Journal of Molecular Medicine

, Volume 86, Issue 3, pp 341–348 | Cite as

Analysis of novel risk loci for type 2 diabetes in a general French population: the D.E.S.I.R. study

  • Stéphane Cauchi
  • Christine Proença
  • Hélène Choquet
  • Stefan Gaget
  • Franck De Graeve
  • Michel Marre
  • Beverley Balkau
  • Jean Tichet
  • David Meyre
  • Martine Vaxillaire
  • Philippe Froguel
  • D.E.S.I.R. Study Group
Rapid Communication


Recently, Genome Wide Association (GWA) studies identified novel single nucleotide polymorphisms (SNPs), highly associated with type 2 diabetes (T2D) in several case-control studies of European descent. However, the impact of these markers on glucose homeostasis in a population-based study remains to be clarified.

The French prospective D.E.S.I.R. study (N = 4,707) was genotyped for 22 polymorphisms within 14 loci showing nominal to strong association with T2D in recently published GWA analyses (CDKAL1, IGFBP2, CDKN2A/2B, EXT2, HHEX, LOC646279, SLC30A8, MMP26, KCTD12, LDLR, CAMTA1, LOC38776, NGN3 and CXCR4). We assessed their effects on quantitative traits related to glucose homeostasis in 4,283 normoglycemic middle-aged participants at baseline and their contribution to T2D incidence during 9 years of follow-up.

Individuals carrying T2D risk alleles of CDKAL1 or SLC30A8 had lower fasting plasma insulin level (rs7756992 P = 0.003) or lower basal insulin secretion (rs13266634 P = 0.0005), respectively, than non-carriers. Furthermore, NGN3 and MMP26 risk alleles associated with higher fasting plasma glucose levels (rs10823406 P = 0.01 and rs2499953 P = 0.04, respectively). However, for these SNPs, only modest associations were found with a higher incidence of T2D: hazard ratios of 2.03 [1.00–4.11] for MMP26 (rs2499953 P = 0.05) and 1.33 [1.02–1.73] for NGN3 (rs10823406 P = 0.03).

We confirmed deleterious effects of SLC30A8, CDKAL1, NGN3 and MMP26 risk alleles on glucose homeostasis in the D.E.S.I.R. prospective cohort. However, in contrast to TCF7L2, the contribution of novel loci to T2D incidence seems only modest in the general middle-aged French population and should be replicated in larger cohorts.


Diabetes Genetics Metabolic Disease 

Supplementary material

109_2007_295_MOESM1_ESM.doc (36 kb)
Supplementary Table 1Clinical characteristics of the D.E.S.I.R. population at baseline (DOC 36.0 KB)


