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.

  • Article
  • Published:

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Abstract

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

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

Access options

Buy this article

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

Figure 1: Associations between glycemic loci and T2D, HDL-cholesterol (HDL-C) and triglyceride concentrations, BMI and WHR.
Figure 2: Per-allele β coefficients for glucose and insulin concentrations versus ORs for T2D.

Similar content being viewed by others

References

  1. 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  PubMed  PubMed Central  Google Scholar 

  2. 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  PubMed  PubMed Central  Google Scholar 

  3. Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Barker, A. et al. Association of genetic loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children. Diabetes 60, 1805–1812 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Ingelsson, E. et al. Detailed physiologic characterization reveals diverse mechanisms for novel genetic loci regulating glucose and insulin metabolism in humans. Diabetes 59, 1266–1275 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Voight, B.F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Park, J.H. et al. Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nat. Genet. 42, 570–575 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Voight, B.F. et al. The Metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 8, e1002793 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Liu, J.Z. et al. A versatile gene-based test for genome-wide association studies. Am. J. Hum. Genet. 87, 139–145 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kuro-o, M. et al. Mutation of the mouse klotho gene leads to a syndrome resembling ageing. Nature 390, 45–51 (1997).

    Article  CAS  PubMed  Google Scholar 

  12. Ohnishi, M., Kato, S., Akiyoshi, J., Atfi, A. & Razzaque, M.S. Dietary and genetic evidence for enhancing glucose metabolism and reducing obesity by inhibiting klotho functions. FASEB J. 25, 2031–2039 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Utsugi, T. et al. Decreased insulin production and increased insulin sensitivity in the klotho mutant mouse, a novel animal model for human aging. Metabolism 49, 1118–1123 (2000).

    Article  CAS  PubMed  Google Scholar 

  14. Rhee, E.J. et al. Relationship between polymorphisms G395A in promoter and C1818T in exon 4 of the KLOTHO gene with glucose metabolism and cardiovascular risk factors in Korean women. J. Endocrinol. Invest. 29, 613–618 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Paroni, G. et al. Klotho locus, metabolic traits, and serum hemoglobin in hospitalized older patients: a genetic association analysis. Age (Omaha) published online (22 June 2011); doi:10.1007/s11357–011–9273-x.

  16. Rampersaud, E. et al. Identification of novel candidate genes for type 2 diabetes from a genome-wide association scan in the Old Order Amish: evidence for replication from diabetes-related quantitative traits and from independent populations. Diabetes 56, 3053–3062 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. Tabassum, R., Chavali, S., Dwivedi, O.P., Tandon, N. & Bharadwaj, D. Genetic variants of FOXA2: risk of type 2 diabetes and effect on metabolic traits in North Indians. J. Hum. Genet. 53, 957–965 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Xing, C., Cohen, J.C. & Boerwinkle, E. A weighted false discovery rate control procedure reveals alleles at FOXA2 that influence fasting glucose levels. Am. J. Hum. Genet. 86, 440–446 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Manning, A.K. et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat. Genet. 44, 659–669 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Jonsson, J., Carlsson, L., Edlund, T. & Edlund, H. Insulin-promoter-factor 1 is required for pancreas development in mice. Nature 371, 606–609 (1994).

    Article  CAS  PubMed  Google Scholar 

  21. Stoffers, D.A., Ferrer, J., Clarke, W.L. & Habener, J.F. Early-onset type-II diabetes mellitus (MODY4) linked to IPF1. Nat. Genet. 17, 138–139 (1997).

    Article  CAS  PubMed  Google Scholar 

  22. Stoffers, D.A., Zinkin, N.T., Stanojevic, V., Clarke, W.L. & Habener, J.F. Pancreatic agenesis attributable to a single nucleotide deletion in the human IPF1 gene coding sequence. Nat. Genet. 15, 106–110 (1997).

    Article  CAS  PubMed  Google Scholar 

  23. Nicolino, M. et al. A novel hypomorphic PDX1 mutation responsible for permanent neonatal diabetes with subclinical exocrine deficiency. Diabetes 59, 733–740 (2010).

    Article  CAS  PubMed  Google Scholar 

  24. Morris, A.P. et al. Large-scale association analysis of the Metabochip provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. published online (12 August 2012); doi:10.1038/ng.2383.

  25. Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Heid, I.M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Teslovich, T.M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Irwin, D.M. & Tan, H. Molecular evolution of the vertebrate hexokinase gene family: identification of a conserved fifth vertebrate hexokinase gene. Comp. Biochem. Physiol. Part D Genomics Proteomics 3, 96–107 (2008).

    Article  PubMed  CAS  Google Scholar 

  29. Frayling, T.M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Richards, J.B. et al. A genome-wide association study reveals variants in ARL15 that influence adiponectin levels. PLoS Genet. 5, e1000768 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Yujiri, T. et al. MEK kinase 1 interacts with focal adhesion kinase and regulates insulin receptor substrate-1 expression. J. Biol. Chem. 278, 3846–3851 (2003).

    Article  CAS  PubMed  Google Scholar 

  32. Meyer, C.F., Wang, X., Chang, C., Templeton, D. & Tan, T.H. Interaction between c-Rel and the mitogen-activated protein kinase kinase kinase 1 signaling cascade in mediating κB enhancer activation. J. Biol. Chem. 271, 8971–8976 (1996).

    Article  CAS  PubMed  Google Scholar 

  33. Lee, F.S., Hagler, J., Chen, Z.J. & Maniatis, T. Activation of the IκBα kinase complex by MEKK1, a kinase of the JNK pathway. Cell 88, 213–222 (1997).

