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. 2008 Nov;57(11):3122-8.
doi: 10.2337/db08-0425. Epub 2008 Aug 11.

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

Mandy van Hoek  1 , Abbas Dehghan, Jacqueline C M Witteman, Cornelia M van Duijn, André G Uitterlinden, Ben A Oostra, Albert Hofman, Eric J G Sijbrands, A Cecile J W Janssens
Affiliations

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

Mandy van Hoek et al. Diabetes. 2008 Nov.

Abstract

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 18 polymorphisms from recent GWA studies on type 2 diabetes in the Rotterdam Study, a prospective, population-based study among homogeneous Caucasian individuals of 55 years and older (genotyped subjects, n = 6,544; 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 18 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 (0.63-0.68) for age, sex, and BMI; and 0.68 (0.66-0.71) for the genetic polymorphisms and clinical characteristics combined.

Conclusions: We showed that 9 of 18 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.

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Figures

FIG. 1.
FIG. 1.
Odds ratios for type 2 diabetes according to the number of risk alleles carried.
FIG. 2.
FIG. 2.
Correlation of predicted type 2 diabetes risks with the risk allele score. Predicted risks of type 2 diabetes were obtained from the logistic regression model with 18 genetic polymorphisms as independent categorical variables.
FIG. 3.
FIG. 3.
ROC curves for prediction of incident type 2 diabetes based on 18 genetic polymorphisms, clinical characteristics (age, sex, and BMI), and both.
See this image and copyright information in PMC

Comment in

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