title: Novel Genes Affecting Blood Pressure Detected Via Gene-Based Association Analysis.
abstract: Hypertension is a common disorder and one of the most important risk factors for cardiovascular diseases. The aim of this study was to identify more novel genes for blood pressure. Based on the publically available SNP-based P values of a meta-analysis of genome-wide association studies, we performed an initial gene-based association study in a total of 69,395 individuals. To find supplementary evidence to support the importance of the identified genes, we performed GRAIL (gene relationships among implicated loci) analysis, protein-protein interaction analysis, functional annotation clustering analysis, coronary artery disease association analysis, and other bioinformatics analyses. Approximately 22,129 genes on the human genome were analyzed for blood pressure in gene-based association analysis. A total of 43 genes were statistically significant after Bonferroni correction (P < 2.3×10(-6)). The evidence obtained from the analyses of this study suggested the importance of ID1 (P = 2.0×10(-6)), CYP17A1 (P = 4.58×10(-9)), ATXN2 (P = 1.07×10(-13)), CLCN6 (P = 4.79×10(-9)), FURIN (P = 1.38×10(-6)), HECTD4 (P = 3.95×10(-11)), NPPA (P = 1.60×10(-6)), and PTPN11 (P = 8.89×10(-10)) in the genetic basis of blood pressure. The present study found some important genes associated with blood pressure, which might provide insights into the genetic architecture of hypertension.
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China.
authors.forename: Huan
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
authors.forename: Xing-Bo
authors.initials: XB
authors.lastname: Mo
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China.
authors.forename: Tan
authors.initials: T
authors.lastname: Xu
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China.
authors.forename: Xiao-Qing
authors.initials: XQ
authors.lastname: Bu
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
authors.forename: Shu-Feng
authors.initials: SF
authors.lastname: Lei
authors.affiliation: Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, People's Republic of China yhzhang@suda.edu.cn.
authors.forename: Yong-Hong
authors.initials: YH
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001794:Blood Pressure / Q000235:genetics*; D016000:Cluster Analysis; D003324:Coronary Artery Disease / Q000235:genetics; D003971:Diastole / Q000235:genetics; D058685:Genetic Pleiotropy; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D058977:Molecular Sequence Annotation; D060066:Protein Interaction Maps; D012984:Software; D013599:Systole / Q000235:genetics
keywords: blood pressure; coronary artery disease; gene-based association; genome-wide association study; protein–protein interaction
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