Background: Risk prediction for coronary heart disease (CHD) events might be improved by the addition of a polygenic risk score (PRS) to conventional risk factors. However, PRS performance has never been assessed in an elderly population without a history of cardiovascular events. 

Methods: We predicted risk of major CHD events in a population of 12,792 healthy elderly individuals of European descent enrolled in the ASPREE trial. PRS was calculated using 1.7 million genetic variants. Participants had no previous history of diagnosed atherothrombotic cardiovascular events, dementia, or persistent physical disability at enrolment. The primary outcome was a composite of incident myocardial infarction or CHD death over 5 years. A multivariable model including conventional risk factors was applied and re-evaluated after adding the PRS. Area under the curve (AUC) and net reclassification were evaluated.

Results: At baseline, mean population age was 75 years and 54.9% were female. In total, 254 incident CHD events occurred. When PRS was added to the multivariable model, it was independently associated with CHD (hazard ratio 1.24 [95% confidence interval [CI] 1.08-1.42], p=0.002) (Figure 1). The AUC of the conventional model was 70.53 (95%CI 67.00-74.06), and after inclusion of the PRS, increased to 71.78 (95%CI 68.32-75.24, p=0.019). Reclassification was improved, as the continuous net reclassification index after adding PRS to the conventional model was 0.25 (95%CI 0.15-0.28).

Conclusion: In a population of healthy elderly individuals, the addition of a PRS to conventional cardiovascular risk factors moderately improved the prediction of incident major CHD events.

Figure 1: Central figure summarizing the main study findings

We evaluated the prognostic accuracy of a previously derived polygenic risk score (metaGRS) to predict 5 years CHD events in a population of healthy elderly individuals. Abbreviations: CHD = coronary heart disease, AUC = area under the curve, HR = hazard ratio, CI = confidence interval.