title: Male-specific genetic effect on hypertension and metabolic disorders.
abstract: Genetic risk factors for hypertension may have age or gender specificity and pleiotropic effects. This study aims to measure the risk of genetic and non-genetic factors in the occurrence of hypertension and related diseases, with consideration of potential confounding factors and age-gender stratification. A discovery set of 352,228 genotyped plus 1.8 million imputed single-nucleotide polymorphisms were analyzed for 2,886 hypertensive cases and 3,440 healthy controls obtained from two community-based cohorts in Korea, and selected gene variants were replicated in the Health Examinee cohort (665 cases and 1,285 controls). Genome-wide association analyses were conducted in 12 groups stratified by age and gender after adjusting for potential covariates under three genetic models. Age, rural area residence, body mass index, family history of hypertension, male gender, current alcohol drinking status, and current smoking status were significantly associated with hypertension (P = 4 × 10(-151) to 0.011). Five gene variants, rs11066280 (C12orf51), rs12229654 and rs3782889 (MYL2), rs2072134 (OAS3), rs2093395 (TREML2), and rs17249754 (ATP2B1), were found to be associated with hypertension mostly in men (P = 4.76 × 10(-14) to 4.46 × 10(-7) in the joint analysis); three SNPs (rs11066280, rs12229654, and rs3782889) remained significant after Bonferroni correction in an independent population. Three gene variants, rs12229654, rs17249754, and rs11066280, were significantly associated with metabolic disorders such as hyperlipidemia and diabetes (P = 0.00071 to 0.0097, respectively). Careful consideration of the potential confounding effects in future genome-wide association studies is necessary to uncover the genetic underpinnings of complex diseases.
authors.affiliation: Department of Medical Genetics, College of Medicine, Hallym University, Chuncheon, Republic of Korea.
authors.forename: Seong Gu
authors.initials: SG
authors.lastname: Heo
authors.forename: Joo-Yeon
authors.initials: JY
authors.lastname: Hwang
authors.forename: Saangyong
authors.initials: S
authors.lastname: Uhmn
authors.forename: Min Jin
authors.initials: MJ
authors.lastname: Go
authors.forename: Burmseok
authors.initials: B
authors.lastname: Oh
authors.forename: Jong-Young
authors.initials: JY
authors.lastname: Lee
authors.forename: Ji Wan
authors.initials: JW
authors.lastname: Park
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure / Q000235:genetics; D015992:Body Mass Index; D016022:Case-Control Studies; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D005260:Female; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D006973:Hypertension / Q000235:genetics*; D016015:Logistic Models; D008297:Male; D015201:Meta-Analysis as Topic; D008659:Metabolic Diseases / Q000235:genetics*; D008875:Middle Aged; D015999:Multivariate Analysis; D020641:Polymorphism, Single Nucleotide; D056910:Republic of Korea; D012307:Risk Factors; D012737:Sex Factors; D014280:Triglycerides / Q000097:blood
chemical_list: D001786:Blood Glucose; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D014280:Triglycerides