A large genomic analysis published in the Journal of The American College of Cardiology evaluated the development and validation of integrated polygenic risk scores (PRS) for cardiovascular risk prediction across multiple conditions. Genotype and clinical data from 245,394 participants in the All of Us Research Program were analyzed. 

Publicly available PRS for eight conditions—coronary artery disease (CAD), atrial fibrillation (AF), type 2 diabetes (T2D), venous thromboembolism (VTE), thoracic aortic aneurysm (TAA), hypertension, severe hypercholesterolemia, and elevated lipoprotein(a) [Lp(a)]—were combined using an elastic-net–based PRSmix model. External validation was conducted in 53,306 participants from the Mass General Brigham Biobank using logistic regression adjusted for age, sex, and ancestry.

Among the validation cohort (55.6% women; mean age 53±17 years), integrated PRS demonstrated consistent discrimination and calibration across all eight traits. Individuals in the high genetic risk category (top 10% of PRS distribution; top 20% for TAA and VTE) had higher odds of disease compared with those at average risk. 

Reported odds ratios (ORs) included CAD (3.7; 95% CI 3.4–4.1), T2D (3.1; 95% CI 2.8–3.3), AF (3.0; 95% CI 2.7–3.3), hypertension (2.1; 95% CI 1.8–2.3), hypercholesterolemia (4.1; 95% CI 3.7–4.5), VTE (1.9; 95% CI 1.6–2.0), TAA (1.7; 95% CI 1.5–1.9), and Lp(a) (41.0; 95% CI 27.0–62.2). Integration of PRS into clinical models improved risk classification, and prospective analyses supported associations with incident outcomes.

Integrated PRS demonstrated consistent performance across multiple cardiovascular traits. Broader prospective validation is required to further establish clinical utility.