MHC variation at high resolution in multiple sclerosis

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We proposed to study at high resolution the Major Histocompatibility Complex (MHC) locus in multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system and common cause of non- traumatic neurological disability in young adults. Over 200 loci have been firmly associated with susceptibility. The main association signal genome-wide maps to the major histocompatibility complex (MHC) gene cluster in chromosome 6p21, and explains up to 10% of the genetic variance underlying risk. This region contains ~165 genes, about half having pivotal roles in the immune system. These include the human leukocyte antigen (HLA) genes, which have been associated with more than 100 infectious, autoimmune and inflammatory disease phenotypes, as well as drug reactions and cancers. Despite a sustained research effort on the HLA region in MS, further studies are needed to generate unifying and testable mechanistic models connected to disease pathogenesis. By examining large and well-characterized cohorts, we aim to reveal important aspects of the contribution of immune polymorphism to both, risk and progression. Our experimental approach involves complete sequencing of the 5 Mb MHC, generating high depth coverage of exonic and intronic as well intergenic segments, thus identifying all possible variants associated with the phenotypes, and distinguishing otherwise identical classical HLA alleles that differ in noncoding regions. In Specific Aim 1 we will sequence the MHC in 2,000 MS cases and 2,000 controls representing European, and African ancestries for a comprehensive analysis of sequence and structure variation. In Specific Aim 2 we will implement a systems-level pathway analysis pipeline, leveraging large open access databases to allow the identification of MHC variants with regulatory potential. Finally, in Specific Aim 3 we will employ genomic editing technologies to setup a robust cellular platform with the capability to efficiently screen the identified candidate variants, prioritizing on regulation of gene expression and gene-gene interactions. Full description of MHC variation in informative, poly-ancestral MS datasets, coupled with state-of the art-bioinformatics and hypothesis driven molecular approaches promises to yield novel insights into the genetic underpinnings of disease susceptibility.