Interactions Between Enhanced Polygenic Risk Scores and Lifestyle for Cardiovascular Disease, Diabetes, and Lipid Levels

Abstract

Background: Both lifestyle and genetic factors confer risk for cardiovascular diseases, type 2 diabetes, and dyslipidemia. However, the interactions between these 2 groups of risk factors were not comprehensively understood due to previous poor estimation of genetic risk. Here we set out to develop enhanced polygenic risk scores (PRS) and systematically investigate multiplicative and additive interactions between PRS and lifestyle for coronary artery disease, atrial fibrillation, type 2 diabetes, total cholesterol, triglyceride, and LDL-cholesterol.

Methods: Our study included 276 096 unrelated White British participants from the UK Biobank. We investigated several PRS methods (P+T, LDpred, PRS continuous shrinkage, and AnnoPred) and showed that AnnoPred achieved consistently improved prediction accuracy for all 6 diseases/traits. With enhanced PRS and combined lifestyle status categorized by smoking, body mass index, physical activity, and diet, we investigated both multiplicative and additive interactions between PRS and lifestyle using regression models.

Results: We observed that healthy lifestyle reduced disease incidence by similar multiplicative magnitude across different PRS groups. The absolute risk reduction from lifestyle adherence was, however, significantly greater in individuals with higher PRS. Specifically, for type 2 diabetes, the absolute risk reduction from lifestyle adherence was 12.4% (95% CI, 10.0%-14.9%) in the top 1% PRS versus 2.8% (95% CI, 2.3%-3.3%) in the bottom PRS decile, leading to a ratio of >4.4. We also observed a significant interaction effect between PRS and lifestyle on triglyceride level.

Conclusions: By leveraging functional annotations, AnnoPred outperforms state-of-the-art methods on quantifying genetic risk through PRS. Our analyses based on enhanced PRS suggest that individuals with high genetic risk may derive similar relative but greater absolute benefit from lifestyle adherence.

Keywords: atrial fibrillation; cardiovascular disease; coronary artery disease; healthy lifestyle; triglycerides.

Figure 1.

Performance of polygenic risk scores (PRS) by different methods. Candidates PRS were generated using four PRS methods (P+T, LDpred, PRS-CS, and AnnoPred). Tuning parameters of each method were selected in the training set, and the predictive performance using the optimal tuning parameters was then assessed in the testing set. The prediction accuracy was measured by area under the receiver operator curve (AUC) and was provided with 95% CI.

Figure 2.

Relative risk of coronary artery disease, atrial fibrillation, and type 2 diabetes stratified by the combination of genetic and lifestyle factors. We partitioned the testing set into 30 groups according to their PRS percentile (10 genetic risk bins) and lifestyle status (three lifestyle bins). The hazard ratios (HRs) were calculated by comparing each group to the group with 40%−60% PRS and intermediate lifestyle. All HRs were adjusted by age, sex and first four genetic principal components and were provided with their corresponding 95% CI. Y-axis was on log-scale.

Figure 3.

Incident events of coronary artery disease, atrial fibrillation, and type 2 diabetes stratified by the combination of genetic and lifestyle factors. We partitioned the testing set into 21 groups according to their PRS percentile (7 genetic risk bins) and lifestyle status (three lifestyle bins). The absolute risk in each group was calculated as the incident rate of each disease in the group, and the absolute risk reduction (ARR) reflected the reduction of absolute risk when changing the lifestyle status from poor to ideal within the same PRS group.

Figure 4.

Lipid levels stratified by the combination of genetic and lifestyle factors. We partitioned the testing set into 30 groups according to their PRS percentile (10 genetic risk bins) and lifestyle status (three lifestyle bins). The mean level of lipid in each group was provided with its associated standard error (SD). Different background color indicated different designation according to the recommendation by the National Cholesterol Education Program (NCEP). Green, yellow and red indicated normal, border high, and high designation, respectively.