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.

Large-scale genome-wide association studies in east Asians identify new genetic loci influencing metabolic traits

Abstract

To identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery meta-analysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall meta-analysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1
Figure 2: Regional plot of new variants that reached genome-wide significance (overall meta P < 5 × 10−8).

References

  1. 1

    Kamatani, Y. et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat. Genet. 42, 210–215 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  2. 2

    Yuan, X. et al. Population-based genome-wide association studies reveal six loci influencing plasma levels of liver enzymes. Am. J. Hum. Genet. 83, 520–528 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  3. 3

    Kottgen, A. et al. Multiple loci associated with indices of renal function and chronic kidney disease. Nat. Genet. 41, 712–717 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  4. 4

    Cho, Y.S. 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).

    CAS  Article  Google Scholar 

  5. 5

    Ong, R.T. & Teo, Y.Y. varLD: a program for quantifying variation in linkage disequilibrium patterns between populations. Bioinformatics 26, 1269–1270 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  6. 6

    Li, C.Z. et al. Polymorphism of OAS-1 determines liver fibrosis progression in hepatitis C by reduced ability to inhibit viral replication. Liver Int. 29, 1413–1421 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  7. 7

    Tessier, M.C. et al. Type 1 diabetes and the OAS gene cluster: association with splicing polymorphism or haplotype? J. Med. Genet. 43, 129–132 (2006).

    CAS  Article  PubMed Central  Google Scholar 

  8. 8

    Francke, U. Williams-Beuren syndrome: genes and mechanisms. Hum. Mol. Genet. 8, 1947–1954 (1999).

    CAS  Article  PubMed Central  Google Scholar 

  9. 9

    Hegele, R.A. et al. A polygenic basis for four classical Fredrickson hyperlipoproteinemia phenotypes that are characterized by hypertriglyceridemia. Hum. Mol. Genet. 18, 4189–4194 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  10. 10

    Kathiresan, S. et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat. Genet. 40, 189–197 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  11. 11

    Wang, J. et al. Polygenic determinants of severe hypertriglyceridemia. Hum. Mol. Genet. 17, 2894–2899 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  12. 12

    Willer, C.J. et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat. Genet. 40, 161–169 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  13. 13

    Kathiresan, S. et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat. Genet. 41, 56–65 (2009).

    CAS  Article  Google Scholar 

  14. 14

    Gaw, A. HDL-C and triglyceride levels: relationship to coronary heart disease and treatment with statins. Cardiovasc. Drugs Ther. 17, 53–62 (2003).

    CAS  Article  PubMed Central  Google Scholar 

  15. 15

    Lee, D.S. et al. γ glutamyl transferase and metabolic syndrome, cardiovascular disease, and mortality risk: the Framingham Heart Study. Arterioscler. Thromb. Vasc. Biol. 27, 127–133 (2007).

    CAS  Article  PubMed Central  Google Scholar 

  16. 16

    Soranzo, N. et al. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat. Genet. 41, 1182–1190 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  17. 17

    Kato, N. et al. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat. Genet. 43, 531–538 (2011).

    CAS  Article  PubMed Central  Google Scholar 

  18. 18

    Manolio, T.A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  19. 19

    Johansen, C.T. et al. Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nat. Genet. 42, 684–687 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  20. 20

    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).

    CAS  Article  PubMed Central  Google Scholar 

  21. 21

    Kottgen, A. et al. New loci associated with kidney function and chronic kidney disease. Nat. Genet. 42, 376–384 (2010).

    Article  PubMed Central  Google Scholar 

  22. 22

    Kolz, M. et al. Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations. PLoS Genet. 5, e1000504 (2009).

    Article  PubMed Central  Google Scholar 

  23. 23

    Ridker, P.M. et al. Loci related to metabolic-syndrome pathways including LEPR, HNF1A, IL6R and GCKR associate with plasma C-reactive protein: the Women′s Genome Health Study. Am. J. Hum. Genet. 82, 1185–1192 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  24. 24

    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).

