Genome-wide pathway analysis of a genome-wide association study on multiple sclerosis

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Abstract

The aims of this study were to identify candidate single nucleotide polymorphisms (SNPs) and mechanisms of multiple sclerosis (MS) and to generate SNP to gene to pathway hypotheses. A MS genome-wide association study (GWAS) dataset that included 505,763 SNPs in 500 cases and 500 controls of European descent was used in this study. Identify candidate Causal SNPs and Pathway (ICSNPathway) analysis was applied to the GWAS dataset. ICSNPathway analysis identified 9 candidate SNPs and 5 pathways, which provided 5 hypothetical biological mechanisms. The candidate SNPs, namely, rs1802127 (MSH5), rs9277471 (human leukocyte antigen [HLA]-DPB1), rs8084 (HLA-DRA), rs7192 (HLA-DRA), rs2072895 (HLA-F), rs2735059 (HLA-F), rs915669 (HLA-G), rs915668 (HLA-G), and rs1063320 (HLA-G) were all at HLA loci (-log10(P) = 3.301-4.000). The most strongly associated pathway was rs1802127 to MSH5 to meiotic recombination and meiotic cell cycle (nominal P < 0.001, false discovery rate [FDR] < 0.001). When HLA loci were excluded, ICSNPathway analysis identified seven candidate non-HLA SNPs (rs5896 [F2], rs8181979 [SHC1], rs9297605 [TAF2], rs669 [A2 M], rs2228043 [IL6ST], rs1061622 [TNFRSF1B], rs1801516 [ATM]) and ten candidate causal pathways, which provided seven hypothetical biological mechanisms (nominal P ≤ 0.001, FDR ≤ 0.047). The most strongly associated pathway was SNP rs5896 to F2 to the transcriptional activation DNA-binding protein B from mRNA (nominal P < 0.001, FDR = 0.006). The application of ICSNPathway analysis to the MS GWAS dataset resulted in the identification of candidate SNPs, pathways, and biological mechanisms that might contribute to MS susceptibility.

Original languageEnglish
Pages (from-to)2557-2564
Number of pages8
JournalMolecular Biology Reports
Volume40
Issue number3
DOIs
Publication statusPublished - 2013 Mar 1

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Keywords

  • Genome-wide association study
  • Multiple sclerosis
  • Pathway-based analysis

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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