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CIS (multiple sclerosis) (case-control) (time-series)

ABSTRACT: Clinically isolated syndrome (CIS) refers to the earliest clinical manifestation of multiple sclerosis (MS). Currently there are no prognostic biological markers that accurately predict conversion of CIS to clinically definite MS (CDMS). Furthermore, the earliest molecular events in MS are still unknown. We used microarrays to study gene expression in naïve CD4+ T cells from 37 CIS patients at time of diagnosis and after one year. Supervised machine-learning methods were used to build predictive models of disease conversion. We identified 975 genes whose expression segregated CIS patients into 4 distinct subgroups. A subset of 108 genes further discriminated patients from one of these (group#1) from other CIS patients. Remarkably, 92% of patients from group #1 converted to CDMS within 9 months. Consistent downregulation of TOB1, a critical regulator of cell proliferation, was characteristic of group #1 patients. Decreased TOB1 expression at the RNA and protein levels was also confirmed in experimental autoimmune encephalomyelitis (EAE). Finally, a genetic association was observed between TOB1 variation and MS progression in an independent cohort. These results indicate that CIS patients at high risk of conversion have impaired regulation of T cell quiescence resulting in earlier activation of pathogenic CD4+ cells. Keywords: Disease state: CIS (Clinically Isolated Syndrome - Multiple Sclerosis) versus control. Time series: some patients and controls were resampled approximately one year later

ORGANISM(S): Homo sapiens

PROVIDER: GSE13732 | GEO | 2008/11/26

SECONDARY ACCESSION(S): PRJNA110795

REPOSITORIES: GEO

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Project description:Molecular mechanisms that influence susceptibility to multiple sclerosis are poorly understood. We conducted a gene expression study in healthy subjects that subsequently developed the disease. Gene expression profiles (HG U133A and A2, Affymetrix, 22,215 transcripts) of peripheral blood mononuclear cells were analyzed in 9 healthy subjects (mean age 19.8+1.1 years) up to 9 years (mean 5.1±1.2 years) before onset of MS (MS to be, MS2b), 11 age-, gender-, and origin-matched subjects that remained MS-free (MSf), and 31 clinically isolated syndrome (CIS) patients. Most informative genes (p<0.05) and significant biological processes were compared. 1051 genes (611 up-regulated, 440 down-regulated) were significantly different between MS2b and MSf subjects. MS2b signature was characterized by down-regulation of the nuclear receptor (NR) family genes including NR subfamily 4 group A member1 (NR4A1, p=0.01), member 3 (NR4A3, p=0.01), NR subfamily 2 group F member 2 (NR2F1, p=0.03) and vitamin D receptor (VDR, p=0.02), all known to be involved in T-cell regulation by apoptosis. Comparison between MS2b and CIS operating networks demonstrated evolution of the altered NR dependent apoptosis regulation. Decreased NR4A1 expression was verified at the mRNA and protein level in an independent cohort of 20 relapsing-remitting MS patients. The identified MS trait is associated with suppressed transcription of NR networks that leads to altered apoptosis of activated T cells and the development of clinical disease. MS2b subjects have already an ongoing process that eventually will lead to clinical disease and our finding are of importance as they suggest the possibility of early detection and prevention of MS. Keywords: disease state analysis Blood samples of healthy subjects that later developed MS (MS-to-be, MS2b, N=9) were identified and used for gene expression study. For each sample of MS2b subject, a sample of an age and gender matched subject that remained MS-free (MSf, N=11) was randomly selected. A cohort of 31 CIS patients who gave blood sample for gene expression analysis within 3 months of the onset of their first neurological event, was used for comparison with the MS2b gene expression signature. For establishment of the CIS gene expression signature, microarray data from 13 age- and sex- matched healthy subjects were used.

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CIS (multiple sclerosis) (case-control) (time-series)

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