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MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups.
Jin, Jin; Zhan, Jianan; Zhang, Jingning; Zhao, Ruzhang; O'Connell, Jared; Jiang, Yunxuan; Buyske, Steven; Gignoux, Christopher; Haiman, Christopher; Kenny, Eimear E; Kooperberg, Charles; North, Kari; Koelsch, Bertram L; Wojcik, Genevieve; Zhang, Haoyu; Chatterjee, Nilanjan.
Afiliación
  • Jin J; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19103, USA. Electronic address: jin.jin@pennmedicine.upenn.edu.
  • Zhan J; 23andMe, Inc., Sunnyvale, CA 94086, USA.
  • Zhang J; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
  • Zhao R; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
  • O'Connell J; 23andMe, Inc., Sunnyvale, CA 94086, USA.
  • Jiang Y; 23andMe, Inc., Sunnyvale, CA 94086, USA.
  • Buyske S; Department of Statistics, Rutgers University, New Brunswick, NJ 08854, USA.
  • Gignoux C; Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Haiman C; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
  • Kenny EE; Icahn Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
  • Kooperberg C; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
  • North K; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA.
  • Koelsch BL; 23andMe, Inc., Sunnyvale, CA 94086, USA.
  • Wojcik G; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
  • Zhang H; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Chatterjee N; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. Electronic address: nilanjan@jhu.edu.
Cell Genom ; 4(4): 100539, 2024 Apr 10.
Article en En | MEDLINE | ID: mdl-38604127
ABSTRACT
Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bivalvos / Herencia Multifactorial Límite: Animals / Humans Idioma: En Revista: Cell Genom Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bivalvos / Herencia Multifactorial Límite: Animals / Humans Idioma: En Revista: Cell Genom Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos