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

被引:16
|
作者
Song, Gwan Gyu [1 ]
Choi, Sung Jae [1 ]
Ji, Jong Dae [1 ]
Lee, Young Ho [1 ]
机构
[1] Korea Univ, Coll Med, Anam Hosp, Div Rheumatol,Dept Internal Med, Seoul 136705, South Korea
关键词
Multiple sclerosis; Genome-wide association study; Pathway-based analysis; RISK; METAANALYSIS; DISEASES; SNPS; TOOL;
D O I
10.1007/s11033-012-2341-1
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:2557 / 2564
页数:8
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