344298
0.0002051
2.85E−06
0.30517
NAG


AL050353
0.000344298
 2.35E−05
4.42E−06
0.179352
OIP2


AL050371
0.000344298
 2.35E−05
 3.7E−06
0.493288
PISD


AL080071
0.000344298
0.0003041
3.12E−06
0.237367
DKFZP564M082


AL080141
1.37131E−05
5.009E−06
2.42E−07
0.330868
SEC31B-1


AL096780
1.37131E−05
5.045E−07
2.13E−06
0.34487
CHKL


AW051579
1.37131E−05
1.613E−06
7.58E−07
0.593476
FLJ10512


D10704
1.37131E−05
1.753E−05
4.69E−07
−0.36791
CHK


D13891
2.10971E−06
2.484E−06
4.57E−05
−0.20577
ID2


D30758
2.10971E−06
1.993E−06
1.58E−05
0.27738
CENTB1


D30783
2.57282E−08
2.829E−08
8.95E−10
−1.65011
EREG


D49677
7.44428E−05
7.048E−06
4.18E−06
0.198707
U2AF1RS2


D50406
1.37131E−05
3.861E−06
2.65E−05
0.461907
RECK


D50525
0.000344298
 4.67E−05
3.02E−06
0.486698


D78579
1.37131E−05
7.048E−06
4.25E−07
−1.65638
NR4A3


D78579
7.44428E−05
7.048E−06
9.62E−07
−1.61438
NR4A3


D80011
7.44428E−05
1.613E−06
 4.2E−07
−0.35073
KIAA0189


D87119
7.44428E−05
 2.35E−05
 1.8E−06
0.425625
GS3955


D87119
7.44428E−05
5.226E−05
4.62E−06
0.557116
GS3955


D87466
1.37131E−05
8.661E−06
1.49E−07
0.466046
KIAA0276


HG1103-HT1103
1.37131E−05
1.613E−06
1.16E−07
−0.39165


HG2007-HT2056
7.44428E−05
9.644E−05
4.01E−06
−0.41408


HG2724-HT2820
1.37131E−05
 3.06E−05
5.17E−06
−1.33814


HG3227-HT3404
2.63714E−07
1.715E−07
1.68E−08
−0.25361


HG4582-HT4987
7.44428E−05
 2.35E−05
4.63E−07
−0.39588


J02939
7.44428E−05
1.613E−06
2.16E−07
−0.87844
SLC3A2


J02973
1.37131E−05
5.045E−07
2.93E−07
−1.30804
THBD


J03258
0.000344298
0.0001695
1.21E−06
−0.58295
VDR


J04130
0.000344298
 2.35E−05
3.02E−06
−0.62071
SCYA4


L04733
0.00137719
 2.35E−05
8.84E−07
0.306455
KNS2


L05424
2.10971E−06
1.329E−07
2.27E−09
−0.58081
CD44


L12002
7.44428E−05
 4.67E−05
1.23E−06
0.286717
ITGA4


L13740
2.63714E−07
2.188E−08
5.83E−08
−1.45891
NR4A1


L13740
1.37131E−05
5.009E−06
 9.1E−08
−0.61928
NR4A1


L13773
1.37131E−05
1.753E−05
6.44E−07
0.247919
MLLT2


L16499
1.37131E−05
8.661E−06
5.12E−06
0.374296
HHEX


L20941
2.63714E−07
1.329E−07
1.78E−06
−0.58618
FTH1


L22075
2.63714E−07
2.488E−07
 1.1E−08
−0.55736
GNA13


L22569
1.37131E−05
8.661E−06
1.52E−06
0.318129
CTSB


L25665
0.000344298
0.0001695
3.34E−06
−0.4513
GNL1


L33881
2.63714E−07
1.715E−07
5.06E−08
−0.59585
PRKCI


L40377
1.37131E−05
5.045E−07
3.49E−07
−0.79409
SERPINB8


L47738
2.57282E−08
4.013E−09
7.54E−09
0.31646
PIR121


L78132
7.44428E−05
5.226E−05
5.15E−07
0.358576
LGALS8


M12267
0.000344298
0.0001695
4.07E−06
−0.3279
OAT


M12959
7.44428E−05
2.577E−05
1.61E−06
0.128482
TRA@


M15330
8.54758E−11
8.548E−11
2.49E−12
−2.13825
IL1B


M17017
7.44428E−05
0.0001187
1.43E−06
−1.74073
IL8


M22919
2.63714E−07
3.119E−07
9.52E−08
−0.81053
MYL6


M23114
2.10971E−06
4.309E−06
1.59E−07
−0.96141
ATP2A2


M24194
7.44428E−05
1.613E−06
4.38E−06
0.560895
GNB2L1


M24283
0.000344298
 4.67E−05
3.71E−06
−1.32611
ICAM1


M24895
2.10971E−06
1.329E−07
1.72E−08
0.476779
AMY2B


M26683
7.44428E−05
0.0001187
 3.7E−06
−0.16179
SCYA2


M27492
0.000344298
0.0004017
2.01E−06
−0.32619
IL1R1


M28130
7.44428E−05
 4.67E−05
8.02E−07
−2.27292
IL8


M31165
7.44428E−05
5.226E−05
1.38E−06
−0.34617
TNFAIP6


M31523
1.37131E−05
1.753E−05
2.09E−06
0.36898
TCF3


M36821
1.37131E−05
8.661E−06
2.21E−07
−0.36334
GRO3


M55153
7.44428E−05
2.577E−05
4.77E−06
−0.27465
TGM2


M58603
7.44428E−05
5.226E−05
1.28E−06
−0.73537
NFKB1


M59040
0.00137719
 2.35E−05
2.82E−06
−0.46271
CD44


M60784
7.44428E−05
5.226E−05
1.24E−06
0.559903
SNRPA


M60922
7.44428E−05
1.511E−05
4.47E−08
0.39657
FLOT2


M62403
7.44428E−05
5.226E−05
5.57E−07
−0.53749
IGFBP4


M63256
0.000344298
5.915E−05
6.54E−07
0.454561
CDR2


M63904
2.57282E−08
1.031E−08
5.38E−09
−0.59612
GNA15


M63978
0.000344298
 4.67E−05
1.77E−06
−0.44762
VEGF


M64571
1.83773E−09
1.838E−09
2.41E−11
0.416659
MAP4


M69199
2.10971E−06
1.993E−06
1.45E−07
−1.9021
G0S2


M73547
1.37131E−05
5.009E−06
 9.2E−08
0.438897
D5S346


M74525
2.10971E−06
2.484E−06
 3.5E−07
−0.61792
UBE2B


M80244
0.000344298
7.048E−06
2.72E−06
−0.8522
SLC7A5


M84443
1.37131E−05
5.045E−07
4.08E−07
0.303567
GALK2


M94856
7.44428E−05
5.226E−05
4.99E−06
−0.23847
FABP5


M95678
0.000344298
7.048E−06
  2E−06
0.432923
PLCB2


M98833
7.44428E−05
1.613E−06
1.52E−06
0.434288
FLI1


N23137
2.10971E−06
2.484E−06
2.06E−07
0.247311
MPHOSPH9


N23137
0.00137719
0.0001695
4.12E−06
0.244083
MPHOSPH9


N30151
7.44428E−05
1.613E−06
5.05E−05
0.393521
STX16


N42007
2.10971E−06
2.484E−06
9.19E−05
0.167986
NUP50


N53547
7.44428E−05
8.556E−05
 1.8E−07
0.296678
MGC5508


N90862
1.37131E−05
5.045E−07
3.28E−08
0.43576
VAMP8


N90866
2.63714E−07
8.227E−08
2.76E−08
0.304525
CDW52


N98667
1.37131E−05
8.661E−06
3.38E−07
0.367127
KIAA1696


R90942
1.37131E−05
5.009E−06
1.05E−05
−0.17696
ST6GALNACIV


S52028
2.10971E−06
5.045E−07
9.62E−08
−0.81662
CTH


S68134
0.000344298
7.048E−06
8.37E−07
−1.64652
CREM


S68134
0.000344298
7.048E−06
4.35E−06
−2.47105
CREM


S68271
0.000344298
7.048E−06
3.03E−06
−2.07185
CREM


S73591
1.37131E−05
1.511E−05
4.68E−06
0.414777
VDUP1


S76638
7.44428E−05
 2.35E−05
7.47E−07
−0.35416
NFKB2


S78187
7.44428E−05
1.613E−06
1.95E−05
0.203265
CDC25B


S78771
0.000344298
5.915E−05
2.55E−06
−0.31389
BRD2


S81914
0.000344298
7.048E−06
4.18E−07
−1.59146
IER3


U02020
1.37131E−05
8.661E−06
1.37E−06
−1.13863
PBEF


U02570
1.37131E−05
2.813E−05
1.26E−06
0.432431
ARHGAP1


U03634
1.37131E−05
1.753E−05
  1E−06
−0.21467
LBC


U04636
0.000344298
5.915E−05
2.81E−06
−1.85123
PTGS2


U05681
7.44428E−05
5.226E−05
3.37E−06
−0.35383
BCL3


U07563
7.44428E−05
 2.35E−05
4.91E−07
−0.25016
ABL1


U09937
1.83773E−09
4.157E−10
2.04E−09
−1.21578
PLAUR


U10117
7.44428E−05
1.511E−05
4.07E−06
0.563673
SCYE1


U11732
1.37131E−05
3.861E−06
3.04E−07
−0.22574
ETV6


U12767
7.44428E−05
1.613E−06
2.84E−07
−1.23483
NR4A3


U12767
0.000344298
7.048E−06
2.55E−07
−2.13744
NR4A3


U13695
7.44428E−05
1.613E−06
1.11E−05
0.805607
PMS1


U15552
1.37131E−05
5.009E−06
1.67E−05
−0.68094
HSU15552


U17760
0.000344298
7.048E−06
4.25E−06
−0.84472
LAMB3


U18300
7.44428E−05
0.000129
2.43E−06
0.183171
DDB2


U20982
2.10971E−06
1.993E−06
 1.2E−08
−0.67125
IGFBP4


U24166
7.44428E−05
1.613E−06
7.52E−06
−0.45293
MAPRE1


U28811
0.000344298
7.048E−06
1.33E−06
0.32855
GLG1


U29171
1.37131E−05
5.009E−06
 1.1E−06
−0.6032
CSNK1D


U29175
1.37131E−05
8.661E−06
 1.9E−06
0.266342
SMARCA4


U29185
2.10971E−06
7.732E−07
1.56E−07
−1.08006
PRNP


U29344
2.10971E−06
9.536E−07
2.35E−07
−0.43842
FASN


U29656
2.10971E−06
7.732E−07
7.52E−08
0.353186
NME3


U29656
7.44428E−05
0.000129
4.31E−06
0.471876
NME3


U32324
1.37131E−05
5.045E−07
3.21E−08
0.334966
IL11RA


U33017
2.63714E−07
1.715E−07
 5.2E−07
0.373581
SLAM


U38847
7.44428E−05
 2.35E−05
9.91E−07
0.222946
TARBP1


U41815
1.37131E−05
5.045E−07
2.16E−07
−0.96931
NUP98


U43774
0.000344298
 2.35E−05
 8.8E−07
−0.39938
FCAR


U44839
2.10971E−06
9.536E−07
2.54E−07
−0.97008
USP11


U47414
2.10971E−06
9.536E−07
2.31E−06
0.370736
CCNG2


U47927
2.57282E−08
2.829E−08
5.53E−09
0.545592
USP5


U48807
1.37131E−05
5.009E−06
4.97E−08
−0.93178
DUSP4


U49187
7.44428E−05
1.511E−05
1.48E−06
0.671467
C6orf32


U49187
7.44428E−05
9.644E−05
3.53E−06
0.511392
C6orf32


U49844
7.44428E−05
7.048E−06
3.67E−07
0.47168
ATR


U50527
1.37131E−05
5.009E−06
5.11E−06
0.416543


U50928
7.44428E−05
1.613E−06
4.72E−06
0.302213
PKD2


U51007
7.44428E−05
1.511E−05
1.49E−06
0.309996
PSMD4


U51205
1.37131E−05
5.045E−07
2.65E−07
−0.76279
COP9


U51478
7.44428E−05
 2.35E−05
 6.1E−07
−0.58
ATP1B3


U51920
2.10971E−06
1.329E−07
7.01E−08
−0.28142
SRP54


U52960
2.10971E−06
1.613E−06
1.51E−07
−0.84863
SURB7


U56998
0.000344298
7.048E−06
 3.7E−06
−0.74294
CNK


U64197
1.83773E−09
1.838E−09
2.95E−10
−0.62373
SCYA20


U65928
7.44428E−05
 4.67E−05
2.85E−07
0.408918
COPS5


U66063
2.10971E−06
2.484E−06
 4.7E−07
0.277185
CAMK2G


U70735
1.37131E−05
8.661E−06
1.82E−06
0.249185
MOV34-34KD


U72066
2.57282E−08
1.031E−08
4.33E−08
−0.34482
RBBP8


U75968
2.10971E−06
1.993E−06
4.36E−06
0.139542
DDX11


U78107
8.54758E−11
3.691E−11
4.04E−12
−0.43769
NAPG


U78302
2.63714E−07
1.715E−07
2.41E−08
0.329878
DECR1


U78798
2.57282E−08
4.013E−09
1.11E−06
−0.3172
TRAF6


U84007
7.44428E−05
1.613E−06
0.000235
0.236422
AGL


U85245
7.44428E−05
1.613E−06
4.57E−07
0.365266
PIP5K2B


U88629
0.000344298
 4.67E−05
9.58E−07
−0.32607
ELL2


U90917
1.37131E−05
1.613E−06
3.89E−07
0.433406
FOXM1


U91543
2.63714E−07
3.119E−07
2.01E−07
0.478678
CHD3


U91616
1.37131E−05
5.045E−07
1.27E−07
−0.80419
NFKBIE


U96876
7.44428E−05
1.613E−06
3.54E−06
−0.45317
INSIG1


U97105
1.37131E−05
1.753E−05
6.56E−07
1.00615
DPYSL2


W28319
1.37131E−05
5.009E−06
 1.5E−05
0.294631
FBLN1


W28612
1.37131E−05
5.009E−06
 1.7E−06
−0.25519


W28743
0.000344298
7.048E−06
2.78E−06
−0.28926
PP1628


X00737
2.10971E−06
9.536E−07
5.21E−08
−0.67074
NP


X02152
1.37131E−05
5.045E−07
4.63E−08
−0.75601
LDHA


X04366
1.37131E−05
2.813E−05
5.11E−06
0.346076
CAPN1


X04500
2.63714E−07
1.715E−07
3.43E−10
−2.12121
IL1B


X06256
1.37131E−05
 2.35E−05
4.89E−07
−0.7357
ITGA5


X13403
7.44428E−05
5.915E−05
4.21E−07
0.146032
POU2F1


X15217
7.44428E−05
 4.67E−05
3.77E−07
−0.2371
SKIL


X15218
8.54758E−11
8.548E−11
 1.4E−10
−1.41501
SKI


X16396
0.000344298
0.0002051
3.27E−06
−0.6151
MTHFD2


X16706
7.44428E−05
1.613E−06
1.23E−06
−1.09747
FOSL2


X53586
1.37131E−05
8.661E−06
 3.4E−07
0.51291
ITGA6


X58141
7.44428E−05
9.644E−05
1.75E−06
0.384254
ADD1


X61123
7.44428E−05
0.0001057
4.17E−07
−1.15256
BTG1


X61498
7.44428E−05
1.613E−06
 8.8E−07
−0.49884
NFKB2


X62535
1.37131E−05
1.613E−06
5.68E−07
0.243937
DGKA


X63368
2.10971E−06
5.045E−07
 2.3E−08
−0.55432
DNAJB2


X64330
7.44428E−05
7.048E−06
2.27E−06
0.297851
ACLY


X66363
2.63714E−07
1.715E−07
6.53E−07
−0.24505
PCTK1


X66436
0.000344298
8.556E−05
1.88E−06
−0.26662


X66945
7.44428E−05
1.511E−05
1.91E−07
−0.35494
FGFR1


X68452
2.57282E−08
4.013E−09
9.12E−11
−0.26618
CCND2


X69392
2.63714E−07
1.329E−07
 1.1E−08
0.297444
RPL26


X70218
1.37131E−05
 3.06E−05
2.44E−06
−0.74691
PPP4C


X74039
1.83773E−09
4.157E−10
1.51E−10
−0.67381
PLAUR


X79882
1.37131E−05
5.045E−07
1.78E−07
0.520965
MVP


X82153
7.44428E−05
1.613E−06
2.27E−06
0.47844