  1. 1.
    Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445:881–885PubMedCrossRefGoogle Scholar
  2. 2.
    Zeggini E, Weedon MN, Lindgren CM et al (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316:1336–1341PubMedCrossRefGoogle Scholar
  3. 3.
    Scott LJ, Mohlke KL, Bonnycastle LL et al (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316:1341–1345PubMedCrossRefGoogle Scholar
  4. 4.
    Saxena R, Voight BF, Lyssenko V et al (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331–1336PubMedCrossRefGoogle Scholar
  5. 5.
    Steinthorsdottir V, Thorleifsson G, Reynisdottir I et al (2007) A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet 39:770–775PubMedCrossRefGoogle Scholar
  6. 6.
    Hattersley AT, McCarthy MI (2005) What makes a good genetic association study. Lancet 366:1315–1323PubMedCrossRefGoogle Scholar
  7. 7.
    Balkau B (1996) An epidemiologic survey from a network of French Health Examination Centres, (D.E.S.I.R.): epidemiologic data on the insulin resistance syndrome. Rev Epidemiol Sante Publique 44:373–375PubMedGoogle Scholar
  8. 8.
    Balkau B, Eschwege E, Tichet J et al (1997) Proposed criteria for the diagnosis of diabetes: evidence from a French epidemiological study (D.E.S.I.R.). Diabetes Metab 23:428–434PubMedGoogle Scholar
  9. 9.
    Cauchi S, Meyre D, Choquet H et al (2006) TCF7L2 variation predicts hyperglycemia incidence in a French general population: the data from an epidemiological study on the Insulin Resistance Syndrome (DESIR) study. Diabetes 55:3189–3192PubMedCrossRefGoogle Scholar
  10. 10.
    Meyre D, Bouatia-Naji N, Vatin V et al (2007) ENPP1 K121Q polymorphism and obesity, hyperglycaemia and type 2 diabetes in the prospective DESIR Study. Diabetologia 50:2090–2096PubMedCrossRefGoogle Scholar
  11. 11.
    Pascoe L, Tura A, Patel SK et al (2007) Common variants of the novel type 2 diabetes genes, CDKAL1 and HHEX/IDE, are associated with decreased pancreatic {beta}-cell function. Diabetes 56(12):3101–4PubMedCrossRefGoogle Scholar
  12. 12.
    Staiger H, Machicao F, Stefan N et al (2007) Polymorphisms within novel risk loci for type 2 diabetes determine beta-cell function. PLoS ONE 2:e832PubMedCrossRefGoogle Scholar
  13. 13.
    Chimienti F, Favier A, Seve M (2005) ZnT-8, a pancreatic beta-cell-specific zinc transporter. Biometals 18:313–317PubMedCrossRefGoogle Scholar
  14. 14.
    Chimienti F, Devergnas S, Pattou F et al (2006) In vivo expression and functional characterization of the zinc transporter ZnT8 in glucose-induced insulin secretion. J Cell Sci 119:4199–4206PubMedCrossRefGoogle Scholar
  15. 15.
    Wei FY, Nagashima K, Ohshima T et al (2005) Cdk5-dependent regulation of glucose-stimulated insulin secretion. Nat Med 11:1104–1108PubMedCrossRefGoogle Scholar
  16. 16.
    Hayes MG, Pluzhnikov A, Miyake K et al (2007) Identification of type 2 diabetes genes in Mexican Americans through genome-wide association studies. Diabetes 56(12):3033–44PubMedCrossRefGoogle Scholar
  17. 17.
    Hanson RL, Bogardus C, Duggan D et al (2007) A search for variants associated with young-onset type 2 diabetes in American Indians in a 100 k genotyping array. Diabetes 56(12):3045–52PubMedCrossRefGoogle Scholar
  18. 18.
    Rampersaud E, Damcott CM, Fu M et al (2007) 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(12):3053–62PubMedCrossRefGoogle Scholar
  19. 19.
    Florez JC, Manning AK, Dupuis J et al (2007) A 100 k genome-wide association scan for diabetes and related traits in the Framingham heart study: replication and integration with other genome-wide datasets. Diabetes 56(12):3063–74PubMedCrossRefGoogle Scholar
  20. 20.
    Mellitzer G, Bonne S, Luco RF et al (2006) IA1 is NGN3-dependent and essential for differentiation of the endocrine pancreas. Embo J 25:1344–1352PubMedCrossRefGoogle Scholar
  21. 21.
    Marchenko ND, Marchenko GN, Weinreb RN et al (2004) Beta-catenin regulates the gene of MMP-26, a novel metalloproteinase expressed both in carcinomas and normal epithelial cells. Int J Biochem Cell Biol 36:942–956PubMedCrossRefGoogle Scholar
  22. 22.
    Grarup N, Rose CS, Andersson EA et al (2007) Studies of association of variants near the HHEX, CDKN2A/B and IGF2BP2 genes with type 2 diabetes and impaired insulin release in 10,705 Danish subjects validation and extension of genome-wide association studies. Diabetes 56(12):3105–11PubMedCrossRefGoogle Scholar
  23. 23.
    Schulze MB, Al-Hasani H, Boeing H et al (2007) Variation in the HHEX-IDE gene region predisposes to type 2 diabetes in the prospective, population-based EPIC-Potsdam cohort. Diabetologia 50:2405–2407PubMedCrossRefGoogle Scholar
  24. 24.
    Bort R, Martinez-Barbera JP, Beddington RS et al (2004) Hex homeobox gene-dependent tissue positioning is required for organogenesis of the ventral pancreas. Development 131:797–806PubMedCrossRefGoogle Scholar
  25. 25.
    Frayling TM (2007) Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev Genet 8:657–662PubMedCrossRefGoogle Scholar
  26. 26.
    Krishnamurthy J, Ramsey MR, Ligon KL et al (2006) p16INK4a induces an age-dependent decline in islet regenerative potential. Nature 443:453–457PubMedCrossRefGoogle Scholar
  27. 27.
    Pasmant E, Laurendeau I, Heron D et al (2007) Characterization of a germ-line deletion, including the entire INK4/ARF locus, in a melanoma-neural system tumor family: identification of ANRIL, an antisense noncoding RNA whose expression coclusters with ARF. Cancer Res 67:3963–3969PubMedCrossRefGoogle Scholar
  28. 28.
    Alvarsson M, Wajngot A, Cerasi E et al (2005) K-value and low insulin secretion in a non-obese white population: predicted glucose tolerance after 25 years. Diabetologia 48:2262–2268PubMedCrossRefGoogle Scholar
  29. 29.
    Hinds DA, Stuve LL, Nilsen GB et al (2005) Whole-genome patterns of common DNA variation in three human populations. Science 307:1072–1079PubMedCrossRefGoogle Scholar
  30. 30.
    American Diabetes Association (1997) Clinical practice recommendations 1997. Diabetes Care 20(Suppl 1):S1–70Google Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Stéphane Cauchi
    • 1
  • Christine Proença
    • 1
  • Hélène Choquet
    • 1
  • Stefan Gaget
    • 1
  • Franck De Graeve
    • 1
  • Michel Marre
    • 2
    • 3
  • Beverley Balkau
    • 4
    • 5
  • Jean Tichet
    • 6
  • David Meyre
    • 1
  • Martine Vaxillaire
    • 1
  • Philippe Froguel
    • 1
    • 7
  • D.E.S.I.R. Study Group
    • 6
  1. 1.CNRS 8090-Institute of BiologyPasteur InstituteLilleFrance
  2. 2.René Diderot-Paris 7 UniversityParisFrance
  3. 3.Department of Endocrinology-Diabetology and NutritionBichat Claude Bernard HospitalParisFrance
  4. 4.INSERM U780-IFR69VillejuifFrance
  5. 5.University of Paris-SudParisFrance
  6. 6.Regional Institute for HealthLa RicheFrance
  7. 7.Imperial College, Section of Genomic MedicineImperial College London, Hammersmith HospitalLondonUK

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