    Article  CAS  PubMed  Google Scholar 

  34. Yujiri, T., Sather, S., Fanger, G.R. & Johnson, G.L. Role of MEKK1 in cell survival and activation of JNK and ERK pathways defined by targeted gene disruption. Science 282, 1911–1914 (1998).

    Article  CAS  PubMed  Google Scholar 

  35. Hirosumi, J. et al. A central role for JNK in obesity and insulin resistance. Nature 420, 333–336 (2002).

    Article  CAS  PubMed  Google Scholar 

  36. Cai, D. et al. Local and systemic insulin resistance resulting from hepatic activation of IKK-β and NF-κB. Nat. Med. 11, 183–190 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Barish, G.D., Narkar, V.A. & Evans, R.M. PPARδ: a dagger in the heart of the metabolic syndrome. J. Clin. Invest. 116, 590–597 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Tanaka, T. et al. Activation of peroxisome proliferator–activated receptor δ induces fatty acid β-oxidation in skeletal muscle and attenuates metabolic syndrome. Proc. Natl. Acad. Sci. USA 100, 15924–15929 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Butler, M. et al. Specific inhibition of PTEN expression reverses hyperglycemia in diabetic mice. Diabetes 51, 1028–1034 (2002).

    Article  CAS  PubMed  Google Scholar 

  40. Wijesekara, N. et al. Muscle-specific Pten deletion protects against insulin resistance and diabetes. Mol. Cell. Biol. 25, 1135–1145 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Fajans, S.S., Bell, G.I. & Polonsky, K.S. Molecular mechanisms and clinical pathophysiology of maturity-onset diabetes of the young. N. Engl. J. Med. 345, 971–980 (2001).

    Article  CAS  PubMed  Google Scholar 

  42. Schmid, J. et al. Modulation of pancreatic islets–stress axis by hypothalamic releasing hormones and 11β-hydroxysteroid dehydrogenase. Proc. Natl. Acad. Sci. USA 108, 13722–13727 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Strawbridge, R.J. et al. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes 60, 2624–2634 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Cui, B. et al. A genome-wide association study confirms previously reported loci for type 2 diabetes in Han Chinese. PLoS ONE 6, e22353 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Raychaudhuri, S. et al. Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet. 5, e1000534 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Withers, D.J. et al. Disruption of IRS-2 causes type 2 diabetes in mice. Nature 391, 900–904 (1998).

    Article  CAS  PubMed  Google Scholar 

  47. Withers, D.J. et al. Irs-2 coordinates Igf-1 receptor–mediated β-cell development and peripheral insulin signalling. Nat. Genet. 23, 32–40 (1999).

    Article  CAS  PubMed  Google Scholar 

  48. Aitman, T.J. et al. Identification of Cd36 (Fat) as an insulin-resistance gene causing defective fatty acid and glucose metabolism in hypertensive rats. Nat. Genet. 21, 76–83 (1999).

    Article  CAS  PubMed  Google Scholar 

  49. Yamagata, K. et al. Mutations in the hepatocyte nuclear factor-1α gene in maturity-onset diabetes of the young (MODY3). Nature 384, 455–458 (1996).

    Article  CAS  PubMed  Google Scholar 

  50. White, M.F. The IRS-signalling system: a network of docking proteins that mediate insulin action. Mol. Cell. Biochem. 182, 3–11 (1998).

    Article  CAS  PubMed  Google Scholar 

  51. Spiegelman, B.M. PPAR-γ: adipogenic regulator and thiazolidinedione receptor. Diabetes 47, 507–514 (1998).

    Article  CAS  PubMed  Google Scholar 

  52. Curtis, R.E., Yin, J., Kinnaird, P. & Xing, E.P. Finding genome-transcriptome-phenome association with structured association mapping and visualization in genamap. Pac. Symp. Biocomput. 327–338 (2012).

  53. Kim, S. & Xing, E.P. Statistical estimation of correlated genome associations to a quantitative trait network. PLoS Genet. 5, e1000587 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Kim, S., Sohn, K.A. & Xing, E.P. A multivariate regression approach to association analysis of a quantitative trait network. Bioinformatics 25, i204–i212 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lehner, B., Crombie, C., Tischler, J., Fortunato, A. & Fraser, A.G. Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways. Nat. Genet. 38, 896–903 (2006).

    Article  CAS  PubMed  Google Scholar 

  56. Higgins, J.P. & Thompson, S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002).

    Article  PubMed  Google Scholar 

  57. Anderson, S.L. et al. Familial dysautonomia is caused by mutations of the IKAP gene. Am. J. Hum. Genet. 68, 753–758 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hiromura, M. et al. YY1 is regulated by O-linked N-acetylglucosaminylation (O-glcNAcylation). J. Biol. Chem. 278, 14046–14052 (2003).

    Article  CAS  PubMed  Google Scholar 

  59. Shimoyama, Y., Nishio, K., Hamajima, N. & Niwa, T. KLOTHO gene polymorphisms G-395A and C1818T are associated with lipid and glucose metabolism, bone mineral density and systolic blood pressure in Japanese healthy subjects. Clin. Chim. Acta 406, 134–138 (2009).

    Article  CAS  PubMed  Google Scholar 

  60. Oguro, R. et al. Association of carotid atherosclerosis with genetic polymorphisms of the klotho gene in patients with hypertension. Geriatr. Gerontol. Int. 10, 311–318 (2010).

    Article  PubMed  Google Scholar 

  61. Freathy, R.M. et al. The functional “KL-VS” variant of KLOTHO is not associated with type 2 diabetes in 5028 UK Caucasians. BMC Med. Genet. 7, 51 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Mullin, B.H. et al. Klotho gene polymorphisms are associated with osteocalcin levels but not bone density of aged postmenopausal women. Calcif. Tissue Int. 77, 145–151 (2005).

