Age-stratified hypertension risk prediction: integrating genetic risk scores with clinical markers in Korean adults

Background Hypertension is a prevalent age-related condition with varying life risk factors. This study aimed to develop age-stratified prediction models integrating genetic risk scores (GRS) with clinical factors to improve hypertension risk stratification. Methods A total of 2159 Korean adults aged 20–86 years were stratified into younger (20–49 years) and older (≥50 years) cohorts. Genome-wide association analysis identified hypertension-associated single-nucleotide polymorphisms (SNPs) for constructing the GRS. Age-specific prediction models were developed and evaluated using receiver operating characteristic curve analysis. Results In younger adults, a GRS4 based on four SNPs with consistent effect directions and strong effects was significantly associated with hypertension after adjusting for body mass index (BMI) and sex (adjusted odds ratio [OR] = 2.79, P < 0.001). Including another SNP with a suggestive effect (GRS5) produced comparable results. In older adults, GRS1 (rs149026664) was significant in the unadjusted model (unadjusted OR = 2.72, P = 0.024), while GRS2 (including rs116861740) remained significant after adjustment for BMI and sex (adjusted OR = 2.65, P = 0.005). Predictive models combining BMI, brachial-ankle pulse wave velocity (ba-PWV), and GRS achieved strong performance, with area under the curve (AUC) = 0.821 (GRS4) and 0.809 (GRS5) in younger adults, and AUC = 0.766 (GRS1) and 0.765 (GRS2) in older adults. Conclusion Age-specific integration of GRS with clinical markers such as BMI and ba-PWV significantly improves hypertension prediction, offering actionable thresholds for precision prevention across age groups. These models provide clinically actionable tools for precision prevention.