Letter | Published:

Multi-ethnic genome-wide association study for atrial fibrillation

Nature Geneticsvolume 50pages12251233 (2018) | Download Citation

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Abstract

Atrial fibrillation (AF) affects more than 33 million individuals worldwide1 and has a complex heritability2. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

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Change history

  • 20 July 2018

    In the version of this article initially published, Supplementary Tables 1, 2, 6, 8, 10 and 19–22 and the Supplementary Note were omitted from the supplementary PDF. The supplementary PDF now includes these items.

References

  1. 1.

    Chugh, S. S. et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 study. Circulation 129, 837–847 (2014).

  2. 2.

    Lubitz, S. A. et al. Association between familial atrial fibrillation and risk of new-onset atrial fibrillation. JAMA 304, 2263–2269 (2010).

  3. 3.

    January, C. T. et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary. J. Am. Coll. Cardiol. 64, 2071–2104 (2014).

  4. 4.

    Benjamin, E. J. et al. Variants in ZFHX3 are associated with atrial fibrillation in individuals of European ancestry. Nat. Genet. 41, 879–881 (2009).

  5. 5.

    Ellinor, P. T. et al. Meta-analysis identifies six new susceptibility loci for atrial fibrillation. Nat. Genet. 44, 670–675 (2012).

  6. 6.

    Sinner, M. F. et al. Integrating genetic, transcriptional, and functional analyses to identify 5 novel genes for atrial fibrillation. Circulation 130, 1225–1235 (2014).

  7. 7.

    Ellinor, P. T. et al. Common variants in KCNN3 are associated with lone atrial fibrillation. Nat. Genet. 42, 240–244 (2010).

  8. 8.

    Christophersen, I. E. et al. Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation. Nat. Genet. 49, 946–952 (2017).

  9. 9.

    Low, S.-K. et al. Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. Nat. Genet. 49, 953–958 (2017).

  10. 10.

    Weng, L.-C. et al. Heritability of atrial fibrillation. Circ. Cardiovasc. Genet. 10, e001838 (2017).

  11. 11.

    Klarin, D. et al. Genetic analysis in UK Biobank links insulin resistance and transendothelial migration pathways to coronary artery disease. Nat. Genet. 49, 1392–1397 (2017).

  12. 12.

    Barbeira, A. N. et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat. Commun. 9, 1825 (2018).

  13. 13.

    Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).

  14. 14.

    Lu, X. et al. Genome-wide association study in Chinese identifies novel loci for blood pressure and hypertension. Hum. Mol. Genet. 24, 865–74 (2015).

  15. 15.

    Nielsen, J. B. et al. Genome-wide association study of 1 million people identifies 111 loci for atrial fibrillation. Preprint at https://www.biorxiv.org/content/early/2018/01/04/242149 (2018).

  16. 16.

    Sinner, M. F. et al. The non-synonymous coding IKr-channel variant KCNH2-K897T is associated with atrial fibrillation: results from a systematic candidate gene-based analysis of KCNH2 (HERG). Eur. Heart J. 29, 907–914 (2008).

  17. 17.

    Olson, T. M. et al. Sodium channel mutations and susceptibility to heart failure and atrial fibrillation. JAMA 293, 447–454 (2005).

  18. 18.

    McNair, W. P. et al. SCN5A mutation associated with dilated cardiomyopathy, conduction disorder, and arrhythmia. Circulation 110, 2163–2167 (2004).

  19. 19.

    van Weerd, J. H. et al. A large permissive regulatory domain exclusively controls Tbx3 expression in the cardiac conduction system. Circ. Res. 115, 432–441 (2014).

  20. 20.

    Schott, J. J. et al. Congenital heart disease caused by mutations in the transcription factor NKX2-5. Science 281, 108–101 (1998).

  21. 21.

    den Hoed, M. et al. Identification of heart rate–associated loci and their effects on cardiac conduction and rhythm disorders. Nat. Genet. 45, 621–631 (2013).

  22. 22.

    Kirchhof, P. et al. PITX2c is expressed in the adult left atrium, and reducing Pitx2c expression promotes atrial fibrillation inducibility and complex changes in gene expression. Circ. Cardiovasc. Genet. 4, 123–133 (2011).

  23. 23.

    Wang, J. et al. Pitx2 prevents susceptibility to atrial arrhythmias by inhibiting left-sided pacemaker specification. Proc. Natl. Acad. Sci. USA 107, 9753–9758 (2010).

  24. 24.

    Syeda, F. et al. PITX2 modulates atrial membrane potential and the antiarrhythmic effects of sodium-channel blockers. J. Am. Coll. Cardiol. 68, 1881–1894 (2016).

  25. 25.

    Nadadur, R. D. et al. Pitx2 modulates a Tbx5-dependent gene regulatory network to maintain atrial rhythm. Sci. Transl. Med. 8, 354ra115 (2016).

  26. 26.

    Tucker, N. R. et al. Diminished PRRX1 expression is associated with increased risk of atrial fibrillation and shortening of the cardiac action potential. Circ. Cardiovasc. Genet. 10, e001902 (2017).

  27. 27.

    Postma, A. V. et al. A gain-of-function TBX5 mutation is associated with atypical Holt–Oram syndrome and paroxysmal atrial fibrillation. Circ. Res. 102, 1433–1442 (2008).

  28. 28.