    Article  CAS  PubMed  Google Scholar 

  63. Zarrabeitia, M.T. et al. Klotho gene polymorphism and male bone mass. Calcif. Tissue Int. 80, 10–14 (2007).

    Article  CAS  PubMed  Google Scholar 

  64. Reue, K., Xu, P., Wang, X.P. & Slavin, B.G. Adipose tissue deficiency, glucose intolerance, and increased atherosclerosis result from mutation in the mouse fatty liver dystrophy (fld) gene. J. Lipid Res. 41, 1067–1076 (2000).

    Article  CAS  PubMed  Google Scholar 

  65. Aulchenko, Y.S. et al. LPIN2 is associated with type 2 diabetes, glucose metabolism, and body composition. Diabetes 56, 3020–3026 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Anderson, C.A. et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat. Genet. 43, 246–252 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Franke, A. et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. Nat. Genet. 42, 1118–1125 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. McGovern, D.P. et al. Genome-wide association identifies multiple ulcerative colitis susceptibility loci. Nat. Genet. 42, 332–337 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Tang, A.T., Campbell, W.B. & Nithipatikom, K. ROCK1 feedback regulation of the upstream small GTPase RhoA. Cell. Signal. 24, 1375–1380 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Nakamura, Y. et al. Marked increase of insulin gene transcription by suppression of the Rho/Rho-kinase pathway. Biochem. Biophys. Res. Commun. 350, 68–73 (2006).

    Article  CAS  PubMed  Google Scholar 

  71. Furukawa, N. et al. Role of Rho-kinase in regulation of insulin action and glucose homeostasis. Cell Metab. 2, 119–129 (2005).

    Article  CAS  PubMed  Google Scholar 

  72. Chun, K.H. et al. In vivo activation of ROCK1 by insulin is impaired in skeletal muscle of humans with type 2 diabetes. Am. J. Physiol. Endocrinol. Metab. 300, E536–E542 (2011).

    Article  CAS  PubMed  Google Scholar 

  73. Yuneva, M.O. et al. The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metab. 15, 157–170 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Hurlbert, M.S. et al. Mice transgenic for an expanded CAG repeat in the Huntington's disease gene develop diabetes. Diabetes 48, 649–651 (1999).

    Article  CAS  PubMed  Google Scholar 

  76. Björkqvist, M. et al. The R6/2 transgenic mouse model of Huntington's disease develops diabetes due to deficient β-cell mass and exocytosis. Hum. Mol. Genet. 14, 565–574 (2005).

    Article  PubMed  CAS  Google Scholar 

  77. Bradley, S.V. et al. Degenerative phenotypes caused by the combined deficiency of murine HIP1 and HIP1r are rescued by human HIP1. Hum. Mol. Genet. 16, 1279–1292 (2007).

    Article  CAS  PubMed  Google Scholar 

  78. Hancock, D.B. et al. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat. Genet. 42, 45–52 (2010).

    Article  CAS  PubMed  Google Scholar 

  79. Cho, M.H. et al. Variants in FAM13A are associated with chronic obstructive pulmonary disease. Nat. Genet. 42, 200–202 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Nomiyama, T. et al. Osteopontin mediates obesity-induced adipose tissue macrophage infiltration and insulin resistance in mice. J. Clin. Invest. 117, 2877–2888 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Pietiläinen, K.H. et al. Global transcript profiles of fat in monozygotic twins discordant for BMI: pathways behind acquired obesity. PLoS Med. 5, e51 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Lyssenko, V. et al. Pleiotropic effects of GIP on islet function involve osteopontin. Diabetes 60, 2424–2433 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Olofsson, L.E. et al. CCAAT/enhancer binding protein α (C/EBPα) in adipose tissue regulates genes in lipid and glucose metabolism and a genetic variation in C/EBPα is associated with serum levels of triglycerides. J. Clin. Endocrinol. Metab. 93, 4880–4886 (2008).

    Article  CAS  PubMed  Google Scholar 

  84. Wu, Z. et al. Cross-regulation of C/EBPα and PPARγ controls the transcriptional pathway of adipogenesis and insulin sensitivity. Mol. Cell 3, 151–158 (1999).

    Article  CAS  PubMed  Google Scholar 

  85. Hollenberg, A.N. et al. Functional antagonism between CCAAT/enhancer binding protein-α and peroxisome proliferator–activated receptor-γ on the leptin promoter. J. Biol. Chem. 272, 5283–5290 (1997).

    Article  CAS  PubMed  Google Scholar 

  86. Keller, S.R. Role of the insulin-regulated aminopeptidase IRAP in insulin action and diabetes. Biol. Pharm. Bull. 27, 761–764 (2004).

    Article  CAS  PubMed  Google Scholar 

  87. D'Orazio, P. et al. Approved IFCC recommendation on reporting results for blood glucose (abbreviated). Clin. Chem. 51, 1573–1576 (2005).

    Article  CAS  PubMed  Google Scholar 

  88. Li, Y., Willer, C., Sanna, S. & Abecasis, G.R. Genotype imputation. Annu. Rev. Genomics Hum. Genet. 10, 387–406 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Howie, B.N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  91. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P.R. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2009).

    Article  CAS  Google Scholar 

  92. Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Mägi, R. & Morris, A.P. GWAMA: software for genome-wide association meta-analysis. BMC Bioinformatics 11, 288 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Folkersen, L. et al. Association of genetic risk variants with expression of proximal genes identifies novel susceptibility genes for cardiovascular disease. Circ. Cardiovasc. Genet. 3, 365–373 (2010).

    Article  CAS  PubMed  Google Scholar 

  96. Myers, S., Bottolo, L., Freeman, C., McVean, G. & Donnelly, P. A fine-scale map of recombination rates and hotspots across the human genome. Science 310, 321–324 (2005).

