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A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.
- Source :
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Nature computational science [Nat Comput Sci] 2025 Feb 07. Date of Electronic Publication: 2025 Feb 07. - Publication Year :
- 2025
- Publisher :
- Ahead of Print
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Abstract
- Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits in 61,838 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered and replicated new associations with lipid traits missed by single-trait analysis.<br />Competing Interests: Competing interests: Z.R.M. and R.D. are employees of Insitro. S.M.G. is an employee of Regeneron Genetics Center. M.E.M. receives research funding from Regeneron Pharmaceutical Inc., unrelated to this project. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. L.M.R. and S.S.R. are consultants for the TOPMed Administrative Coordinating Center (via Westat). P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech/Roche and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Esperion Therapeutics, Foresite Capital, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, Merck, Novartis, TenSixteen Bio and Tourmaline Bio, equity in Bolt, Candela, Mercury, MyOme, Parameter Health, Preciseli and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. X. Lin is a consultant of AbbVie Pharmaceuticals and Verily Life Sciences. The other authors declare no competing interests.<br /> (© 2025. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Details
- Language :
- English
- ISSN :
- 2662-8457
- Database :
- MEDLINE
- Journal :
- Nature computational science
- Publication Type :
- Academic Journal
- Accession number :
- 39920506
- Full Text :
- https://doi.org/10.1038/s43588-024-00764-8