    Lahat, H. et al. A missense mutation in a highly conserved region of CASQ2 is associated with autosomal recessive catecholamine-induced polymorphic ventricular tachycardia in Bedouin families from Israel. Am. J. Hum. Genet. 69, 1378–1384 (2001).

  29. 29.

    Lahat, H. et al. Autosomal recessive catecholamine- or exercise-induced polymorphic ventricular tachycardia: clinical features and assignment of the disease gene to chromosome 1p13-21. Circulation 103, 2822–2827 (2001).

  30. 30.

    Corrado, D., Link, M. S. & Calkins, H. Arrhythmogenic right ventricular cardiomyopathy. N. Engl. J. Med. 376, 61–72 (2017).

  31. 31.

    Gerull, B. et al. Mutations in the desmosomal protein plakophilin-2 are common in arrhythmogenic right ventricular cardiomyopathy. Nat. Genet. 36, 1162–1164 (2004).

  32. 32.

    Ackerman, M. J. et al. HRS/EHRA expert consensus statement on the state of genetic testing for the channelopathies and cardiomyopathies. Heart Rhythm 8, 1308–1339 (2011).

  33. 33.

    Weng, L.-C. et al. Genetic predisposition, clinical risk factor burden, and lifetime risk of atrial fibrillation. Circulation 137, 1027–1038 (2017).

  34. 34.

    Korn, J. M. et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253–1260 (2008).

  35. 35.

    Goldstein, J. I. et al. zCall: a rare variant caller for array-based genotyping. Bioinformatics 28, 2543–2545 (2012).

  36. 36.

    Pulit, S. L. et al. Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study. Lancet Neurol. 15, 174–184 (2016).

  37. 37.

    Bycroft, C. et al. Genome-wide genetic data on ~500,000 UK Biobank participants. Preprint at https://www.biorxiv.org/content/early/2017/07/20/166298 (2017).

  38. 38.

    The Haplotype Reference Consortium et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).

  39. 39.

    Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).

  40. 40.

    Auton, A. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

  41. 41.

    Francioli, L. C. et al. Whole-genome sequence variation, population structure and demographic history of the Dutch population. Nat. Genet. 46, 818–825 (2014).

  42. 42.

    Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).

  43. 43.

    Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

  44. 44.

    Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

  45. 45.

    Bellenguez, C., Strange, A., Freeman, C., Donnelly, P. & Spencer, C. C. A. A robust clustering algorithm for identifying problematic samples in genome-wide association studies. Bioinformatics 28, 134–135 (2012).

  46. 46.

    Aulchenko, Y. S., Struchalin, M. V. & van Duijn, C. M. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11, 134 (2010).

  47. 47.

    Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

  48. 48.

    Chanda, P., Huang, H., Arking, D. E. & Bader, J. S. Fast association tests for genes with FAST. PLoS One 8, e68585 (2013).

  49. 49.

    R Core Team. R: A Language and Environment for Statistical Computing. http://www.r-project.org/ (2015).

  50. 50.

    Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

  51. 51.

    Fadista, J., Manning, A. K., Florez, J. C. & Groop, L. The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants. Eur. J. Hum. Genet. 24, 1202–1205 (2016).

  52. 52.

    Higgins, J. P. T., Thompson, S. G., Deeks, J. J. & Altman, D. G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).

  53. 53.

    McLaren, W. et al. The Ensembl Variant Effect Predictor. Genome Biol. 17, 122 (2016).

  54. 54.

    Schwarz, J. M., Rödelsperger, C., Schuelke, M. & Seelow, D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat. Methods 7, 575–576 (2010).

  55. 55.

    Kumar, P., Henikoff, S. & Ng, P. C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 4, 1073–1081 (2009).

  56. 56.

    Chun, S. & Fay, J. C. Identification of deleterious mutations within three human genomes. Genome Res. 19, 1553–1561 (2009).

  57. 57.

    Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

  58. 58.

    Ernst, J. & Kellis, M. Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues. Nat. Biotechnol. 33, 364–376 (2015).

  59. 59.

    Ward, L. D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930–D934 (2012).

  60. 60.

    Pers, T. H., Timshel, P. & Hirschhorn, J. N. SNPsnap: a Web-based tool for identification and annotation of matched SNPs. Bioinformatics 31, 418–420 (2015).

  61. 61.

    Fay, M. P. & Shaw, P. A. Exact and asymptotic weighted logrank tests for interval censored data: the interval R package. J. Stat. Softw. 36, 1–34 (2010).

  62. 62.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

  63. 63.

    Harrow, J. et al. GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

  64. 64.

    Delaneau, O. et al. A complete tool set for molecular QTL discovery and analysis. Nat. Commun. 8, 15452 (2017).

  65. 65.

    GTEx Consortium. The Genotype–Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

  66. 66.

    Aguet, F. et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

  67. 67.

    Gamazon, E. R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091–1098 (2015).

  68. 68.

    Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).

  69. 69.

    Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).

  70. 70.

    Segrè, A. V. et al. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).

  71. 71.

    Welter, D. et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42, D1001–D1006 (2014).

  72. 72.

    MacArthur, J. et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017).

  73. 73.

    Loh, P.-R. et al. Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis. Nat. Genet. 47, 1385–1392 (2015).

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Acknowledgements

A full list of acknowledgments appears in the Supplementary Notes.

Author information

Author notes

  1. These authors contributed equally: Carolina Roselli, Mark D. Chaffin, Lu-Chen Weng.

  2. These authors jointly supervised this work: Steven A. Lubitz, Kathryn L. Lunetta, Patrick T. Ellinor.

Affiliations

  1. Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA

    • Carolina Roselli
    • , Mark D. Chaffin
    • , Lu-Chen Weng
    • , Christopher D. Anderson
    • , Krishna G. Aragam
    • , Daniel I. Chasman
    • , Seung Hoan Choi
    • , Ingrid E. Christophersen
    • , Brian R. Daniels
    • , Tonu Esko
    • , Namrata Gupta
    • , Sekar Kathiresan
    • , Lauren Margolin
    • , Christopher Newton-Cheh
    • , Sara L. Pulit
    • , Jonathan Rosand
    • , Natalia Rost
    • , J. Gustav Smith
    • , Nathan R. Tucker
    • , Steven A. Lubitz
    •  & Patrick T. Ellinor
  2. Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA

    • Lu-Chen Weng
    • , Ingrid E. Christophersen
    • , Paul L. Huang
    • , Nathan R. Tucker
    • , Steven A. Lubitz
    •  & Patrick T. Ellinor
  3. University Hospital Basel, Basel, Switzerland

    • Stefanie Aeschbacher
    •  & David Conen
  4. Cardiovascular Research Institute Basel, Basel, Switzerland

    • Stefanie Aeschbacher
    •  & David Conen
  5. Laboratory for Molecular Cardiology, The Heart Centre, Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark

    • Gustav Ahlberg
    • , Morten S. Olesen
    • , Lena Refsgaard
    • , Jesper H. Svendsen
    •  & Peter E. Weeke
  6. The Danish National Research Foundation Centre for Cardiac Arrhythmia, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark

    • Gustav Ahlberg
    • , Morten S. Olesen
    •  & Lena Refsgaard
  7. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

    • Gustav Ahlberg
    • , Morten S. Olesen
    • , Lena Refsgaard
    •  & Jesper H. Svendsen
  8. Divisions of Preventive and Cardiovascular Medicine, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA

    • Christine M. Albert
    •  & Paul M. Ridker
  9. Department of Clinical Sciences, Lund University, Malmo, Sweden

    • Peter Almgren
    •  & Marju Orho-Melander
  10. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    • Alvaro Alonso
  11. Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA

    • Christopher D. Anderson
    • , Krishna G. Aragam
    • , Sekar Kathiresan
    • , Christopher Newton-Cheh
    • , Jonathan Rosand
    •  & Michael A. Rosenberg
  12. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    • Dan E. Arking
  13. Departments of Cardiovascular Medicine, Cellular and Molecular Medicine, Molecular Cardiology, and Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA

    • John Barnard
    • , Mina K. Chung
    • , Jonathan D. Smith
    • , Han Sun
    •  & David R. Van Wagoner
  14. Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA

    • Traci M. Bartz
  15. NHLBI and Boston University’s Framingham Heart Study, Framingham, MA, USA

    • Emelia J. Benjamin
    • , Honghuang Lin
    •  & Kathryn L. Lunetta
  16. Department of Medicine, Boston University School of Medicine, Boston, MA, USA

    • Emelia J. Benjamin
    •  & Honghuang Lin
  17. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA

    • Emelia J. Benjamin
  18. Predoctoral Training Program in Human Genetics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    • Nathan A. Bihlmeyer
  19. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA

    • Joshua C. Bis
    • , Jennifer A. Brody
    • , Rozenn N. Lemaitre
    •  & Kerri L. Wiggins
  20. Division of Cardiology, Emory University and Atlanta VA Medical Center, Atlanta, GA, USA

    • Heather L. Bloom
  21. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA

    • Eric Boerwinkle
  22. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • Erwin B. Bottinger
    • , Ruth J. F. Loos
    • , Yingchang Lu
    •  & Claudia Schurman
  23. Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • Erwin B. Bottinger
  24. Johns Hopkins University, Baltimore, MD, USA

    • Hugh Calkins
    •  & Esra Gucuk Ipek
  25. Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK

    • Archie Campbell
    •  & David Porteous
  26. Penn Cardiovascular Institute and Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Thomas P. Cappola
    • , Kenneth B. Margulies
    •  & Michael P. Morley
  27. Intermountain Heart Institute, Intermountain Medical Center, Murray, UT, USA

    • John Carlquist
    • , Michael J. Cutler
    •  & Stacey Knight
  28. Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA

    • John Carlquist
  29. Divisions of Preventive Medicine and Genetics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA

    • Daniel I. Chasman
  30. Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA

    • Lin Y. Chen
  31. Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA

    • Yii-Der Ida Chen
    • , Xiuqing Guo
    • , Henry J. Lin
    • , Kent D. Taylor
    •  & Jie Yao
  32. Seoul National University Hospital, Seoul, Korea

    • Eue-Keun Choi
  33. Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Drammen, Norway

    • Ingrid E. Christophersen
    •  & Arnljot Tveit
  34. Baltimore Veterans Affairs Medical Center, Department of Neurology, Baltimore, MD, USA

    • John W. Cole
  35. University of Maryland School of Medicine, Department of Neurology, Baltimore, MD, USA

    • John W. Cole
  36. Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada

    • David Conen
    • , Guillaume Paré
    •  & Sébastien Thériault
  37. Department of Biostatistics, University of Liverpool, Liverpool, UK

