Shangqing (Joyce) Jiang
Disease Risk Prediction and Value of Polygenic Risk Scores
A key goal of precision medicine is to identify patients at higher disease risk and target them with preventative treatment and screening. Polygenic risk scores (PRS) estimate an individual’s genetic risk for a given disease by aggregating the effect of genomewide common genetic variants associated with the condition. However, before clinical implementation of PRS, we need to improve their predictive accuracy and assess their clinical and economic value. Colorectal cancer is one of the leading causes of cancer death in the United States. My research aims to improve PRS predictive accuracy for colorectal cancer risk using machine-learning methods. I will also quantify the value of PRS in guiding colorectal cancer screening using health economic modeling. My work will help generate a better PRS prediction algorithm for colorectal cancer, which may be of interest for future research and clinical use. I also hope my work will inform policymakers about the value of PRS in improving health outcomes and help payers with reimbursement decisions for PRS.
The predoctoral fellowship from PhRMA Foundation has been a tremendous honor to me. It not only provides me with generous financial support, but also it encourages me to continuously deliver high-quality research in health outcomes.