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Diabetes Care. 2014 Sep;37(9):2508-14. doi: 10.2337/dc14-0560. Epub 2014 Jun 19.

Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes.

Author information

1
Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Diabetes Unit, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA gwalford@partners.org jcflorez@partners.org.
2
General Medicine Division, Massachusetts General Hospital, Boston, MA.
3
Department of Medicine, Harvard Medical School, Boston, MA General Medicine Division, Massachusetts General Hospital, Boston, MA Division of Endocrinology and Metabolic Diseases, Department of Medicine, University of Verona Medical School and Hospital Trust of Verona, Verona, Italy.
4
Department of Medicine, Harvard Medical School, Boston, MA Section of General Internal Medicine, VA Boston Healthcare System, Boston, MA Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA.
5
Department of Medicine, Harvard Medical School, Boston, MA Cardiovascular Division, Brigham and Women's Hospital, Boston, MA.
6
Department of Medicine, Harvard Medical School, Boston, MA Renal Division, Massachusetts General Hospital, Boston, MA.
7
Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN.
8
Department of Medicine, Harvard Medical School, Boston, MA General Medicine Division, Massachusetts General Hospital, Boston, MA Framingham Heart Study of the National Heart, Lung, and Blood Institute, Framingham, MA.
9
Department of Medicine, Harvard Medical School, Boston, MA Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA Cardiology Division, Massachusetts General Hospital, Boston, MA.
10
Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Diabetes Unit, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA gwalford@partners.org jcflorez@partners.org.

Abstract

OBJECTIVE:

A genetic risk score (GRS) comprised of single nucleotide polymorphisms (SNPs) and metabolite biomarkers have each been shown, separately, to predict incident type 2 diabetes. We tested whether genetic and metabolite markers provide complementary information for type 2 diabetes prediction and, together, improve the accuracy of prediction models containing clinical traits.

RESEARCH DESIGN AND METHODS:

Diabetes risk was modeled with a 62-SNP GRS, nine metabolites, and clinical traits. We fit age- and sex-adjusted logistic regression models to test the association of these sources of information, separately and jointly, with incident type 2 diabetes among 1,622 initially nondiabetic participants from the Framingham Offspring Study. The predictive capacity of each model was assessed by area under the curve (AUC).

RESULTS:

Two hundred and six new diabetes cases were observed during 13.5 years of follow-up. The AUC was greater for the model containing the GRS and metabolite measurements together versus GRS or metabolites alone (0.820 vs. 0.641, P < 0.0001, or 0.820 vs. 0.803, P = 0.01, respectively). Odds ratios for association of GRS or metabolites with type 2 diabetes were not attenuated in the combined model. The AUC was greater for the model containing the GRS, metabolites, and clinical traits versus clinical traits only (0.880 vs. 0.856, P = 0.002).

CONCLUSIONS:

Metabolite and genetic traits provide complementary information to each other for the prediction of future type 2 diabetes. These novel markers of diabetes risk modestly improve the predictive accuracy of incident type 2 diabetes based only on traditional clinical risk factors.

PMID:
24947790
PMCID:
PMC4140156
DOI:
10.2337/dc14-0560
[Indexed for MEDLINE]
Free PMC Article

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