CTSK


X82209
2.10971E−06
5.045E−07
1.37E−09
−0.45281
MN1


X87949
7.44428E−05
1.613E−06
4.05E−07
−0.54468
HSPA5


X98172
7.44428E−05
 4.67E−05
5.29E−07
0.507556
CASP8


X99142
1.37131E−05
8.661E−06
1.24E−06
−0.29773
KRTHB6


X99656
1.37131E−05
5.045E−07
1.68E−06
−0.23553
SH3GL1


Y00630
2.57282E−08
3.695E−08
6.65E−09
−2.38485
SERPINB2


Y08683
1.37131E−05
5.045E−07
4.71E−06
0.492738
CPT1B


Y14768
1.37131E−05
5.045E−07
7.26E−08
0.248383
LTB


Y18004
1.37131E−05
5.009E−06
4.19E−07
−0.9465
SCML2


Z11697
1.37131E−05
5.045E−07
3.55E−06
−1.21033
CD83


Z14000
0.000344298
0.0002051
3.91E−06
−0.33734
RING1


Z24724
2.63714E−07
2.188E−08
5.96E−09
−1.10426


Z32860
1.37131E−05
5.009E−06
7.81E−06
0.133192


Z93930
2.63714E−07
2.488E−07
2.42E−05
−0.39839
XBP1
















TABLE III










Differential Gene Expression in acute MS relapse vs. remission













TNOM
Info
t-Test
Log Fold



Identifier
PValue
PValue
PValue
Change
Symbol















AI828210
5.38E−06
5.38E−06
8.37E−06
−0.18947
KIAA0284


D14710
6.73E−05
3.19E−05
2.89E−05
−0.35496
ATP5A1


U46692
6.73E−05
3.19E−05
0.000284
−0.49741
CSTB


AF061261
6.73E−05
3.19E−05
3.22E−05
−0.28274
MBLL


U51712
6.73E−05
3.19E−05
0.003464
−0.42775
SMAP31


AB014558
6.73E−05
4.25E−05
0.000473
0.694784
CRY2


AB007936
6.73E−05
4.25E−05
0.000958
−0.25409
KIAA0467


AC002115
6.73E−05
4.25E−05
0.000147
0.622841
MGC10433


AF052160
6.73E−05
4.25E−05
0.000182
−0.46468


S78085
0.000538
0.000104
0.000102
−0.55064
PDCD2


AL096719
0.000538
0.000104
0.000089
−0.22287
PFN2


U61234
0.000538
0.000104
0.000844
0.299182
TBCC


X12451
0.000538
0.000251
0.000876
1.04444
CTSL


M35531
0.000538
0.000251
0.000241
−0.20303
FUT1


M64174
0.000538
0.000251
3.43E−05
−0.5508
JAK1


AB018269
0.000538
0.000251
7.39E−05
−0.18186
KIAA0726


R92331
0.000538
0.000251
0.000104
0.289994
MT1E


U19487
0.000538
0.000251
0.001738
−0.25888
PTGER2


AF040965
0.000538
0.000251
0.000775
0.48898
RES4-25


U07563
0.000538
0.000251
3.61E−05
−0.16779
RRP4


L40377
0.000538
0.000251
0.009479
0.452416
SERPINB8


AL080234
0.000538
0.000251
0.000377
−0.52631


AJ242015
0.003096
0.00039
0.013957
0.281618
ADAM28


D86324
0.003096
0.00039
0.001801
−0.34728
CMAH


M94065
0.003096
0.00039
0.002391
−0.13976
DHODH


AC004382
0.003096
0.00039
0.000121
−0.20383
DKFZP434K046


X54326
0.003096
0.00039
0.002734
−0.39559
EPRS


W25921
0.003096
0.00039
9.41E−05
−0.39027
GNS


X92110
0.003096
0.00039
0.000103
−1.00581
HCGVIII-1


W28589
0.003096
0.00039
0.000225
−0.20949
HSPD1


S66213
0.003096
0.00039
0.000134
−0.28606
ITGA6


AB011158
0.000538
0.00039
0.000047
−0.163
KIAA0586


AB023209
0.003096
0.00039
0.003354
−0.09151
KIAA0992


AF035940
0.003096
0.00039
0.008457
0.282437
MAGOH


M31724
0.003096
0.00039
0.000671
0.569343
PTPN1


X74262
0.003096
0.00039
0.000062
−0.37623
RBBP4


J05249
0.003096
0.00039
0.00045
−0.52346
RPA2


M55531
0.003096
0.00039
0.023054
−0.22329
SLC2A5


AI865431
0.003096
0.00039
0.00027
0.423067
TNFRSF5


W28203
0.003096
0.00039
0.007983
−0.17484


W28667
0.003096
0.00039
0.000846
−0.49488


D13628
0.000538
0.000529
0.034335
−0.10398
ANGPT1


U03271
0.000538
0.000529
0.000286
−0.1675
CAPZB


U05259
0.000538
0.000529
0.003589
0.551328
CD79A


L13278
0.000538
0.000529
7.27E−05
−0.43636
CRYZ


M91670
0.000538
0.000529
0.003472
0.600255
E2-EPF


AB029030
0.000538
0.000529
0.000657
−0.13458
KIAA1107


AF016098
0.000538
0.000529
0.000433
−0.16189
NRP2


X76091
0.000538
0.000529
0.004691
0.161349
RFX2


U52191
0.000538
0.000529
0.00229
1.2356
SMCY


AA203345
0.000538
0.000529
0.001228
−0.50409
STX16


U96113
0.000538
0.000529
0.000394
−0.41425
WWP1


AL050263
0.000538
0.000529
0.000224
−0.15981


Z48579
0.000538
0.000799
0.000184
−0.30836
ADAM10


M31452
0.000538
0.000799
0.002899
−0.13022
C4BPA


AC003107
0.000538
0.000799
0.000262
−0.16818
COMP


M91670
0.000538
0.000799
0.000792
0.41925
E2-EPF


AB023235
0.000538
0.000799
0.001348
−0.30138
KIAA1018


X89960
0.000538
0.000799
0.026837
−0.35169
MCSP


D55654
0.000538
0.000799
0.019331
−0.2254
MDH1


U02683
0.000538
0.000799
0.030035
−0.09324
NRF1


S90469
0.000538
0.000799
0.000785
0.23032
POR


AF020543
0.000538
0.000799
0.004286
−0.25061
PPT2


M34181
0.000538
0.000799
0.000055
−0.5883
PRKACB


AF095448
0.000538
0.000799
0.000588
−0.24961
RAI3


AF027150
0.000538
0.000799
0.000979
−0.16012
SIP1


X02344
0.000538
0.000799
0.000918
0.430531
TUBB2


X02344
0.000538
0.000799
0.002225
0.296682
TUBB2


AI701164
0.000538
0.000799
0.000115
−0.23639
UBE2G1


U96113
0.000538
0.000799
9.77E−05
−0.45711
WWP1


AF016052
0.000538
0.000799
0.001254
−0.19092
ZNF24


U21551
0.003096
0.00103
0.000836
0.278219
BCAT1


X77794
0.003096
0.00103
3.72E−05
−0.81938
CCNG1


AF070530
0.003096
0.00103
0.014908
0.276942
CL24751


AB002331
0.003096
0.00103
0.001714
−0.17304
DATF1


AI004207
0.003096
0.00103
0.000762
−0.1648
FLJ00002


L76200
0.003096
0.00103
0.000824
0.444479
GUK1


U26398
0.003096
0.00103
0.001182
−0.29185
INPP4A


U69883
0.003096
0.00103
0.007922
0.103614
KCNN1


M13452
0.003096
0.00103
0.000467
0.405856
LMNA


AA126505
0.003096
0.00103
0.002
−0.39781
NCAM1


U88620
0.003096
0.00103
0.007562
−0.3532
OGG1


M33336
0.003096
0.00103
0.001568
−0.26454
PRKAR1A


AB015982
0.003096
0.00103
0.000382
−0.27486
PRKCN


H68340
0.003096
0.00103
0.001222
0.516352
RNAHP


M28225
0.003096
0.00103
0.000686
1.0733
SCYA2


X97064
0.003096
0.00103
0.003207
−0.19906
SEC23A


X68560
0.003096
0.00103
0.007856
0.437567
SP3


AF064094
0.003096
0.00103
0.000287
−0.19385
TADA2L


AB007872
0.003096
0.00103
0.000119
−0.20778
ZNF264


W28255
0.013622
0.001698
0.001407
−0.24426
76P


AB007934
0.003096
0.001698
0.003182
−0.24405
ACF7


AL049954
0.013622
0.001698
0.024193
−0.25818
AHCYL1


U90546
0.003096
0.001698
0.000105
−0.34074
BTN3A2


AL035291
0.013622
0.001698
0.007668
0.506107
CH1


AF031647
0.013622
0.001698
0.004755
0.257244
COPS3


M57888
0.003096
0.001698
0.004549
−0.64384
CTLA1


AF000987
0.003096
0.001698
0.009455
0.247586
EIF1AY


U55766
0.003096
0.001698
0.00066
0.795017
HRB2


L12002
0.013622
0.001698
0.005765
−0.1942
ITGA4


D14661
0.013622
0.001698
0.011324
0.391267
KIAA0105


D63875
0.013622
0.001698
0.002192
−0.36411
KIAA0155


AB018285
0.013622
0.001698
0.001545
0.550994
KIAA0742


AB023180
0.013622
0.001698
0.001642
0.253479
KIAA0963


AL080102
0.013622
0.001698
0.003651
0.435751
KIAA1856


M22637
0.013622
0.001698
0.003792
−0.27794
LYL1


D85131
0.013622
0.001698
0.005126
−0.12291
MAZ


D37965
0.013622
0.001698
0.01111
−0.09143
PDGFRL


Y18207
0.003096
0.001698
0.003474
−0.17238
PPP1R3C


L49229
0.013622
0.001698
0.000336
−0.36639
RB1


U77664
0.013622
0.001698
0.002354
0.193666
RPP38


AL040137
0.003096
0.001698
0.008384
−0.23366
SAP18


D31764
0.013622
0.001698
0.01295
−0.13299
SNX17


X57655
0.013622
0.001698
0.002476
−0.17382
SPINK2


M19267
0.013622
0.001698
0.013582
0.262886
TPM1


M12959
0.013622
0.001698
0.003907
−0.08942
TRA@


AA160724
0.013622
0.001698
0.005695
0.267002


U37122
0.003096
0.002135
0.000571
−0.59281
ADD3


AA903720
0.003096
0.002135
0.002557
0.244618
BAP29


M93107
0.003096
0.002135
0.00187
−0.19146
BDH


M17754
0.003096
0.002135
0.010333
−0.10769
BN51T


X15882
0.003096
0.002135
0.0023
0.227769
COL6A2


D15057
0.003096
0.002135
0.002814
−0.26776
DAD1


S62138
0.003096
0.002135
0.002442
1.1158
DDIT3


AB026436
0.003096
0.002135
0.011189
0.711919
DUSP10


W27152
0.003096
0.002135
0.009498
−0.1614
FLJ10569


AB001106
0.003096
0.002135
0.002408
0.444617
GMFB


D87120
0.003096
0.002135
0.00475
0.236706
GS3786


AI200373
0.003096
0.002135
0.003822
−0.31066
H2AFI


U15085
0.003096
0.002135
0.011743
0.328857
HLA-DMB


U90549
0.003096
0.002135
0.001654
−0.26437
HMG17L3


AI760162
0.003096
0.002135
0.001313
−0.47775
HT012


AB018306
0.003096
0.002135
0.000371
0.316202
KIAA0763


D14696
0.003096
0.002135
0.016949
0.259239
LAPTM4A


U23852
0.003096
0.002135
0.001207
−0.2593
LCK


U70735
0.003096
0.002135
0.0002
−0.20846
MOV34-34KD


X79865
0.003096
0.002135
0.0141
0.418466
MRPL12


AI547258
0.003096
0.002135
0.001223
0.267951
MT2A


L40387
0.003096
0.002135
0.00038
0.211973
OASL


AB019517
0.003096
0.002135
0.023004
0.219453
PKIG


M58459
0.003096
0.002135
0.001362
1.46854
RPS4Y


X57348
0.003096
0.002135
0.004255
0.22047
SFN


M74558
0.003096
0.002135
0.001205
0.219185
SIL


U34044
0.003096
0.002135
0.000831
−0.21289
SPS


U49928
0.003096
0.002135
0.000886
−0.31189
TAB1


X05839
0.003096
0.002135
0.008747
0.214552
TGFB1


U16296
0.003096
0.002135
0.006585
−0.14857
TIAM1


U63127
0.003096
0.002135
0.000538
−0.38925
TIC


U03397
0.003096
0.002135
0.005156
−0.34157
TNFRSF9


M21624
0.003096
0.002135
0.001748
−0.51878
TRD@


D83198
0.003096
0.002135
0.028975
−0.17519
YF13H12


HG960-HT960
0.003096
0.002135
0.003089
0.145701


HG4724-HT5166
0.003096
0.002135
0.002446
−0.25728


D00654
0.003096
0.004342
9.79E−05
−0.1819
ACTG2


U54645
0.013622
0.004342
0.004228
−0.25281
AK2


M93405
0.003096
0.004342
0.020651
0.126156
ALDH6A1


U73960
0.003096
0.004342
0.002279
0.555806
ARL4


U26455
0.003096
0.004342
0.006562
−0.53911
ATM


M33519
0.003096
0.004342
0.011169
−0.33327
BAT3


U90028
0.003096
0.004342
0.000396
−0.24971
BICD1


AB002384
0.003096
0.004342
0.002855
−0.46941
C6orf32


M74093
0.003096
0.004342
0.000763
−0.33022
CCNE1


AA203246
0.003096
0.004342
0.007014
−0.16607
CDC2L5


X66358
0.013622
0.004342
0.007122
−0.1886
CDKL1


U30872
0.003096
0.004342
0.001715
−0.164
CENPF


AB020675
0.013622
0.004342
0.002913
−0.25056
CNTNAP2


M13207
0.013622
0.004342
0.01388
0.122241
CSF2


AA173896
0.013622
0.004342
0.008401
0.305133
CYB5-M


L78267
0.003096
0.004342
0.04708
0.103949
D15S226E


AL080120
0.013622
0.004342
0.001834
−0.12922
DKFZP564O0423


U13896
0.013622
0.004342
0.020482
−0.10291
DLG1


AF034970
0.013622
0.004342
0.010371
−0.10568
DOK2


D12686
0.013622
0.004342
0.003493
0.170378
EIF4G1


AB002386
0.003096
0.004342
0.000131
−0.39255
EZH1


M15059
0.003096
0.004342
0.002497
0.2061
FCER2


W27545
0.013622
0.004342
0.004445
0.379682
FLJ20259


M84443
0.003096
0.004342
0.000101
−0.27085
GALK2


AF029777
0.013622
0.004342
0.001427
−0.22426
GCN5L2


D63876
0.013622
0.004342
