Is genetic testing useful to predict type 2 diabetes?

Abstract

The early identification of individuals at risk for type 2 diabetes (T2D) enables prevention. Recent genome-wide association studies (GWAS) have added at least 40 genetic variants to the list of already well characterized T2D risk predictors, including family history, obesity, and elevated fasting plasma glucose levels. Although these variants can significantly predict T2D alone and as a part of genotype risk scores, they do not yet offer clinical discrimination beyond that achieved with common clinical measurements. Future progress on at least two research fronts may improve the predictive performance of genotype information. First, expanded GWAS efforts in non-European populations will allow targeted sequencing of risk loci and the identification of true causal variants. Second, studies with longer prediction time horizons may demonstrate that genotype information performs better than clinical risk predictors over a longer period of the life course. At present, however, genetic testing cannot be recommended for clinical T2D risk prediction in adults.

Fig. 1

ROC curves for five type 2 diabetes prediction models from Framingham Offspring Study. The four clinical models have higher C statistics than the personal model. Reprinted with permission from Wilson, et al. Arch Intern Med. 2007;167(10):1068–1074. Copyright © 2007 American Medical Association. All rights reserved.

Fig. 2

The 28-year cumulative incidence of type 2 diabetes by genotype risk score in 2377 participants in the Framingham Offspring Study. Reprinted with permission from the Massachusetts Medical Society, Copyright^© 2008.

Fig. 3

Baseline ages and time horizons of six prospective studies reporting genetic prediction of type 2 diabetes.^,,,, Arrow origins and bars correspond to mean age +/−1 standard deviation and arrow length corresponds to mean follow-up time, unless otherwise noted. ^aMedian baseline age and interquartile range are shown. ^bMedian follow-up time is shown.