Background: Polygenic risk scores (PRS) can be used to predict ischemic stroke (IS). However, further validation of PRS performance is required in independent populations,  particularly in older people in which the majority of strokes occurs. 

Methods: We predicted risk of incident IS events in a population of 12,792 healthy older individuals of European descent enrolled in the ASPREE trial. The PRS was calculated using 3.6 million genetic variants. Participants had no previous history of diagnosed atherothrombotic cardiovascular events, dementia, or persistent physical disability at enrollment. The primary outcome was IS over 5 years, with stroke sub-types as secondary outcomes (large vessel, small vessel, cardioembolic). A multivariable model including conventional risk factors was applied and re-evaluated after adding the PRS, either as a continuous or categorical variable. Area under the curve (AUC) and net reclassification were evaluated.

Results: At baseline, mean population age was 75 years; 54.9% were women. In total, 173 incident IS events occurred over a median follow-up of 4.7 years. When PRS was added to the multivariable model as a continuous variable it was independently associated with IS (hazard ratio 1.41 [95% confidence interval [CI] 1.20-1.65] per standard deviation of the PRS, p<0.001). The PRS alone was a better discriminator for IS events than most conventional risk factors, including gender, cholesterol and family history (Table 1). PRS as a categorical variable was a significant predictor in the highest tertile (HR 1.74, p=0.004) compared to lowest. The AUC of the conventional model was 66.6% (95%CI 62.2-71.1), and after inclusion of the PRS, improved to 68.5 (95%CI 64.0-73.0) (p=0.095). In sub-group analysis, the continuous PRS remained an independent predictor for large vessel and cardioembolic stroke, but not for small vessel stroke. Reclassification was improved, as the continuous net reclassification index after adding PRS to the conventional model was 0.25 (95%CI 0.17-0.43).

Conclusion: PRS is an independent predictor of incident IS in a healthy older population, and moderately improves prediction over conventional risk factors. Genomic prediction may provide clinical utility for IS, patricianly when patient risk is close to a treatment threshold.

Table 1: Area under the curve for each predictor, the conventional model and the PRS added to the conventional model 

*p-value compared to the conventional model = 0.0948. Abbreviations: HDL-c = high density lipoprotein cholesterol, PRS = polygenic risk score, AUC = area under the curve, CI = confidence interval. The analyses are based on 11,385 individuals and 158 IS events.