Yun Li, PhD (Professor, Genetics) together with first author Elena Kharitonova (PhD Student, Biostatistics) have published a in the American Journal of Human Genetics (AJHG) titled 鈥淓ndoPRS: Incorporating endophenotype information to improve polygenic risk scores for clinical endpoints 鈥� a study in asthma鈥�.
This paper introduces endoPRS, 鈥渁 weighted lasso model that incorporates information from relevant endophenotypes to improve disease risk prediction without making assumptions about the genetic architecture underlying the endophenotype-disease relationship.鈥澛� The team applied the endoPRS model to predict the risk of childhood-onset asthma in UK Biobank and All of Us data sets by leveraging a paired genome-wide association study of eosinophil count, a relevant endophenotype, and found that endoPRS significantly improves prediction and transferability compared to many existing PRS methods.