{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,11,6]],"date-time":"2026-11-06T05:41:36Z","timestamp":1793943696921,"version":"4.8.0"},"posted":{"date-parts":[[2026,5,24]]},"group-title":"Genetic and Genomic Medicine","reference-count":109,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,5,24]],"date-time":"2026-05-24T00:00:00Z","timestamp":1779580800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,5,24]]},"abstract":"<jats:p>Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries.<\/jats:p>\n                <jats:p>We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis.<\/jats:p>\n                <jats:p>\n                  Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in\n                  <jats:italic>ANKRD12<\/jats:italic>\n                  implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in\n                  <jats:italic>NAA15<\/jats:italic>\n                  link protein acetylation processes to type 2 diabetes risk.\n                <\/jats:p>\n                <jats:p>BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.<\/jats:p>","DOI":"10.64898\/2026.05.21.26353759","type":"posted-content","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T01:45:12Z","timestamp":1779673512000},"source":"Crossref","is-referenced-by-count":1,"title":["The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0824-0047","authenticated-orcid":false,"given":"Duncan S","family":"Palmer","sequence":"first","affiliation":[{"name":"Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK"},{"name":"Department of Statistics, University of Oxford, Oxford, UK"},{"name":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"The Pioneer Centre for SMARTbiomed, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barney","family":"Hill","sequence":"additional","affiliation":[{"name":"Centre for Human Genetics, University of Oxford, Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sam","family":"Hodgson","sequence":"additional","affiliation":[{"name":"Wolfson Institute of Population Health, Queen Mary University of London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maarja","family":"J\u00f5eloo","sequence":"additional","affiliation":[{"name":"Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georgios","family":"Kalantzis","sequence":"additional","affiliation":[{"name":"Wellcome Sanger Institute, Hinxton, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Athanasios","family":"Kousathanas","sequence":"additional","affiliation":[{"name":"Genomics England, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoshi","family":"Koyama","sequence":"additional","affiliation":[{"name":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Personalized Medicine, Mass General Brigham, Boston, MA, USA"},{"name":"Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA"},{"name":"Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhan","family":"Lu","sequence":"additional","affiliation":[{"name":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA"},{"name":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinichi","family":"Namba","sequence":"additional","affiliation":[{"name":"Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"},{"name":"Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zachary B","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Division of Translational Medicine and Human Genetics, 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