title: Systematic Characterization and Prediction of Human Hypertension Genes.
abstract: Hypertension is a major cardiovascular risk factor and accounts for a large part of cardiovascular mortality. In this work, we analyzed the properties of hypertension genes and found that when compared with genes not yet known to be involved in hypertension regulation, known hypertension genes display distinguishing features: (1) hypertension genes tend to be located at network center; (2) hypertension genes tend to interact with each other; and (3) hypertension genes tend to enrich in certain biological processes and show certain phenotypes. Based on these features, we developed a machine-learning algorithm to predict new hypertension genes. One hundred and seventy-seven candidates were predicted with a posterior probability >0.9. Evidence supporting 17 of the predictions has been found.
authors.affiliation: From the Institute of Cardiovascular Sciences and Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University Health Science Center, Beijing, People's Republic of China (Y.-H.L., N.W.); Special Medical Ward (Geratology Department), First Hospital of Tsinghua University Beijing, People's Republic of China (G.-G.Z.); and The Advanced Institute for Medical Sciences, Dalian Medical University, China (N.W.). liyanhui@bjmu.edu.cn nanpingwang2003@yahoo.com.
authors.forename: Yan-Hui
authors.initials: YH
authors.lastname: Li
authors.affiliation: From the Institute of Cardiovascular Sciences and Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University Health Science Center, Beijing, People's Republic of China (Y.-H.L., N.W.); Special Medical Ward (Geratology Department), First Hospital of Tsinghua University Beijing, People's Republic of China (G.-G.Z.); and The Advanced Institute for Medical Sciences, Dalian Medical University, China (N.W.).
authors.forename: Gai-Gai
authors.initials: GG
authors.lastname: Zhang
authors.affiliation: From the Institute of Cardiovascular Sciences and Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University Health Science Center, Beijing, People's Republic of China (Y.-H.L., N.W.); Special Medical Ward (Geratology Department), First Hospital of Tsinghua University Beijing, People's Republic of China (G.-G.Z.); and The Advanced Institute for Medical Sciences, Dalian Medical University, China (N.W.). liyanhui@bjmu.edu.cn nanpingwang2003@yahoo.com.
authors.forename: Nanping
authors.initials: N
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D020022:Genetic Predisposition to Disease; D006801:Humans; D006973:Hypertension / Q000235:genetics*; D010641:Phenotype; D011506:Proteins / Q000235:genetics* / Q000378:metabolism; D012307:Risk Factors
chemical_list: D011506:Proteins
keywords: algorithm; hypertension; network; prediction; support vector machine