10.18710/VC2PSH Nielsen, Jonas B. Jonas B. Nielsen https://orcid.org/0000-0002-6654-2852 NTNU – Norwegian University of Science and Technology Willer, Cristen J. Cristen J. Willer https://orcid.org/0000-0001-5645-4966 University of Michigan DataverseNO 2021 Medicine, Health and Life Sciences Atrial fibrillation GWAS The Trøndelag Health Study (HUNT) Cardiac arrhythmia Ischemic heart failure deCODE The Michigan Genomics Initiative (MGI) DiscovEHR UK Biobank The AFGen Consortium NTNU – Norwegian University of Science and Technology University of Michigan NTNU – Norwegian University of Science and Technology NTNU – Norwegian University of Science and Technology Gabrielsen, Maiken E. Maiken E. Gabrielsen NTNU – Norwegian University of Science and Technology 2018-07-30 2021-06-01 2021-06-17 2023-09-28 Summary statistics (results) from GWAS analysis. 10.1038/S41588-018-0171-3 10.18710/VC2PSH/H3QF9Z 10.18710/VC2PSH/OPHTTA 2387197598 7164 text/plain text/plain 1.1 Creative Commons CC0 1.0 Universal Public Domain Dedication. To identify genetic variation underlying atrial fibrillation, the most common cardiac arrhythmia, we performed a genome-wide association study of >1,000,000 people, including 60,620 atrial fibrillation cases and 970,216 controls. We identified 142 independent risk variants at 111 loci and prioritized 151 functional candidate genes likely to be involved in atrial fibrillation. Many of the identified risk variants fall near genes where more deleterious mutations have been reported to cause serious heart defects in humans (GATA4, MYH6, NKX2-5, PITX2, TBX5)1, or near genes important for striated muscle function and integrity (for example, CFL2, MYH7, PKP2, RBM20, SGCG, SSPN). Pathway and functional enrichment analyses also suggested that many of the putative atrial fibrillation genes act via cardiac structural remodeling, potentially in the form of an ‘atrial cardiomyopathy’2, either during fetal heart development or as a response to stress in the adult heart. The data format is .tbl METAL, 2011-03-25 GCTA, 1.91.1 Plink, 1.9 SAIGE, 0.19 BOLT-LMM, 2.3.1 EPACTS, 3.3 Genome Analysis Toolkit, 3.4.0 DEPICT, 2014-07-21 GREGOR, 1.4.0 R software pSI package, 1.1 Philips TraceMasterVue ECG Management System R, 3.4.3 Python, 3.4.5 BAFRegress, 0.9.3 Illumina GenomeStudio, Module 1.9.4, algorithm GenTrain 2.0 LASER, 2.0 Minimac, 3 SQLite, 3 Norway, Trøndelag, Iceland United States, Michigan, United Kingdom