Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases.

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Bibliographic Details
Title: Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases.
Authors: Lassen FH; Centre for Human Genetics, University of Oxford, Oxford, UK., Kalantzis G; Wellcome Sanger Institute, Hinxton, UK., Eoli A; Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany; Windreich Department of Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Hill B; Centre for Human Genetics, University of Oxford, Oxford, UK., Sonehara K; Wellcome Sanger Institute, Hinxton, UK; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Namba S; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Wade I; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK., Hodgson S; Wolfson Institute of Population Health, Queen Mary University of London, London, UK., Zhou W; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Neale BM; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Karczewski KJ; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Okada Y; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan., van Heel DA; Blizard Institute, Queen Mary University of London, London, UK., Finer S; Wolfson Institute of Population Health, Queen Mary University of London, London, UK., Lindgren CM; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK; Ellison Institute of Technology, Oxford, UK; Department of Statistics, University of Oxford, Oxford, UK., Heyne HO; Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany; Windreich Department of Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Martin HC; Wellcome Sanger Institute, Hinxton, UK. Electronic address: hcm@sanger.ac.uk., Palmer DS; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Statistics, University of Oxford, Oxford, UK; The Pioneer Centre for SMARTbiomed, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK. Electronic address: duncan.palmer@stats.ox.ac.uk.
Corporate Authors: BioBank Japan Project, Genes & Health Research Team, BRaVa Consortium
Source: American journal of human genetics [Am J Hum Genet] 2026 Jun 04; Vol. 113 (6), pp. 1330-1346. Date of Electronic Publication: 2026 May 01.
Publication Type: Journal Article; Meta-Analysis
Journal Info: Publisher: Cell Press Country of Publication: United States NLM ID: 0370475 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1537-6605 (Electronic) Linking ISSN: 00029297 NLM ISO Abbreviation: Am J Hum Genet Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1537-6605
DOI:10.1016/j.ajhg.2026.04.005