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Genome–wide association studies provide new insights into type 2 diabetes aetiology

Nature Reviews Genetics volume 8, pages 657–662 (2007)Cite this article

Abstract

Human geneticists are currently in the middle of a race. Thanks to a new technology in the form of 'genome-wide chips', investigators can potentially find many novel disease genes in one large experiment. Type 2 diabetes has been hot out of the blocks with six recent publications that together provide convincing evidence for six new gene regions involved in the condition. Together with candidate approaches, these studies have identified 11 confirmed genomic regions that alter the risk of type 2 diabetes in the European population. One of these regions, the fat mass and obesity associated gene (FTO), represents by far the best example of an association between common variation and fat mass in the general population.

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Figure 1: Distribution of body mass index in type 2 diabetic patients compared with non-diabetic individuals of a similar age.
Figure 2: Effect sizes of the 11 common variants confirmed to be involved in type 2 diabetes risk.
Figure 3: Association statistics from one of the five type 2 diabetes genome-wide association studies20.

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References

  1. Neel, J. V. in The Genetics of Diabetes Mellitus (eds Creutzfeldt, W., Kobberling, J. & Neel, J. V.) 1–11 (Springer, Berlin; New York, 1976).

    Book  Google Scholar 

  2. O'Rahilly, S., Wainscoat, J. S. & Turner, R. C. Type 2 (non-insulin-dependent) diabetes. New genetics for old nightmares. Diabetologia 31, 407–414 (1988).

    Article  CAS  Google Scholar 

  3. Horikawa, Y. et al. Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus. Nature Genet. 26, 163–175 (2000).

    Article  CAS  Google Scholar 

  4. Florez, J. C. et al. Haplotype structure and genotype–phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region. Diabetes 53, 1360–1368 (2004).

    Article  CAS  Google Scholar 

  5. Gloyn, A. L. et al. Large-scale association studies of variants in genes encoding the pancreatic β-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes 52, 568–572 (2003).

    Article  CAS  Google Scholar 

  6. Nielsen, E. M. et al. The E23K variant of Kir6.2 associates with impaired post-OGTT serum insulin response and increased risk of type 2 diabetes. Diabetes 52, 573–577 (2003).

    Article  CAS  Google Scholar 

  7. Altshuler, D. et al. The common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nature Genet. 26, 76–80 (2000).

    Article  CAS  Google Scholar 

  8. Gudmundsson, J. et al. Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes. Nature Genet. 39, 977–983 (2007).

    Article  CAS  Google Scholar 

  9. Winckler, W. et al. Evaluation of common variants in the six known maturity-onset diabetes of the young (MODY) genes for association with type 2 diabetes. Diabetes 56, 685–693 (2007).

    Article  CAS  Google Scholar 

  10. Sandhu, M. S. et al. Common variants in WFS1 confer risk of type 2 diabetes. Nature Genet. 39, 951–953 (2007).

    Article  CAS  Google Scholar 

  11. Barroso, I. et al. Dominant negative mutations in human PPARγ are associated with severe insulin resistance, diabetes mellitus and hypertension. Nature 402, 880–883 (1999).

    Article  CAS  Google Scholar 

  12. Gloyn, A. L. et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N. Engl. J. Med. 350, 1838–1849 (2004).

    Article  CAS  Google Scholar 

  13. Inoue, H. et al. A gene encoding a transmembrane protein is mutated in patients with diabetes mellitus and optic atrophy (Wolfram syndrome). Nature Genet. 20, 143–148 (1998).

    Article  CAS  Google Scholar 

  14. Nishigori, H. et al. Frameshift mutation, A263fsinsGG, in the hepatocyte nuclear factor-1β gene associated with diabetes and renal dysfunction. Diabetes 47, 1354–1355 (1998).

    CAS  PubMed  Google Scholar 

  15. Grant, S. F. et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nature Genet. (2006).

  16. 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 

  17. 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 

  18. 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 

  19. Steinthorsdottir, V. et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nature Genet. 39, 770–775 (2007).

    Article  CAS  Google Scholar 

  20. Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007).