    • James Cook
    •  & Andrew P. Morris
  38. Maastricht University Medical Center+ and Cardiovascular Research Institute Maastricht, Department of Cardiology, Maastricht, The Netherlands

    • Harry J. Crijns
    • , Elton A. Dudink
    • , Bas L. Kietselaer
    •  & Bob Weijs
  39. Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Scott M. Damrauer
  40. Department of Surgery, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA

    • Scott M. Damrauer
  41. University of Illinois Chicago, Chicago, IL, USA

    • Dawood Darbar
  42. Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany

    • Graciela Delgado
    •  & Marcus E. Kleber
  43. Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    • Joshua C. Denny
    • , Jay A. Montgomery
    • , Dan M. Roden
    • , Christian Shaffer
    • , M. Benjamin Shoemaker
    • , Peter E. Weeke
    • , Quinn S. Wells
    •  & Zachary T. Yoneda
  44. Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany

    • Martin Dichgans
    •  & Rainer Malik
  45. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    • Martin Dichgans
  46. German Center for Neurodegenerative Diseases (DZNE), Munich, Germany

    • Martin Dichgans
  47. Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany

    • Marcus Dörr
    •  & Stephan B. Felix
  48. DZHK (German Centre for Cardiovascular Research), partner site: Greifswald, Greifswald, Germany

    • Marcus Dörr
    • , Stephan B. Felix
    • , Alexander Teumer
    • , Uwe Völker
    •  & Stefan Weiss
  49. Cardiovascular Division and Lillehei Heart Institute, University of Minnesota, Minneapolis, MN, USA

    • Samuel C. Dudley
  50. University of Massachusetts Medical School Worcester, Worcester, MA, USA

    • Nada Esa
    • , David D. McManus
    •  & Kahraman Tanriverdi
  51. Estonian Genome Center, University of Tartu, Tartu, Estonia

    • Tonu Esko
    •  & Maris Teder-Laving
  52. Heart Center, Department of Cardiology, Tampere University Hospital, Finland and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland

    • Markku Eskola
    • , Jussi Hernesniemi
    •  & Kjell Nikus
  53. Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia

    • Diane Fatkin
    •  & Renee Johnson
  54. St Vincent’s Hospital, Darlinghurst, New South Wales, Australia

    • Diane Fatkin
  55. Faculty of Medicine, University of New South Wales, Kensington, New South Wales, Australia

    • Diane Fatkin
  56. Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK

    • Ian Ford
  57. Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands

    • Oscar H. Franco
    • , Albert Hofman
    • , Maryam Kavousi
    •  & Maartje N. Niemeijer
  58. Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

    • Bastiaan Geelhoed
    • , Michiel Rienstra
    • , Joylene E. Siland
    • , Pim Van Der Harst
    • , Isabelle C. Van Gelder
    •  & Niek Verweij
  59. Dept. of Neuroscience, Saint Francis Medical Center, Trenton, NJ, USA

    • Raji P. Grewal
  60. School of Health and Medical Sciences, Seton Hall University, South Orange, NJ, USA

    • Raji P. Grewal
  61. Icelandic Heart Association, Kopavogur, Iceland

    • Vilmundur Gudnason
    •  & Albert V. Smith
  62. Faculty of Medicine, University of Iceland, Reykavik, Iceland

    • Vilmundur Gudnason
    •  & Albert V. Smith
  63. Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden

    • Stefan Gustafsson
    •  & Erik Ingelsson
  64. Division of Cardiovascular Medicine and Abboud Cardiovascular Research Center, University of Iowa, Iowa City, IA, USA

    • Rebecca Gutmann
    •  & Barry London
  65. Cardiovascular Genetics and Genomics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden

    • Anders Hamsten
  66. Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, MD, USA

    • Tamara B. Harris
    •  & Lenore J. Launer
  67. MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK

    • Caroline Hayward
    •  & Jennifer Huffman
  68. Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA

    • Susan R. Heckbert
    •  & Nicholas L. Smith
  69. Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

    • Susan R. Heckbert
    • , Bruce M. Psaty
    •  & Nicholas L. Smith
  70. Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center–Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland

    • Jussi Hernesniemi
    • , Terho Lehtimäki
    • , Leo-Pekka Lyytikäinen
    •  & Ilkka Seppälä
  71. Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK

    • Lynne J. Hocking
  72. Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo, Brazil

    • Andrea R. V. R. Horimoto
    •  & Jose E. Krieger
  73. Boston VA Research Institute, Inc., Boston, MA, USA

    • Jie Huang
  74. Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    • Erik Ingelsson
  75. Laboratory for Cardiovascular Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    • Kaoru Ito
  76. Department of Neurology, Neurovascular Research Group IMIM–Hospital del Mar (Institut Hospital del Mar d’Investigacions Médiques), Barcelona, Spain

    • Jordi Jimenez-Conde
  77. Universitat Autònoma de Barcelona, Medicine Department, Barcelona, Spain

    • Jordi Jimenez-Conde
  78. Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands

    • J. Wouter Jukema
    •  & Stella Trompet
  79. Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands

    • J. Wouter Jukema
  80. Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands

    • J. Wouter Jukema
  81. Department of Medicine I, University Hospital Munich, Ludwig-Maximilians-University, Munich, Germany

    • Stefan Kääb
    • , Martina Müller-Nurasyid
    • , Benjamin Neumann
    • , Katharina Schramm
    •  & Moritz F. Sinner
  82. DZHK (German Centre for Cardiovascular Research), partner site: Munich Heart Alliance, Munich, Germany

    • Stefan Kääb
    • , Adnan Kastrati
    • , Martina Müller-Nurasyid
    • , Heribert Schunkert
    •  & Moritz F. Sinner
  83. Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center–Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland

    • Mika Kähönen
  84. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    • Yoichiro Kamatani
    •  & Siew-Kee Low
  85. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA

    • John P. Kane
    •  & Clive R. Pullinger
  86. Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany

    • Adnan Kastrati
    • , Thorsten Kessler
    • , Heribert Schunkert
    •  & Lingyao Zeng
  87. Department of Neurology, Medical University of Graz, Graz, Austria

    • Petra Katschnig-Winter
  88. Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK

    • Paulus Kirchhof
  89. Sandwell and West Birmingham Hospitals NHS Trust and University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK

    • Paulus Kirchhof
  90. AFNET, Muenster, Germany

    • Paulus Kirchhof
  91. Department of Medicine, University of Utah, Salt Lake City, UT, USA

    • Stacey Knight
  92. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    • Michiaki Kubo
  93. Department of Cardio-Thoracic Surgery, Heart Center, Tampere University Hospital, and Finnish Cardiovascular Research Center–Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland

    • Jari Laurikka
  94. Dept. Disease Genomics, Bayer, Wuppertal, Germany

    • Kirsten Leineweber
  95. Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA

    • Man Li
  96. Division of Nephrology & Hypertension, Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA

    • Man Li
  97. Korea University Guro Hospital, Seoul, Korea

    • Hong Euy Lim
  98. Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden

    • Lars Lind
  99. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK

    • Cecilia M. Lindgren
    •  & Anubha Mahajan
  100. Transplantation Laboratory, Medicum, University of Helsinki, Helsinki, Finland

    • Marja-Liisa Lokki
    •  & Efthymia Vlachopoulou
  101. The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Ruth J. F. Loos
    • , Yingchang Lu
    •  & Claudia Schurman
  102. The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • Ruth J. F. Loos
  103. Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK

    • Peter W. Macfarlane
  104. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    • Patrik K. Magnusson
    •  & Nancy L. Pedersen
  105. Heart Institute, University of São Paulo, São Paulo, Brazil

    • Alfredo J. Mansur
  106. Division of Cardiology, University of California, San Francisco, San Francisco, California, USA

    • Gregory M. Marcus
  107. Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria

    • Winfried März
  108. Synlab Academy, Synlab Services GmbH, Mannheim, Germany

    • Winfried März
  109. Department of Internal Medicine, Clinical Sciences, Lund University, Malmo, Sweden

    • Olle Melander
  110. Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX, USA

    • Sanghamitra Mohanty
    •  & Andrea Natale
  111. Dell Medical School, Austin, TX, USA

    • Sanghamitra Mohanty
    •  & Andrea Natale
  112. Institute of Genetic Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany

    • Martina Müller-Nurasyid
    •  & Katharina Schramm
  113. University of Pennsylvania, Philadelphia, PA, USA

    • Saman Nazarian
  114. Department of Clinical Sciences, Lund University and Skåne University Hospital, Malmo, Sweden

    • Peter Nilsson
  115. Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands

    • Raymond Noordam
    •  & Stella Trompet
  116. Atrial Fibrillation NETwork, Muenster, Germany

    • Heidi Oellers
  117. Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK

    • Sandosh Padmanabhan
  118. Yonsei University Health System, Seoul, Korea

    • Hui-Nam Pak
    •  & Pil-Sung Yang
  119. Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada

    • Guillaume Paré
    •  & Sébastien Thériault
  120. Department of Neurology, Faculty of Medicine, Jagiellonian University Medical College, Krakow, Poland

    • Joanna Pera
    •  & Agnieszka Slowik
  121. Laboratory of Genetics and Molecular Biology, Heart Institute, University of São Paulo, São Paulo, Brazil

    • Alexandre Pereira
  122. Department of Genetics, Harvard Medical School, Boston, MA, USA

    • Alexandre Pereira
  123. Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA

    • Bruce M. Psaty
  124. Department of Genetics, Center for Molecular Medicine, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands

    • Sara L. Pulit
  125. Li Ka Shing Center for Health Information and Discovery, Big Data Institute, Oxford University, Oxford, UK

    • Sara L. Pulit
  126. Division of Cardiovascular Medicine, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA

    • Daniel J. Rader
  127. Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain

    • Marta Ribasés
  128. Department of Psychiatry, Hospital Universitari Vall d’Hebron, Barcelona, Spain

    • Marta Ribasés
  129. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain

    • Marta Ribasés
  130. University Institute of Clinical Chemistry, University of Bern, Bern, Switzerland

    • Lorenz Risch
  131. Labormedizinisches Zentrum Dr. Risch, Schaan, Liechtenstein

    • Lorenz Risch
  132. University of Colorado School of Medicine, Aurora, CO, USA

    • Michael A. Rosenberg
  133. J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA

    • Natalia Rost
  134. Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA

    • Jerome I. Rotter
  135. Division of Cardiology, University of Pittsburgh, Pittsburgh, PA, USA

    • Samir Saba
    •  & Alaa A. Shalaby
  136. Division of Cardiology, University of Alberta, Edmonton, Alberta, Canada

    • Roopinder K. Sandhu
  137. Department of General and Interventional Cardiology, University Heart Centre Hamburg, Hamburg, Germany

