Premium
Gene–environment interactions related to blood pressure traits in two community‐based Korean cohorts
Author(s) -
Lim Ji Eun,
Kim Hye Ok,
Rhee Sang Youl,
Kim Mi Kyung,
Kim YeonJung,
Oh Bermseok
Publication year - 2019
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.22195
Subject(s) - single nucleotide polymorphism , blood pressure , waist , genome wide association study , body mass index , cohort , genetic association , quantitative trait locus , snp , genetics , gene–environment interaction , biology , cohort study , medicine , demography , genotype , gene , sociology
Hypertension is a complex disorder caused by genetic and environmental risk factors. Recently, genome‐wide association studies (GWASs) identified more than 100 genetic variants for blood pressure traits and hypertension. However, the interactions between these genetic variants and environmental factors have not been systematically investigated. Therefore, we examined the interaction between genetic and environmental risk factors in blood pressure traits using the genetic risk score (GRS). Two Korean community‐based cohorts, Cohort I (KARE; N = 8,840) and Cohort II (CAVAS; N = 9,599), were used for this study, and GRSs were calculated from 42 GWAS single‐nucleotide polymorphisms (SNPs) that were validated for their association in these cohorts. We calculated GRSs in both ways by considering the effect sizes of each SNP (weighted GRS) and not considering the effect sizes (unweighted GRS). The unweighted GRS was strongly associated with systolic blood pressure, diastolic blood pressure, and hypertension ( p = 9.03 × 10 –47 , p = 9.41 × 10 –48 , and p = 3.22 × 10 –55 by meta‐analysis, respectively) and the weighted GRS showed the similar results. The environmental factors of body mass index, waist circumference, and drinking status were significantly associated with blood pressure traits, and the interaction between these factors and GRSs were examined. However, no interactions were found with either the GRS or the individual SNPs considered for the GRS. Our findings show that it is challenging to find GRS–environment interactions regarding blood pressure traits.