    Article  CAS  Google Scholar 

  21. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  22. 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  Google Scholar 

  23. Chanock, S. J. et al. Replicating genotype-phenotype associations. Nature 447, 655–660 (2007).

    Article  CAS  Google Scholar 

  24. Bort, R., Martinez-Barbera, J. P., Beddington, R. S. & Zaret, K. S. HEX homeobox gene-dependent tissue positioning is required for organogenesis of the ventral pancreas. Development 131, 797–806 (2004).

    Article  CAS  Google Scholar 

  25. Helgadottir, A. et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316, 1491–1493 (2007).

    Article  CAS  Google Scholar 

  26. McPherson, R. et al. A common allele on chromosome 9 associated with coronary heart disease. Science 316, 1488–1491 (2007).

    Article  CAS  Google Scholar 

  27. Krishnamurthy, J. et al. p16INK4a induces an age-dependent decline in islet regenerative potential. Nature 443, 453–537 (2006).

    Article  CAS  Google Scholar 

  28. Ubeda, M., Rukstalis, J. M. & Habener, J. F. Inhibition of cyclin-dependent kinase 5 activity protects pancreatic β-cells from glucotoxicity. J. Biol. Chem. 281, 28858–28864 (2006).

    Article  CAS  Google Scholar 

  29. Wei, F. Y. et al. Cdk5-dependent regulation of glucose-stimulated insulin secretion. Nature Med. 11, 1104–1108 (2005).

    Article  CAS  Google Scholar 

  30. van der Hoeven, F. et al. Programmed cell death is affected in the novel mouse mutant Fused toes (Ft). Development 120, 2601–2607 (1994).

    CAS  PubMed  Google Scholar 

  31. Pearson, E. et al. Variation in TCF7L2 influences glycemic response to sulfonylureas. Diabetes 56, 2178–2182 (2007).

    Article  CAS  Google Scholar 

  32. Easton, D. F. et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447, 1087–1093 (2007).

    Article  CAS  Google Scholar 

  33. Dina, C. et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nature Genet. 39, 724–726 (2007).

    Article  CAS  Google Scholar 

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Acknowledgements

I would like to thank specifically M. Weedon and R. Freathy for help and advice on the article, and more generally all my colleagues in Exeter and Oxford with whom I worked on the UK type 2 diabetes genome-wide study.

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Authors and Affiliations

  1. Genetics of Complex Traits, Institute of Biomedical and Clinical Sciences, Peninsula Medical School, University of Exeter, Exeter, EX1 2LV, UK

    Timothy M. Frayling

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DATABASES

OMIM

bipolar disorder

Crohn disease

hypertension

early myocardial infarction

rheumatoid arthritis

type 1 diabetes

type 2 diabetes

Wolfram syndrome

FURTHER INFORMATION

deCoDe genetics

Haploview

Glossary

Body mass index

(BMI). BMI is an easy way of estimating how fat people are. It is measured as weight in kilograms divided by height in metres squared (kg/m2). A BMI < 25 is considered normal, ≥25 to <30 overweight and ≥30 obese.

Deep sequencing

Systematic sequencing of contiguous sequence in many individuals.

Linkage disequilibrium

A measure of associations between alleles at different loci, which indicates whether particular haplotypes are more common than expected. We use the r2 definition, which equates directly to power. For example, an r2 of 0.8 equates to 80% power.

Odds ratio

A measurement of association in case–control studies, defined as the odds of exposure to the susceptibility allele in cases compared with that in controls. If the odds ratio is significantly greater than one, then the allele is associated with an increased risk of the disease.

Population admixture

A process that leads to a composite gene pool in which at least some individuals come from more than one population.

r2 value

A standard way of quantifying the degree of correlation between polymorphisms. An r2 of 1 indicates that the two variants would give exactly the same genotypes for an individual.

Sibling relative risk

The chance of being affected by a condition if a sibling is affected, relative to a member of the general population. Siblings of people with type 2 diabetes are three to four times more likely to develop the illness than others.

Tagging

Identifying subsets of markers ('tags') that describe patterns of association or haplotypes among larger marker sets. Tag SNPs are single nucleotide polymorphisms that are correlated with, and therefore can serve as a proxy for, common variation in a region that has not been directly analysed.

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Frayling, T. Genome–wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev Genet 8, 657–662 (2007). https://doi.org/10.1038/nrg2178

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