    Article  CAS  PubMed  Google Scholar 

  97. Raychaudhuri, S. et al. Genetic variants at CD28, PRDM1 and CD2/CD58 are associated with rheumatoid arthritis risk. Nat. Genet. 41, 1313–1318 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

AGES: The AGES-Reykjavik study was supported by a contract from the National Institutes of Health (N01-AG-1-2100), National Institute on Aging Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament).

ALSPAC: We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council (grant 74882), the Wellcome Trust (grants 076467 and 092731) and the University of Bristol provide core support for ALSPAC.

AMC-PAS: AMC-PAS is grateful to M.D. Trip and S. Sivapalaratnam for their input in collecting the data.

Amish: We gratefully thank our Amish community and research volunteers for their long-standing partnership in research and acknowledge the dedication of our Amish liaisons, field workers and the Amish Research Clinic staff, without whom these studies would not have been possible. The Amish studies are supported by grants and contracts from the US NIH, including R01 AG18728, R01 HL088119, U01 GM074518, U01 HL072515-06, U01 HL84756, R01 DK54261, the University of Maryland General Clinical Research Center grant M01 RR 16500, the Mid-Atlantic Nutrition Obesity Research Center grant P30 DK72488, the Baltimore Diabetes Research and Training Center grant P60DK79637 and the T32 training grant AG000219 (M.E.M.). In addition, this project was supported by National Research Initiative Competitive Grant 2007-35205-17883 from the US Department of Agriculture (USDA) National Institute of Food and Agriculture.

ARIC: We thank the staff and participants of the ARIC study for their important contributions. The Atherosclerosis Risk in Communities (ARIC) Study is carried out as a collaborative study that is supported by National Heart, Lung, and Blood Institute (NHLBI) contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022, R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and US NIH contract HHSN268200625226C. Infrastructure was partly supported by grant UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. We are grateful for resources provided by the University of Minnesota Supercomputing Institute.

ASAP: The ASAP study was funded by a donation from F. Lundberg.

ASCOT: We thank all ASCOT trial participants, physicians, nurses and practices in the participating countries for their important contributions to the study. In particular, we thank C. Muckian and D. Toomey for their help in DNA extraction, storage and handling. This work was supported by Pfizer for the ASCOT study and the collection of the ASCOT DNA repository, by Servier Research Group and by Leo Laboratories. Genotyping was funded by a Wellcome Trust Strategic Award (083948).

BLSA: The BLSA was supported in part by the Intramural Research Program of the National Institute on Aging of the US NIH. A portion of that support was through an R&D contract with the MedStar Research Institute.

Busselton Health Study (BSN): The Busselton Health Study acknowledges the generous support for the 1994/5 follow-up study from Healthway, Western Australia, the numerous Busselton community volunteers who assisted with data collection and the study participants from the Shire of Busselton. The BHS is supported by The Great Wine Estates of the Margaret River region of Western Australia.

CHS: This research at CHS was supported by NHLBI contracts N01-HC-85239, N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150 and N01-HC-45133 and NHLBI grants HL080295, HL075366, HL087652 and HL105756, with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG-023629, AG-15928, AG-20098 and AG-027058 from the National Institute on Aging (see URLs). DNA handling and genotyping were supported in part by National Center for Research Resources grant M01-RR00425 to the Cedars-Sinai General Clinical Research Center Genotyping Core and National Institute of Diabetes and Digestive and Kidney Diseases grant DK063491 to the Southern California Diabetes Endocrinology Research Center. B. Psaty serves on a Data and Safety Monitoring Board (DSMB) for a clinical trial of a device funded by the manufacturer (Zoll-Lifecor).

CLHNS: We thank the Office of Population Studies Foundation research and data collection teams and the study participants who generously provided their time for this study. This work was supported by US NIH grants DK078150, TW05596, HL085144, RR20649, ES10126 and DK56350.

CoLaus: The authors also express their gratitude to the participants in the Lausanne CoLaus study and to the investigators who have contributed to the recruitment, in particular, Y. Barreau, A.-L. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. The CoLaus study was supported by research grants from the Swiss National Science Foundation (grant 33CSCO-122661), from GlaxoSmithKline and from the Faculty of Biology and Medicine of Lausanne, Switzerland. P.V. and G.W. received an unrestricted grant from GlaxoSmithKline to build the CoLaus study.

CROATIA-Korcula: The authors collectively thank a large number of individuals for their help in organizing, planning and carrying out the field work related to the project: S. Jankovic and staff at the University of Split Medical School; B. Salzer from the biochemistry laboratory 'Salzer'; local general practitioners and nurses; and the employees of several other Croatian institutions who participated in the field work, including but not limited to the University of Rijeka; the Croatian Institute of Public Health; and the Institutes of Public Health in Split and Dubrovnik. SNP genotyping of the Korcula samples was carried out by Helmholtz Zentrum München. The work is supported by the European Union framework program 6 EUROSPAN project (contract LSHG-CT-2006-018947) and grant 216-1080315-0302 (to I.R.) from the Croatian Ministry of Science, Education and Sport. Studies carried out on the Croatian island of Korcula were supported by Medical Research Council, UK.

CROATIA-Split: The authors collectively thank a large number of individuals for their help in organizing, planning and carrying out the field work related to the project: S. Jankovic and staff at the University of Split Medical School; B. Salzer from the biochemistry laboratory 'Salzer'; local general practitioners and nurses; and the employees of several other Croatian institutions who participated in the field work. including but not limited to the University of Rijeka; the Croatian Institute of Public Health; and the Institutes of Public Health in Split and Dubrovnik. SNP genotyping of the Split samples was carried out by AROS Applied Biotechnology. The work is supported by grant 216-1080315-0302 (to I.R.) from the Croatian Ministry of Science, Education and Sport. Studies carried out in the Croatian city of Split were supported by Medical Research Council, UK.

