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

Authors
Song, Gwan GyuChoi, Sung JaeJi, Jong DaeLee, Young Ho
Issue Date
3월-2013
Publisher
SPRINGER
Keywords
Multiple sclerosis; Genome-wide association study; Pathway-based analysis
Citation
MOLECULAR BIOLOGY REPORTS, v.40, no.3, pp.2557 - 2564
Indexed
SCIE
SCOPUS
Journal Title
MOLECULAR BIOLOGY REPORTS
Volume
40
Number
3
Start Page
2557
End Page
2564
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/103800
DOI
10.1007/s11033-012-2341-1
ISSN
0301-4851
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 (-log(10)(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 a parts per thousand currency sign 0.001, FDR a parts per thousand currency sign 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.
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