Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Identification of six new genetic loci associated with atrial fibrillation in the Japanese population

Nature Genetics volume 49, pages 953–958 (2017)Cite this article

Subjects

Abstract

Atrial fibrillation is the most common cardiac arrhythmia and leads to stroke. To investigate genetic loci associated with atrial fibrillation in the Japanese population, we performed a genome-wide association study (GWAS) that included 8,180 atrial fibrillation cases and 28,612 controls with follow-up in an additional 3,120 cases and 125,064 controls. We replicated previously reported loci and identified six new loci, near the KCND3, PPFIA4, SLC1A4–CEP68, HAND2, NEBL and SH3PXD2A genes. Five of the six new loci were specifically associated with atrial fibrillation in the Japanese population after comparing our data to those from individuals of European ancestry, suggesting that there might be different genetic factors affecting susceptibility across ancestry groups. Our study discovered variants in the HAND2, KCND3 and NEBL genes, which are relevant to atrial fibrillation susceptibility. The involvement of PPFIA4 and SH3PXD2A in axon guidance also suggested a role in disease pathogenesis. Our findings may contribute to a better understanding of atrial fibrillation susceptibility and pathogenesis.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Regional association plots for six new loci associated with atrial fibrillation in the Japanese population.

Similar content being viewed by others

References

  1. Inoue, H. et al. Prevalence of atrial fibrillation in the general population of Japan: an analysis based on periodic health examination. Int. J. Cardiol. 137, 102–107 (2009).

    Article  PubMed  Google Scholar 

  2. Fox, C.S. et al. Parental atrial fibrillation as a risk factor for atrial fibrillation in offspring. J. Am. Med. Assoc. 291, 2851–2855 (2004).

    Article  CAS  Google Scholar 

  3. Gudbjartsson, D.F. et al. Variants conferring risk of atrial fibrillation on chromosome 4q25. Nature 448, 353–357 (2007).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Dewland, T.A., Olgin, J.E., Vittinghoff, E. & Marcus, G.M. Incident atrial fibrillation among Asians, Hispanics, blacks, and whites. Circulation 128, 2470–2477 (2013).

    Article  PubMed  Google Scholar 

  9. Pe'er, I., Yelensky, R., Altshuler, D. & Daly, M.J. Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet. Epidemiol. 32, 381–385 (2008).

    Article  PubMed  Google Scholar 

  10. So, H.C., Gui, A.H., Cherny, S.S. & Sham, P.C. Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases. Genet. Epidemiol. 35, 310–317 (2011).

    Article  PubMed  Google Scholar 

  11. JCS Joint Working Group. Guidelines for pharmacotherapy of atrial fibrillation (JCS 2013). Circ. J. 78, 1997–2021 (2014).

  12. Zollner, S. & Pritchard, J.K. Overcoming the winner's curse: estimating penetrance parameters from case–control data. Am. J. Hum. Genet. 80, 605–615 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. McFadden, D.G. et al. A GATA-dependent right ventricular enhancer controls dHAND transcription in the developing heart. Development 127, 5331–5341 (2000).

    CAS  PubMed  Google Scholar 

  14. Morikawa, Y. & Cserjesi, P. Cardiac neural crest expression of Hand2 regulates outflow and second heart field development. Circ. Res. 103, 1422–1429 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Dunah, A.W. et al. LAR receptor protein tyrosine phosphatases in the development and maintenance of excitatory synapses. Nat. Neurosci. 8, 458–467 (2005).

    Article  CAS  PubMed  Google Scholar 

  16. Santiago-Medina, M., Gregus, K.A., Nichol, R.H., O'Toole, S.M. & Gomez, T.M. Regulation of ECM degradation and axon guidance by growth cone invadosomes. Development 142, 486–496 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kirby, M.L. & Stewart, D.E. Neural crest origin of cardiac ganglion cells in the chick embryo: identification and extirpation. Dev. Biol. 97, 433–443 (1983).