CROATIA-Vis: The authors collectively thank a large number of individuals for their help in organizing, planning and carrying out the field work related to the project: P. Rudan and staff of the Institute for Anthropological Research in Zagreb; S. Jankovic and staff at the University of Split Medical School; A. Vorko-Jovic and staff and medical students of the Andrija Stampar School of Public Health of the Faculty of Medicine at the University of Zagreb; B. Salzer from the biochemistry laboratory 'Salzer'; local general practitioners and nurses; and the employees of several other Croatian institutions who participated in the field work. including but not limited to the University of Rijeka; the Croatian Institute of Public Health; and the Institutes of Public Health in Split and Dubrovnik. SNP genotyping of the Vis samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility at Western General Hospital. The work is supported by the European Union framework program 6 EUROSPAN project (contract LSHG-CT-2006-018947) and grant 216-1080315-0302 (to I.R.) from the Croatian Ministry of Science, Education and Sport. Studies carried out on the Croatian island of Vis were supported by Medical Research Council, UK.

DESIR: We thank all the participants of the D.E.S.I.R study, E. Eury and S. Lobbens for technical support for the genotyping and O. Lantieri and M. Marre from the D.E.S.I.R study. Genotyping was supported by the Conseil Régional Nord-Pas-de-Calais Fonds Européen de Développement Economique et Regional CPER axe Cartdiodiabète 2010–2011 grant to N.B.-N.

deCODE: We thank the individuals who participated in the study and whose contributions made this work possible. The research performed at deCODE genetics was in part funded through the European Union's Seventh Framework Programme (FP7/2007-2013) ENGAGE project, grant HEALTH-F4-2007-201413.

DIAGEN: We are grateful to all of the patients who cooperated in this study and to their referring physicians and diabetologists in Saxony. The presented study was supported by the Commission of the European Communities, Directorate C–Public Health and Risk Assessment, Health & Consumer Protection, grant agreement 2004310, and by the Dresden University of Technology Funding Grant Med Drive.

DPS: The DPS has been financially supported by grants from the Academy of Finland (117844, 40758, 211497 and 118590), the EVO funding of the Kuopio University Hospital from the Ministry of Health and Social Affairs (5254), the Finnish Funding Agency for Technology and Innovation (40058/07), the Nordic Centre of Excellence on Systems biology in controlled dietary interventions and cohort studies (SYSDIET; 070014), the Finnish Diabetes Research Foundation, the Yrjö Jahnsson Foundation (56358), the Sigrid Juselius Foundation, the Juho Vainio Foundation and TEKES grants 70103/06 and 40058/07.

DR's EXTRA: The DR's EXTRA Study was supported by grants from the Ministry of Education and Culture of Finland (627;2004-2011), the Academy of Finland (102318 and 123885), Kuopio University Hospital, the Finnish Diabetes Association, the Finnish Heart Association, the Päivikki and Sakari Sohlberg Foundation, a European Union FP6 Integrated Project (EXGENESIS, LSHM-CT-2004-005272), the city of Kuopio and the Social Insurance Institution of Finland (4/26/2010).

EAS (Metabochip): EAS was supported by the British Heart Foundation. Genotyping was supported by a grant from the Chief Scientist Office, Scotland, and was performed at the Wellcome Trust Clinical Research Facility in Edinburgh.

EGCUT: EGCUT was financed by FP7 grants (201413 and 245536), a grant from the Estonian government (SF0180142s08), the European Union through the European Regional Development Fund, in the framework of the Centre of Excellence in Genomics and a grant from the University of Tartu (SP1GVARENG).

Ely: We are grateful to all the volunteers and to the staff of St. Mary's Street Surgery, Ely and the study team. The Ely Study was funded by the MRC (MC_U106179471) and Diabetes UK. Genotyping in the Ely and Fenland studies was supported in part by an MRC-GlaxoSmithKline pilot programme grant (G0701863).

ERF: We thank the participants from Genetic Research in Isolated Populations, Erasmus Rucphen Family and their general practitioners, who made this work possible. This study is financially supported by the Netherlands Organization for Scientific Research (NWO), the European Union framework program 6 EUROSPAN project (contract LSHG-CT-2006-018947), the ENGAGE project (grant HEALTH-F4-2007-201413), the International Stichting Alzheimer Onderzoek (ISAO), Hersenstichning Nederland (HSN) and the Centre for Medical Systems Biology (CMSB 1&2) in the framework of the Netherlands Genomics Initiative (NGI).

FamHS: The Family Heart Study (FamHS) was supported by US NIH grants RO1-HL-087700 and RO1-HL-088215 (to M.A.P.) from HNLBI and RO1-DK-8925601 and RO1-DK-075681 (to I.B.B.) from NIDDK.

Fenland: The Fenland Study is funded by the Wellcome Trust and the Medical Research Council (MC_U106179471). We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams. Biochemical assays were performed by the National Institute for Health Research, Cambridge Biomedical Research Centre, Core Biochemistry Assay Laboratory, and the Cambridge University Hospitals NHS Foundation Trust, Department of Clinical Biochemistry.

FIN-D2D 2007: The FIN-D2D study has been financially supported by the hospital districts of Pirkanmaa, South Ostrobothnia and Central Finland, the Finnish National Public Health Institute (current National Institute for Health and Welfare), the Finnish Diabetes Association, the Ministry of Social Affairs and Health in Finland, the Academy of Finland (grant 129293), the Commission of the European Communities, Directorate C–Public Health (grant agreement 2004310) and Finland's Slottery Machine Association.

