A genome-wide association study in the Japanese population identifies susceptibility loci for type 2 diabetes at UBE2E2 and C2CD4A-C2CD4B (original) (raw)

References

  1. O'Rahilly, S., Barroso, I. & Wareham, N.J. Genetic factors in type 2 diabetes: the end of the beginning? Science 307, 370–373 (2005).
    Article CAS Google Scholar
  2. Grant, S.F. et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat. Genet. 38, 320–323 (2006).
    Article CAS Google Scholar
  3. Sladek, R. et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445, 881–885 (2007).
    Article CAS Google Scholar
  4. Zeggini, E. et al. Replication of genome-wide association signals in U.K. samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007).
    Article CAS Google Scholar
  5. Scott, L.J. et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345 (2007).
    Article CAS Google Scholar
  6. Saxena, R. et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316, 1331–1336 (2007).
    Article CAS Google Scholar
  7. Steinthorsdottir, V. et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat. Genet. 39, 770–775 (2007).
    Article CAS Google Scholar
  8. Zeggini, E. et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat. Genet. 40, 638–645 (2008).
    Article CAS Google Scholar
  9. Rung, J. et al. Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nat. Genet. 41, 1110–1115 (2009).
    Article CAS Google Scholar
  10. Yasuda, K. et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nat. Genet. 40, 1092–1097 (2008).
    Article CAS Google Scholar
  11. Unoki, H. et al. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat. Genet. 40, 1098–1102 (2008).
    Article CAS Google Scholar
  12. Chan, J.C. et al. Diabetes in Asia: epidemiology, risk factors, and pathophysiology. J. Am. Med. Assoc. 301, 2129–2140 (2009).
    Article CAS Google Scholar
  13. Price, A.L. et al. Principal components analysis corrects for stratification in genomewide association studies. Nat. Genet. 38, 904–909 (2006).
    Article CAS Google Scholar
  14. Yamaguchi-Kabata, Y. et al. Japanese population structure, based on SNP genotypes from 7003 individuals compared to other ethnic groups: effects on population-based association studies. Am. J. Hum. Genet. 83, 445–456 (2008).
    Article CAS Google Scholar
  15. Freedman, M.L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).
    Article CAS Google Scholar
  16. 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 Google Scholar
  17. Horikoshi, M. et al. Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population. Diabetologia 50, 2461–2466 (2007).
    Article CAS Google Scholar
  18. Omori, S. et al. Association of CDKAL1, IGF2BP2, CDKN2A/B, HHEX, SLC30A8, and KCNJ11 with susceptibility to type 2 diabetes in a Japanese population. Diabetes 57, 791–795 (2008).
    Article CAS Google Scholar
  19. Horikawa, Y. et al. Replication of genome-wide association studies of type 2 diabetes susceptibility in Japan. J. Clin. Endocrinol. Metab. 93, 3136–3141 (2008).
    Article CAS Google Scholar
  20. Horikoshi, M. et al. A genetic variation of the transcription factor 7-like 2 gene is associated with risk of type 2 diabetes in the Japanese population. Diabetologia 50, 747–751 (2007).
    Article CAS Google Scholar
  21. Dupuis, J. et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet. 42, 105–116 (2010).
    Article CAS Google Scholar
  22. Saxena, R. et al. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat. Genet. 42, 142–148 (2010).
    Article CAS Google Scholar
  23. Kimura, M. et al. cDNA cloning, characterization, and chromosome mapping of UBE2E2 encoding a human ubiquitin-conjugating E2 enzyme. Cytogenet. Cell Genet. 78, 107–111 (1997).
    Article CAS Google Scholar
  24. Hartley, T., Brumell, J. & Volchuk, A. Emerging roles for the ubiquitin-proteasome system and autophagy in pancreatic beta-cells. Am. J. Physiol. Endocrinol. Metab. 296, E1–E10 (2009).
    Article CAS Google Scholar
  25. Kitiphongspattana, K., Mathews, C.E., Leiter, E.H. & Gaskins, H.R. Proteasome inhibition alters glucose-stimulated (pro)insulin secretion and turnover in pancreatic beta-cells. J. Biol. Chem. 280, 15727–15734 (2005).
    Article CAS Google Scholar
  26. Kawaguchi, M., Minami, K., Nagashima, K. & Seino, S. Essential role of ubiquitin-proteasome system in normal regulation of insulin secretion. J. Biol. Chem. 281, 13015–13020 (2006).
    Article CAS Google Scholar
  27. López-Avalos, M.D. et al. Evidence for a role of the ubiquitin-proteasome pathway in pancreatic islets. Diabetes 55, 1223–1231 (2006).
    Article Google Scholar
  28. Matthews, D.R. et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419 (1985).
    Article CAS Google Scholar
  29. Warton, K., Foster, N.C., Gold, W.A. & Stanley, K.K. A novel gene family induced by acute inflammation in endothelial cells. Gene 342, 85–95 (2004).
    Article CAS Google Scholar
  30. Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2009).
    Article CAS Google Scholar
  31. Bouatia-Naji, N. et al. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat. Genet. 41, 89–94 (2009).
    Article CAS Google Scholar
  32. Lyssenko, V. et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat. Genet. 41, 82–88 (2009).
    Article CAS Google Scholar
  33. Sparsø, T. et al. The GCKR rs780094 polymorphism is associated with elevated fasting serum triacylglycerol, reduced fasting and OGTT-related insulinaemia, and reduced risk of type 2 diabetes. Diabetologia 51, 70–75 (2008).
    Article Google Scholar
  34. Ohnishi, Y. et al. A high-throughput SNP typing system for genome-wide association studies. J. Hum. Genet. 46, 471–477 (2001).
    Article CAS Google Scholar
  35. Devlin, B. & Risch, N. A comparison of linkage disequilibrium measures for fine-scale mapping. Genomics 29, 311–322 (1995).
    Article CAS Google Scholar
  36. Wigginton, J.E., Cutler, D.J. & Abecasis, G.R. A note on exact tests of Hardy-Weinberg equilibrium. Am. J. Hum. Genet. 76, 887–893 (2005).
    Article CAS Google Scholar