0.002737
0.396946
GGA3


AB020645
0.003096
0.004342
0.003907
−0.37377
GLS


U77948
0.003096
0.004342
0.000818
−0.35677
GTF2I


AF035555
0.003096
0.004342
0.018388
−0.17666
HADH2


AF055001
0.003096
0.004342
0.010744
0.724714
HERPUD1


D32129
0.003096
0.004342
0.005364
−0.13287
HLA-A


AF043586
0.003096
0.004342
0.001047
−0.30021
IGL@


U53831
0.013622
0.004342
0.01853
0.488267
IRF7


AB002344
0.003096
0.004342
0.001658
0.705775
KIAA0346


AI677689
0.013622
0.004342
0.004375
−0.1411
KIAA0685


AB023153
0.003096
0.004342
0.04282
−0.39134
KIAA0936


AB023226
0.003096
0.004342
0.000111
−0.71413
KIAA1009


AI148772
0.013622
0.004342
0.03739
0.532454
KYNU


AB006780
0.003096
0.004342
0.010236
0.178362
LGALS3


AL050405
0.003096
0.004342
0.008144
0.311843
LOC51634


L35253
0.013622
0.004342
0.001324
−0.46397
MAPK14


R93527
0.013622
0.004342
0.000372
0.264207
MT1H


AF108145
0.003096
0.004342
0.001206
−0.14877
MYLE


M96980
0.013622
0.004342
0.002106
−0.16409
MYT1


S76638
0.013622
0.004342
0.04529
0.171344
NFKB2


D88674
0.013622
0.004342
0.045232
0.346415
OAZIN


AL050353
0.013622
0.004342
0.016071
−0.11979
OIP2


AL080119
0.003096
0.004342
0.001961
−0.40821
PAI-RBP1


X76770
0.013622
0.004342
0.005011
−0.10613
PAPOLA


D11466
0.003096
0.004342
0.009752
0.738127
PIGA


W28299
0.003096
0.004342
0.001225
−0.17755
PINK1


U83981
0.003096
0.004342
0.014327
0.28747
PPP1R15A


X14968
0.013622
0.004342
0.004727
0.105215
PRKAR2A


M55284
0.003096
0.004342
0.003435
−0.17401
PRKCH


M15036
0.003096
0.004342
0.010965
−0.25119
PROS1


Y00638
0.003096
0.004342
0.004977
−0.30956
PTPRC


Y00815
0.003096
0.004342
0.015344
0.116938
PTPRF


M38258
0.003096
0.004342
0.009252
−0.14193
RARG


AF025654
0.003096
0.004342
0.002302
−0.39122
RNGTT


M60724
0.013622
0.004342
0.004732
−0.22065
RPS6KB1


AB006202
0.013622
0.004342
0.003028
−0.18268
SDHD


AA890010
0.003096
0.004342
0.00546
−0.21285
SEC22L1


X62822
0.003096
0.004342
0.039707
−0.21593
SIAT1


L41680
0.003096
0.004342
0.001771
−0.16486
SIAT8D


X15217
0.003096
0.004342
0.007377
0.149306
SKIL


L13857
0.003096
0.004342
0.005721
−0.11073
SOS1


U09564
0.003096
0.004342
0.001203
−0.27717
SRPK1


Z75330
0.013622
0.004342
0.031796
−0.11359
STAG1


X92762
0.003096
0.004342
0.001021
−0.27946
TAZ


AF064090
0.003096
0.004342
0.006206
0.303013
TNFSF14


U47634
0.003096
0.004342
0.0057
0.278205
TUBB4


L27071
0.003096
0.004342
0.000732
−0.39906
TXK


D78514
0.003096
0.004342
0.000681
−0.2599
UBE2G1


AF085807
0.003096
0.004342
0.005801
0.124457
UPK1A


U66561
0.003096
0.004342
0.002542
0.448044
ZNF184


X78925
0.013622
0.004342
0.001898
0.351929
ZNF267


HG2510-HT2606
0.013622
0.004342
0.007016
0.179499


W27419
0.003096
0.004342
0.006325
0.341787


AF054589
0.003096
0.004342
0.030568
−0.50762


H98552
0.003096
0.004342
0.017185
−0.1057


AI056697
0.003096
0.004342
0.000329
−0.20147


X00351
0.003096
0.005207
0.001506
−0.12928
ACTB


AF006082
0.003096
0.005207
0.002797
−0.34587
ACTR2


Y09443
0.003096
0.005207
0.002286
−0.17646
AGPS


U22961
0.003096
0.005207
0.003092
0.147932
ALB


AF002163
0.003096
0.005207
0.002447
−0.37588
AP3D1


D87461
0.003096
0.005207
0.004809
−0.26338
BCL2L2


AF013759
0.003096
0.005207
0.004946
−0.18574
CALU


L22005
0.003096
0.005207
0.006442
0.131869
CDC34


AL109689
0.003096
0.005207
0.013291
−0.24945
CGI-142


U91543
0.003096
0.005207
0.014143
−0.25258
CHD3


X82153
0.003096
0.005207
0.013882
−0.31742
CTSK


AJ001687
0.003096
0.005207
0.000224
−0.64837
D12S2489E


M13149
0.003096
0.005207
0.008717
−0.13824
HRG


Y10313
0.003096
0.005207
0.006846
0.464769
IFRD1


D63485
0.003096
0.005207
0.000985
−0.31599
IKKE


D87077
0.003096
0.005207
0.043072
−0.21138
KIAA0240


AB007864
0.003096
0.005207
0.001569
0.256672
KIAA0404


X75346
0.003096
0.005207
0.001841
0.331699
MAPKALPK2


L07648
0.003096
0.005207
0.010594
0.226817
MXI1


AB028993
0.003096
0.005207
0.0247
0.133216
NLGN1


D45333
0.003096
0.005207
0.002104
0.302454
PFDN1


M65254
0.003096
0.005207
0.002619
0.262897
PPP2R1B


M86852
0.003096
0.005207
0.004274
0.172251
PXMP3


X97795
0.003096
0.005207
0.021131
−0.18349
RAD54L


U14970
0.003096
0.005207
0.001894
−0.1353
RPS5


X74570
0.003096
0.005207
0.00345
0.210049
SIAT4C


X98248
0.003096
0.005207
0.010403
−0.50617
SORT1


U17714
0.003096
0.005207
0.002081
−0.19372
ST13


W28869
0.003096
0.005207
0.001369
−0.38498
TEGT


M12125
0.003096
0.005207
0.000178
−0.09929
TPM2


L27071
0.003096
0.005207
0.003834
−0.36074
TXK


M60614
0.003096
0.005207
0.001757
−0.25283
WIT-1


HG4074-HT4344
0.003096
0.005207
0.004175
0.589048


AL031846
0.003096
0.005207
0.004012
−0.42132


HG1980-HT2023
0.003096
0.005207
0.002314
0.711234


AF022853
0.047678
0.006683
0.002056
−0.30792
ABCC1


X02994
0.047678
0.006683
0.036598
−0.12393
ADA


D25304
0.047678
0.006683
0.002258
−0.44746
ARHGEF6


M23115
0.047678
0.006683
0.016518
−0.1243
ATP2A2


U87408
0.047678
0.006683
0.008628
−0.33961
B1


AA135683
0.047678
0.006683
0.010045
0.6329
BASP1


M22491
0.047678
0.006683
0.020141
−0.10386
BMP3


M28170
0.047678
0.006683
0.014303
0.280093
CD19


M16336
0.047678
0.006683
0.011755
−0.19993
CD2


U37022
0.047678
0.006683
0.028135
−0.06885
CDK4


U66469
0.047678
0.006683
0.004123
0.616896
CGR19


AI037867
0.047678
0.006683
0.009634
−0.11973
CKTSF1B1


J03071
0.047678
0.006683
0.011153
−0.23776
CSH2


M55265
0.047678
0.006683
0.01278
−0.1479
CSNK2A1


M33317
0.047678
0.006683
0.014832
−0.17753
CYP2A7


U37143
0.013622
0.006683
0.001908
0.171138
CYP2J2


AL049942
0.013622
0.006683
0.00076
−0.20245
DKFZP564F1422


AL050015
0.013622
0.006683
0.008524
−0.13959
DKFZP564O243


L35594
0.013622
0.006683
0.002806
0.216985
ENPP2


J03796
0.047678
0.006683
0.002596
−0.28198
EPB41


AC002398
0.013622
0.006683
0.003226
−0.27062
F25965


X15376
0.013622
0.006683
0.014388
−0.15607
GABRG2


M90656
0.047678
0.006683
0.006961
−0.15968
GCLC


AF062006
0.013622
0.006683
0.001442
0.200117
GPR49


X61755
0.013622
0.006683
0.000491
−0.19331
HOXC5


D21851
0.047678
0.006683
0.017915
0.153927
KIAA0028


AB007976
0.047678
0.006683
0.032427
0.228873
KIAA0507


AI871396
0.047678
0.006683
0.001957
−0.48312
KIAA0557


AB020660
0.047678
0.006683
0.001858
−0.27616
KIAA0853


X93595
0.047678
0.006683
0.026214
0.245064
KIR3DL2


AB002405
0.047678
0.006683
0.003681
−0.19481
LAK-4P


X07228
0.047678
0.006683
0.046458
0.113484
LIPC


U50529
0.047678
0.006683
0.001977
0.310499
LOC88523


AF040963
0.047678
0.006683
0.012629
0.148739
MAD4


U59423
0.047678
0.006683
0.01126
−0.1341
MADH1


U85430
0.013622
0.006683
0.000224
−0.41454
NFATC3


X80878
0.047678
0.006683
0.010021
−0.16096
NFRKB


AF005043
0.013622
0.006683
0.00078
−0.15296
PARG


D49818
0.047678
0.006683
0.021976
−0.10631
PFKFB4


M28393
0.013622
0.006683
0.003241
−0.16419
PRF1


Y00062
0.047678
0.006683
0.011868
−0.2415
PTPRC


L07758
0.047678
0.006683
0.008943
0.201883
PWP1


U57094
0.047678
0.006683
0.014944
−0.31108
RAB27A


M35416
0.013622
0.006683
0.002789
−0.41233
RALB


X75042
0.047678
0.006683
0.003614
0.659166
REL


AF038250
0.047678
0.006683
0.004198
0.395171
SFRS3


L27213
0.013622
0.006683
0.001014
−0.13065
SLC4A3


Y09568
0.047678
0.006683
0.005799
−0.3407
SNAP23


AA205857
0.013622
0.006683
0.00048
0.27495
SNRPD3


U07794
0.047678
0.006683
0.007632
−0.20733
TXK


J05428
0.013622
0.006683
0.00573
−0.08342
UGT2B7


U09848
0.047678
0.006683
0.011538
−0.26846
ZNF36


J00287
0.047678
0.006683
0.000953
−0.28381


AB007882
0.013622
0.009369
0.006034
−0.17275
ADCY6


AF072810
0.013622
0.009369
0.016137
−0.32509
BAZ1B


AB004066
0.013622
0.009369
0.00789
0.494455
BHLHB2


U37547
0.013622
0.009369
0.00478
0.544595
BIRC2


AB024704
0.013622
0.009369
0.010893
−0.11914
C20orf1


AC004084
0.013622
0.009369
0.005491
−0.17437
CAPRI


L12691
0.013622
0.009369
0.018291
−0.18848
DEFA3


L19161
0.013622
0.009369
0.001645
−0.27253
EIF2S3


M82882
0.013622
0.009369
0.003966
0.478256
ELF1


X81625
0.013622
0.009369
0.003918
0.762544
ETF1


M15059
0.013622
0.009369
0.035106
0.313247
FCER2


AA284298
0.013622
0.009369
0.028745
−0.12535
FLJ22269


U13044
0.013622
0.009369
0.017986
−0.32813
GABPA


Z12173
0.013622
0.009369
0.001297
−0.32703
GNS


U06631
0.013622
0.009369
0.003506
−0.37935
H326


X75315
0.013622
0.009369
0.002959
1.06191
HSRNASEB


AF064084
0.013622
0.009369
0.017927
−0.10308
ICMT


AB002330
0.013622
0.009369
0.048512
−0.09076
KIAA0332


AB014569
0.013622
0.009369
0.010011
0.709572
KIAA0669


AI970189
0.013622
0.009369
0.001778
0.569801
KIAA0997


AB028960
0.013622
0.009369
0.001825
−0.15403
KIAA1037


AJ005273
0.013622
0.009369
0.001449
0.379277
KIN


L00352
0.013622
0.009369
0.004231
0.554465
LDLR


X54304
0.013622
0.009369
0.000863
−0.19567
MLCB


AI693193
0.013622
0.009369
0.023978
−0.25831
MTX1


AF047487
0.013622
0.009369
0.001312
−0.33746
NCK2


AF037448
0.013622
0.009369
0.00743
0.204106
NSAP1


AF000152
0.013622
0.009369
0.025216
−0.34592
OS4


U02882
0.013622
0.009369
0.017536
0.892321
PDE4D


X89416
0.013622
0.009369
0.005129
−0.1405
PPP5C


U27516
0.013622
0.009369
0.004164
−0.17553
RAD52


D23660
0.013622
0.009369
0.01215
0.149327
RPL4


AB016247
0.013622
0.009369
0.019879
0.416634
SC5DL


U44754
0.013622
0.009369
0.005273
0.158396
SNAPC1


AI660929
0.013622
0.009369
0.000698
−0.15764
T1A-2


X01060
0.013622
0.009369
0.005079
0.27369
TFRC


J02973
0.013622
0.009369
0.006825
0.835338
THBD


L41690
0.013622
0.009369
0.020209
−0.32814
TRADD


X89066
0.013622
0.009369
0.000396
−0.2226
TRPC1


AB024327
0.013622
0.009369
0.031
0.260875
UNRIP


AF033199
0.013622
0.009369
0.02842
−0.1806
ZNF204


AL080123
0.013622
0.009369
0.018447
0.215445
ZNF23


AB007885
0.013622
0.009369
0.025803
−0.22701
ZNF262


U40462
0.013622
0.009369
0.004101
−0.29722
ZNFN1A1


HG3477-HT3670
0.013622
0.009369
0.00042
−0.2367


L42324
0.013622
0.009369
0.015195
0.283048
GPR18


AA975427
0.013622
0.009369
0.002377
−0.26992


AL049957
0.013622
0.009369
0.007809
0.133451


AL022398
0.013622
0.009369
0.017529
−0.48579


HG2689-HT2785
0.013622
0.009369
0.029818
0.202486


AF034373
0.013622
0.014679
0.00591
−0.26511
A2LP


X83467
0.013622
0.014679
0.006111
−0.25837
ABCD3


U41766
0.047678
0.014679
0.014363
