Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets
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PROVIDER: PRJNA834633 | ENA |
REPOSITORIES: ENA
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2012-03-23 | E-GEOD-32413 | biostudies-arrayexpress
Project description:Systemic sclerosis (SSc) shows complex clinical manifestations including progressive skin and internal organ fibrosis. SSc can be divided into 'intrinsic subsets' by gene expression suggesting patient-specific heterogeneity in pathogenesis or temporal evolution of disease. Here we validate these subsets using an independent patient population, and test whether the genes vary over time with patients changing subsets as disease progresses, or if the genes are a stable feature of the patients within each subset. Skin biopsies were analyzed from 13 dSSc patients enrolled in an open label study of rituximab, 9 dSSc patients not treated with rituximab, and 9 healthy controls. These data recapitulate the patient 'intrinsic subsets' described previously with gene expression associated with cell proliferation, inflammatory processes, and a normal-like group. Serial skin biopsies showed consistent and non-progressing gene expression. We were unable to detect significant differences in gene expression before and after rituximab treatment, consistent with an apparent lack of clinical response. Serial biopsies from each patient stayed within the same gene expression subset regardless of treatment regimen or the time point at which they were taken. This demonstrates the intrinsic subsets are an inherent, reproducible and stable feature of SSc that is independent of disease duration.
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Project description:Pathway expression analysis in systemic sclerosis revealed key mediators driving pathology within each of the intrinsic gene expression subsets. Genome-wide expression profiling in systemic sclerosis (SSc) has identified four 'intrinsic' subsets of disease (fibroproliferative, inflammatory, limited, and normal-like), each of which appear to be driven by distinct signaling pathways. Here we examine experimentally derived gene expression signatures for thirteen agonists to better understand the molecular mechanisms underlying each intrinsic subsets. Pathway-specific gene signatures were compared against skin biopsy microarray data consisting of 329 microarray hybridizations from 287 unique biopsies representing 111 patients. Hierarchical clustering recapitulated the four SSc 'intrinsic' gene expression subsets, along with an intermediate subset exhibiting both inflammatory and fibroproliferative gene expression signatures. The fibroproliferative subset is most strongly associated with the PDGF gene signature, while the inflammatory subset demonstrated strong activation of NF-kappaB, characterized by early induction of TH2 signals, which transitions to a more TH17-like immune response over time. The limited subset was associated with IFNalpha signaling, combined with strong downregulation of PDGF signaling. The inflammatory-proliferative subset shows downregulation of NF-kappaB-associated pathways in conjunction with increased PDGF signaling, suggestive of a transitional state linking the inflammatory and fibroproliferative subsets. IL-13 signaling was strongly associated with early disease, while TGFbeta signaling was associated with more severe disease. Together these data suggest a multi-step, progressive model of disease pathogenesis driven by distinct pathways. Targeting these pathways based upon a patient's underlying disease subset should improve therapeutic outcomes. In vitro treatment of human dermal fibroblasts was performed to identify pathway-specific gene signatures. These gene signatures were then compared against systemic sclerosis skin biopsy microarrays to determine the overall contribution of each pathway to disease. This study includes re-analysis of 247 skin biopsy samples from GSE9285, GSE32413, and GSE45485. Links to these Samples are provided below. The re-processed normalized data for these Samples are included in the supplementary file 'GSE56308_247_Skin_Biopsy_Reanalysis_Samples.txt'.
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