Combining Genomics With Lipid and Inflammatory Biomarkers to Predict Coronary Artery Disease Risk: UK Biobank Study

Clinical Snapshot

Key Findings

• P Value: P-interaction ≤0.001 for sex differences in CAD PRS; P<0.0001 for age interactions

• Effect Size: Combined 4-biomarker model: 4.65-fold increased risk when all biomarkers elevated

• Primary Outcome: Incident coronary artery disease over 12 years

• Nnt Or Sensitivity: C-statistic 0.753 for combined model vs 0.740 for pooled cohort equations; 32.0% net reclassification improvement

• Confidence Interval: Individual HRs: CAD PRS 1.79 (1.70-1.89), LDL-C 1.60 (1.48-1.66), hsCRP 1.64 (1.57-1.72), Lp(a) 1.20 (1.12-1.29)

Clinical Application

CAD PRS requires genetic testing infrastructure; other biomarkers routinely available in clinical practice Relevant to Australian practice; LDL-C and hsCRP widely available through Medicare; genetic testing emerging through initiatives like Australian Genomics. Aligns with RACGP cardiovascular risk assessment guidelines Middle-aged adults (40-69 years) without established CAD seeking cardiovascular risk assessment

Abstract

BACKGROUND: Coronary artery disease (CAD) polygenic risk score (PRS), low-density-lipoprotein cholesterol (LDL-C), lipoprotein(a) (Lp(a)), and high-sensitivity C-reactive protein (hsCRP) are biomarkers that predict CAD. It is unclear whether integrating genomics with lipid and inflammatory biomarkers could complement traditional risk scores in identifying people at risk of CAD. OBJECTIVES: This study assesses the predictive value of CAD PRS, LDL-C, Lp(a), and hsCRP for incident CAD across different age and sex groups. METHODS: Participants (n = 215,695) from the UK Biobank aged 40 to 69 years with baseline CAD PRS, LDL-C, Lp(a), and hsCRP values were followed for 12 years to assess the incidence of CAD. We evaluated a multivariable-adjusted Cox model that included all 4 biomarkers, net reclassification index, C-statistics, and population attributable risk across different age and sex groups. RESULTS: Over a 12-year follow-up, 4,721 men and 2,425 women developed CAD. The HRs for incident CAD associated with each biomarker elevation were 1.79 (95% CI: 1.70-1.89) for CAD PRS, 1.60 (95% CI: 1.48-1.66) for LDL-C, 1.20 (95% CI: 1.12-1.29) for Lp(a), and 1.64 (95% CI: 1.57-1.72) for hsCRP. CAD PRS demonstrated a stronger association in men (HR per SD: 1.49; 95% CI: 1.45-1.54) than women (HR per SD: 1.37; 95% CI: 1.31-1.44; P-interaction ≤ 0.001). All biomarkers conferred greater HRs at younger ages (P < 0.0001). Individuals with all biomarkers elevated had a 4.65-fold increased risk of CAD compared with those with no elevated biomarkers. A combined 4-biomarker model had a higher C-statistic of 0.753 compared with the pooled cohort equations (C-statistic of 0.740). The C-statistic of the combined 4-biomarker model was also higher in younger individuals in both sexes and yielded a 32.0% continuous net reclassification index when compared with the pooled cohort equations. CONCLUSIONS: CAD PRS, LDL-C, hsCRP, and Lp(a) show independent age- and sex-specific associations with CAD. Measuring all 4 biomarkers may improve midlife CAD risk prediction for both male and female patients.

References

1. 1.Farah, R., Kim, M. S., Truong, B., Sui, Y., Cho, S. M. J., Urbut, S. M., Patel, A., Ridker, P. M., Natarajan, P., & Fahed, A. C. (2026). Combining genomics with lipid and inflammatory biomarkers to predict coronary artery disease risk: UK Biobank study. Journal of the American College of Cardiology. https://doi.org/10.1016/j.jacc.2026.01.076