{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Venkatesh SS"],"funding":["Eesti Teadusagentuur","BLRD VA","University of Leicester (College of Life Sciences) and Health Data Research UK","NICHD NIH HHS","Novo Nordisk UK Research Foundation","Novartis Foundation","Li Ka Shing Foundation","U.S. Department of Health & Human Services | National Institutes of Health (NIH)","Alan Turing Institute","RCUK | Engineering and Physical Sciences Research Council (EPSRC)","Eesti Teadusagentuur (Estonian Research Council)","National Institute for Health Research (NIHR)","Rhodes Scholarships","RCUK | Engineering and Physical Sciences Research Council","University of Leicester","Bill and Melinda Gates Foundation","Wellcome Trust","Clarendon Fund and the Medical Sciences Doctoral Training Centre at the University of Oxford","U.S. Department of Health & Human Services | National Institutes of Health"],"pagination":["5801"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11237142"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE "],"journal":["Nature communications"],"pubmed_title":["Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records."],"pmcid":["PMC11237142"],"funding_grant_id":["NIHR Oxford Biomedical Research Centre, Oxford","203141/Z/16/Z","PSG759","I01 BX004821","NIHR203311","I01 BX003340","INV-024200","P50 HD104224","Bayes4Health","1P50HD104224-01","221782/Z/20/Z"],"pubmed_authors":["Wilson P","Wittemans LBL","Ho YL","Nellaker C","Palmer DS","Vainik U","Lindgren CM","Ganjgahi H","Cho K","Sun YV","Million Veteran Program","Venkatesh SS","Estonian Biobank Research Team","Holmes C","Nicholson G","Hui Q","Esko T","Magi R","Metspalu A","Milani L","Nelis M","Coley K","Hudjashov G","Linchangco GV","Arumae K"],"additional_accession":[]},"is_claimable":false,"name":"Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.","description":"Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2026-06-01T07:34:40.286Z","creation":"2025-04-07T12:06:04.721Z"},"accession":"S-EPMC11237142","cross_references":{"pubmed":["38987242"],"doi":["10.1038/s41467-024-49998-0"]}}