0.473526
ADAM9


D67031
0.013622
0.014679
0.007826
−0.4645
ADD3


U84011
0.013622
0.014679
0.012995
−0.2499
AGL


M74088
0.013622
0.014679
0.038601
−0.16952
APC


U67092
0.047678
0.014679
0.047381
−0.10935
ATM


AI033692
0.047678
0.014679
0.010056
−0.2417
BCRP1


X92106
0.013622
0.014679
0.001377
−0.33994
BLMH


Z22535
0.047678
0.014679
0.021613
−0.09832
BMPR1A


X79067
0.047678
0.014679
0.0381
0.14954
BRF1


X86098
0.013622
0.014679
0.000807
−0.34829
BS69


U72649
0.047678
0.014679
0.029157
0.227444
BTG2


X95592
0.047678
0.014679
0.014127
0.201273
C1D


D78586
0.047678
0.014679
0.028845
−0.05709
CAD


D30742
0.047678
0.014679
0.028215
0.180381
CAMK4


AF035582
0.047678
0.014679
0.002042
0.530946
CASK


U60521
0.047678
0.014679
0.002353
0.552837
CASP9


AL035079
0.013622
0.014679
0.00063
−0.78567
CAT


AF094481
0.047678
0.014679
0.024569
0.149973
CGGBP1


X83378
0.013622
0.014679
0.025603
0.133485
CLCN6


AB002332
0.047678
0.014679
0.003136
−0.20009
CLOCK


D13146
0.013622
0.014679
0.017967
−0.13385
CNP


S80864
0.013622
0.014679
0.011106
−0.33164
CYCL


D17530
0.047678
0.014679
0.005519
−0.15234
DBN1


U87947
0.047678
0.014679
0.011279
0.222382
EMP3


M60459
0.047678
0.014679
0.010174
−0.10156
EPOR


AB018247
0.013622
0.014679
0.000348
0.423577
FE65L2


AB028973
0.013622
0.014679
0.046458
−0.12088
FLJ10883


AL080172
0.047678
0.014679
0.02693
−0.063
FLJ21919


AF032886
0.047678
0.014679
0.009814
0.232307
FOXO3A


U00928
0.047678
0.014679
0.01307
−0.0915
FUS


M14660
0.047678
0.014679
0.011038
0.732462
FUT10


AI935146
0.047678
0.014679
0.044653
0.246267
GALNT3


U28811
0.047678
0.014679
0.007572
−0.21558
GLG1


AF001903
0.013622
0.014679
0.001957
−0.28636
HADHSC


Y09306
0.047678
0.014679
0.045083
−0.08024
HIPK3


AL022723
0.047678
0.014679
0.041021
0.165267
HLA-G


M80469
0.013622
0.014679
0.037453
−0.12099
HLA-J


M16937
0.013622
0.014679
0.002262
−0.13536
HOXB7


X98307
0.013622
0.014679
0.011852
−0.0908
HSHUR7SEQ


HG2855-HT2995
0.047678
0.014679
0.030595
0.16813
HSP70


X87949
0.047678
0.014679
0.028569
0.296273
HSPA5


W68830
0.013622
0.014679
0.007971
−0.22855
HSPC022


D49410
0.047678
0.014679
0.040369
0.153358
HUMIL3RA12


AL049470
0.013622
0.014679
0.010492
0.283688
HYPB


Y10659
0.047678
0.014679
0.024205
−0.1217
IL13RA1


X52015
0.047678
0.014679
0.006637
0.417081
IL1RN


AF047492
0.047678
0.014679
0.002557
0.25738
IMPG1


U96919
0.013622
0.014679
0.003221
−0.19947
INPP4A


U12897
0.013622
0.014679
0.002496
−0.15016
IPW


S62539
0.013622
0.014679
0.012982
−0.20615
IRS1


AF029778
0.047678
0.014679
0.018006
−0.14486
JAG2


W25934
0.047678
0.014679
0.016925
0.363279
JTV1


X56681
0.047678
0.014679
0.004935
0.713663
JUND


M64934
0.047678
0.014679
0.003162
−0.1823
KEL


D86975
0.047678
0.014679
0.048475
0.163408
KIAA0222


AB020701
0.013622
0.014679
0.013946
0.283086
KIAA0894


AB023141
0.047678
0.014679
0.017326
−0.33543
KIAA0924


AB023148
0.013622
0.014679
0.016218
−0.27496
KIAA0931


AB023227
0.047678
0.014679
0.043542
0.316063
KIAA1010


AB028963
0.047678
0.014679
0.039194
−0.12296
KIAA1040


AL080188
0.047678
0.014679
0.016745
−0.10387
KIAA1775


AJ224162
0.013622
0.014679
0.002225
−0.24337
LAS


L25931
0.013622
0.014679
0.00482
−0.2367
LBR


AC004410
0.047678
0.014679
0.017457
0.210096
LOC56928


AB009462
0.047678
0.014679
0.012892
0.131673
LRP3


AF077820
0.013622
0.014679
0.003095
−0.40005
LRP5


X59408
0.047678
0.014679
0.018321
−0.3029
MCP


L13773
0.013622
0.014679
0.002741
−0.18297
MLLT2


X82209
0.047678
0.014679
0.010828
0.178564
MN1


X96401
0.013622
0.014679
0.001643
0.317165
MNT


M30818
0.047678
0.014679
0.032832
0.292682
MX2


V00568
0.013622
0.014679
0.008535
−0.58978
MYC


D50692
0.013622
0.014679
0.043374
−0.20783
MYCBP


AB007191
0.013622
0.014679
0.022026
−0.18098
MYCBP


X17576
0.013622
0.014679
0.001641
−0.26027
NCK1


X61498
0.013622
0.014679
0.006234
0.307667
NFKB2


AF052093
0.047678
0.014679
0.001318
−0.31976
NJMU-R1


X00737
0.047678
0.014679
0.037385
0.219194
NP


U02020
0.047678
0.014679
0.014866
0.650286
PBEF


X66362
0.047678
0.014679
0.006159
0.137944
PCTK3


AF026086
0.047678
0.014679
0.006555
−0.18222
PEX1


L25441
0.047678
0.014679
0.011907
0.146471
PGGT1B


AL021366
0.013622
0.014679
0.002775
0.425217
PHF1


D85418
0.013622
0.014679
0.004449
−0.31688
PIGC


D30037
0.047678
0.014679
0.001579
−0.21226
PITPNB


AB006746
0.047678
0.014679
0.0356
0.189986
PLSCR1


AF054182
0.013622
0.014679
0.002098
−0.54761
PMPCB


S87759
0.013622
0.014679
0.007522
0.39052
PPM1A


M13057
0.047678
0.014679
0.032523
−0.19317
PRH1


M64992
0.047678
0.014679
0.047326
0.178696
PSMA1


X58288
0.047678
0.014679
0.002633
0.409542
PTPRM


AD000092
0.047678
0.014679
0.028359
0.137917
RAD23A


U79716
0.013622
0.014679
0.003409
0.195389
RELN


U69198
0.047678
0.014679
0.048001
0.085316
RFNG


AF117829
0.047678
0.014679
0.003668
0.377251
RIPK2


AF039029
0.047678
0.014679
0.002146
−0.28622
RNUT1


AW021542
0.013622
0.014679
0.000677
−0.29232
SAP18


U64197
0.047678
0.014679
0.021124
0.220476
SCYA20


AB023136
0.013622
0.014679
0.00288
−0.10963
SEC15B


AF055006
0.013622
0.014679
0.011241
0.238955
SEC6


Z46606
0.047678
0.014679
0.005778
−0.1566
SMARCA3


L25270
0.047678
0.014679
0.002401
−0.15644
SMCX


M60618
0.013622
0.014679
0.006316
0.235838
SP100


AI739308
0.013622
0.014679
0.001861
−0.57419
SRP46


U52960
0.047678
0.014679
0.02599
0.429086
SURB7


D50863
0.013622
0.014679
0.006582
−0.13005
TESK1


D64015
0.013622
0.014679
0.007587
−0.3629
TIAL1


AB001523
0.047678
0.014679
0.027565
0.164838
TMEM1


L21715
0.013622
0.014679
0.000862
0.309808
TNNI2


AF045583
0.047678
0.014679
0.043887
−0.16757
TULP3


AJ001340
0.013622
0.014679
0.002396
−0.17031
U3-55K


AB015344
0.013622
0.014679
0.008107
−0.31161
UBQLN2


J03824
0.013622
0.014679
0.005864
−0.18849
UROS


AF022789
0.047678
0.014679
0.006582
0.309267
USP12


U48801
0.013622
0.014679
0.003849
−0.17743
VEGFB


HG544-HT544
0.047678
0.014679
0.010549
0.454218


S66666
0.013622
0.014679
0.003364
−0.14303


AI687419
0.047678
0.014679
0.039394
−0.3657


W28800
0.047678
0.014679
0.004582
0.270831


AL080111
0.013622
0.014679
0.001378
−0.36029


AF070536
0.047678
0.014679
0.006685
0.199364


AF070633
0.047678
0.014679
0.010142
−0.1635


AF054998
0.013622
0.014679
0.007913
−0.21157


HG3725-HT3981
0.047678
0.014679
0.027792
−0.11953


HG1614-HT1614
0.013622
0.014679
0.006999
−0.45233


M22324
0.013622
0.01669
0.009982
0.283293
ANPEP


AC005955
0.013622
0.01669
0.004346
0.137324
CEACAM4


S68134
0.013622
0.01669
0.005372
1.92718
CREM


S68271
0.013622
0.01669
0.009154
1.49785
CREM


M24069
0.013622
0.01669
0.003022
0.249971
CSDA


AF000984
0.013622
0.01669
0.004295
0.46432
DBY


AF055917
0.013622
0.01669
0.015434
0.102855
F2RL3


U27333
0.013622
0.01669
0.012662
0.136047
FUT6


X89887
0.013622
0.01669
0.009728
0.152829
HIRA


L42243
0.013622
0.01669
0.002638
0.218644
IFNAR2


AI950382
0.013622
0.01669
0.00744
0.601631
KIAA0585


AI950382
0.013622
0.01669
0.002126
0.519735
KIAA0585


U17760
0.013622
0.01669
0.044392
0.431131
LAMB3


L48692
0.013622
0.01669
0.041233
0.63409
LOC56902


X94232
0.013622
0.01669
0.016402
0.326694
MAPRE2


AA037278
0.013622
0.01669
0.01607
0.119411
MGC10882


L13740
0.013622
0.01669
0.007795
0.355688
NR4A1


U12767
0.013622
0.01669
0.011648
1.30268
NR4A3


D78579
0.013622
0.01669
0.005896
1.11766
NR4A3


X17042
0.013622
0.01669
0.015594
0.239796
PRG1


U48296
0.013622
0.01669
0.003124
0.864101
PTP4A1


M83221
0.013622
0.01669
0.012321
0.192956
RELB


AF107463
0.013622
0.01669
0.009662
0.419254
SPF30


L47276
0.013622
0.01669
0.004673
0.194449
TOP2A


X00734
0.013622
0.01669
0.010039
0.347307
TUBB5


X51521
0.013622
0.01669
0.010303
0.60161
VIL2


S54641
0.013622
0.01669
0.008483
0.183207
ZNF124


M91029
0.013622
0.022759
0.010686
0.450612
AMPD2


AB021638
0.136189
0.022759
0.024881
−0.1126
APBA3


AL120559
0.013622
0.022759
0.004505
0.577915
ARPP-19


AF039656
0.013622
0.022759
0.006991
0.68481
BASP1


AB020623
0.047678
0.022759
0.009696
0.418826
BCAS2


X60201
0.013622
0.022759
0.011758
−0.1576
BDNF


U56637
0.047678
0.022759
0.008899
−0.28102
CAPZA1


AW043690
0.047678
0.022759
0.031971
0.134862
CCK


D13627
0.047678
0.022759
0.019298
0.203913
CCT8


U56998
0.013622
0.022759
0.024403
0.442545
CNK


U71267
0.047678
0.022759
0.007233
−0.13426
CNOT4


F27891
0.047678
0.022759
0.02847
0.119514
COX6A2


U78524
0.013622
0.022759
0.002554
0.353034
DDXBP1


AF043733
0.047678
0.022759
0.005645
0.22771
DEDD


X64229
0.013622
0.022759
0.013033
−0.20244
DEK


AL050284
0.047678
0.022759
0.002819
0.232244
DKFZP586M1019


L05147
0.013622
0.022759
0.021168
0.111752
DUSP3


U15642
0.013622
0.022759
0.013339
0.474421
E2F5


U31556
0.047678
0.022759
0.011303
0.335871
E2F5


AC004262
0.047678
0.022759
0.004968
−0.25642
EMR2


AA181196
0.047678
0.022759
0.009459
−0.10534
FLJ11712


U74612
0.013622
0.022759
0.014802
−0.18783
FOXM1


W28281
0.013622
0.022759
0.011042
0.813742
GABARAPL1


AI183417
0.013622
0.022759
0.011016
0.117979
GABPB1


L13720
0.013622
0.022759
0.014471
−0.1601
GAS6


X15722
0.013622
0.022759
0.029451
−0.19175
GSR


Y07595
0.013622
0.022759
0.003113
−0.20996
GTF2H4


L43821
0.047678
0.022759
0.005863
−0.20401
HEF1


L10379
0.013622
0.022759
0.02006
−0.15961
HRIHFB2206


X99209
0.013622
0.022759
0.021333
−0.14942
HRMT1L1


X77956
0.013622
0.022759
0.009598
0.591031
ID1


AL021707
0.013622
0.022759
0.004161
1.79061
KIAA0063


AB007896
0.013622
0.022759
0.006273
−0.41247
KIAA0436


AB014528
0.047678
0.022759
0.001992
−0.31837
KIAA0628


AB014607
0.013622
0.022759
0.000764
−0.15753
KIAA0707


AB018290
0.013622
0.022759
0.034506
−0.28703
KIAA0747


AB018337
0.013622
0.022759
0.008466
−0.41118
KIAA0794


AB023161
0.013622
0.022759
0.018461
−0.15095
KIAA0944


AB023202
0.013622
0.022759
0.005879
−0.19156
KIAA0985


U80743
0.013622
0.022759
0.000544
−0.30322
KIAA1498


X13794
0.047678
0.022759
0.018671
−0.12764
LDHB


Z34975
0.013622
0.022759
0.012256
−0.29089
LDLC


AI341656
0.047678
0.022759
0.021482
−0.26002
LIM


X87342
0.013622
0.022759
0.006652
−0.23382
LLGL2


U29671
0.047678
0.022759
0.001133
−0.2617
MAP3K1


Z14138
0.013622
0.022759
0.00408