FINRISK/DILGOM: The DILGOM study received support from the Etelä-Pohjanmaa Hospital District, the Pohjois-Pohjanmaa Hospital District, the Keski-Suomi Hospital District, the Pirkanmaa Hospital District and the Pohjois-Savo Hospital District. The DILGOM survey was funded by the Academy of Finland (grant 118065). V.S. was supported by the Academy of Finland (grant 139635 and 129494).

Framingham Heart Study: This research was conducted in part using data and resources from the Framingham Heart Study of the NHLBI of the US NIH and the Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the NHLBI's Framingham Heart Study (contract N01-HC-25195) and its contract with Affymetrix for genotyping services (contract N02-HL-6-4278). A portion of this research used the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. The study is also supported by NIDDK R01 DK078616 to J.B.M., J.D. and J.C.F. and NIDDK K24 DK080140 to J.B.M.

FUSION: Support for FUSION was provided by NIH grants R01-DK062370 (to M. Boehnke), R01-DK072193 (to K.L.M.) and intramural project number 1Z01-HG000024 (to F.S.C.). Genome-wide genotyping was conducted by the Johns Hopkins University Genetic Resources Core Facility SNP Center at the Center for Inherited Disease Research (CIDR), with support from CIDR NIH contract N01-HG-65403.

GEMS: We thank the investigators S. Grundy, P. Barter, R. McPherson, R. Mahley, T. Bersot and A. Kesaniemi for collection of the samples. The GEMS study was sponsored in part by GlaxoSmithKline.

GENOA: We thank E. Boerwinkle and J. Cunningham for their help with genotyping. The Genetic Epidemiology Network of Arteriopathy (GENOA) study is supported by US NIH grants HL087660 and HL100245 from the NHLBI.

GenomEUtwin: We acknowledge support from the European Commission under Quality of Life and Management of the Living Resources of the Fifth Framework Program (GenomEUtwin QLG2-CT-2002-01254). The study is also supported by ENGAGE–European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement 201413.

GLACIER: The GLACIER Study is nested within the Northern Sweden Health and Disease Study, and phenotyping was conducted as part of the Västerbotten Intervention Project. We thank the participants and the investigators from these studies for their valuable contributions, with specific thanks to L. Weinehall, Å. Agren, K. Enquist and T. Johansson. The GLACIER Study and part the salary of P.W.F. were funded by grants from the Swedish Research Council, the Swedish Heart-Lung Foundation, Novo Nordisk, the Umeå Medical Research Foundation and the Swedish Diabetes Association (to P.W.F.). Genotyping for this specific project was funded by the Wellcome Trust Sanger Institute. I.B. acknowledges funding from Wellcome Trust grant 098051, the UK NIHR Cambridge Biomedical Research Centre and the MRC Centre for Obesity and Related Metabolic Diseases. We thank E. Gray, D. Simpkin, S. Hunt and the staff of the Wellcome Trust Sanger Institute Sample Logistics, Genotyping and Variation Informatics Facilities.

GoDARTS: The study was funded by the Wellcome Trust, Tenovus Tayside and the Medical Research Council, UK.

Health ABC: This study was supported by National Institute on Aging contracts N01AG62101, N01AG62103 and N01AG62106 and in part by the Intramural Research Program of the US NIH, the National Institute on Aging. The GWAS was funded by National Institute on Aging grant 1R01AG032098-01A1 to Wake Forest University Health Sciences, and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the NIH to Johns Hopkins University, contract HHSN268200782096C.

Health2000: The Health 2000 Study is funded by the National Institute for Health and Welfare (THL), the Finnish Centre for Pensions (ETK), the Social Insurance Institution of Finland (KELA), the Local Government Pensions Institution (KEVA) and other organizations listed on the website of the survey. GWAS genotyping was supported by the Wellcome Trust Sanger Institute.

InChianti: The InCHIANTI study baseline (1998–2000) was supported as a targeted project (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by the US National Institute on Aging (contracts 263 MD 9164 and 263 MD 821336).

KORA F4: We thank all members of field staff who were involved in the planning and conduct of the MONICA/KORA Augsburg studies. The MONICA/KORA Augsburg studies were financed by the Helmholtz Zentrum München–Research Center for Environment and Health and supported by grants from the German Federal Ministry of Education and Research (BMBF), the Federal Ministry of Health, the Ministry of Innovation, Science, Research and Technology of North Rhine-Westphalia, the German National Genome Research Network (NGFN) and the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ.

LEIPZIG_ADULT_IFB: We thank all those who participated in the studies. This work was supported by grants from Integrated Research and Treatment Centre (IFB) Adiposity Diseases (K7-36 to A. Körner) and from the Clinical Research Group Atherobesity KFO 152 (projects BL 833/1-1 and Stu192/6-1).

LEIPZIG_CHILHOOD_IFB: We are grateful to all the patients and families for contributing to the study. We greatly appreciate the support of the Obesity Team and the Auxo Team of the Leipzig University Children's Hospital for management of the patients and to the Pediatric Research Center Lab Team for support with DNA banking. This work was supported by grants from Integrated Research and Treatment Centre (IFB) Adiposity Diseases (K7-36 to A. Körner) and from the Clinical Research Group Atherobesity KFO 152 (projects KO3512/1-2 to A.K.).

LURIC: The authors extend appreciation to the participants in the LURIC study; without their collaboration, this article would not have been written. We thank the LURIC study team members who are either temporarily or permanently involved in patient recruitment, sample collection and data handling and the laboratory staff at the Ludwigshafen General Hospital and the Universities of Freiburg and Ulm. LURIC received funding through the Sixth Framework Programme (integrated project Bloodomics, grant LSHM-CT-2004-503485) and Seventh Framework Programme (integrated project AtheroRemo, grant agreement 201668) of the European Union.

METSIM: The METSIM study was funded by the Academy of Finland (grants 77299 and 124243).

