Current genetic testing for coronary artery disease (CAD) mainly targets monogenic variants in severe hypercholesterolaemia. GenProbCAD combines monogenic pathogenic variants with polygenic risk scores for CAD and for lipoprotein(a), developed and validated in the UK Biobank (two cohorts of 226,145) and applied in a community biobank (20,477). The integrated score predicted CAD better than monogenic variants or the polygenic score alone and flagged 16% as high-risk — 46-fold more than monogenic carriers — with comparable CAD prevalence and consistent prediction across all LDL strata and ancestries. A universal strategy would hypothetically capture ~21% of all incident CAD, versus 0.3% with current monogenic testing.
Current genetic testing for coronary artery disease (CAD) primarily targets monogenic variants in individuals with severe hypercholesterolemia. Whether supplementing monogenic testing with polygenic risk scores for CAD and Lp(a; lipoprotein[a]) levels [PRSLp(a)] improves identification of high-risk individuals in the general population remains understudied.
A genetic probability for CAD (GenProbCAD), incorporating monogenic pathogenic variants (PVs), polygenic risk scores for CAD, and PRSLp(a) was developed using Cox regression in 226 145 UK Biobank participants, validated in the remaining 226 145 UK Biobank participants, and applied to 20 477 participants of the Genomic Health Initiative, a community-based health care biobank. Predictive performance was evaluated and adjusted for clinical risk factors.
In the UK Biobank development cohort, PVs, polygenic risk scores for CAD and PRSLp(a) were each independently associated with CAD. In the UK Biobank validation cohort, GenProbCAD outperformed PVs and the polygenic risk score in predicting CAD and reclassified risk among PV carriers. GenProbCAD identified 16% of participants as high risk, 46-fold more than PV carriers (0.35%), with comparable observed CAD prevalence (15.60% versus 15.43%). Nearly 50% of CAD with high-risk GenProbCAD were premature. GenProbCAD also independently predicted incident CAD after adjusting for clinical risk factors. Importantly, high-risk individuals defined by GenProbCAD showed consistently elevated CAD incidence across all low-density lipoprotein cholesterol strata. When UK Biobank-derived coefficients and cutoffs were applied in the Genomic Health Initiative, GenProbCAD substantially outperformed the PV-only strategy, identifying 1966 high-risk participants (345 developed CAD), far exceeding the 20 PV carriers detected among those with low-density lipoprotein cholesterol ≥190 mg/dL (5 developed CAD). A universal genetic testing strategy using GenProbCAD would hypothetically identify 20.75% of all incident CAD, 69-fold higher than current monogenic testing (0.3%). Results were generally consistent across ancestry populations, although the sample size of non-European participants was limited.
GenProbCAD, a novel integrated genetic risk tool combining monogenic PVs, polygenic risk scores for CAD, and PRSLp(a), improves identification of individuals at high genetic risk for CAD across diverse populations.
