Combining Polygenic Risk Scores to Predict Myocardial Infarction in the Canadian Longitudinal Study on Aging

Background and Aims : Estimating the risk of developing complex pathologies, such as coronary artery disease (CAD), is now possible by aggregating data from genome-wide association studies (GWAS) into polygenic risk scores (PRS). This study aims to evaluate the performance of PRS derived from CAD and blood lipids GWAS to predict myocardial infarction (MI).Methods: Using publicly available GWAS data (CARDIoGRAMplusC4D consortium for CAD and UK Biobank for blood lipids concentration and number of lipoprotein particles, obtained from nuclear magnetic resonance), we derived multiple PRS in individuals of European ancestry aged between 45 and 86 years, in the Canadian Longitudinal Study on Aging cohort. These PRS included >1.12 million of genetic variants and were calculated using LDpred2. Odds ratios (OR) for prevalent MI (971 cases and 18,628 controls) and their 95% confidence interval are reported from adjusted logistic regressions (age, sex and 10 genetic principal components) for 1-SD increase of each PRS distribution.Conclusions: The combination of several PRS derived from common genetic variants associated with CAD and blood lipids has the potential to improve the prediction of MI. Background and Aims : Estimating the risk of developing complex pathologies, such as coronary artery disease (CAD), is now possible by aggregating data from genome-wide association studies (GWAS) into polygenic risk scores (PRS). This study aims to evaluate the performance of PRS derived from CAD and blood lipids GWAS to predict myocardial infarction (MI). Methods: Using publicly available GWAS data (CARDIoGRAMplusC4D consortium for CAD and UK Biobank for blood lipids concentration and number of lipoprotein particles, obtained from nuclear magnetic resonance), we derived multiple PRS in individuals of European ancestry aged between 45 and 86 years, in the Canadian Longitudinal Study on Aging cohort. These PRS included >1.12 million of genetic variants and were calculated using LDpred2. Odds ratios (OR) for prevalent MI (971 cases and 18,628 controls) and their 95% confidence interval are reported from adjusted logistic regressions (age, sex and 10 genetic principal components) for 1-SD increase of each PRS distribution. Conclusions: The combination of several PRS derived from common genetic variants associated with CAD and blood lipids has the potential to improve the prediction of MI.