Systematic common and rare variant association testing in 392,030 whole genomes in All of Us

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Authors: Wenhan Lu, Robert J. Carroll, Matthew Solomonson, Jeremy Guez, Megan K. He, Daniel Marten, Alejandro Martinez-Carrosco, Yue Wang, Connor Dowd, Masahiro Kanai, Bram L. Gorissen, Aymone Kouame
+37 more James Brogan, Bennett J. Waxse, Ryan Samarakoon, Justin A. Cook, Jun Qian, Yu Zhou, Karmel W. Choi, Melissa Basford, Michael Lyons, Jodell E. Linder, Samantha Stewart, Namrata Gupta, Patrick Schultz, Daniel Goldstein, Christopher Llanwarne, Jacqueline I. Goldstein, Edmund G. C. Higham, Daniel C. King, Duncan S. Palmer, Jared S. Elenbaas, Greg Rohlicek, Qin He, Julia K. Goodrich, Jordan W. Smoller, Lee Lichtenstein, Stacey B. Gabriel, Alicia R. Martin, Jason H. Karnes, Scott Joseph Hebbring, Mark J Daly, Tara Dutka, Anjene Musick, Joshua C. Denny, Wei Zhou, Dan M. Roden, Benjamin M. Neale, Konrad J. Karczewski
Cited by: 1
References: 55

Abstract

Abstract Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide (“All by All”) computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

Fields of Study & Subjects

Genetic Associations and Epidemiology Genomics and Rare Diseases Bioinformatics and Genomic Networks

Publication details

Journal / source
medRxiv
Publisher
openRxiv
Publication date
12 May 2026
Language
EN
Document type
Preprint