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A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits

Nature Genetics volume 41, pages 527–534 (2009)Cite this article

Abstract

To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 × 10−9) and 6q22 (rs12110693, P = 1.6 × 10−9), with the latter ∼400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 × 10−7). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 × 10−12) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 × 10−11), tibia (P = 1.6 × 10−6) and heel (P = 1.9 × 10−10). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 × 10−3, P = 1.4 × 10−7 and P = 6.0 × 10−4, respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways.

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Figure 1: Comparison of genetic background between subjects from Ansung and Ansan cohorts.
Figure 2: Quantile-quantile plots for the eight quantitative traits.
Figure 3: Six newly identified loci showing strong evidence of association.

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Acknowledgements

This work was supported by a grant from the Ministry for Health, Welfare and Family Affairs, Republic of Korea (4845-301-430-260-00), and an intramural grant from the Korea National Institute of Health, Korea Center for Disease Control, Republic of Korea (4845-301-430-210-13).

Author information

Authors and Affiliations

  1. Center for Genome Science, National Institute of Health, Seoul, Korea

    Yoon Shin Cho, Min Jin Go, Young Jin Kim, Jee Yeon Heo, Ji Hee Oh, Hyo-Jeong Ban, Mi Hee Lee, Dong-Joon Kim, Miey Park, Seung-Hun Cha, Jun-Woo Kim, Bok-Ghee Han, Haesook Min, Younjhin Ahn, Man Suk Park, Hye Ree Han, Jong-Young Lee, Bermseok Oh & Hyung-Lae Kim

  2. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea

    Dankyu Yoon & Taesung Park

  3. DNA Link, Seoul, Korea

    Hye-Yoon Jang, Eun Young Cho & Jong-Eun Lee

  4. Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea

    Nam H Cho

  5. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Korea

    Chol Shin

  6. Department of Statistics, College of Natural Science, Seoul National University, Seoul, Korea

    Taesung Park

  7. Department of Medical Genetics, Hallym University, College of Medicine, Chuncheon, Korea

    Ji Wan Park

  8. Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, Korea

    Jong-Keuk Lee

  9. GlaxoSmithKline, Philadelphia, Pennsylvania, USA

    Lon Cardon

  10. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK

    Geraldine Clarke & Mark I McCarthy

  11. Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK

    Mark I McCarthy

  12. Korea Centers for Disease Control and Prevention, Seoul, Korea

    Jong-Koo Lee

  13. Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Seoul, Korea

    Bermseok Oh

Authors
  1. Yoon Shin Cho
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Contributions

The study was designed by H-.L.K., B.O., J-.K.L. and J-.Y.L. Genotyping experiments were performed by J-.E.L., J.H.O., D-.J.K., M.P., S-.H.C., H-.Y.J. and E.Y.C. DNA sample preparation was carried out by M.H.L., J-.W.K. and B-.G.H. Phenotype information was collected by H.M., Y.A., M.S.P., N.H.C. and C.S. Statistical analysis was performed by M.J.G., D.Y., H.R.H., T.P., G.C. and Y.S.C. Bioinformatic analysis was conducted by Y.J.K., J.Y.H., H-.J.B., L.C. and Y.S.C. The manuscript was written by Y.S.C., B.O., J.W.P., J-.K.L., M.I.M. and H-.L.K. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Bermseok Oh or Hyung-Lae Kim.

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Supplementary Figures 1–8, Supplementary Tables 1–9, Supplementary Methods (PDF 3008 kb)

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Cho, Y., Go, M., Kim, Y. et al. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. Nat Genet 41, 527–534 (2009). https://doi.org/10.1038/ng.357

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