Key result
Polygenic risk score boosts early-onset CAD prediction to an AUC of ~0.93 alongside clinical factors.
Why the study?
Polygenic risk scores can potentially improve coronary artery disease prediction beyond traditional models, but their utility and predictive performance needed evaluation in the Latvian population.
Does a polygenic risk score improve the prediction of early-onset coronary artery disease compared to conventional risk factors in a Latvian population?
Case-Control (n=133)
No
Does a polygenic risk score improve the prediction of early-onset coronary artery disease compared to conventional risk factors in a Latvian population?
Integrating a polygenic risk score with traditional clinical risk factors significantly enhances the early identification of premature coronary artery disease.
Answers are grounded in this paper and cite their sources.
PRS may improve early-onset CAD prediction alongside clinical factors; leaves open generalizability beyond this small cross-sectional cohort.
Study objective Polygenic risk scores (PRS) are increasingly recognized for their potential to improve coronary artery disease (CAD) prediction beyond traditional clinical models. This study evaluated the utility of genome-wide association study (GWAS) - derived PRS and pathway-specific PRS (PS-PRS) in the Latvian population, aiming to assess their association with CAD and compare their predictive performance with conventional risk factors. Design, participants and main outcome measures The study included 90 early-onset CAD patients and 43 controls with no evidence of atherosclerotic lesions on coronary angiography, with next-generation sequencing performed. PRS was calculated using 192 single nucleotide variants identified from the CARDIoGRAMplusC4D GWAS meta-analysis. The predictive accuracy of PRS, PS-PRS, clinical risk factors, and their combinations was analyzed via ROC curves. Results The average age was 48.7 years in CAD patients and 49.8 in controls. CAD patients showed significantly higher PRS (mean 0.31) compared to controls (mean − 0.65; p < 0.0001). PRS alone had moderate discriminatory power (AUC = 0.773), slightly lower than LDL cholesterol (AUC = 0.775) and total cholesterol (AUC = 0.821). Combining clinical risk factors improved prediction (AUC = 0.872), with the highest accuracy when PRS was integrated with all clinical factors (AUC = 0.933). The PRS distributions were significantly elevated in early-onset CAD patients across the angiogenesis/tissue repair pathway (p = 0.00038), inflammation pathway (p = 0.043), vascular remodelling pathway (p = 0.0116), and pathway of genes with unknown function in atherosclerosis (p = 0.0035), but overall PRS demonstrated superior discrimination compared to pathway-specific PRS. Conclusions Incorporating PRS enhances early-onset CAD risk prediction. Pathway specific PRS had lower discriminative ability than the overall PRS.
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Kanašniece et al. (2026) conducted a case-control in Early-onset coronary artery disease (n=133). Polygenic risk score (PRS) vs. Conventional clinical risk factors and controls without CAD was evaluated on Predictive accuracy (AUC) of PRS for early-onset CAD (AUC 0.772, 95% CI 0.689-0.85, p=<0.0001). A polygenic risk score was significantly associated with early-onset coronary artery disease and improved predictive accuracy when combined with clinical risk factors (AUC 0.933).
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