0.81232
MAP3K8


AI743606
0.013622
0.022759
0.00269
−0.19764
MEL


AF052183
0.013622
0.022759
0.002151
−0.19631
MGC2722


AL050356
0.013622
0.022759
0.002743
−0.42417
MINPP1


AF041081
0.013622
0.022759
0.019282
−0.21627
MN7


U59302
0.013622
0.022759
0.003859
0.280175
NCOA1


W28360
0.013622
0.022759
0.016633
0.272057
NCUBE1


U97198
0.013622
0.022759
0.001352
−0.20163
NLP_1


AA194159
0.013622
0.022759
0.004614
−0.40044
PEX10


U38964
0.013622
0.022759
0.004912
−0.23793
PMS2L8


D38498
0.013622
0.022759
0.003965
−0.58306
PMS2L9


AA996066
0.013622
0.022759
0.003514
−0.21994
PMS2L9


AB029028
0.013622
0.022759
0.027753
−0.29778
RAP140


AA402524
0.047678
0.022759
0.005359
−0.11564
RBM9


U79745
0.013622
0.022759
0.00409
0.777629
SLC16A6


X98332
0.013622
0.022759
0.002282
−0.20078
SLC22A1


D42045
0.013622
0.022759
0.006867
−0.19726
SNM1


M76231
0.013622
0.022759
0.009942
0.13899
SPR


U76366
0.013622
0.022759
0.015416
−0.09378
TCOF1


U09087
0.013622
0.022759
0.00607
−0.26017
TMPO


AF049140
0.047678
0.022759
0.011115
−0.21894
UBE2V2


AF038962
0.047678
0.022759
0.007219
−0.44337
VDAC3


D84145
0.013622
0.022759
0.002923
0.574155
WS-3


Y09723
0.047678
0.022759
0.001292
0.234149
ZNF151


AL049991
0.013622
0.022759
0.007094
0.245237


AL050148
0.013622
0.022759
0.013128
−0.26398


AI014538
0.013622
0.022759
0.003507
−0.15278


AI732885
0.047678
0.022759
0.043886
−0.10293


U14573
0.013622
0.022759
0.04259
−0.11614


U82987
0.013622
0.024606
0.00343
−0.17272
BBC3


L12168
0.013622
0.024606
0.007944
−0.22028
CAP


V00571
0.013622
0.024606
0.005873
0.132015
CRH


AL022398
0.013622
0.024606
0.015005
−0.44535
DJ434O14.3


AL080081
0.013622
0.024606
0.007659
0.548836
DNAJB9


X85116
0.013622
0.024606
0.039531
−0.24601
EPB72


AJ007669
0.013622
0.024606
0.019404
−0.23162
FANCG


AW024285
0.013622
0.024606
0.007049
0.311562
FLJ12443


W27666
0.013622
0.024606
0.009544
−0.25685
FLJ14393


AA908993
0.013622
0.024606
0.015356
−0.12684
FLJ14393


U90917
0.013622
0.024606
0.016602
−0.23386
FOXM1


AF017445
0.013622
0.024606
0.025525
−0.33517
FPGT


AJ238764
0.013622
0.024606
0.030667
0.197763
GNE


J04501
0.013622
0.024606
0.007821
−0.23523
GYS1


X56841
0.013622
0.024606
0.022605
−0.23469
HLA-E


M63438
0.013622
0.024606
0.005389
−0.75873
IGKC


S66213
0.013622
0.024606
0.011362
−0.09802
ITGA6


AB007870
0.013622
0.024606
0.002855
0.657213
KIAA0410


N29665
0.013622
0.024606
0.008301
−0.49779
KIAA0618


AB018353
0.013622
0.024606
0.033864
−0.3542
KIAA0810


D10522
0.013622
0.024606
0.028464
0.22227
MACS


AF004709
0.013622
0.024606
0.018118
−0.09931
MAPK13


W28275
0.013622
0.024606
0.005871
−0.27591
MGC11061


AF087020
0.013622
0.024606
0.032064
−0.13544
MPZL1


U61981
0.013622
0.024606
0.012069
−0.20932
MSH3


U90942
0.013622
0.024606
0.004002
0.179029
MYO5A


D50370
0.013622
0.024606
0.008327
−0.11492
NAP1L3


U91512
0.013622
0.024606
0.00493
0.549889
NINJ1


AF069987
0.013622
0.024606
0.007336
−0.16953
NIT1


U37689
0.013622
0.024606
0.007097
−0.17369
POLR2H


L19067
0.013622
0.024606
0.006406
0.148517
RELA


X13482
0.013622
0.024606
0.016873
0.241998
SNRPA1


D16827
0.013622
0.024606
0.004314
−0.16954
SSTR5


AB011420
0.013622
0.024606
0.030791
0.171669
STK17A


L39060
0.013622
0.024606
0.026797
−0.24028
TAF1A


AB011169
0.013622
0.024606
0.004017
−0.24355
TEB4


U69108
0.013622
0.024606
0.024472
−0.17595
TRAF5


AB011004
0.013622
0.024606
0.00265
1.03158
UAP1


AB014584
0.013622
0.024606
0.028525
−0.1337
UBE4B


HG3914-HT4184
0.013622
0.024606
0.025854
−0.12454


Z32860
0.013622
0.024606
0.002037
−0.11041


U25849
0.013622
0.024606
0.00632
−0.43498


AF052100
0.013622
0.024606
0.006718
−0.2297


X59268
0.013622
0.024606
0.003586
0.479423
GTF2B


AF007142
0.013622
0.024606
0.01864
−0.34584


AI312646
0.013622
0.024606
0.027596
−0.14991


AL022318
0.047678
0.028192
0.049355
−0.11704
APOBEC1L


M30704
0.047678
0.028192
0.00926
0.279668
AREG


AF001307
0.047678
0.028192
0.018109
−0.12594
ARNT


AB020680
0.047678
0.028192
0.007009
0.227256
BAG5


AF018631
0.047678
0.028192
0.008344
−0.13689
BTD


D64110
0.047678
0.028192
0.022809
0.398412
BTG3


Z11697
0.047678
0.028192
0.024131
0.750492
CD83


M31516
0.047678
0.028192
0.021562
0.517068
DAF


AF000982
0.047678
0.028192
0.025357
0.29808
DDX3


L77566
0.047678
0.028192
0.01243
0.178957
DGSI


AL096725
0.047678
0.028192
0.007381
0.436688
DKFZP434B103


AL080201
0.047678
0.028192
0.044829
−0.11576
DKFZP434F162


AL050286
0.047678
0.028192
0.004267
−0.22397
DKFZP586A011


Y13350
0.047678
0.028192
0.015562
0.137002
DNAJA2


AJ223333
0.047678
0.028192
0.013836
−0.17437
DNMT2


L34075
0.047678
0.028192
0.013848
−0.25236
FRAP1


D31766
0.047678
0.028192
0.029287
−0.09623
GNPI


Z80776
0.047678
0.028192
0.002034
0.143491
H2AFG


K03183
0.047678
0.028192
0.040298
0.163306
HUMCGBBA3


X57025
0.047678
0.028192
0.009135
0.437394
IGF1


X56681
0.047678
0.028192
0.012885
0.423181
JUND


AB007916
0.047678
0.028192
0.00772
−0.45744
KIAA0447


AI672098
0.047678
0.028192
0.014331
0.160649
KIAA0934


AB029020
0.047678
0.028192
0.035285
−0.3101
KIAA1097


W27233
0.047678
0.028192
0.019918
−0.24802
KIDINS220


AL049341
0.047678
0.028192
0.001943
−0.3086
LOC57209


AL049422
0.047678
0.028192
0.028823
0.264129
LOC84549


AF010193
0.047678
0.028192
0.003729
0.927225
MADH7


AF007134
0.047678
0.028192
0.009151
−0.1209
MAPK8IP1


L04731
0.047678
0.028192
0.025599
−0.07236
MLL


AB014547
0.047678
0.028192
0.023787
−0.15831
MTMR4


U91616
0.047678
0.028192
0.018681
0.377931
NFKBIE


X75918
0.047678
0.028192
0.019713
1.21948
NR4A2


AL049842
0.047678
0.028192
0.022698
0.201258
NUFIP1


U57843
0.047678
0.028192
0.011796
−0.13969
PIK3CD


S76965
0.047678
0.028192
0.012413
0.426208
PKIA


AL023553
0.047678
0.028192
0.00321
−0.15608
PMM1


M93425
0.047678
0.028192
0.019899
−0.36854
PTPN12


AF044968
0.047678
0.028192
0.006887
0.121898
PVRL2


M28211
0.047678
0.028192
0.050065
−0.08518
RAB4


AF083255
0.047678
0.028192
0.021248
−0.27368
RNAHP


U04897
0.047678
0.028192
0.013893
0.278167
RORA


AL031228
0.047678
0.028192
0.020491
−0.22382
SACM2L


Y08262
0.047678
0.028192
0.008184
−0.34195
SCA2


AF000652
0.047678
0.028192
0.001533
0.415218
SDCBP


D31891
0.047678
0.028192
0.00536
−0.18144
SETDB1


X66079
0.047678
0.028192
0.008707
0.129642
SPIB


Z96932
0.047678
0.028192
0.013622
−0.14003
SSNA1


D43642
0.047678
0.028192
0.015302
−0.26409
TCFL1


D50919
0.047678
0.028192
0.016207
−0.23972
TRIM14


X01703
0.047678
0.028192
0.004339
0.386096
TUBA3


AF022375
0.047678
0.028192
0.015198
0.503607
VEGF


AF062346
0.047678
0.028192
0.014763
0.455053
ZNF216


J04755
0.047678
0.028192
0.014444
0.302274


AA524802
0.047678
0.028192
0.036226
−0.24775


AL096749
0.047678
0.028192
0.017041
0.106309


M21259
0.047678
0.028192
0.025927
0.18378


X61587
0.047678
0.037364
0.024028
0.222788
ARHG


J04027
0.047678
0.037364
0.019918
0.336927
ATP2B1


W28091
0.047678
0.037364
0.016936
−0.1567
BBS4


U03106
0.047678
0.037364
0.004064
0.915096
CDKN1A


AL049924
0.047678
0.037364
0.001517
−0.23208
DKFZP547G1110


L19161
0.047678
0.037364
0.006578
−0.49859
EIF2S3


AF052123
0.136189
0.037364
0.013524
−0.24445
FLJ10814


AA522530
0.047678
0.037364
0.038021
0.413536
FLJ20500


AJ011001
0.047678
0.037364
0.016436
−0.63045
GPR56


U50079
0.047678
0.037364
0.013178
−0.37546
HDAC1


AI796944
0.047678
0.037364
0.011597
0.216392
HIS1


S82986
0.047678
0.037364
0.006441
−0.20652
HOXC6


AB011173
0.047678
0.037364
0.01376
−0.26283
KIAA0601


AB023160
0.047678
0.037364
0.029467
−0.23276
KIAA0943


AJ001685
0.047678
0.037364
0.015208
−0.48906
KLRC3


AJ000673
0.047678
0.037364
0.009021
−0.38103
KLRD1


AB002450
0.047678
0.037364
0.003391
−0.37426
LOC51014


U68385
0.047678
0.037364
0.007651
−0.16327
MEIS3


AI688516
0.047678
0.037364
0.017859
−0.15146
NDUFA2


W28770
0.047678
0.037364
0.005269
−0.16121
NP25


L41827
0.047678
0.037364
0.011308
0.139896
NRG1


X84373
0.047678
0.037364
0.00725
0.77533
NRIP1


M25897
0.047678
0.037364
0.025747
−0.41462
PF4


U50062
0.047678
0.037364
0.018154
0.19401
RIPK1


AJ011785
0.047678
0.037364
0.017907
−0.07616
SIX6


X70683
0.047678
0.037364
0.0155
−0.10219
SOX4


AL035699
0.047678
0.037364
0.006561
−0.15185
TBPL1


D15050
0.047678
0.037364
0.016133
0.990791
TCF8


AF017146
0.047678
0.037364
0.002975
−0.20652
TOP3B


U54996
0.047678
0.037364
0.00691
−0.17359
ZW10


HG4234-HT4504
0.047678
0.037364
0.003258
−0.13985


X04500
0.047678
0.058634
0.02228
0.857952
IL1B
















TABLE IV










Differential Gene Expression in MOG-reactive T-cells-MS vs.


Healthy
















Fold
Pvalue


Identifier
Symbol
Name
Function
Change
t-test















Up







regulated


M35878
IGFBP3
insulin-like growth
modulate IGF activity
5.8
0.03




factor binding protein 3


AB002318
KIAA0320
KIAA0320 protein

2.4
0.05


AF024710
VEGF
vascular endothelial
endothelial cell
2.3
0.02




growth factor
proliferation


AA628946
KHSRP
KH-type splicing
mRNA processing
2.2
0.01




regulatory protein


L42374
PPP2R5B
protein phosphatase 2,
protein phosphatase
2.1
0.05




regulatory subunit B


U54644
TUB
tubby (mouse)
may be a
1.8
0.01




homolog
transcription factor


AB023167
KIAA0950
lifeguard
Apoptosis
1.8
0.006


X62654
CD63
CD63 antigen
growth regulation
1.8
0.03




(melanoma 1 antigen)


H98552

cDNA

1.8
0.01




DKFZp586I0523


AL050395
MOF
member of MYST
histone acetyl
1.7
0.03




acetyl transferases
transferases


L27213
SLC4A3
solute carrier family 4,
inorganic anion
1.7
0.01




anion exchange 3
exchanger


AF014837
M6A
putative
Transcription factor
1.6
0.05




methyltransferase


AB014537
KIAA0637
KIAA0637 gene
Apoptosis
1.5
0.003




product


D13969
ZNF144
zinc finger protein 144
DNA-Binding protein
1.5
0.04




(Mel-18)


AJ012590
H6PD
hexose-6-phosphate
Oxidoreductase
1.5
0.04




dehydrogenase


M13995
BCL2
B-cell CLL/lymphoma 2
Apoptosis
1.5
0.03


AI760801

chromosome 19,

1.5
0.009




cosmid R31180


AI660963
MAP3K12
mitogen-activated
Transferase
1.5
0.02




protein 3 kinase 12
cytoplasmic


Down


regulated


D45248
PSME2
proteasome activator
Protein degradation
−1.5
0.04




subunit 2 (PA28 beta)


