Using High Throughput Approach to Identify/Characterize Functional Variants on MS

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

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Abstract

Abstract Multiple sclerosis (MS) is an autoimmune disease for which there is limited pathogenic understanding and no cure. Genome wide association studies (GWAS) on MS have identified >200 MS-associated loci. These loci represent thousands of genetic variants, usually in single nucleotide polymorphisms (SNPs), in linkage disequilibrium (LD). However, GWAS doesn't tell which one of them is the causal/functional SNP (fSNP) in each locus. This technical drawback leaves a ?gap? between GWAS and specific mechanism that translates into limited opportunities for biological insight and therapeutic intervention. To overcome this limitation, we have developed two novel techniques: functional Single Nucleotide Polymorphism-seq (fSNP-seq) and Flanking Restriction Enzyme-mediated DNA Pulldown (FREP). fSNP-seq is a high throughput method to identify experimentally which SNPs are likely to bind regulatory proteins and therefore to represent fSNPs. FREP uses an fSNP sequence as ?bait? to identify associated regulatory proteins in a semi high throughput way. Using these techniques, we have identified three fSNPs on a MS-associated CD40 locus that have been confirmed by EMSA, an allele-specific luciferase reporter assay and CRISPR/Cas9, and we also identified four regulatory proteins that regulate CD40 expression via these fSNPs. On the basis of these preliminary data, we propose two aims to apply our new methods to the entire GWAS data on MS. First, we will use our new insights into CD40 locus to define a potentially targetable CD40 regulatory protein complex. Second, we will employ fSNP-seq to undertake high- throughput identification of fSNPs among 4573 SNPs in LD with 196 risk loci for MS. We will use FREP to systematically identify regulatory proteins that control the expression of MS-associated genes via the MS fSNPs by focusing on the MS-associated antigen presenting genes such as CD86, CD80 and MHCI for this R21 application. Together, these studies will help us to generate a MS- associated signal transduction and allele-specific transcription network (MS- STAST network), with the goal of identifying novel targets for MS therapy.