title: Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease.
abstract: Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Mingming
authors.initials: M
authors.lastname: Zhang
authors.affiliation: College of Science, Northeast Forestry University, Harbin, China.
authors.forename: Hongbo
authors.initials: H
authors.lastname: Mu
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Zhenwei
authors.initials: Z
authors.lastname: Shang
authors.affiliation: Department of Cardiovascular Surgery, The Second Affiliated Hospital of Harbin Medical University, China.
authors.forename: Kai
authors.initials: K
authors.lastname: Kang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Hongchao
authors.initials: H
authors.lastname: Lv
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Lian
authors.initials: L
authors.lastname: Duan
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Li
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Xinren
authors.initials: X
authors.lastname: Chen
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yanbo
authors.initials: Y
authors.lastname: Teng
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. Electronic address: jiangyongshuai@gmail.com.
authors.forename: Yongshuai
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. Electronic address: zhangruijie_2015@163.com.
authors.forename: Ruijie
authors.initials: R
authors.lastname: Zhang
mesh_terms: D066264:Datasets as Topic; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium; D010300:Parkinson Disease / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide
keywords: Parkinson disease; genome-wide association study; pathway analysis; single nucleotide polymorphism (SNP)