Nature GeneticsGenetic & Genomic MedicinePeer-reviewed journal article
Multi-trait and multi-ancestry genetic analysis of comorbid lung diseases and traits improves genetic discovery and polygenic risk prediction
Yixuan HeiD, Wenhan LuiD, Yon Ho JeeiD, Mu-Yi ShihiD, Ying WangiD, Kristin TsuoiD, David C. QianiD, James A. DiaoiD, Hailiang HuangiD, Chirag J. PateliD, Jinyoung ByuniD, Bogdan PaşaniuciD, Elizabeth G. AtkinsoniD, Christopher Ian AmosiD, Yen‐Chen Anne FengiD, Matthew R. MolliD, Michael H. ChoiD, Alicia R. MartiniD
Abstract
While respiratory diseases such as COPD and asthma share many risk factors, most studies investigate them in insolation and in predominantly European ancestry populations. Here, we conducted the most powerful multi-trait and -ancestry genetic analysis of respiratory diseases and auxiliary traits to date. Our approach improves the power of genetic discovery across traits and ancestries, identifying 44 novel loci associated with lung function in individuals of East Asian ancestry. Using these results, we developed PRSxtra (cross TRait and Ancestry), a multi-trait and -ancestry polygenic risk score approach that leverages shared components of heritable risk via pleiotropic effects. PRSxtra significantly improved the prediction of asthma, COPD, and lung cancer compared to trait- and ancestry-matched PRS in a multi-ancestry cohort from the All of Us Research Program, especially in diverse populations. PRSxtra identified individuals in the top decile with over four-fold odds of asthma and COPD compared to the first decile. Our results present a new framework for multi-trait and -ancestry studies of respiratory diseases to improve genetic discovery and polygenic prediction.
- organism: human
- assay: GWAS summary statistics
- research focus: polygenic risk
- approach: statistical model
- Citations
- 2
- FWCI
- 7.91
- Field percentile
- top 4%
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