medRxivGenetic & Genomic MedicinePreprint
Systematic common and rare variant association testing in 392,030 whole genomes in All of Us
Wenhan LuiD, Robert J. CarrolliD, Matthew SolomonsoniD, Jérémy GueziD, Megan K. HeiD, Daniel Marten, Alejandro Martínez-CarrascoiD, Ying WangiD, Connor S. Dowd, Masahiro KanaiiD, Bram L. GorisseniD, Aymone Kouame, James Brogan, Bennett J. WaxseiD, Ryan SamarakooniD, Justin A. Cook, Jun Qian, Yu ZhouiD, Karmel W. ChoiiD, Melissa BasfordiD, Michael Lyons, Jodell E. LinderiD, Samantha StewartiD, Namrata GuptaiD, Patrick SchultziD, , Konrad J. KarczewskiiD
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.
- organism: human
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- research focus: fine-mapping
- approach: statistical model
- Citations
- 4
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