    CAS  Article  PubMed Central  Google Scholar 

  25. 25

    Yang, Q. et al. Multiple genetic loci influence serum urate levels and their relationship with gout and cardiovascular disease risk factors. Circ. Cardiovasc. Genet. 3, 523–530 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  26. 26

    Han, J.W. et al. Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nat. Genet. 41, 1234–1237 (2009).

    CAS  Article  Google Scholar 

  27. 27

    Amundadottir, L. et al. Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer. Nat. Genet. 41, 986–990 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  28. 28

    Tregouet, D.A. et al. Common susceptibility alleles are unlikely to contribute as strongly as the FV and ABO loci to VTE risk: results from a GWAS approach. Blood 113, 5298–5303 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  29. 29

    Qi, L. et al. Genetic variants in ABO blood group region, plasma soluble E-selectin levels and risk of type 2 diabetes. Hum. Mol. Genet. 19, 1856–1862 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  30. 30

    Barbalic, M. et al. Large-scale genomic studies reveal central role of ABO in sP-selectin and sICAM-1 levels. Hum. Mol. Genet. 19, 1863–1872 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  31. 31

    Chung, C.M. et al. A genome-wide association study identifies new loci for ACE activity: potential implications for response to ACE inhibitor. Pharmacogenomics J 10, 537–544 (2010).

    CAS  Article  PubMed Central  Google Scholar 

  32. 32

    Ferrucci, L. et al. Common variation in the beta-carotene 15,15′-monooxygenase 1 gene affects circulating levels of carotenoids: a genome-wide association study. Am. J. Hum. Genet. 84, 123–133 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  33. 33

    Shete, S. et al. Genome-wide association study identifies five susceptibility loci for glioma. Nat. Genet. 41, 899–904 (2009).

    CAS  Article  PubMed Central  Google Scholar 

  34. 34

    Todd, J.A. et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat. Genet. 39, 857–864 (2007).

    CAS  Article  PubMed Central  Google Scholar 

  35. 35

    Nakamura, Y. The BioBank Japan Project. Clin. Adv. Hematol. Oncol. 5, 696–697 (2007).

    Google Scholar 

  36. 36

    Korn, J.M. et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253–1260 (2008).

    CAS  Article  PubMed Central  Google Scholar 

  37. 37

    Gabriel, S., Ziaugra, L. & Tabbaa, D. SNP genotyping using the Sequenom MassARRAY iPLEX platform. Curr. Protoc. Hum. Genet. Chapter 2, Unit 2.12 (2009).

  38. 38

    Johnson, R., McNutt, P., MacMahon, S. & Robson, R. Use of the Friedewald formula to estimate LDL-cholesterol in patients with chronic renal failure on dialysis. Clin. Chem. 43, 2183–2184 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

    CAS  Article  PubMed Central  Google Scholar 

  40. 40

    Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    CAS  Article  PubMed Central  Google Scholar 

  41. 41

    Whitehead, A. Meta-analysis of controlled clinical trials 336 (John Wiley & Sons, Chichester, New York, New York, USA, 2002).

  42. 42

    Ioannidis, J.P., Patsopoulos, N.A. & Evangelou, E. Heterogeneity in meta-analyses of genome-wide association investigations. PLoS ONE 2, e841 (2007).

    Article  PubMed Central  Google Scholar 

  43. 43

    Devlin, B., Roeder, K. & Wasserman, L. Genomic control, a new approach to genetic-based association studies. Theor. Popul. Biol. 60, 155–166 (2001).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

This work was supported by grants from Korea Centers for Disease Control and Prevention (4845-301, 4851-302, 4851-307) and an intramural grant from the Korea National Institute of Health (2010-N73002-00), the Republic of Korea. The Shanghai study was supported by grants from National 973 Program (2011CB504001), National Natural Science Foundation of China (30800617), China. BioBank Japan project is supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan.

Author information

Affiliations

Authors

Consortia

Contributions

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

Corresponding author

Correspondence to Yoon Shin Cho.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

A list of members is provided in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Tables 1–9 and Supplementary Figures 1–5. (PDF 6368 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Kim, Y., Go, M., Hu, C. et al. Large-scale genome-wide association studies in east Asians identify new genetic loci influencing metabolic traits. Nat Genet 43, 990–995 (2011). https://doi.org/10.1038/ng.939

Download citation

Further reading

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