    Article  CAS  PubMed  Google Scholar 

  18. Duarri, A. et al. Mutations in potassium channel kcnd3 cause spinocerebellar ataxia type 19. Ann. Neurol. 72, 870–880 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Duarri, A. et al. Spinocerebellar ataxia type 19/22 mutations alter heterocomplex Kv4.3 channel function and gating in a dominant manner. Cell. Mol. Life Sci. 72, 3387–3399 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Duarri, A. et al. The L450F mutation in KCND3 brings spinocerebellar ataxia and Brugada syndrome closer together. Neurogenetics 14, 257–258 (2013).

    Article  PubMed  Google Scholar 

  21. Lee, Y.C. et al. Mutations in KCND3 cause spinocerebellar ataxia type 22. Ann. Neurol. 72, 859–869 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Smets, K. et al. First de novo KCND3 mutation causes severe Kv4.3 channel dysfunction leading to early onset cerebellar ataxia, intellectual disability, oral apraxia and epilepsy. BMC Med. Genet. 16, 51 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Olesen, M.S. et al. A novel KCND3 gain-of-function mutation associated with early-onset of persistent lone atrial fibrillation. Cardiovasc. Res. 98, 488–495 (2013).

    Article  CAS  PubMed  Google Scholar 

  24. Bang, M.L. & Chen, J. Roles of nebulin family members in the heart. Circ. J. 79, 2081–2087 (2015).

    Article  PubMed  Google Scholar 

  25. Eulitz, S. et al. Identification of Xin-repeat proteins as novel ligands of the SH3 domains of nebulin and nebulette and analysis of their interaction during myofibril formation and remodeling. Mol. Biol. Cell 24, 3215–3226 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Moncman, C.L. & Wang, K. Targeted disruption of nebulette protein expression alters cardiac myofibril assembly and function. Exp. Cell Res. 273, 204–218 (2002).

    Article  CAS  PubMed  Google Scholar 

  27. Maiellaro-Rafferty, K. et al. Altered regional cardiac wall mechanics are associated with differential cardiomyocyte calcium handling due to nebulette mutations in preclinical inherited dilated cardiomyopathy. J. Mol. Cell. Cardiol. 60, 151–160 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Purevjav, E. et al. Nebulette mutations are associated with dilated cardiomyopathy and endocardial fibroelastosis. J. Am. Coll. Cardiol. 56, 1493–1502 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lubitz, S.A. et al. Independent susceptibility markers for atrial fibrillation on chromosome 4q25. Circulation 122, 976–984 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kuriyama, S. et al. The Tohoku Medical Megabank Project: design and mission. J. Epidemiol. 26, 493–511 (2016).

    Article  PubMed  Google Scholar 

  31. Freedman, M.L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).

    Article  CAS  PubMed  Google Scholar 

  32. Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We express our heartfelt gratitude to all the participants in this study. We would like to express our gratefulness to the staff of TMM, J-MICC, JPHC and BBJ for their outstanding assistance. We extend our appreciation to N. Miyagawa and other members of the Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences for their support. This study was in part supported by the Naito Foundation Natural Science Scholarship to T.T. This study was also funded by the BioBank Japan project and the Tohoku Medical Megabank project, which is supported by the Ministry of Education, Culture, Sports, Sciences and Technology Japan and the Japan Agency for Medical Research and Development. The JPHC Study has been supported by the National Cancer Research and Development Fund since 2010 and was supported by a Grant-in-Aid for Cancer Research from the Ministry of Health, Labour and Welfare of Japan from 1989 to 2010. The J-MICC Study was supported by Grants-in-Aid for Scientific Research for Priority Areas of Cancer (17015018) and Innovative Areas (221S0001) and the JSPS KAKENHI Grant (16H06277) from the Japan Ministry of Education, Science, Sports, Culture and Technology. The following research institutions participated in the study: Chiba Cancer Center, University of Shizuoka, Nagoya City University, Aichi Cancer Center, Nagoya University, Shiga University of Medical Science, Kyoto Prefectural University of Medicine, University of Tokushima, Kyushu University, Saga University and Kagoshima University. This work was supported by grants from the US National Institutes of Health to P.T.E. (1RO1HL092577, R01HL128914, K24HL105780). P.T.E. is also supported by an Established Investigator Award from the American Heart Association (13EIA14220013) and by the Fondation Leducq (14CVD01).