    • Renate B. Schnabel
    •  & Tanja Zeller
  138. DZHK (German Centre for Cardiovascular Research), partner site: Hamburg/Kiel/Lübeck, Hamburg, Germany

    • Renate B. Schnabel
    •  & Tanja Zeller
  139. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • Stuart A. Scott
  140. Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA

    • Svati Shah
    •  & Albert Sun
  141. Cardiology Division, Pittsburgh VA Healthcare System, Pittsburgh, Pennsylvania, USA

    • Alaa A. Shalaby
  142. Korea University Anam Hospital, Seoul, Korea

    • Jaemin Shim
  143. Heart and Lung Center HUS, Helsinki University Central Hospital, Helsinki, Finland

    • Juha Sinisalo
  144. Division of Population Health Sciences, University of Dundee, Dundee, UK

    • Blair H. Smith
  145. Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden

    • J. Gustav Smith
  146. Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston Salem, NC, USA

    • Elsayed Z. Soliman
  147. Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, USA

    • Nona Sotoodehnia
  148. Department of Epidemiology and Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands

    • Bruno H. Stricker
    •  & Andre G. Uitterlinden
  149. Inspectorate of Health Care, Utrecht, The Netherlands

    • Bruno H. Stricker
  150. Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University Graduate School of Medical and Dental Sciences, Tokyo, Japan

    • Toshihiro Tanaka
  151. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany

    • Alexander Teumer
  152. Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    • Arnljot Tveit
  153. Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany

    • Uwe Völker
    •  & Stefan Weiss
  154. Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

    • Biqi Wang
    •  & Kathryn L. Lunetta
  155. Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, USA

    • Raul Weiss
  156. Division of Cardiology, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada

    • Jorge A. Wong
  157. University of Cincinnati College of Medicine, Cincinnati, OH, USA

    • Daniel Woo
  158. Departments of Neurology and Public Health Science, University of Virginia Health System, Charlottesville, VA, USA

    • Bradford B. Worrall
  159. Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, USA

    • Steven A. Lubitz
    •  & Patrick T. Ellinor

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Contributions

C.R., M.D.C., E.J.B., K.L.L., S.A.L., P.T.E. and H.L. drafted and finalized the manuscript. H.J.C., E.A.D., B.L.K., B. Weijs, S. Kääb, M.M.-N., B.N., K.S., M.F.S., J.L., A.A., L.Y.C., K.L., S.A., D.C., G.P., L. Risch, S. Thériault, T.T., C. Schurman, S.A.S., J.C.D., D.M.R., Q.S.W., C.R., M.D.C., K.G.A., B.R.D., N.G., S. Kathiresan, L.M., P.L.H., J.B., M.K.C., J.D.S., H. Sun, D.R.V.W., T.M.B., J.C.B., J.A.B., G.A., M.S.O., L. Refsgaard, J.H.S., D.F., R.J., S. Shah, P.K., R.B.S., T.E., M.T.-L., E.J.B., B. Wang, K.L.L., M. Kähönen, T.L., I.E.C., I.C.V.G., B.G., M. Rienstra, J.E.S., P.V.D.H., N.V., H.L.B., S.C.D., R.G., B.L., S. Saba, A.A.S., R.W., H.C., R.N.L., N.L.S., K.L.W., S.R.H., B.M.P., N.S., J. Carlquist, M.J.C., S. Knight, M.E.K., W.M., P.A., O.M., M.O.-M., X.G., H.J.L., J.I.R., K.D.T., S.H.C., N.R.T., S.A.L., P.T.E., C.N.-C., M.A.R., C.D.A., P.N., J.J.G.S., H. Schunkert, T.P.C., K.B.M., I.F., J.J.W.J., P.W.M., R.N., S. Trompet, O.H.F., A. Hofman, M. Kavousi, M.N.N., B.H. Stricker, A.G.U., R.P.G., J.J.-C., S.L.P., S.M., A. Hamsten, J.P.K., G.M.M., C.R.P., A.P.M., S.G., E. Ingelsson, H.L., D.D., J.A.M., M.M.B.S., Z.T.Y., C. Shaffer, P.E.W., C.M.A., D.I.C., R.K.S., J.W., M. Dichgans and R.M. contributed to and revised the manuscript. H.J.C., E.A.D., B.L.K., B. Weijs, S. Kääb, M.M.-N., B.N., K.S., M.F.S., V.G., T.B.H., L.J.L., A.V.S., M.E., J. Hernesniemi, J.L., I.S., A.A., D.E.A., N.A.B., E.B., L.Y.C., M.L., E.Z.S., S.A., D.C., G.P., L. Risch, S. Thériault, K.I., Y.K., M. Kubo, S.-K.L., T.T., E.B.B., R.J.F.L., Y.L., C. Schurman, S.A.S., J.C.D., D.M.R., Q.S.W., C.R., M.D.C., L.-C.W., K.G.A., N.G., S. Kathiresan, L.M., P.L.H., J.B., M.K.C., J.D.S., H. Sun, D.R.V.W., T.M.B., J.C.B., J.A.B., M.-L.L., J. Sinisalo, E.V., G.A., M.S.O., L. Refsgaard, J.H.S., D.F., R.J., A. Sun, P.K., H.O., R.B.S., T.Z., T.E., M.T.-L., E.J.B., B. Wang, K.L.L., M. Kähönen, T.L., L.-P.L., K.N., I.E.C., A. Tveit, B.G., J.E.S., N.V., H.L.B., S.C.D., R.G., B.L., S. Saba, A.A.S., R.W., A.C., C.H., L.J.H., J. Huffman, S.P., D.P., B.H. Smith, H.C., E. Ipek, S.N., R.N.L., N.L.S., K.L.W., S.R.H., B.M.P., N.S., J. Carlquist, M.J.C., S. Knight, E.-K.C., H.E.L., H.-N.P., J. Shim, P.-S.Y., G.D., J. Huang, M.E.K., P.A., O.M., M.O.-M., Y.-D.C., X.G., K.D.T., J.Y., S.A.L., P.T.E., C.N.-C., M.A.R., J.R., N.R., C.D.A., P.N., J.J.G.S., A.K., T.K., H. Schunkert, L.Z., T.P.C., S.M.D., K.B.M., M.P.M., D.J.R., I.F., J.J.W.J., S. Trompet, O.H.F., A. Hofman, M. Kavousi, M.N.N., B.H. Stricker, A.G.U., M. Dörr, S.B.F., A. Teumer, U.V., S.W., J.W.C., R.P.G., J.J.-C., P.K.-W., J.P., S.L.P., M. Ribasés, A. Slowik, D.W., B.B.W., A.R.V.R.H., J.E.K., A.J.M., A.P., S.M., A.N., A. Hamsten, P.K.M., N.L.P., J.P.K., G.M.M., C.R.P., J. Cook, L.L., C.M.L., A.M., A.P.M., S.G., E. Ingelsson, N.E., K.T., H.L., D.D.M., D.D., J.A.M., M.M.B.S., Z.T.Y., C. Shaffer, P.E.W., C.M.A., D.I.C., P.M.R., M. Dichgans and R.M. contributed to study-specific GWAS by providing phenotype data or performing data analyses. C.R., M.D.C. and S.L.P. performed meta-analyses. N.R.T., P.T.E., T.P.C., K.B.M., M.P.M. and H.L. contributed samples sequencing or performed left atrial eQTL analyses. C.R., M.D.C., L.-C.W., K.L.L., S.H.C., N.R.T. and H.L. performed downstream analyses. K.I., T.T., K.L.L., S.R.H., S.A.L. and P.T.E. conceived designed and supervised the overall project.

