Cited by 876Cardiac electrophysiology and arrhythmiasAtrial Fibrillation Management and OutcomesGenetic Associations and Epidemiology

Biobank-driven genomic discovery yields new insight into atrial fibrillation biology

Open access
Nielsen, Jonas B., Thorolfsdottir, Rosa B., Fritsche, Lars G., Zhou, Wei, Skov, Morten W., Graham, Sarah E., Herron, Todd J., McCarthy, Shane +41 more·2018·Nature Genetics

Published version of a preprint

Abstract

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 claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41588-018-0171-3

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The scale of genetic analysis based on sequence data still lags behind genome-wide genotyping data, with the largest sequence-based datasets one tenth the size of the largest GWAS.

    “The scale of genetic analysis based on sequence data still lags behind that of genome-wide genotyping data (the largest sequence-based datasets are one tenth the size of the largest GWAS90–92), although reductions in sequencing costs are decreasing the differential.”

    From A brief history of human disease genetics (2020) · cites this paper as [90]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 70 · Cited by 876

Authors
Nielsen, J. B., Thorolfsdottir, R. B., Fritsche, L. G., Zhou, W., Skov, M. W., Graham, S. E., Herron, T. J., McCarthy, S., Schmidt, E. M., Sveinbjornsson, G., Surakka, I., Mathis, M. R., Yamazaki, M., Crawford, R. D., Gabrielsen, M. E., Skogholt, A. H., Holmen, O. L., Lin, M., Wolford, B. N., Dey, R., Dalen, H., Sulem, P., Chung, J. H., Backman, J. D., Arnar, D. O., Thorsteinsdottir, U., Baras, A., O’Dushlaine, C., Holst, A. G., Wen, X., Hornsby, W., Dewey, F. E., Boehnke, M., Kheterpal, S., Mukherjee, B., Lee, S., Kang, H. M., Holm, H., Kitzman, J., Shavit, J. A., Jalife, J., Brummett, C. M., Teslovich, T. M., Carey, D. J., Gudbjartsson, D. F., Stefansson, K., Abecasis, G. R., Hveem, K., & Willer, C. J.
Affiliations
  • University of Michigan (US)
  • Norwegian University of Science and Technology (NO)
  • Copenhagen University Hospital (DK)
  • Regeneron (United States) (US)
  • Medical Device Development and Regulation Research Center (JP)
  • deCODE Genetics (Iceland) (IS)
  • Geisinger Health System (US)
Corresponding author
  • Abecasis, Gonçalo R.
  • Hveem, Kristian
  • Willer, Cristen J.
Venue
Nature Genetics
Published
2018-07-30
Volume
50
Issue
9
Pages
1234-1239
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
OpenAlex
W2884743521
Cited by
876
References
70
Citations by year
2026: 64 · 2025: 130 · 2024: 181 · 2023: 129 · 2022: 108 · 2021: 115 · 2020: 84 · 2019: 53 · 2018: 11 · 2016: 1
FWCI
51.83
Type
journal article
Language
en
Open access
Locations
  • Nature Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Hirsla (Landspítali University Hospital) (submittedVersion)
Funders
  • American Heart Association
  • Hjerteforeningen
  • Norges Teknisk-Naturvitenskapelige Universitet
  • Lundbeckfonden (R220-2016-1434)
  • H. Lundbeck A/S
  • National Institutes of Health (1r01hl130705-01a1)
  • Japan Society for the Promotion of Science (15KK0341, 18H02802)
  • Norwegian Institute of Public Health
  • National Heart, Lung, and Blood Institute (R01HL127564, R01HL124232, R01-HL130705, R35HL135824, R01HL117626, R01HL109946)
  • National Human Genome Research Institute (T32HG000040)
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
atrial fibrillation, genetic risk variants, genome-wide association study, cardiac arrhythmias, atrial cardiomyopathy, cardiac structural remodeling, fetal heart development, cardiomyopathy genes, MYH6, GATA4, Nkx2.5, TBX5, biobanks
MeSH terms
Atrial Fibrillation, Heart Defects, Congenital, Humans, Mutation, Risk, Biological Specimen Banks, Genetic Predisposition to Disease, Genomics, Genome-Wide Association Study

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review