Riyaz S. Patel

This study evaluates polygenic risk scores for population screening, individual risk prediction, and risk stratification, finding poor performance across all three applications.

This study evaluates how polygenic risk scores for coronary artery disease (CAD) relate to future events in individuals with and without CAD, finding attenuated or inverse associations in established cases.

This paper introduces a mathematical framework to improve Mendelian randomization analysis for drug targets by addressing horizontal pleiotropy when proteins are the risk factors.

This paper develops a genomic risk score for coronary artery disease using 1.7 million variants and tests it in UK Biobank, showing it outperforms conventional risk factors in predicting CAD risk.