Competing interests

P.T.E is the PI on a grant from Bayer to the Broad Institute focused on the genetics and therapeutics of AF. B.M.P. serves on the DSMB of a clinical trial funded by Zoll LifeCor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. P.K. receives research support from the European Union, the British Heart Foundation, the Leducq Foundation, the Medical Research Council (UK) and the German Centre for Cardiovascular Research, and from several drug and device companies active in AF, and has received honoraria from several such companies. P.K. is also listed as an inventor on two patents held by University of Birmingham (Atrial Fibrillation Therapy WO 2015140571, Markers for Atrial Fibrillation WO 2016012783). K.L. is an employee of Bayer. The genotyping of participants in the Broad AF study and the expression analysis of LA tissue samples were supported by a grant from Bayer to the Broad Institute. S.N. is a consultant to Biosense Webster, Siemens and Cardiosolv. S.N. also receives research grants from NIH/NHLBI, Siemens, Biosense Webster and Imricor. S. Kathiresan has received grant support from Bayer and Amarin; holds equity in San Therapeutics and Catabasis; and has received personal fees for participation in scientific advisory boards for Catabasis, Regeneron Genetics Center, Merck, Celera, Genomics PLC, Corvidia Therapeutics and Novo Ventures. S. Kathiresan also received personal fees for consulting services from Novartis, AstraZeneca, Alnylam, Eli Lilly Company, Leerink Partners, Merck, Noble Insights, Bayer, Ionis Pharmaceuticals, Novo Ventures, Haug Partners LLC and Genetic Modifiers Newco, Inc. S.A.L. receives sponsored research support from Bristol Myers Squibb, Bayer, Biotronik and Boehringer Ingelheim, and has consulted for St. Jude Medical/Abbott and Quest Diagnostics. The remaining authors have no disclosures.

Corresponding author

Correspondence to Patrick T. Ellinor.

Integrated Supplementary Information

  1. Supplementary Figure 1 Quantile–quantile plot of combined ancestry meta-analysis.

    Quantile–quantile plot of combined ancestry meta-analysis for n = 12,149,979 included variants and λGC = 1.0948.

  2. Supplementary Figure 2 Venn diagram for genes near sentinel variants from combined ancestry meta-analysis within enriched gene sets, by functional groups.

    The Venn diagram shows genes that are within enriched gene set from the gene set enrichment analysis and within 500 kb of a sentinel variant. The genes were manually grouped into functional categories based on their corresponding gene sets. The diagram shows the overlap between the genes and the functional categories.

  3. Supplementary Figure 3 Manhattan plot of European-ancestry meta-analysis.

    The plot shows novel (red and purple) and known (blue) genetic loci associated with AF at a significance level of P < 1 × 10–8 (dotted line) for the European-ancestry meta-analysis (n = 537,409). The significance level accounts for multiple testing of independent variants with MAF ≥0.1% using a Bonferroni correction. P values (two-sided) were derived from a meta-analysis using a fixed-effects model with an inverse-variance-weighted approach. Loci in purple did not reach genome-wide significance in the combined ancestry meta-analysis. Gene labels correspond to the nearest gene(s). The y axis has a break between –log10 (P) of 25 and 400 to emphasize the novel loci.

