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Genomics of type 2 diabetes mellitus: implications for the clinician

Nature Reviews Endocrinology volume 5, pages 429–436 (2009)Cite this article

Abstract

Our understanding of the genetics of type 2 diabetes mellitus (T2DM) has changed, in part owing to implementation of genome-wide association studies as a method for unraveling the genetic architecture of complex traits. These studies enable a global search throughout the nuclear genome for variants that are associated with specific phenotypes. Currently, single nucleotide polymorphisms in about 24 different genetic loci have been associated with T2DM. Most of these genetic loci are associated with the insulin secretion pathway rather than insulin resistance. Study design, heritability differences and the intrinsic properties of in vivo insulin resistance measures might partially explain why only a few loci associated with insulin resistance have been detected through genome-wide association approaches. Despite the success of these approaches at detecting loci associated with T2DM, currently known associations explain only a small amount of the genetic variance involved in the disease. Compared with previous studies, larger cohorts might be needed to identify variants of smaller effect sizes and lower allele frequencies. Finally, the current list of genetic loci that are related to T2DM does not seem to offer greater predictive value in determining diabetes risk than do commonly used phenotypic risk factors and family history.

Key Points

  • Family and twin studies have demonstrated that type 2 diabetes mellitus has a substantial genetic component

  • Linkage analysis can be useful to find mutations that cause monogenic diabetes, such as maturity-onset diabetes of the young

  • Genome-wide association studies have been useful as a global screen for loci that might be involved in common forms of type 2 diabetes mellitus

  • Most of the diabetes-related genes that have been discovered so far seem to be involved in insulin secretion, not insulin resistance

  • Incorporation of the currently known diabetes-related polymorphisms into diabetes prediction models does not markedly improve their predictive ability compared with commonly measured phenotypic risk factors and family history

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Figure 1: Statistical power of the DIAGRAM meta-analysis (n = 9,562) to detect diabetes-related variants of different ORs across various risk allele frequencies, assuming complete coverage.36
Figure 2: ROC curves for the 'simple clinical model' in Framingham Heart Study participants with and without the genotype score.77

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Acknowledgements

E. S. Stolerman is supported by NIH Training Grant T32 GM007748 in Genetics. J. C. Florez is supported by a Physician Scientist Development Award by the Massachusetts General Hospital and a Clinical Scientist Development Award from the Doris Duke Charitable Foundation.

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  1. Diabetes Unit–Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA

    Elliot S. Stolerman & Jose C. Florez

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J. C. Florez declares having received one-time consulting fees from the following companies: Merck, Pfizer, bioStrategies Group, XOMA and Publicis Healthcare Communications Group (engaged by Amylin Pharmaceuticals). E. S. Stolerman declares no competing interests.

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Stolerman, E., Florez, J. Genomics of type 2 diabetes mellitus: implications for the clinician. Nat Rev Endocrinol 5, 429–436 (2009). https://doi.org/10.1038/nrendo.2009.129

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