Jingning Zhang

Apr 14, 2024 | nature.com | Jingning Zhang |Jin Jin |Haoyu Zhang

AbstractGreat efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER).

Sep 25, 2023 | nature.com | Haoyu Zhang |Jingning Zhang |Thomas Ahearn |Zhi Yu |TONY CHEN |Montserrat Garcia-Closas | +1 more

AbstractPolygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning.

Sep 21, 2023 | biorxiv.org | Jin Jin |Jianan Zhan |Jingning Zhang |Ruzhang Zhao

AbstractPolygenic risk scores (PRS) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across different populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in the summary statistics from genome-wide association studies (GWAS) across multiple ancestry groups.