title: Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.
abstract: BACKGROUND
  Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date.
  
  
  OBJECTIVE
  We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets.
  
  
  METHODS
  Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets.
  
  
  RESULTS
  In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2.
  
  
  CONCLUSIONS
  We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.
authors.affiliation: School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
authors.forename: Guiyou
authors.initials: G
authors.lastname: Liu
authors.affiliation: Department of Neurology and Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China.
authors.forename: Fang
authors.initials: F
authors.lastname: Zhang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yongshuai
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Neurology, Tianjin First Central Hospital, Tianjin, China.
authors.forename: Zhongying
authors.initials: Z
authors.lastname: Gong
authors.affiliation: Department of Neurology, Tianjin HuanHu Hospital, Tianjin, China.
authors.forename: Shoufeng
authors.initials: S
authors.lastname: Liu
authors.affiliation: Department of Neurology, Tianjin NanKai Hospital, Tianjin, China.
authors.forename: Xiuju
authors.initials: X
authors.lastname: Chen
authors.affiliation: School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
authors.forename: Qinghua
authors.initials: Q
authors.lastname: Jiang
authors.affiliation: Department of Neurology and Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China.
authors.forename: Junwei
authors.initials: J
authors.lastname: Hao
mesh_terms: D016022:Case-Control Studies; D015870:Gene Expression / Q000235:genetics; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D009103:Multiple Sclerosis / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012306:Risk
keywords: Multiple sclerosis; gene expression; gene-based test; genome-wide association studies; immune pathways; pathway analysis