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Diabetes Publish Ahead of Print published online ahead of print August 11, 2008
DOI: 10.2337/db08-0425
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Original Research

Predicting type 2 diabetes based on polymorphisms from genome wide association studies: a population-based study

Mandy van Hoek, MD1,2, Abbas Dehgan, MD2, Jacqueline C.M. Witteman, PhD2, Cornelia M. van Duijn, PhD2,3, André G. Uitterlinden, MD, PhD1,2, Ben A. Oostra, PhD2,3, Albert Hofman, MD, PhD2, Eric J.G. Sijbrands, MD, PhD1, and A.Cecile J.W. Janssens, PhD4

1Department of Internal Medicine,
2Epidemiology & Biostatistics
3Clinical Genetics, Genetic Epidemiology Unit and
4Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands

Objective: Prediction of type 2 diabetes based on genetic testing might improve identification of high-risk subjects. Genome Wide Association (GWA) studies identified multiple new genetic variants that associate with type 2 diabetes. The predictive value of genetic testing for prediction of type 2 diabetes in the general population is unclear.

Research Design and Methods: We investigated eighteen polymorphisms from recent GWA studies on type 2 diabetes in the Rotterdam study, a prospective, population-based study among homogeneous Caucasian individuals of 55years and older. (genotyped subjects n=6544; prevalent cases, n=686; incident cases during follow-up, n=601; mean follow-up 10.6 years). The predictive value of these polymorphisms was examined alone and in addition to clinical characteristics using logistic and Cox regression analyses. The discriminative accuracy of the prediction models was assessed by the Area under the Receiver Operating Characteristic curves (AUCs).

Results: Of the eighteen polymorphisms, the ADAMTS9, CDKAL1, CDKN2A/B-rs1412829, FTO, IGF2BP2, JAZF1, SLC30A8, TCF7L2 and WFS1 variants were associated with type 2 diabetes risk in our population. The AUC was 0.60(95% CI 0.57-0.63) for prediction based on the genetic polymorphisms, 0.66(95% CI 0.63-0.68) for age, sex and BMI and 0.68(95% CI 0.66-0.71) for the genetic polymorphisms and clinical characteristics combined.

Conclusions: We showed that nine out of eighteen well-established genetic risk variants were associated with type 2 diabetes in a population-based study. Combining genetic variants has low predictive value for future type 2 diabetes at a population-based level. The genetic polymorphisms only marginally improved the prediction of type 2 diabetes beyond clinical characteristics.

Correspondence: e.sijbrands{at}erasmusmc.nl


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M. J. Khoury, R. Valdez, and A. Albright
Public Health Genomics Approach to Type 2 Diabetes
Diabetes, November 1, 2008; 57(11): 2911 - 2914.
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