Year: 2026
Type: preprint
Abstract: Modern large-scale genetic association analyses of imaging and omics data reveal unprecedented details of the genetic architecture of complex traits. Such analyses involve scanning thousands of phenotypes using linear mixed model-based genome-wide association study tools to control for sample relatedness. However, current LMM tools are not designed for such scale, creating a computational burden that hinders discovery. We propose TorchGWAS2, a cost-effective solution that overcomes the bottleneck using a deterministic variance-correction algorithm for LMMs, making it well-suited for GPU acceleration. TorchGWAS2 is applicable to unrelated and related individuals, cross-sectional and longitudinal studies, with and without missing data, and its computational complexity scales linearly with the number of phenotypes, genetic variants, and individuals. TorchGWAS2 showed more powerful association testing across 128 retinal image-derived endophenotypes of pairs of eyes from 64,703 UK Biobank participants and achieved two orders of magnitude speed-up analyzing 1,023 circulating metabolites in 16,352 Trans-Omics for Precision Medicine participants.
Source: medRxiv
Authors: Mengyu Zhang, Ziqian Xie, Samaneh Salehi Nasab, Nannan Wang, Xingzhong Zhao, Taryn Alkis, John Barnard, Thomas W. Blackwell, Russell P. Bowler, Shinhye Chung, Michael H. Cho, Clary B. Clish, Emily Drzymalla, Anne M. Evans, Nora Franceschini, Robert E. Gerszten, Madeline G. Gillman, Megan L. Grove, Nancy L. Heard-Costa, Scott R. Hutton, Rachel S. Kelly, Charles Kooperberg, Martin G. Larson, Jessica Lasky-Su, Deborah A. Meyers, Franklin P. Ockerman, Laura M. Raffield, Alexander P. Reiner, Stephen S. Rich, Jerome I. Rotter, Albert V. Smith, Kent D. Taylor, Ramachandran S. Vasan, Scott T. Weiss, Kari E. Wong, Alexis C. Wood, Prescott G. Woodruff, Lang Wu, Ronit I. Yarden, Junsun Yu, Laura Y. Zhou, Bing Yu, Degui Zhi, Han Chen
Institutions: The University of Texas Health Science Center at Houston, Yale University, Cleveland Clinic, Cleveland Clinic Research, University of Michigan, Brigham and Women's Hospital, Harvard University, Broad Institute, University of North Carolina at Chapel Hill, Metabolon (United States), Boston University, Framingham Heart Study, Fred Hutch Cancer Center, University of Arizona, University of Washington, University of Virginia, The Lundquist Institute, Harbor–UCLA Medical Center, The University of Texas at San Antonio Health Science Center, Baylor College of Medicine, University of California, San Francisco, Louisiana State University Health Sciences Center New Orleans, National Heart, Lung, and Blood Institute, Indiana University School of Medicine, New York University
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funder: National Institutes of Health
OpenAlex ID: W7213429021
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