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Acknowledgements

We thank all participating doctors and staff from collaborating institutes for providing DNA samples. We also thank the technical staff of the Laboratory for Endocrinology and Metabolism at the RIKEN Center for Genomic Medicine for providing technical assistance. We thank the technical staff of the Laboratory for Genotyping Development at the RIKEN Center for Genomic Medicine for SNP genotyping. We also thank all the participants and the staff of the BioBank Japan project. This work was partly supported by a grant from the Leading Project of Ministry of Education, Culture, Sports, Science and Technology Japan.

Funding for the Singapore portion of the study was supported by the National Medical Research Council (NMRC/1115/2007). We thank the staff of the National Healthcare Group Polyclinics and the National University of Singapore for their contributions towards the establishment of the Singapore Diabetes Cohort Study.

The Korean panel was supported by a grant from the Korea Health 21 Research and Development Project, Ministry of Health, Welfare, and Family Affairs, Republic of Korea (00-PJ3-PG6-GN07-001).

The Danish study was funded by grants from the Lundbeck Foundation Centre of Applied Medical Genomics for Personalized Disease Prediction, Prevention and Care (LuCAMP), European Union (EUGENE2) grant LSHM-CT-2004-512013, EXGENESIS (Health benefits of exercise: identification of genes and signaling pathways involved in effects of exercise on insulin resistance, obesity and the metabolic syndrome) grant LSHM-CT-2004- 005272 and the Danish Diabetes Association and the Danish Agency for Science, Technology and Innovation, grant no. 271-06-0539. The Inter99 was initiated by T. Jørgensen (primary investigator), K. Borch-Johnsen (co-primary investigator), H. Ibsen and T.F. Thomsen. The steering committee comprises T. Jørgensen, K. Borch-Johnsen and C. Pisinger. The ADDITION (The Anglo-Danish-Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care) study Denmark was initiated by K. Borch-Johnsen (primary investigator), T. Lauritzen (primary investigator) and A. Sandbæk.

