Grant: CIHR Fellowship

Many diseases are preventable by early detection and/or intervention if we knew who is most at risk. For diseases like coronary artery disease (CAD), risk predictions are made based on age and sex in combination with known risk factors (e.g. family history, cholesterol levels, body mass index, smoking habits). However, there is also a strong genetic component to the likelihood you will develop CAD (~50% of total). My research focuses on Polygenic Risk Scores (PGS), a method that can be used to predict genetic predisposition for a disease by aggregating the effects of variants across an individual's genome. Studies have shown that currently used risk prediction methods for multiple diseases can be improved by including PGS. Despite the benefits of PGS, there is both a lack of standardization and an incomplete understanding of their predictive ability (especially in people of non-European ancestry). This hinders PGS' adoption in clinical practice. To fill these gaps in our understanding, I am creating the PGS Catalog: a foundational resource to distribute the information necessary to apply and understand PGS for a wide range of diseases and traits. I will also perform a systematic comparison of PGS to measure PGS predictive ability and identify the best PGS for each trait (where multiple exist). Through this research I will identify any deficits in generalizability across ancestries and between sexes that need to be corrected. Finally, I will use the PGS to measure their ability to predict disease risk in rare disease patients, measuring how PGS combine with rare mutations. Together my research aims to establish the PGS Catalog as a foundational resource to advance our understanding of disease risk prediction using genetics, while also enabling new research and clinical uses of PGS.