Pathway Approach to Decoding Multiple Sclerosis

Abstract

Multiple sclerosis (MS) is characterized as a neurodegenerative autoimmune disease. This clinically complex disease has provided great challenges for geneticists over the years. With the advent of genome-wide association studies (GWAS), the strong genetic component associated with MS is finally beginning to be characterized. One of the first discoveries to emerge in this new era was the association with rs6897932 in the interleukin-7 receptor alpha chain (IL7RA) gene. The goal of the work presented in this dissertation was to identify additional genes that increase one’s susceptibility to MS. Our studies involved examining genes in the extended biological pathway related to IL7RA to identify novel associations. Through this approach, we identified two additional novel gene regions that are likely associated with MS. These results help to further delineate the genetic architecture of MS and validate our pathway approach as an effective method to identify novel associations associated in a complex disease. We began our investigation with a discovery screen containing SNPs from 73 genes with putative functional relationships to IL7RA and subsequently genotyped 7,865 single nucleotide polymorphism (SNPs) in and around these genes. Two of the gene regions examined, IL7 and SOCS1, had significantly associated SNPs that further replicated in an independent case-control dataset with joint p-values reaching 8.29x10-5 and 3.48x10-7, respectively, exceeding the threshold for experiment-wide significance. Our results also implicated two additional novel gene regions that are likely to be associated with MS: PRKCE with p-values reaching 3.47x10-4 and BCL2 with p-values reaching 4.32x10-4. The TYK2 gene, which emerged in our analysis, also has recently been associated with MS in other studies. The work presented in this dissertation confirmed two novel regions and implicated several others that need further examination as MS disease loci. Thus, using the pathway approach in conjunction with large datasets and dense genotyping, the etiology of MS is finally starting to be dissected. By building on the knowledge of these gene effects, these studies will hopefully result in further understanding of the pathogenesis of MS.