  4. Supplementary Figure 4 Quantile–quantile plot of European-ancestry meta-analysis.

    Quantile–quantile plot of European-ancestry meta-analysis for n = 9,362,422 included variants and λGC = 1.1194.

  5. Supplementary Figure 5 Manhattan plot of African-American meta-analysis.

    The plot shows known (blue) genetic loci associated with AF at a significance level of P < 1 × 10–8 (dotted line), for the African-American-ancestry meta-analysis (n = 8,967). The significance level accounts for multiple testing of independent variants with MAF ≥ 0.1% using a Bonferroni correction. P values (two-sided) were derived from a meta-analysis using a fixed-effects model with an inverse-variance-weighted approach. The gene label corresponds to the nearest gene.

  6. Supplementary Figure 6 Quantile–quantile plot of African-American-ancestry meta-analysis.

    Quantile–quantile plot of African-American-ancestry meta-analysis for n = 8,640,046 included variants and λGC = 0.997.

  7. Supplementary Figure 7 Regional plots for 4q25 for European, Japanese and African American ancestry and pairwise LD between sentinel variants at 4q25.

    ac, Regional plots of 4q25 for European-ancestry results (a, n = 537,409), Japanese-ancestry results (b, n = 36,792) and African-American-ancestry results (c, n = 8,967). LD is shown based on the 1000 Genomes phase 1 v3 reference, using the populations EUR (a), ASN (b) and AFR (c). d, Pairwise LD (r2) for the sentinel variants based on the LD from the 1000 Genomes phase 1 v3 reference for EUR (n = 379), ASN (n = 286) and AFR (n = 246) ancestry. 1000G, 1000 Genomes; AA, African American; AFR, African; ASN, Asian; EUR, European; JAP, Japanese; LD, linkage disequilibrium.

  8. Supplementary Figure 8 Forest plots of odds ratios, and allele frequency plots, by ancestry for sentinel variants with significant heterogeneity.

    ac, Forest plots of odds ratios and pie charts of allele frequencies across ancestries (EUR, n = 537,409; JAP, n = 36,792; AA, n = 8,967; BRAZ, n = 1,664; HISP, n = 3,358) for sentinel variants with significant heterogeneity, close to PITX2 (a), NEURL (b) and ZFHX3 (c). Shown are odds ratios with 95% confidence intervals. Frequencies of the effect allele are depicted in blue; frequencies of the reference allele are depicted in orange. AA, African American; BRAZ, Brazilian; EUR, European; HISP, Hispanic; JAP, Japanese.

  9. Supplementary Figure 9 Enrichment of atrial fibrillation–associated loci across ChromHMM regulatory regions.

    a,b, Percent overlap of loci with regulatory regions (promoter, enhancer, DNase) based on the Roadmap Epigenomics Consortium 25-state model across all tissues (a) and cardiac tissues (b). Each locus includes sentinel variant and proxies with r2 > 0.6. The P values were derived from one-tailed permutation tests (n = 1,000). 1000 Genomes control loci were matched to atrial fibrillation sentinel SNPs via SNPSnap (n = 93,000). Atrial fibrillation–associated loci are from the combined ancestry analysis (n = 93). The sentinel SNP for one AF locus could not be matched in SNPSnap and was excluded from this analysis. The box plot depicts the following values: the center represents the median, the top and bottom of the box represent the first and third quartile, the whiskers reach to 1.5 times the interquartile range, and data points outside the whiskers are plotted as outliers. *P = 0.001. 1000G, 1000 Genomes; AF, atrial fibrillation.

Supplementary information

  1. Supplementary Text, Figures and Tables

    Supplementary Figures 1–9, Supplementary Tables 1, 2, 6, 8, 10 and 19–22, and Supplementary Notes

  2. Reporting Summary

  3. Supplementary Table 3

    Known loci in combined ancestry meta-analysis

  4. Supplementary Table 4

    Gene set enrichment analysis results for combined ancestry meta-analysis

  5. Supplementary Table 5

    Novel and known loci in ancestry-specific meta-analyses

  6. Supplementary Table 7

    Loci with multiple signals identified by conditional and joint analysis for European-ancestry meta-analysis

  7. Supplementary Table 9

    Chromatin states for sentinel variants and proxies from Roadmap Epigenomics across all tissues and heart

  8. Supplementary Table 11

    Significant cis-eQTLs for sentinel variants from combined ancestry meta-analysis in GTEx heart tissues

  9. Supplementary Table 12

    Probable AF susceptibility genes for loci from combined ancestry meta-analysis

  10. Supplementary Table 13

    Transcriptome-wide results based on summary-level data from combined ancestry meta-analysis

  11. Supplementary Table 14

    Association to diseases and traits in NHGRI-EBI GWAS catalog for sentinel variants or proxies from combined ancestry meta-analysis

  12. Supplementary Table 15

    PheWAS results in UK Biobank for sentinel variants from combined ancestry meta-analysis

  13. Supplementary Table 16

    134 loci associated with atrial fibrillation

  14. Supplementary Table 17

    Baseline summary for GWAS

  15. Supplementary Table 18

    GWAS summary on genotyping, QC, imputation and analysis per study

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DOI

https://doi.org/10.1038/s41588-018-0133-9