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Nature Genetics
Published online: 26 April 2009 | :10.1038/ng.357:10.1038/ng.357

 

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

Yoon Shin Cho1, Min Jin Go1, Young Jin Kim1, Jee Yeon Heo1, Ji Hee Oh1, Hyo-Jeong Ban1, Dankyu Yoon2, Mi Hee Lee1, Dong-Joon Kim1, Miey Park1, Seung-Hun Cha1, Jun-Woo Kim1, Bok-Ghee Han1, Haesook Min1, Younjhin Ahn1, Man Suk Park1, Hye Ree Han1, Hye-Yoon Jang3, Eun Young Cho3, Jong-Eun Lee3, Nam H Cho4, Chol Shin5, Taesung Park2,6, Ji Wan Park7, Jong-Keuk Lee8, Lon Cardon9, Geraldine Clarke10, Mark I McCarthy10,11, Jong-Young Lee1, Jong-Koo Lee12, Bermseok Oh1,13 & Hyung-Lae Kim1

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 times 10-9) and 6q22 (rs12110693, P = 1.6 times 10-9), with the latter approx400 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 times 10-7). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 times 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 times 10-11), tibia (P = 1.6 times 10-6) and heel (P = 1.9 times 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 times 10-3, P = 1.4 times 10-7 and P = 6.0 times 10-4, respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways.

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  1. Center for Genome Science, National Institute of Health, Seoul, Korea.
  2. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea.
  3. DNA Link, Seoul, Korea.
  4. Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea.
  5. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Korea.
  6. Department of Statistics, College of Natural Science, Seoul National University, Seoul, Korea.
  7. Department of Medical Genetics, Hallym University, College of Medicine, Chuncheon, Korea.
  8. Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, Korea.
  9. GlaxoSmithKline, Philadelphia, Pennsylvania, USA.
  10. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
  11. Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK.
  12. Korea Centers for Disease Control and Prevention, Seoul, Korea.
  13. Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Seoul, Korea.

Correspondence to: Hyung-Lae Kim1 e-mail: hyung505@nih.go.kr

Correspondence to: Bermseok Oh1,13 e-mail: ohbs@khu.ac.kr

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