Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease. (6th January 2017)

• Record Type: Journal Article
• Authors: Zhang, Mingming; Mu, Hongbo; Shang, Zhenwei; Kang, Kai; Lv, Hongchao; Duan, Lian; Li, Jin; Chen, Xinren; Teng, Yanbo; Jiang, Yongshuai; Zhang, Ruijie
• Is Part Of: Neuroscience. Volume 340(2017)
• Page Start: 398
• Page End: 410
• Publication Date: 2017-01-06
• Subjects: AD Alzheimer's disease -- CAMs cell adhesion molecules -- dbGaP Genotypes and Phenotypes -- ECM extra cellular matrix -- FAK focal adhesion kinase -- FAs focal adhesions -- FDR false discovery rate -- GWAS genome-wide association study -- HLA Human Leucocyte Antigen -- HWE Hardy–Weinberg equilibrium -- KEGG Kyoto Encyclopedia of Genes and Genomes -- LD Linkage disequilibrium -- NINDS National Institute of Neurological Disorders and Stroke -- PD Parkinson's disease -- RA rheumatoid arthritis -- SNP single nucleotide polymorphism; Parkinson disease -- pathway analysis -- single nucleotide polymorphism (SNP) -- genome-wide association study; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2016.11.004
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: We performed pathway analysis based on the moderate genes. Among our results, there are four pathways to be reported in previous studies. Our findings implied that there was an association between immune response and PD. 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 nervous system. 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.