Unravelling the multiple sclerosis complex disease trait through an immune transcriptional regulatory network approach

Multiple Sclerosis (MS), the most common disabling neurological disease affecting young adults in developed countries, is a complex genetic disease associated with both environmental and genetic risk factors. In most cases, the risk factors' individual associations with MS are so weak that any meaningful understanding of the disease will require the identification of molecular pathways that contribute to MS liability. We therefore hypothesisedthat the complex genetic phenotype is driven by a co-ordinated expression of transcriptional regulatory networks. To test this, we generated a weighted gene co-expression network based on 712 pooled Affymetrix Human Gene 1.0 ST array analyses of magnetic bead sorted B cells, CD4 and CD8 T cells, NK cells and monocytes, from 67 untreated relapsing/remitting MS patients and 102 Healthy Controls (HC). Sixteen relatively independent gene modules were identified. For each leukocyte population, the strength of differential expression between patients and HC was assessed, by ranking genes by Mann Whitney U test and ANOVA, and each transcript was tested across the network to identify modules of interest. A group of transcripts we named the “Black” module was most significantly associated with MS in monocytes & was strongly down-regulated in patients. Twelve highly differentially expressed genes with high centrality were identified and the top annotation clusters comprised the immune processes: Natural killer cell mediated cytotoxicity & Antigen processing and presentation. We propose that manipulating the module as a whole may provide a new perspective on the aetiology of complex genetic diseases and offer novel therapies for MS