Key result
The GPSMult polygenic risk score significantly predicted incident coronary artery disease with a hazard ratio of 1.73 per standard deviation increase, outperforming previously published scores across multiple ancestries.
Why the study?
Accurate stratification of coronary artery disease risk remains a critical need.
Does a multi-ancestry polygenic risk score (GPSMult) improve risk prediction and reclassification for coronary artery disease compared to prior scores and clinical risk equations?
Observational (n=325,991)
Yes
Does a multi-ancestry polygenic risk score (GPSMult) improve risk prediction and reclassification for coronary artery disease compared to prior scores and clinical risk equations?
Hazard Ratio: 1.73 (95% CI 1.7–1.76)
p-value: p=<0.001
A multi-ancestry polygenic risk score significantly improves coronary artery disease risk prediction and reclassification across diverse populations compared to clinical risk factors and previous European-centric scores.
May enhance CAD reclassification beyond PCE across ancestries; extends prior PRS data but leaves open clinical adoption.
Accurate stratification of coronary artery disease (CAD) risk remains a critical need. A new polygenic score (GPS Mult ) incorporates CAD genome-wide association data across five ancestries (>269,000 cases, >1,178,000 controls) with genetic association data for ten CAD risk factors. GPS Mult associates with an OR/SD 2.14, (95%CI:2.10-2.19,P<0.001) for prevalent CAD and HR/SD 1.73 (95%CI 1.70-1.76,P<0.001) for incident CAD. When compared with the previously published GPS 2018 in external datasets, GPS Mult demonstrated 73%, 46%, and 113% increase in effect size for individuals of African, European, and South Asian ancestry, respectively, and significantly outperformed recently published CAD polygenic scores. GPS Mult identifies individuals with CAD risk extremes, including the top 3% of the population at equivalent risk for a new CAD event as those with prior CAD having a second event. Integrating GPS Mult with the Pooled Cohort Equations results in 7.0% [95%CI:5.9%-8.2%,P<0.001] net reclassification improvement at the 7.5% threshold. Large-scale integration genetic association data for CAD and related traits from diverse populations meaningfully improves polygenic risk prediction.
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Patel et al. (2023) conducted an observational in Coronary artery disease (n=325,991). GPSMult (Multi-ancestry polygenic risk score) vs. Previously published polygenic scores (e.g., GPS2018) or average genetic risk was evaluated on Incident coronary artery disease (per standard deviation increase in GPSMult) (HR 1.73, 95% CI 1.70-1.76, p=<0.001). The GPSMult polygenic risk score significantly predicted incident coronary artery disease with a hazard ratio of 1.73 per standard deviation increase, outperforming previously published scores across multiple ancestries.
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