W28612

ESTs

−1.5
0.02


Z46389
VASP
vasodilator-stimulated
Signal transduction
−1.6
0.02




phosphoprotein


AA152202
FLJ14639
hypothetical protein

−1.6
0.02




FLJ14639


AF080561
RBM14
RNA binding motif
RNA binding protein
−1.7
0.03




protein 14


D50922
KIAA0132
Kelch-like ECH-
ECH-associated
−1.7
0.03




associated protein 1
protein 1


AF025441
OIP5
Opa-interacting protein 5

−1.8
0.04


AF080227
EED
embryonic ectoderm
transcriptional
−1.8
0.04




development
repressor


D87957
RQCD1
required for cell
sex differentiation
−1.9
0.03




differentiation


X61498
NFKB2
nuclear factor of kappa
expression of
−1.9
0.05




light polypeptide
inflammatory genes




Bcells


X52425
IL4R
interleukin 4 receptor
receptor signalling
−2
0.04





protein


L08069
DNAJA1
DnaJ (Hsp40)
protein folding and
−2
0.04




homolog, subfamily A,
transport




member 1


AF071504
STX11
syntaxin 11
protein transport
−2.1
0.03


M11717
HSPA1A
heat shock 70 kD
heat shock response
−2.2
0.03




protein 1A


M59830
HSPA1B
heat shock 70 kD
heat shock response
−2.2
0.03




protein 1B


M16441
TNF
Human tumor necrosis
Inflammatory
−2.3
0.05




factor
response


D89077
SLA
Src-like-adapter

−2.4
0.05


U77949
CDC6
cell division cycle 6, S. cerevisiae
DNA replication
−2.5
0.02




homolog
checkpoint


D38549
KIAA0068
KIAA0068 protein

−2.5
0.01


L23959
TFDP1
transcription factor Dp-1
cycle progression G1
−2.5
0.01





to S-phase


L78833
BRCA1
Breast cancer

−2.7
0.04




susceptibility gene


M63193
ECGF1
endothelial cell growth
stimulates
−2.8
0.01




factor 1
angiogenesis


AF035625
STK11
serine/threonine kinase
Peutz-Jeghers
−2.9
0.04




11
syndrome


J04130
SCYA4
small inducible
Cell-to-cell signalling
−2.9
0.05




cytokine A4


X93086
BLVRA
biliverdin reductase A
biliverdin reductase
−4
0.03
















TABLE V










Differential Gene Expression in Probable MS vs. Healthy















t-Test
Log Fold



Identification
TNOM PValue
Info PValue
PValue
Change
Gene Symbol















NM_018049.1
0.000233
0.000233
2.46E−05
0.438337
FLJ10297


NM_005886.1
0.000233
0.000233
0.000553
0.35972
KATNB1


NM_000161.1
0.000233
0.000233
0.000297
−0.48848
GCH1


NM_001539.1
0.000233
0.000233
0.000144
−0.58017
DNAJA1


AF349571.1
0.004202
0.004202
0.000274
1.78925
HBA1


M25079.1
0.004202
0.004202
0.000247
1.59503
HBB


V00489
0.004202
0.004202
0.000268
1.54947


BC005931.1
0.004202
0.004202
0.000296
1.48707
HBA2


T50399
0.004202
0.004202
0.000275
1.43533
HBA2


NM_024567.1
0.004202
0.004202
0.002206
1.42146
FLJ21616


AF105974.1
0.004202
0.004202
0.001086
1.3896
HBA1


NM_000558.2
0.004202
0.004202
0.000707
1.3348
HBA1


AI133353
0.004202
0.004202
0.000897
1.29746
HBG2


AF059180
0.004202
0.004202
0.000309
1.29355


AF349114.1
0.004202
0.004202
0.000163
1.27511
HBB


BE547674
0.004202
0.004202
0.002947
0.636619


NM_012452.1
0.004202
0.004202
0.000541
0.570818
TNFRSF13B


AA314406
0.004202
0.001401
0.002013
0.520631
TRAP95


NM_015909.1
0.004202
0.001401
0.000398
0.501733
NAG


NM_006868.1
0.004202
0.004202
0.002711
0.49862
RAB31


BC000305.1
0.004202
0.004202
0.006921
0.475733
CASP6


L77566
0.004202
0.001401
0.00033
0.446293
DGSI


BF971416
0.004202
0.004202
0.002405
0.410742
DKFZP586N0721


BE879367
0.004202
0.004202
0.00056
0.382484
AKAP2


NM_001640.2
0.004202
0.001401
0.004091
0.36631
APEH


BC001808.1
0.004202
0.004202
0.012997
0.347043
NM23-H6


AL049539
0.004202
0.004202
0.010738
0.2822
KIAA0255


BC000580.1
0.004202
0.001401
0.014166
0.270658
PH-4


NM_012151.2
0.004202
0.001401
0.000685
0.267664
F8A


BC004423.1
0.004202
0.004202
0.012194
0.249144
TNRC5


NM_004890.1
0.004202
0.001401
0.010332
0.134439
SPAG7


AB029040
0.004202
0.004202
0.010819
−0.14172
KIAA1117


NM_025160.1
0.004202
0.001401
0.004986
−0.21141
FLJ21016


AW162015
0.004202
0.004202
0.301224
−0.24766
ZNF143


NM_005574.2
0.004202
0.004202
0.107595
−0.24939
LMO2


NM_014670.1
0.004202
0.004202
0.025534
−0.27225
BZW1


AL117643.1
0.004202
0.004202
0.046495
−0.27766


AA628948
0.004202
0.001401
0.000319
−0.28951
ADSS


AF251062.1
0.004202
0.001401
0.000435
−0.30924
LOC84549


AL564683
0.004202
0.004202
0.018258
−0.44633
CEBPB


NM_014999.1
0.004202
0.004202
0.001021
−0.47304
RAB21


NM_017723.1
0.004202
0.004202
0.02759
−0.49548
FLJ20245


NM_003264.1
0.004202
0.004202
0.002592
−0.49551
TLR2


AF062347.1
0.004202
0.004202
0.00529
−0.51432
ZNF216


NM_004556.1
0.004202
0.004202
0.001134
−0.53489
NFKBIE


U92014.1
0.004202
0.004202
0.003064
−0.59511


NM_014778.1
0.004202
0.004202
0.001106
−0.65156
KIAA0410


NM_015384.1
0.004202
0.004202
0.002943
−0.68193
IDN3


AK022513.1
0.004202
0.004202
0.001326
−0.68416
DUSP10


NM_003246.1
0.004202
0.001401
0.000162
−1.44745
THBS1


AI812030
0.004202
0.001401
7.42E−05
−1.51098
THBS1


NM_000559.1
0.035714
0.035247
0.006202
1.93991
HBG1


NM_000184.1
0.035714
0.04225
0.009164
1.67513
HBG2


NM_005564.1
0.035714
0.04225
0.010814
1.03322
LCN2


AF274863.1
0.035714
0.00747
0.007719
0.952868
SEC31B-1


NM_002288.2
0.035714
0.015406
0.010689
0.834313
LAIR2


M87789.1
0.035714
0.04225
0.058518
0.79032
IGHG3


NM_005764.1
0.035714
0.04225
0.053679
0.789147
DD96


AK000168.1
0.035714
0.04225
0.038176
0.763766
KIAA1919


NM_020037.1
0.035714
0.035247
0.061379
0.746143
ABCC3


AF103529.1
0.035714
0.035247
0.015284
0.736268


AV698647
0.035714
0.035247
0.017411
0.616137
IGLJ3


AI357539
0.035714
0.04225
0.00558
0.601843
MGC4126


NM_015935.1
0.035714
0.035247
0.021683
0.593818
CGI-01


D38535
0.035714
0.04225
0.016025
0.571168
ITIH4


AA723370
0.035714
0.04225
0.039917
0.570325
LOC51011


AF227968.1
0.035714
0.00747
0.005308
0.566516
SH2B


X12530.1
0.035714
0.04225
0.056335
0.559172
MS4A1


AI348935
0.035714
0.035247
0.014129
0.546773
CALR


NM_003422.1
0.035714
0.04225
0.006737
0.536815
ZNF42


NM_015559.1
0.035714
0.04225
0.028795
0.536316
SETBP1


NM_013378.1
0.035714
0.035247
0.005191
0.532564
VPREB3


NM_004912.1
0.035714
0.015406
0.003037
0.52082
CCM1


NM_006230.1
0.035714
0.015406
0.007471
0.517979
POLD2


NM_006235.1
0.035714
0.035247
0.021726
0.515263
POU2AF1


AL037557
0.035714
0.00747
0.002786
0.511724
POLR2I


NM_014703.1
0.035714
0.00747
0.006709
0.4938
KIAA0800


NM_015670.1
0.035714
0.035247
0.045708
0.464156
SENP3


AA643304
0.035714
0.015406
0.004712
0.459694


AI948503
0.035714
0.04225
0.017964
0.45625
ABCC4


BC002807.1
0.035714
0.04225
0.100759
0.455683
MS4A1


AF123539.1
0.035714
0.035247
0.028286
0.454603
HTCD37


AA149644
0.035714
0.00747
0.02413
0.450082
JAM3


BC000585.1
0.035714
0.04225
0.033113
0.44368
SLC21A11


AB044806.1
0.035714
0.04225
0.007766
0.433985
KCNH2


U37025
0.035714
0.035247
0.046971
0.427213
SULT1A1


NM_020166.2
0.035714
0.035247
0.006318
0.423798
MCCC1


NM_002876.1
0.035714
0.035247
0.026644
0.414867
RAD51C


NM_002387.1
0.035714
0.035247
0.01092
0.409481
MCC


NM_005816.1
0.035714
0.04225
0.103051
0.407348
TACTILE


H95263
0.035714
0.035247
0.069113
0.406766


NM_003146.1
0.035714
0.035247
0.003146
0.405309
SSRP1


NM_003550.1
0.035714
0.035247
0.054105
0.403851
MAD1L1


AK022494.1
0.035714
0.00747
0.001189
0.397073
RAB3GAP


NM_006400.2
0.035714
0.035247
0.021072
0.396297
DCTN2


NM_006012.1
0.035714
0.035247
0.015241
0.394779
CLPP


NM_014921.1
0.035714
0.035247
0.014463
0.394308
LEC2


NM_025056.1
0.035714
0.00747
0.01912
0.393739
FLJ23185


NM_003573.1
0.035714
0.04225
0.026053
0.393337
LTBP4


NM_000132.2
0.035714
0.035247
0.005292
0.392442
F8


AF031824.1
0.035714
0.035247
0.190243
0.389129
CST7


NM_001841.1
0.035714
0.035247
0.07115
0.387067
CNR2


NM_018391.1
0.035714
0.035247
0.138584
0.386982
FLJ23277


U79248.1
0.035714
0.00747
0.007475
0.386419


NM_024332.1
0.035714
0.04225
0.039154
0.386198
C6.1A


BF510692
0.035714
0.04225
0.046782
0.385324
PAX5


AA243774
0.035714
0.035247
0.050456
0.381631
MMP24


AL121964
0.035714
0.035247
0.107681
0.373759
MAP3K7


L25275.1
0.035714
0.035247
0.020684
0.372971
SULT1A3


AB018289.1
0.035714
0.035247
0.002286
0.37263
KIAA0746


NM_000294.1
0.035714
0.035247
0.011432
0.367693
PHKG2


BC001906.1
0.035714
0.035247
0.107947
0.366899
MTX1


NM_000651.1
0.035714
0.04225
0.047953
0.365471
CR1


NM_001667.1
0.035714
0.00747
0.009661
0.362105
ARL2


AI133727
0.035714
0.00747
0.018354
0.358884
ZAP


BC002873.1
0.035714
0.035247
0.048711
0.358052
DKFZP564J0123


NM_004178.2
0.035714
0.035247
0.007313
0.356459
TARBP2


BG532929
0.035714
0.035247
0.037215
0.356254
SSB


NM_018094.1
0.035714
0.035247
0.014302
0.351314
GSPT2


AC004531
0.035714
0.00747
0.01714
0.350445
DDX28


NM_001981.1
0.035714
0.035247
0.010776
0.347051
EPS15


AB020689.1
0.035714
0.035247
0.024594
0.346253
KIAA0882


NM_001055.1
0.035714
0.035247
0.056416
0.344937
SULT1A1


NM_022067.1
0.035714
0.035247
0.001332
0.337713
FLJ12707


NM_000195.1
0.035714
0.00747
0.014156
0.3312
HPS1


NM_022914.1
0.035714
0.00747
0.167735
0.331082
24432


NM_003627.1
0.035714
0.035247
0.062759
0.330371
POV1


NM_022060.1
0.035714
0.035247
0.010717
0.328122
FLJ12816


BF446180
0.035714
0.035247
0.02537
0.326347
PDCD2


U28169.1
0.035714
0.035247
0.0891
0.326218
SULT1A2


AF316873.1
0.035714
0.035247
0.022727
0.3257
PINK1


NM_017615.1
0.035714
0.035247
0.087717
0.325056
FLJ20003


NM_015853.1
0.035714
0.035247
0.021537
0.321089
LOC51035


NM_018449.1
0.035714
0.035247
0.01461
0.318475
UBAP2


NM_007056.1
0.035714
0.035247
0.013827
0.318086
SWAP2


AV702994
0.035714
0.035247
0.010766
0.316138
LOC51668


AK021884.1
0.035714
0.04225
0.016862
0.315879
NPEPPS


U64898.1
0.035714
0.035247
0.012705
0.309446
NRD1


AI431902
0.035714
0.035247
0.026163
0.307321
FLJ13491


NM_003689.1
0.035714
0.04225
0.03366
0.306281
AKR7A2


BE791629
0.035714
0.00747
0.039522
0.304821
CGTHBA


NM_016194.1
0.035714
0.035247
0.060249
0.303474
GNB5


NM_014965.1
0.035714
0.035247
0.013547
0.298042
KIAA1042


NM_003363.1
0.035714
0.035247
0.018393
0.295239
USP4


U88964
0.035714
0.035247
0.019349
0.294427
ISG20


BC001782.1
0.035714
0.035247
0.059026
0.293156
GAS2L1


BC004361.1
0.035714
0.04225
0.084538
0.292509
PSCD2


NM_017840.1
0.035714
0.035247
0.003929
0.290472
MRPL16


NM_006321.1
0.035714
0.015406
0.006688
0.288723
ARIH2


AI341234
0.035714
0.035247
0.007356
0.284699
CORO1B


N20923
0.035714
0.035247
0.020271
0.280552
FYN


L42531.1
0.035714
0.035247
0.008554
0.280023


AK000818.1
0.035714
0.035247
0.02226
0.277695
FLJ20811


NM_000633.1
0.035714
0.035247
0.044639
0.276897
BCL2


BE551347
0.035714
0.035247
0.209003
0.276406
FLJ13052


AK000161.1
0.035714
0.04225
0.016752
0.276103
FLJ20154


AI798908
0.035714
0.04225
0.015969
0.274921
KIAA0226


NM_005111.1
0.035714
0.035247
0.01405
0.273732
CRYZL1


NM_024551.1
0.035714
0.035247
0.00372
0.272684
FLJ21432


BC006214.1
0.035714
0.00747
0.006244
0.268704
IRO039700


AI123527
0.035714
0.04225
0.105392
0.268349
KIAA0092


NM_004379.1
0.035714
0.035247
0.047229
0.267796
CREB1


AA643304
0.035714
0.035247
0.039678
0.258201


NM_013417.1
0.035714
0.035247
0.047087
0.257738
IARS


AK025432.1
0.035714
0.035247
0.051871
0.257456
KIAA0564


AB028960
0.035714
0.04225
0.040942
0.254827
KIAA1037


NM_000048.1
0.035714
0.04225
0.038931
0.254447
ASL


NM_002808.1
0.035714
0.035247
0.023966
0.250129
PSMD2


NM_001054.1
0.035714
0.035247
0.062598
0.248696
SULT1A2


NM_005428.2
0.035714
0.035247
0.007185
0.248439
VAV1


NM_022758.1
0.035714
0.04225
0.011489
0.246401
FLJ22195


AY009128.1
0.035714
0.035247
0.084938
0.246257
NIFU


AB017004.1
0.035714
0.035247
0.079567
0.244954
PMS2L8


NM_000249.1
0.035714
0.04225
0.021274
0.243441
MLH1


U51007.1
0.035714
0.035247
0.042753
0.242223


BC002640.1
0.035714
0.035247
0.074751
0.240603


NM_016284.1
0.035714
0.00747
0.001929
0.240076
KIAA1007


NM_002414.1
0.035714
0.035247
0.063998
0.239013
MIC2


BC000212.1
0.035714
0.035247
0.021052
0.237577
GTF3C2


NM_004398.2
0.035714
0.035247
0.040656
0.235252
DDX10


NM_024713.1
0.035714
0.035247
0.048887
0.234927
FLJ22557


NM_002810.1
0.035714
0.035247
0.038558
0.234593
PSMD4


NM_030580.1
0.035714
0.035247
0.031263
0.233466
MGC10520


AB007896.1
0.035714
0.035247
0.211816
0.231563
KIAA0436


NM_003954.1
0.035714
0.04225
0.051916
0.230862
MAP3K14


NM_025207.1
0.035714
0.035247
0.020823
0.230015
PP591


NM_016323.1
0.035714
0.035247
0.051393
0.228764
LOC51191


NM_016069.1
0.035714
0.04225
0.132766
0.223618
Magmas


NM_013349.1
0.035714
0.035247
0.028748
0.223073
SPUF


NM_000884.1
0.035714
