Multi-trait and multi-ancestry genetic analysis of comorbid lung diseases and traits improves genetic discovery and polygenic risk prediction

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. Competing Interest Statement MHC has received grant support from GSK, consulting fees from Apogee and BMS, and speaking fees from Illumina. MM has received consulting fees from TheaHealth, 2ndMD, Axon Advisors, Verona Pharma, and Sanofi. ARM has received speaker fees from Novartis. All other authors declare no competing interests. Funding Statement This work was supported by the National Institutes of Health under award number T32HG010464, K99/R00MH117229, U01HG011719. MHC was supported by R01HL168199, R01HL162813, and R01HL153248, and R01HL135142. We are grateful for the volunteers who participated in the All of Us Research Program. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All of Us individual level data is available to authorized users on the Researcher Workbench (https://workbench.researchallofus.org/). Approval to use the dataset for this project was obtained from the All of Us Institutional Review Board. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Declaration of interest, funding sources, and additional supplementary information. Data Availability All data produced in the present study are available upon reasonable request to the authors.