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

Geoffrey A. Walford, Bianca C. Porneala, Marco Dauriz, Jason L. Vassy, Susan Cheng, Eugene P. Rhee, Thomas J. Wang, James B. Meigs, Robert E. Gerszten, Jose C. Florez

Research output: Contribution to journalArticlepeer-review

80 Scopus citations

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 wasmodeledwith a 62-SNP GRS, ninemetabolites, 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.

Original languageEnglish (US)
Pages (from-to)2508-2514
Number of pages7
JournalDiabetes care
Volume37
Issue number9
DOIs
StatePublished - Sep 2014
Externally publishedYes

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Advanced and Specialized Nursing

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