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Author notes

  1. Toshimasa Yamauchi, Kazuo Hara and Shiro Maeda: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    Toshimasa Yamauchi, Kazuo Hara, Momoko Horikoshi, Masahiro Nakamura, Hayato Fujita, Miki Okada-Iwabu, Masato Iwabu, Nobuhiro Shojima & Takashi Kadowaki
  2. Department of Integrated Molecular Science on Metabolic Diseases, 22nd Century Medical and Research Center, The University of Tokyo, Tokyo, Japan
    Toshimasa Yamauchi, Miki Okada-Iwabu & Masato Iwabu
  3. Laboratory for Endocrinology and Metabolism, RIKEN Center for Genomic Medicine, Yokohama, Kanagawa, Japan
    Shiro Maeda
  4. Department of Metabolic Disorder, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
    Kazuki Yasuda
  5. Laboratory for Statistical Analysis, RIKEN Center for Genomic Medicine, Yokohama, Kanagawa, Japan
    Atsushi Takahashi & Naoyuki Kamatani
  6. Hagedorn Research Institute, Gentofte, Denmark
    Niels Grarup, Gitte Andersen, Torben Hansen & Oluf Pedersen
  7. Centre National de la Recherche Scientifique–Unité Mixte de Recherche–8090, Institute of Biology and Lille 2 University, Pasteur Institute, Lille, France
    Stephane Cauchi, Delphine Beury & Philippe Froguel
  8. Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
    Daniel P K Ng
  9. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
    Ronald C W Ma, Wing-Yee So & Juliana C N Chan
  10. Laboratory for Medical Informatics, RIKEN Center for Genomic Medicine, Yokohama, Kanagawa, Japan
    Tatsuhiko Tsunoda
  11. Laboratory for Genotyping Development, RIKEN Center for Genomic Medicine, Yokohama, Kanagawa, Japan
    Michiaki Kubo
  12. Department of Medicine, Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan
    Hirotaka Watada & Ryuzo Kawamori
  13. Department of Medicine, Shiga University of Medical Science, Otsu, Shiga, Japan
    Hiroshi Maegawa & Atsunori Kashiwagi
  14. Department of Life Science, Laboratory of Genomic Diversity, Sogang University, 1 Shinsu-dong, Mapo-gu, Seoul, Korea
    Hyoung Doo Shin
  15. Steno Diabetes Center, Gentofte, Denmark
    Daniel R Witte & Torben Hansen
  16. Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
    Daniel R Witte & Oluf Pedersen
  17. Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
    Torben Jørgensen
  18. Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
    Torben Jørgensen & Oluf Pedersen
  19. Department of General Practice, University of Aarhus, Aarhus, Denmark
    Torsten Lauritzen & Annelli Sandbæk
  20. Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
    Torben Hansen
  21. Department of Medicine, Metabolism and Endocrinology, St. Marianna University School of Medicine, Kawasaki, Kanagawa, Japan
    Toshihiko Ohshige, Shintaro Omori & Yasushi Tanaka
  22. Keio University Health Center, Tokyo, Japan
    Ikuo Saito & Hiroshi Hirose
  23. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kawasaki Medical School, Kurashiki, Okayama, Japan
    Kohei Kaku
  24. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
    Kyong Soo Park
  25. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
    E Shyong Tai
  26. Medical Court Life Care Clinic, Hiroshima, Japan
    Chikako Ito
  27. Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
    Masato Kasuga
  28. Centre and Department of Genomic Medicine, Hammersmith Hospital, Imperial College London, London, UK
    Philippe Froguel
  29. Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
    Yusuke Nakamura

Authors

  1. Toshimasa Yamauchi
  2. Kazuo Hara
  3. Shiro Maeda
  4. Kazuki Yasuda
  5. Atsushi Takahashi
  6. Momoko Horikoshi
  7. Masahiro Nakamura
  8. Hayato Fujita
  9. Niels Grarup
  10. Stephane Cauchi
  11. Daniel P K Ng
  12. Ronald C W Ma
  13. Tatsuhiko Tsunoda
  14. Michiaki Kubo
  15. Hirotaka Watada
  16. Hiroshi Maegawa
  17. Miki Okada-Iwabu
  18. Masato Iwabu
  19. Nobuhiro Shojima
  20. Hyoung Doo Shin
  21. Gitte Andersen
  22. Daniel R Witte
  23. Torben Jørgensen
  24. Torsten Lauritzen
  25. Annelli Sandbæk
  26. Torben Hansen
  27. Toshihiko Ohshige
  28. Shintaro Omori
  29. Ikuo Saito
  30. Kohei Kaku
  31. Hiroshi Hirose
  32. Wing-Yee So
  33. Delphine Beury
  34. Juliana C N Chan
  35. Kyong Soo Park
  36. E Shyong Tai
  37. Chikako Ito
  38. Yasushi Tanaka
  39. Atsunori Kashiwagi
  40. Ryuzo Kawamori
  41. Masato Kasuga
  42. Philippe Froguel
  43. Oluf Pedersen
  44. Naoyuki Kamatani
  45. Yusuke Nakamura
  46. Takashi Kadowaki

Contributions

T.K., S.M., T.Y. and K.H. planned and coordinated the study. Y.N. managed BioBank Japan. K.H., S.M., K.Y., M.H., T.Y., M.K., H.W., H.M., H.D.S., D.R.W., T.J., T.L., A.S., T.H., T.O., S.O., I.S., K.K., H.H., W.-Y.S., D.B., E.S.T., C.I., Y.T., A.K., R.K., M.K., O.P. and T.K. recruited and phenotyped or genotyped subject cohorts. A.T., T.T., N.K., S.M., K.H., M.N., H.F., M.O.-I., M.I., N.S., N.G., G.A., S.C., D.P.K.N., R.C.W.M., M.K., T.Y., K.K., J.C.N.C., K.S.P., P.F., T.H., O.P. and T.K. analyzed the genotyping data. T.Y., T.K., S.M. and K.H. wrote the manuscript. All authors contributed to the final version of the manuscript.

Corresponding authors

Correspondence toShiro Maeda or Takashi Kadowaki.

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Competing interests

The authors declare no competing financial interests.

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Yamauchi, T., Hara, K., Maeda, S. et al. A genome-wide association study in the Japanese population identifies susceptibility loci for type 2 diabetes at UBE2E2 and C2CD4A-C2CD4B.Nat Genet 42, 864–868 (2010). https://doi.org/10.1038/ng.660

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