MICROS: For the MICROS study, we thank the primary care practitioners R. Stocker, S. Waldner, T. Pizzecco, J. Plangger and U. Marcadent and the personnel of the Hospital of Silandro (Department of Laboratory Medicine) for their participation and collaboration in the research project. In South Tyrol, the study was supported by the Ministry of Health and Department of Educational Assistance, University and Research of the Autonomous Province of Bolzano and the South Tyrolean Sparkasse Foundation.

NFBC66: We thank P. Rantakallio (launch of NFBC1966 and 1986) and O. Tornwall and M. Jussila (DNA biobanking). The authors would like to acknowledge the contribution of the late Academian of Science Leena Peltonen. NFBC1986(1966) received financial support from the Academy of Finland (project grants 104781, 120315, 129269, 1114194, Center of Excellence in Complex Disease Genetics and SALVE), University Hospital Oulu, Biocenter, University of Oulu, Finland (75617), the European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643), NHLBI grant 5R01HL087679-02 through the STAMPEED program (1RL1MH083268-01), US NIH/National Institute of Mental Health (NIMH) (5R01MH63706:02), ENGAGE project and grant agreement HEALTH-F4-2007-201413, the Medical Research Council, UK (G0500539, G0600705 and PrevMetSyn/SALVE) and the Wellcome Trust (project grant GR069224). DNA extraction, sample quality control, biobank upkeeping and aliquotting were performed at the National Public Health Institute at Biomedicum Helsinki and were supported financially by the Academy of Finland and Biocentrum Helsinki.

NFBC86: The research of V.L. is funded in part through the European Community's Seventh Framework Programme (FP7/2007-2013), ENGAGE project, grant agreement HEALTH-F4-2007- 201413. The research of I.P. is funded in part through the European Community's Seventh Framework Programme (FP7/2007-2013), ENGAGE project, grant agreement HEALTH-F4-2007-201413.

NTRNESDA: Funding was obtained from the Netherlands Organization for Scientific Research (NWO; MagW/ZonMW, 904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008 and Middelgroot- 911-09-032); Spinozapremie (SPI 56-464-14192); the Center for Medical Systems Biology (CMSB) (NWO Genomics); NBIC/BioAssist/RK/2008.024; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL; 184.021.007); the VU University Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the European Science Foundation (ESF): Genomewide Analyses of European Twin and Population Cohorts (EU/QLRT-2001-01254); the European Community's Seventh Framework Program (FP7/2007-2013): ENGAGE (HEALTH-F4-2007-201413); the European Science Council (ERC) Genetics of Mental Illness (230374); Rutgers University Cell and DNA Repository cooperative agreement (NIMH U24 MH068457-06); Collaborative Study of the Genetics of DZ Twinning (US NIH R01D0042157-01A); and the Genetic Association Information Network, a public-private partnership between the NIH and Pfizer, Affymetrix and Abbott Laboratories.

ORCADES: We would like to acknowledge the invaluable contributions of L. Anderson, the research nurses in Orkney and the administrative team in Edinburgh. ORCADES was supported by the Scottish Executive Health Department, the Royal Society and the European Union Framework Programme 6 EUROSPAN project (contract LSHG-CT-2006-018947). DNA extractions were performed at the Wellcome Trust Clinical Research Facility in Edinburgh.

PIVUS: Genotyping was performed by the SNP&SEQ Technology Platform in Uppsala (see URLs). We thank T. Axelsson, A.-C. Wiman and C. Pöntinen for their excellent assistance with genotyping. The SNP Technology Platform is supported by Uppsala University, Uppsala University Hospital and the Swedish Research Council for Infrastructures. E.I. is supported by grants from the Swedish Research Council, the Swedish Heart-Lung Foundation, the Swedish Foundation for Strategic Research and the Royal Swedish Academy of Science.

PREVEND: PREVEND genetics is supported by the Dutch Kidney Foundation (grant E033), the US National Institutes of Health (grant LM010098), The Netherlands Organization for Health Research and Development (NWO VENI grant 916.761.70) and the Dutch Interuniversity Cardiology Institute Netherlands (ICIN).

PROCARDIS: The PROCARDIS study was supported by the European Community Sixth Framework Programme (LSHM-CT- 2007-037273), AstraZeneca, the British Heart Foundation, the Oxford BHF Centre of Research Excellence, the Wellcome Trust (075491/Z/04), the Swedish Research Council, the Knut and Alice Wallenberg Foundation, the Swedish Heart-Lung Foundation, the Torsten and Ragnar Söderberg Foundation, the Strategic Cardiovascular Program of Karolinska Institutet and Stockholm County Council, the Foundation for Strategic Research and the Stockholm County Council (560283).

PROSPER: The PROSPER/PHASE study has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement HEALTH-F2-2009-223004. PROSPER/PHASE is supported by grants from the Interuniversity Cardiology Institute of the Netherlands (ICIN) and the Durrer Center for Cardiogenetic Research, both of which are Institutes of the Netherlands Royal Academy of Arts and Sciences (KNAW); the Center for Medical Systems Biology (CMSB), a center of excellence approved by the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research (NWO); and the Netherlands Consortium for Healthy Ageing (NCHA). The research leading to the PROSPER study was sponsored by Bristol Myers Squibb.

Rotterdam Study: The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. We thank P. Arp, M. Jhamai, M. Verkerk, L. Herrera and M. Peters for their help in creating the GWAS database and K. Estrada and M.V. Struchalin for their support in the creation and analysis of imputed data. The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organization of Scientific Research NWO Investments (175.010.2005.011 and 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) project 050-060-810, the European Community's Seventh Framework Programme (FP7/2007-2013) and the ENGAGE project, grant agreement HEALTH-F4-2007-201413. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII) and the Municipality of Rotterdam.