Author information

Authors and Affiliations

  1. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Siew-Kee Low, Atsushi Takahashi & Yoichiro Kamatani

  2. Faculty of Pharmacy, University of Sydney, Sydney, New South Wales, Australia

    Siew-Kee Low

  3. Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Osaka, Japan

    Atsushi Takahashi

  4. Department of Bio-Informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan

    Yusuke Ebana & Tetsushi Furukawa

  5. Laboratory for Cardiovascular Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Kouichi Ozaki, Kaoru Ito & Toshihiro Tanaka

  6. Laboratory for Medical Genome Sciences, Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan

    Kouichi Ozaki

  7. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA

    Ingrid E Christophersen & Patrick T Ellinor

  8. Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA

    Ingrid E Christophersen

  9. Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway

    Ingrid E Christophersen

  10. Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan

    Soichi Ogishima & Masayuki Yamamoto

  11. Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan

    Mamoru Satoh & Makoto Sasaki

  12. Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan

    Taiki Yamaji & Motoki Iwasaki

  13. Center for Public Health Sciences, National Cancer Center, Tokyo, Japan

    Shoichiro Tsugane

  14. Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan

    Keitaro Tanaka

  15. Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan

    Mariko Naito & Kenji Wakai

  16. Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan

    Hideo Tanaka

  17. Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan

    Hideo Tanaka

  18. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Michiaki Kubo

  19. Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University Graduate School of Medical and Dental Sciences, Tokyo, Japan

    Toshihiro Tanaka

Authors
  1. Siew-Kee Low
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Atsushi Takahashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yusuke Ebana
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kouichi Ozaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ingrid E Christophersen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Patrick T Ellinor
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Soichi Ogishima
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Masayuki Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Mamoru Satoh
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Makoto Sasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Taiki Yamaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Motoki Iwasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Shoichiro Tsugane
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Keitaro Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Mariko Naito
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Kenji Wakai
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Hideo Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Tetsushi Furukawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Michiaki Kubo
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Kaoru Ito
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Yoichiro Kamatani
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Toshihiro Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

AFGen Consortium

Contributions

S.-K.L., K.I. and Y.K. wrote the manuscript. S.-K.L., A.T. and Y.K. conducted the data analyses. Y.E., K.O. and T.F. conducted replication genotyping, I.E.C., P.T.E. and the AFGen Consortium provided data from the AFGen Consortium. M.K. conducted SNP genotyping. Y.E., S.O., M.Y., M. Satoh, M. Sasaki, T.Y., M.I., S.T., K.T., M.N., K.W., H.T., T.F. and M.K. collected the samples. S.-K.L., A.T., K.I., Y.K. and T.T. designed the study.

Corresponding authors

Correspondence to Kaoru Ito, Yoichiro Kamatani or Toshihiro Tanaka.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

A full list of members and affiliations appears in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Tables 1, 2 and 7–11, and Supplementary Note (PDF 3606 kb)

Supplementary Table 3

Association studies after adjusting for the effect of diabetes. (XLSX 52 kb)

Supplementary Table 4

Association studies after adjusting for the effect of myocardial infarction. (XLSX 49 kb)

Supplementary Table 5

Association studies after adjusting for the effect of heart failure. (XLSX 53 kb)

Supplementary Table 6

Association of atrial fibrillation variants with other traits according to the GWAS catalog (12 December 2016). (XLSX 49 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Low, SK., Takahashi, A., Ebana, Y. et al. Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. Nat Genet 49, 953–958 (2017). https://doi.org/10.1038/ng.3842

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3842

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing