Why the study?
The role of renin-angiotensin-aldosterone system genes in hypertension has been widely studied across ethnicities, but not in a Thai population.
Are polymorphisms in RAAS-related genes (ACE, AGT, AGTR1, CYP11B2) associated with hypertension in a Thai population?
Are polymorphisms in RAAS-related genes (ACE, AGT, AGTR1, CYP11B2) associated with hypertension in a Thai population?
This study found no evidence of an association between four common RAAS-related gene polymorphisms and hypertension in a Thai population.
First RAAS gene data in Thais; leaves open whether variants inform hypertension care.
Introduction . The roles of genes in the renin‐angiotensin‐aldosterone system (RAAS) in hypertension, including angiotensin‐converting enzyme (ACE), angiotensinogen (AGT), angiotensin II receptor type 1 (AGTR1), and aldosterone synthase (CYP11B2), have been widely studied across different ethnicities, but there has been no such investigation in Thai population. Materials and Methods . Using 4,150 Thais recorded in the Electricity Generating Authority of Thailand (EGAT) study, we examined the association of rs1799752, rs699, rs5186, and rs1799998 located in or near ACE , AGT , AGTR1 , and CYP11B2 genes in hypertension. We investigated their roles in hypertension using multivariate logistic regression and further examined their roles in blood pressure (BP) using quantile regression. Sex, age, and BMI were adjusted as potential confounders. Results . We did not observe associations between hypertension and rs1799752 ( P = 0.422), rs699 ( P = 0.36), rs5186 ( P = 0.49), and rs1799998 ( P = 0.71). No evidence of association between these SNPs and BP was found across an entire distribution. A nonlinear relationship between age and BP was observed. Conclusion . In Thai population, our study showed no evidence of association between RAAS‐related genes and hypertension. While our study is the first and largest study to investigate the role of RAAS‐related genes in hypertension in Thai population, restricted statistical power due to limited sample size is a limitation.
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Charoen et al. (2019) studied this question.
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