SardiNIA: The authors thank all the volunteers and the mayors of the four towns involved. This work was supported in part by the Intramural Research Program of the National Institute on Aging through the US NIH and by contract NO1-AG-1-2109 from the NIA to the SardiNIA (ProgeNIA) team.

SCARFSHEEP: Funding for the study was provided by the European Commission (LSHM-CT-2007-037273), the Swedish Heart-Lung Foundation, the Swedish Research Council (2669, 8691), the Knut and Alice Wallenberg Foundation, the Foundation for Strategic Research, the Torsten and Ragnar Söderberg Foundation, the Strategic Cardiovascular Programme of Karolinska Institutet and the Stockholm County Council (560183).

SORBS: We thank all those who participated in the studies. This work was supported by grants from Integrated Research and Treatment Centre (IFB) Adiposity Diseases (K7-36 to M.S. and A. Körner), from the Clinical Research Group Atherobesity KFO 152 (projects BL 833/1-1 to M.B. and Stu192/6-1 to M.S.). R.M. acknowledges financial support from the European Commission under a Marie Curie Intra-European Fellowship. P.K. acknowledges financial support from the Boehringer Ingelheim Foundation.

SUVIMAX : This work was supported by the Institut National de la Santé et de la Recherche Médicale, the Institut National de la Recherche Agronomique, the Université Paris 13, the Centre National de Génotypage and the Commissariat à L'Energie Atomique.

Swedish Twin Registry: We thank T. Axelsson, A.-C. Wiman and C. Pöntinen for their excellent assistance with genotyping. This work was supported by grants from the US NIH (AG028555, AG08724, AG04563, AG10175 and AG08861), the Swedish Research Council, the Swedish Heart-Lung Foundation, the Swedish Foundation for Strategic Research, the Royal Swedish Academy of Science and ENGAGE (within the European Union Seventh Framework Programme, HEALTH-F4-2007-201413). Genotyping was performed by the SNP&SEQ Technology Platform (see URLs). The SNP Technology Platform is supported by Uppsala University, Uppsala University Hospital and the Swedish Research Council for Infrastructures.

THISEAS: We thank all the dieticians and clinicians for their contribution to the project. Recruitment for THISEAS was partially funded by a research grant (PENED 2003) from the Greek General Secretary of Research and Technology.

TRAILS: TRAILS (TRacking Adolescents' Individual Lives Survey) is a collaborative project involving various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen and the Parnassia Bavo group, all in The Netherlands. We are grateful to all adolescents and their parents and teachers who participated in this research and to everyone who worked on this project and made it possible. TRAILS has been financially supported by grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grants 60-60600-98-018 and 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 457-03-018, GB-MaGW 452-04-314 and GB-MaGW 452-06-004; NWO large-sized investment grant 175.010.2003.005; and NWO Longitudinal Survey and Panel Funding 481-08-013); the Sophia Foundation for Medical Research (projects 301 and 393), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006) and the participating universities. Statistical analyses were carried out on the Genetic Cluster Computer (see URLs), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation.

TwinsUK: The study was funded by the Wellcome Trust; European Community's Seventh Framework Programme (FP7/2007-2013), grant agreement HEALTH-F2-2008-201865-GEFOS, (FP7/2007-2013), ENGAGE project grant agreement HEALTH-F4-2007-201413, and the Fifth Framework Programme GenomEUtwin Project (QLG2-CT-2002-01254). The study also receives support from the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's & St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King''s College London. T.D.S. is an NIHR senior Investigator. The project also received support from a Biotechnology and Biological Sciences Research Council (BBSRC) project grant (G20234). The authors acknowledge the funding and support of the National Eye Institute via an NIH/CIDR genotyping project (to T. Young).

ULSAM: Genotyping was performed by the SNP&SEQ Technology Platform in Uppsala (see URLs). We thank T. Axelsson, A.-C. Wiman and C. Pöntinen for their excellent assistance with genotyping. The SNP Technology Platform is supported by Uppsala University, Uppsala University Hospital and the Swedish Research Council for Infrastructures. E.I. is supported by grants from the Swedish Research Council, the Swedish Heart-Lung Foundation, the Swedish Foundation for Strategic Research, and the Royal Swedish Academy of Science.

Whitehall II: The WHII study has been supported by grants from the Medical Research Council; the Economic and Social Research Council; British Heart Foundation (BHF); the Health and Safety Executive; the Department of Health; the NHLBI (HL36310), the US, NIH: National Institute on Aging (AG13196), US, NIH; the Agency for Health Care Policy Research (HS06516); and the John D. and Catherine T. MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health. Genotyping in WHII was supported by BHF grant PG/07/133/24260 and by an MRC-GlaxoSmithKline pilot programme grant (85374). S. Raychaudhuri is supported by the US NIH (K08AR055688).

Author information

Authors and Affiliations

Authors

Consortia

Contributions

Writing group: R.A.S., V.L., R.P.W., E.W., M.M., R.J.S., N.B.-N., M.I.M., P.W.F., J.B.M., T.M.T., J.C.F., C. Langenberg, E.I., I.P. and I.B. wrote the manuscript. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Jose C Florez, Claudia Langenberg, Erik Ingelsson, Inga Prokopenko or Inês Barroso.

Ethics declarations

Competing interests

I.B. and spouse own stock in GlaxoSmithKline and Incyte.

Additional information

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

Supplementary Note

41588_2012_BFng2385_MOESM34_ESM.pdf

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Supplementary Tables 1–7 (XLS 344 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Scott, R., Lagou, V., Welch, R. et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 44, 991–1005 (2012). https://doi.org/10.1038/ng.2385

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.2385

This article is cited by

Search

Quick links