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This study investigates the association of 5 single nucleotide polymorphisms (SNPs) in selected genes (ABO, VEGFA, BDKRB2, NOS3, and ADRB2) with blood pressure (BP) response to enalapril. The study further assessed genetic interactions that exist within these genes and their implications in enalapril treatment response among South African adults with hypertension. A total of 284 participants belonging to the Nguni tribe of South Africa on continuous treatment for hypertension were recruited. Five SNPs in enalapril pharmacogenes were selected and genotyped using MassArray. Uncontrolled hypertension was defined as BP ≥140/90 mm Hg. The association between genotypes, alleles, and BP response to treatment was determined by fitting multivariate logistic regression model analysis, and genetic interactions between SNPs were assessed by multifactor dimensionality reduction. Majority of the study participants were female (75.00%), Xhosa (78.87%), and had uncontrolled hypertension (69.37%). All 5 SNPs were exclusively detected among Swati and Zulu participants. In the multivariate (adjusted) logistic model analysis, ADRB2 rs1042714 GC (adjusted odds ratio [AOR] = 2.31; 95% confidence interval [CI] 1.02–5.23; P = .044) and BDKRB2 rs1799722 CT (AOR = 2.74; 95% CI 1.19–6.28; P = .017) were independently associated with controlled hypertension in response to enalapril. While the C allele of VEGFA rs699947 (AOR = 0.37; 95% CI 0.15–0.94; P = .037) was significantly associated with uncontrolled hypertension. A significant interaction between rs699947, rs495828, and rs2070744 (cross-validation consistency = 10/10; P = .0005) in response to enalapril was observed. We confirmed the association of rs1042714 (ADRB2) and rs1799722 (BDKRB2) with controlled hypertension and established an interaction between rs699947 (VEGFA), rs495828 (ABO), and rs2070744 (NOS3) with BP response to enalapril. Our findings have provided substantial evidence for the use of SNPs as predictors for enalapril response among South Africans adults with hypertension.

This study examines the rate and the influencing factors of glycemic control among adult residents living with DM in Mkhondo Municipality of South Africa. In this cross-sectional study, 157 individuals attending care for DM were recruited. Glycemic control status was categorized as poor if glycated hemoglobin (HbA1c) > 7% and very poor if HbA1c ≥ 9%. Multivariate regression analysis was used to identify the significant determinants of poor and very poor glycemic control. The majority of the study participants were females (84.71%) and above 45 years old (88.55%). The overall prevalence of poor glycemic control was 77.71% (n = 122), while very poor glycemic control occurred in 50.6% (n = 80) of the study cohort. In the multivariate logistic regression model analysis, African traditional [AOR = 0.15; 95% confidence interval (95% CI) 0.04–0.57], fast food consumption (AOR = 5.89; 95% CI 2.09–16.81), elevated total cholesterol (TC) [odds ratio (OR) = 2.33; 95% CI 1.50–5.17], elevated low-density lipoprotein cholesterol (LDL-C) (AOR = 5.28; 95% CI 1.89–14.69), and triglyceride (TG) (AOR = 4.39; 95% CI 1.48–13.00) were the independent and significant determinants of poor glycemic control. Age (AOR = 0.46; 95% CI 0.23–0.92) was the only independent and significant determinant of very poor glycemic control. We found a high rate of poor glycemic control (77.71%) possibly attributed to religious affiliation, fast food consumption, and dyslipidemia. On the contrary, about half of the study sample had very poor glycemic control (HbA1c ≥9%), which was predominant among younger cohort with diabetes mellitus. Interventions aimed at improving glycemic control in this population must also target religious practice, dietary patterns and dyslipidemia as well as tailored-approach for young people.