0.035247
0.064347
0.222421
IMPDH2


BG167570
0.035714
0.04225
0.108243
0.219652
DKFZp762N1910


NM_004551.1
0.035714
0.00747
0.06025
0.217427
NDUFS3


BG231932
0.035714
0.04225
0.079649
0.210447
CLN2


NM_017851.1
0.035714
0.035247
0.036308
0.209956
FLJ20509


NM_006519.1
0.035714
0.035247
0.032991
0.202387
TCTEL1


AF032900.1
0.035714
0.035247
0.174549
0.200739
COQ7


AL535380
0.035714
0.035247
0.265205
0.198073
BTG1


AW118862
0.035714
0.035247
0.02173
0.193753
RREB1


NM_000382.1
0.035714
0.035247
0.27948
0.193509
ALDH3A2


NM_024419.1
0.035714
0.035247
0.164883
0.190623
PGS1


NM_003904.1
0.035714
0.035247
0.245676
0.190422
ZNF259


AI928526
0.035714
0.00747
0.036861
0.185624
JTV1


NM_024581.1
0.035714
0.035247
0.230867
0.185323
FLJ13942


AF085357.1
0.035714
0.035247
0.110175
0.184965
FLOT1


NM_004475.1
0.035714
0.035247
0.072642
0.180483
FLOT2


AF334103.1
0.035714
0.00747
0.009664
0.17511
GU2


NM_017829.1
0.035714
0.035247
0.110207
0.174515
CECR5


NM_004214.3
0.035714
0.04225
0.016835
0.157902
FIBP


NM_017704.1
0.035714
0.04225
0.16159
0.157672
FLJ20189


NM_003592.1
0.035714
0.035247
0.038652
0.146241
CUL1


AI537887
0.035714
0.035247
0.467375
0.139355
EPB72


NM_023935.1
0.035714
0.035247
0.049119
0.125305
C20orf116


BG398414
0.035714
0.035247
0.286856
0.123085
RPA1


NM_016243.1
0.035714
0.035247
0.279995
0.121894
LOC51706


NM_012199.1
0.035714
0.035247
0.093241
0.118547
EIF2C1


AK024029.1
0.035714
0.04225
0.450393
0.11646
MAP-1


NM_004848.1
0.035714
0.035247
0.486492
0.113516
ICB-1


AF144638.1
0.035714
0.035247
0.255571
0.10089
SGPL1


D86062.1
0.035714
0.035247
0.532398
0.084417
C21orf33


NM_000655.2
0.035714
0.035247
0.535745
0.081167
SELL


NM_018643.1
0.035714
0.035247
0.870775
0.057399
TREM1


NM_018326.1
0.035714
0.035247
0.929375
0.035048
HIMAP4


NM_005371.2
0.035714
0.035247
0.876737
0.025127
METTL1


NM_007002.1
0.035714
0.035247
0.911541
0.010422
ADRM1


NM_004723.1
0.035714
0.035247
0.975685
−0.00562
ARHGEF2


U31501
0.035714
0.035247
0.724549
−0.0658
FXR2


NM_005338.3
0.035714
0.04225
0.126911
−0.0661
HIP1


AB006589.1
0.035714
0.035247
0.00542
−0.10655
ESR2


AA868754
0.035714
0.035247
0.304519
−0.10746
KIAA0650


AU144792
0.035714
0.035247
0.008623
−0.11362


AF320999.1
0.035714
0.035247
0.289096
−0.11449
RTN4


NM_013229.1
0.035714
0.035247
0.529181
−0.13735
APAF1


NM_018690.1
0.035714
0.04225
0.261146
−0.14482
APOB48R


D42055.1
0.035714
0.04225
0.007978
−0.14841
NEDD4


BF968633
0.035714
0.035247
0.135003
−0.14873
RNF4


AK026678.1
0.035714
0.035247
0.00833
−0.15056
STAG2


NM_014671.1
0.035714
0.035247
0.392979
−0.15386
KIAA0010


NM_030979.1
0.035714
0.035247
0.087494
−0.15652
PABPC3


BG429214
0.035714
0.035247
0.273519
−0.15766


NM_006892.1
0.035714
0.035247
0.001922
−0.15828
DNMT3B


NM_018975.1
0.035714
0.035247
0.042202
−0.16723
RAP1


AL137335.1
0.035714
0.035247
0.306422
−0.17292
RANBP7


NM_014016.1
0.035714
0.035247
0.398036
−0.17365
SACM1L


NM_012198.1
0.035714
0.035247
0.391555
−0.17556
GCA


NM_024586.1
0.035714
0.04225
0.011965
−0.19298
OSBPL9


N64643
0.035714
0.035247
0.16498
−0.19313
KIAA0625


NM_005951.1
0.035714
0.035247
0.156965
−0.1942
MT1H


NM_002264.1
0.035714
0.035247
0.138195
−0.1949


AF182415.1
0.035714
0.04225
0.325959
−0.19495
RBM8A


BE674061
0.035714
0.035247
0.015036
−0.20133
PIN4


NM_004973.2
0.035714
0.00747
0.103071
−0.20162
JMJ


U58852.1
0.035714
0.035247
0.510508
−0.20606
NPAT


NM_005565.2
0.035714
0.035247
0.037541
−0.2105
LCP2


NM_004941.1
0.035714
0.035247
0.229189
−0.21215
DDX8


U02297.1
0.035714
0.035247
0.252672
−0.21782
SELPLG


NM_002940.1
0.035714
0.035247
0.112373
−0.22731
ABCE1


AL550657
0.035714
0.035247
0.069403
−0.23303
BSG


BG387770
0.035714
0.035247
0.032984
−0.2362
MGC32104


AL050205.1
0.035714
0.04225
0.352078
−0.23748
LOC113251


NM_016653.1
0.035714
0.035247
0.003387
−0.23765
ZAK


AA742237
0.035714
0.035247
0.120935
−0.23853
BAT2


NM_021183.1
0.035714
0.035247
0.069121
−0.24239
LOC57826


AB014527.1
0.035714
0.035247
0.005636
−0.24315
CLASP2


AF091086.1
0.035714
0.035247
0.124853
−0.24621
CL640


NM_006748.1
0.035714
0.04225
0.141473
−0.24728
SLA


NM_025238.1
0.035714
0.035247
0.046507
−0.24841
BTBD1


NM_018638.2
0.035714
0.035247
0.074405
−0.24942
EKI1


NM_002913.1
0.035714
0.04225
0.092197
−0.24967


NM_002863.1
0.035714
0.035247
0.034567
−0.25494
PYGL


AF226044.1
0.035714
0.035247
0.023966
−0.25679
SNRK


NM_016217.1
0.035714
0.035247
0.01673
−0.25733
LOC51696


AF084943.1
0.035714
0.035247
0.024841
−0.26011
MINPP1


N22548
0.035714
0.04225
0.03686
−0.26164
ROCK1


AF033850.1
0.035714
0.035247
0.110532
−0.26338
PLD2


NM_014445.1
0.035714
0.00747
0.007058
−0.26858
SERP1


NM_016196.1
0.035714
0.035247
0.014278
−0.27109
KIAA0682


NM_012252.1
0.035714
0.035247
0.020625
−0.27124
TFEC


W72082
0.035714
0.035247
0.180599
−0.27284
C1QR1


NM_016166.1
0.035714
0.035247
0.071782
−0.27429
PIAS1


NM_022470.1
0.035714
0.035247
0.072884
−0.27655
WIG1


NM_030797.1
0.035714
0.035247
0.039197
−0.27728
DKFZP566A1524


NM_002199.2
0.035714
0.035247
0.250656
−0.27789
IRF2


BC003360.1
0.035714
0.035247
0.02171
−0.27851
DDX18


NM_004504.2
0.035714
0.035247
0.020834
−0.27873
HRB


NM_012072.2
0.035714
0.035247
0.118494
−0.27892
C1QR1


NM_018230.1
0.035714
0.035247
0.071301
−0.28019
NUP133


NM_002727.1
0.035714
0.04225
0.038559
−0.28438
PRG1


BC005338.1
0.035714
0.035247
0.114062
−0.28524
CAPZA2


U60521.1
0.035714
0.04225
0.066643
−0.29174
CASP9


AW188198
0.035714
0.035247
0.005126
−0.29178
TNFAIP6


BE908931
0.035714
0.035247
0.017009
−0.29572


U64661
0.035714
0.04225
0.030982
−0.29704


AL021395
0.035714
0.04225
0.02084
−0.29857


NM_015176.1
0.035714
0.035247
0.059688
−0.299
KIAA0483


NM_002857.1
0.035714
0.04225
0.04761
−0.29944
PXF


U70451.1
0.035714
0.035247
0.003458
−0.30169
MYD88


NM_018042.1
0.035714
0.035247
0.020209
−0.30409
FLJ10260


AL049265.1
0.035714
0.04225
0.136618
−0.30472


NM_024081.1
0.035714
0.035247
0.020267
−0.30513
TMG4


AI796169
0.035714
0.035247
0.023959
−0.31104
GATA3


AA160522
0.035714
0.035247
0.056044
−0.31114
UBE3A


AL136621.1
0.035714
0.04225
0.06859
−0.31538
ZNF198


NM_003051.1
0.035714
0.035247
0.028776
−0.3171
SLC16A1


AW572909
0.035714
0.035247
0.027025
−0.31713
KIAA0874


NM_017782.1
0.035714
0.04225
0.017104
−0.32078
FLJ20360


AK001821.1
0.035714
0.04225
0.013182
−0.32145
MGC4170


AW001847
0.035714
0.035247
0.204195
−0.32259
APLP2


BF196931
0.035714
0.04225
0.003706
−0.3226
ZFP95


AJ223333.1
0.035714
0.035247
0.023593
−0.32279
DNMT2


NM_005213.1
0.035714
0.04225
0.216305
−0.32285
CSTA


AF142419.1
0.035714
0.04225
0.013772
−0.33425
QKI


NM_020375.1
0.035714
0.035247
0.07666
−0.33473
C12orf5


NM_021970.1
0.035714
0.04225
0.054987
−0.33505
MAP2K1IP1


AK023816.1
0.035714
0.035247
0.136952
−0.34214


NM_012238.3
0.035714
0.00747
0.018308
−0.3438
SIRT1


AF205218.1
0.035714
0.035247
0.033088
−0.34674
NS1-BP


NM_001660.2
0.035714
0.035247
0.020387
−0.35015
ARF4


NM_001196.1
0.035714
0.015406
0.020544
−0.35511
BID


NM_002970.1
0.035714
0.035247
0.064201
−0.35676
SAT


AC074331
0.035714
0.035247
0.01515
−0.35767


M75715.1
0.035714
0.035247
0.010802
−0.3577
ETF1


NM_018657.2
0.035714
0.04225
0.021807
−0.3681
MYNN


NM_003370.1
0.035714
0.035247
0.056143
−0.37617
VASP


AI761561
0.035714
0.035247
0.084393
−0.37861
HK2


NM_002657.2
0.035714
0.035247
0.043402
−0.39004
PLAGL2


NM_004565.1
0.035714
0.035247
0.086212
−0.39025
PEX14


AK023837.1
0.035714
0.04225
0.083366
−0.39056
KIAA1025


AL117354
0.035714
0.00747
0.011916
−0.39754
LOC50999


NM_001356.2
0.035714
0.035247
0.029134
−0.41337
DDX3


NM_018573.1
0.035714
0.015406
0.00529
−0.41757
PRO1068


NM_030799.1
0.035714
0.035247
0.075235
−0.42088
SMAP-5


AA524053
0.035714
0.04225
0.031361
−0.42442


NM_002748.1
0.035714
0.035247
0.023266
−0.42563
MAPK6


NM_002053.1
0.035714
0.035247
0.053201
−0.43747
GBP1


AB023227.1
0.035714
0.04225
0.003343
−0.43985
KIAA1010


AW193511
0.035714
0.035247
0.012709
−0.44652
HIS1


AW272611
0.035714
0.04225
0.024277
−0.44899
TMPO


AI671747
0.035714
0.00747
0.02288
−0.45263
MISS


AI688580
0.035714
0.035247
0.035918
−0.45484
SURB7


NM_002502.1
0.035714
0.035247
0.107712
−0.45745
NFKB2


NM_004267.1
0.035714
0.04225
0.030352
−0.47177
CHST2


X15132.1
0.035714
0.035247
0.041452
−0.47259
SOD2


NM_012093.1
0.035714
0.035247
0.011606
−0.47474
AK5


D26067.1
0.035714
0.035247
0.003438
−0.47644
KIAA0033


NM_001166.2
0.035714
0.04225
0.015252
−0.48334
BIRC2


NM_016545.1
0.035714
0.035247
0.029826
−0.48723
IER5


NM_021122.2
0.035714
0.035247
0.070882
−0.49855
FACL2


NM_017936.1
0.035714
0.035247
0.008293
−0.5016
FLJ20707


NM_000574.1
0.035714
0.035247
0.022743
−0.50532
DAF


AL050144.1
0.035714
0.015406
0.000822
−0.52839
ZNF363


NM_005346.2
0.035714
0.035247
0.10824
−0.5359
HSPA1B


NM_022725.1
0.035714
0.035247
0.023814
−0.53779
FANCF


AI348010
0.035714
0.035247
0.226116
−0.54348


AI927993
0.035714
0.035247
0.054067
−0.54478
OSBP


BE327172
0.035714
0.035247
0.091317
−0.54925
JUN


AI741876
0.035714
0.00747
0.025182
−0.57505


NM_003107.1
0.035714
0.035247
0.078087
−0.59709
SOX4


BE383139
0.035714
0.035247
0.00951
−0.60058
RARA


NM_018398.1
0.035714
0.035247
0.016221
−0.603
CACNA2D3


NM_000201.1
0.035714
0.035247
0.036915
−0.62554
ICAM1


NM_002229.1
0.035714
0.035247
0.129802
−0.64436
JUNB


NM_021960.1
0.035714
0.04225
0.024176
−0.66914
MCL1


NM_016010.1
0.035714
0.00747
0.015684
−0.68307
LOC51101


NM_004417.2
0.035714
0.035247
0.043377
−0.68458
DUSP1


NM_025195.1
0.035714
0.035247
0.055882
−0.68638
C8FW


NM_004418.2
0.035714
0.035247
0.306591
−0.68934
DUSP2


AB017493.1
0.035714
0.015406
0.010224
−0.6982
COPEB


AF064824.1
0.035714
0.035247
0.010071
−0.70109
RIPK2


NM_005354.2
0.035714
0.035247
0.04394
−0.70667
JUND


NM_006469.1
0.035714
0.035247
0.006453
−0.71493
NS1-BP


NM_006290.1
0.035714
0.035247
0.155375
−0.73437
TNFAIP3


AI339541
0.035714
0.035247
0.039838
−0.76402
JUND


AF087853.1
0.035714
0.035247
0.076647
−0.77217
GADD45B


AL031602
0.035714
0.035247
0.015158
−0.78504


BF575213
0.035714
0.035247
0.007144
−0.78651


M68956.1
0.035714
0.00747
0.001933
−0.79718
MARCKS


NM_004907.1
0.035714
0.035247
0.006503
−0.81053
ETR101


AW083357
0.035714
0.035247
0.009893
−0.81405
IL1RN


AF153820.1
0.035714
0.035247
0.004403
−0.82757
KCNJ2


AI608725
0.035714
0.035247
0.010119
−0.83319
ICAM1


NM_000958.1
0.035714
0.015406
0.003112
−0.86354
PTGER4


AA083483
0.035714
0.035247
0.012228
−0.88452
FTH1


NM_002664.1
0.035714
0.00747
0.000855
−0.88664
PLEK


AL031602
0.035714
0.015406
0.00038
−0.88673


W27419
0.035714
0.015406
0.000361
−0.95575


NM_002852.1
0.035714
0.035247
0.001716
−0.97365
PTX3


NM_001964.1
0.035714
0.035247
0.068287
−0.99045
EGR1


AF078077.1
0.035714
0.035247
0.017058
−1.003
GADD45B


NM_015714.1
0.035714
0.035247
0.210858
−1.05996
G0S2


BC004490.1
0.035714
0.035247
0.068201
−1.06388
FOS


AI738896
0.035714
0.035247
0.071526
−1.09453
TNFAIP3


AW973834
0.035714
0.035247
0.030817
−1.09468


NM_004895.1
0.035714
0.035247
0.004992
−1.10724
CIAS1


U08839.1
0.035714
0.035247
0.030968
−1.1245
PLAUR


BC005020.1
0.035714
0.035247
0.022893
−1.13801
PPIF


NM_005627.1
0.035714
0.035247
0.010834
−1.16132
SGK


NM_015675.1
0.035714
0.035247
0.022251
−1.16822
GADD45B


AI433595
0.035714
0.015406
0.002395
−1.17663
PLEK


NM_002135.1
0.035714
0.035247
0.009942
−1.19934
NR4A1


NM_003407.1
0.035714
0.035247
0.0028
−1.30448
ZFP36


NM_004233.1
0.035714
0.035247
0.045128
−1.33091
CD83


NM_001432.1
0.035714
0.035247
0.001942
−1.33633
EREG


NM_002228.2
0.035714
0.035247
0.007227
−1.34352
JUN


NM_004049.1
0.035714
0.035247
0.004927
−1.41895
BCL2A1


U83981
0.035714
0.035247
0.005806
−1.46885
PPP1R15A


NM_006018.1
0.035714
0.035247
0.002094
−1.50671
HM74


BG491844
0.035714
0.035247
0.011957
−1.61438
JUN


BC002646.1
0.035714
0.035247
0.002438
−1.64136
JUN


NM_000963.1
0.035714
0.035247
0.025772
−1.65759
PTGS2


AY029180.1
0.035714
0.035247
0.011082
−1.69399
PLAUR


NM_014330.2
0.035714
0.035247
0.003245
−1.74665
PPP1R15A


NM_003897.1
0.035714
0.035247
0.002981
−1.89968
IER3


M57731.1
0.035714
0.035247
0.001811
−1.9703
CXCL2


NM_000584.1
0.035714
0.035247
0.030747
−2.54298
IL8


NM_000576.1
0.035714
0.035247
0.000992
−2.66025
IL1B


M15330
0.035714
0.035247
0.001505
−2.71142
IL1B









It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination.


Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims. All publications, patents, patent applications and sequences identifies by a GenBank accession number mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent, patent application or sequence was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention.

Claims
  • 1. A method of diagnosing a subject with multiple sclerosis, the method comprising determining a level of expression of at least one gene selected from the group consisting of the genes listed in Tables I-V in a sample obtained from the subject, wherein a substantial difference between said level of expression of said gene in said sample obtained from said subject and a normal expression level of said gene is an indication that the subject is afflicted with multiple sclerosis.
  • 2. The method of claim 1, wherein said normal expression level of said at least one gene is determined by measuring said level of expression of said gene in at least one control sample obtained from at least one healthy individual.
  • 3. The method of claim 2, wherein said sample includes peripheral blood mononuclear cells.
  • 4. The method of claim 1, wherein said substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.
  • 5. The method of claim 1, wherein said level of expression of said at least one gene is determined by quantifying a level of a protein product thereof in said sample.
  • 6. The method of claim 5, wherein quantifying a level of said protein is effected using a reagent which specifically binds with said protein.
  • 7. The method of claim 6, wherein said reagent comprises an antibody or fragments thereof.
  • 8. The method of claim 1, wherein said at least one gene is selected from the genes listed in Table I.
  • 9. The method of claim 1, wherein said at least one gene is selected from the genes listed in Table II.
  • 10. The method of claim 1, wherein said at least one gene is selected from the genes listed in Table III.
  • 11. The method of claim 1, wherein said at least one gene is selected from the genes listed in Table IV.
  • 12. The method of claim 1, wherein said at least one gene is selected from the genes listed in Table V.
  • 13. The method of claim 1, wherein the level of expression of said at least one gene in said sample is determined by detecting the presence in said sample of a transcribed polynucleotide or portion thereof.
  • 14. The method of claim 13, wherein said transcribed polynucleotide is mRNA.
  • 15. The method of claim 13, wherein said transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with said transcribed polynucleotide or portion thereof.
  • 16. The method of claim 1, wherein said sample from a subject is T cells, and said at least one gene is selected from the genes listed in Table IV and whereas said normal expression of said gene is T-cell expression.
  • 17. The method of claim 16, wherein said substantial difference is at least a 1.5 fold change.
  • 18. The method of claim 1, wherein said at least one gene comprises at least 10 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 19. The method of claim 1, wherein said at least one gene comprises at least 50 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 20. The method of claim 1, wherein said at least one gene comprises at least 100 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 21. The method of claim 1, wherein said at least one gene comprises at least 250 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 22. The method of claim 1, wherein said at least one gene comprises at least 500 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 23. The method of claim 1, wherein said at least one gene comprises at least 750 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 24. The method of claim 1, wherein said at least one gene comprises at least 1000 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 25. The method of claim 1, wherein said at least one gene comprises at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 26. A method of diagnosing a subject with multiple sclerosis, the method comprising the step of determining a level of expression of each of the genes listed in Tables I-V in a sample obtained from the subject, wherein a substantial difference between expression levels of said genes in said sample obtained from said subject and normal expression levels of said genes is an indication that the subject is afflicted with multiple sclerosis.
  • 27. The method of claim 26, wherein said normal expression levels of said genes is determined by measuring said level of expression of said genes in at least one control sample obtained from at least one healthy individual.
  • 28. The method of claim 26, wherein said sample includes peripheral blood mononuclear cells.
  • 29. The method of claim 26, wherein said substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.
  • 30. The method of claim 26, wherein said level of expression of said genes is determined by quantifying a level of a protein product thereof in said sample.
  • 31. The method of claim 30, wherein quantifying a level of said protein is effected using a reagent which specifically binds with said protein.
  • 32. The method of claim 31, wherein said reagent comprises an antibody or fragments thereof.
  • 33. The method of claim 26, wherein the level of expression of said genes in said sample is determined by detecting the presence in said sample of a transcribed polynucleotide or portion thereof.
  • 34. The method of claim 33, wherein said transcribed polynucleotide is mRNA.
  • 35. The method of claim 34, wherein said transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with said transcribed polynucleotide or portion thereof.
  • 36. A method of monitoring a state of multiple sclerosis in a subject, the method comprising monitoring a level of expression of at least one gene selected from the group consisting of the genes listed in Tables I-V over a predetermined time period, wherein substantial difference between the levels of expression of said at least one gene over said predetermined time period indicates a change in a state of the multiple sclerosis in the subject.
  • 37. The method of claim 36, wherein monitoring said level of expression of at least one gene over said predetermined time period is effected by periodically obtaining a sample from the individual and determining said level of expression of said at least one gene in said sample.
  • 38. The method of claim 37, wherein said sample includes peripheral blood mononuclear cells.
  • 39. The method of claim 36, wherein said substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.
  • 40. The method of claim 36, wherein said level of expression of said at least one gene is determined by quantifying a level of a protein product thereof in said sample.
  • 41. The method of claim 36, wherein quantifying a level of said protein is effected using a reagent which specifically binds with said protein.
  • 42. The method of claim 41, wherein said reagent comprises an antibody or fragments thereof.
  • 43. The method of claim 36, wherein said at least one gene is selected from the genes listed in Table I.
  • 44. The method of claim 36, wherein said at least one gene is selected from the genes listed in Table II.
  • 45. The method of claim 36, wherein said at least one gene is selected from the genes listed in Table III.
  • 46. The method of claim 36, wherein said at least one gene is selected from the genes listed in Table IV.
  • 47. The method of claim 36, wherein said at least one gene is selected from the genes listed in Table V.
  • 48. The method of claim 36, wherein the level of expression of said at least one gene in said sample is determined by detecting the presence in said sample of a transcribed polynucleotide or portion thereof.
  • 49. The method of claim 48, wherein said transcribed polynucleotide is mRNA.
  • 50. The method of claim 48, wherein said transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with said transcribed polynucleotide or portion thereof.
  • 51. The method of claim 36, wherein said sample from a subject is T cells, and said at least one gene is selected from the genes listed in Table IV and whereas said normal expression of said gene is T-cell expression.
  • 52. The method of claim 51, wherein said substantial difference is at least a 1.5 fold change.
  • 53. The method of claim 36, wherein said at least one gene comprises at least 10 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 54. The method of claim 36, wherein said at least one gene comprises at least 50 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 55. The method of claim 36, wherein said at least one gene comprises at least 100 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 56. The method of claim 36, wherein said at least one gene comprises at least 250 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 57. The method of claim 36, wherein said at least one gene comprises at least 500 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 58. The method of claim 36, wherein said at least one gene comprises at least 750 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 59. The method of claim 36, wherein said at least one gene comprises at least 1000 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 60. The method of claim 36, wherein said at least one gene comprises at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 61. A method of assessing the efficacy of a treatment regimen on multiple sclerosis in a subject, the method comprising determining a level of expression of at least one gene selected from the group consisting of the genes listed in Tables I-V in samples obtained from the subject prior to, and following exposure to the treatment regimen, wherein a substantial difference in the expression level of said at least one gene between said samples is an indication that the treatment regimen is efficacious in treating multiple sclerosis in said subject.
  • 62. The method of claim 61, wherein said treatment regimen is administering at least one test compound for inhibiting multiple sclerosis.
  • 63. The method of claim 61, wherein said treatment regimen is an environmental condition.
  • 64. The method of claim 61, wherein said samples include peripheral blood mononuclear cells.
  • 65. The method of claim 61, wherein said substantial difference is a difference statistically significant at a confidence level of p=0.05 as determined by at least one test selected from the group consisting of a t-test, a TNoM and an INFO score.
  • 66. The method of claim 61, wherein said level of expression of said at least one gene is determined by quantifying a level of a protein product thereof in said sample.
  • 67. The method of claim 66, wherein quantifying a level of said protein is effected using a reagent which specifically binds with said protein.
  • 68. The method of claim 67, wherein said reagent comprises an antibody or fragments thereof.
  • 69. The method of claim 61, wherein said at least one gene is selected from the genes listed in Table I.
  • 70. The method of claim 61, wherein said at least one gene is selected from the genes listed in Table II.
  • 71. The method of claim 61, wherein said at least one gene is selected from the genes listed in Table III.
  • 72. The method of claim 61, wherein said at least one gene is selected from the genes listed in Table IV.
  • 73. The method of claim 61, wherein said at least one gene is selected from the genes listed in Table V.
  • 74. The method of claim 61, wherein the level of expression of said at least one gene in said samples is determined by detecting the presence in said samples of a transcribed polynucleotide or portion thereof.
  • 75. The method of claim 74, wherein said transcribed polynucleotide is mRNA.
  • 76. The method of claim 74, wherein said transcribed polynucleotide or portion thereof is detected via a labeled probe which specifically hybridizes with said transcribed polynucleotide or portion thereof.
  • 77. The method of claim 61, wherein said at least one gene comprises at least 10 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 78. The method of claim 61, wherein said at least one gene comprises at least 50 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 79. The method of claim 61, wherein said at least one gene comprises at least 100 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 80. The method of claim 61, wherein said at least one gene comprises at least 250 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 81. The method of claim 61, wherein said at least one gene comprises at least 500 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 82. The method of claim 61, wherein said at least one gene comprises at least 750 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 83. The method of claim 61, wherein said at least one gene comprises at least 1000 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 84. The method of claim 61, wherein said at least one gene comprises at least 1200 genes each independently selected from the group consisting of the genes listed in Tables I-V.
  • 85. A kit for diagnosing multiple sclerosis in a subject, the kit comprising components suitable for determining expression levels of at least one gene selected from the group of genes listed in Tables I-V.
  • 86. The kit of claim 85, wherein said reagents include at least one polynucleotide sequence selected capable of specifically hybridizing with an transcription product of said at least one gene and reagents for detecting and optionally quantifying a complex formed from said at least one polynucleotide sequence and said transcription product.
  • 87. The kit of claim 85, wherein said reagents include at least one antibody selected capable of specifically binding a polypeptide product of said at least one gene and reagents for detecting and optionally quantifying a complex formed from said at least one antibody and said polypeptide product.
  • 88. The kit of claim 85, wherein said at least one gene is selected from the genes listed in Table I.
  • 89. The kit of claim 85, wherein said at least one gene is selected from the genes listed in Table II.
  • 90. The kit of claim 85, wherein said at least one gene is selected from the genes listed in Table III.
  • 91. The method of claim 88, wherein said at least one gene is selected from the genes listed in Table IV.
  • 92. The method of claim 85, wherein said at least one gene is selected from the genes listed in Table V.
  • 93. The kit of claim 85, wherein the kit further comprises packaging material identifying the kit as useful from diagnosing MS.
  • 94. A polynucleotide array comprising at least 10 and no more than 1500 polynucleotide sequences, wherein each of said sequences is selected capable of hybridizing with a transcription product of a polynucleotide sequence of a gene selected from the group of genes listed in Tables I-V.
  • 95. The polynucleotide array of claim 94, wherein said array is selected having polynucleotide sequences capable of diagnosing subjects suspected of suffering from multiple sclerosis.
  • 96. The polynucleotide array of claim 94, wherein said array is selected having polynucleotide sequences capable of diagnosing subjects suspected of suffering from probable multiple sclerosis.
  • 97. The polynucleotide array of claim 94, wherein said array is selected capable of diagnosing subjects suspected of suffering from primary progressive multiple sclerosis.
  • 98. The polynucleotide array of claim 94, wherein said array is selected capable of diagnosing subjects suspected of suffering from relapsing multiple sclerosis.
  • 99. The polynucleotide array of claim 94, wherein said gene is selected from the genes listed in Table I.
  • 100. The polynucleotide array of claim 94, wherein said gene is selected from the genes listed in Table II.
  • 101. The polynucleotide array of claim 94, wherein said gene is selected from the genes listed in Table III.
  • 102. The polynucleotide array of claim 94, wherein said gene is selected from the genes listed in Table IV.
  • 103. The polynucleotide array of claim 94, wherein said gene is selected from the genes listed in Table V.
  • 104. An array comprising at least 10 and no more than 1500 antibodies or antibody fragments each capable of specifically binding a protein product of a gene selected from the group of genes listed in Tables I-V.
  • 105. The array of claim 104, wherein said array is selected having antibodies or antibody fragments capable of diagnosing subjects suspected of suffering from multiple sclerosis.
  • 106. The array of claim 104, wherein said array is selected having antibodies or antibody fragments capable of diagnosing subjects suspected of suffering from probable multiple sclerosis.
  • 107. The array of claim 104, wherein said array is selected capable of diagnosing subjects suspected of suffering from primary progressive multiple sclerosis.
  • 108. The array of claim 104, wherein said array is selected capable of diagnosing subjects suspected of suffering from relapsing multiple sclerosis.
  • 109. The array of claim 104, wherein said gene is selected from the genes listed in Table I.
  • 110. The array of claim 104, wherein said gene is selected from the genes listed in Table II.
  • 111. The array of claim 104, wherein said gene is selected from the genes listed in Table III.
  • 112. The array of claim 104, wherein said gene is selected from the genes listed in Table IV.
  • 113. The array of claim 104, wherein said gene is selected from the genes listed in Table V.
PCT Information
Filing Document Filing Date Country Kind
PCT/IL03/00208 WO
Provisional Applications (1)
Number Date Country
60365800 Mar 2002 US