Metabolite Traits and Genetic Risk Provide Complementary Information for the Prediction of Future Type 2 Diabetes | Zendy

Geoffrey Walford | Zendy; Bianca Porneala | Zendy; Marco Dauriz | Zendy; Jason L. Vassy | Zendy; Susan Cheng | Zendy; Eugene P. Rhee | Zendy; Thomas J. Wang | Zendy; James B. Meigs | Zendy; Robert E. Gerszten | Zendy; José C. Florez | Zendy

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Metabolite Traits and Genetic Risk Provide Complementary Information for the Prediction of Future Type 2 Diabetes

Author(s) -

Geoffrey Walford,

Bianca Porneala,

Marco Dauriz,

Jason L. Vassy,

Susan Cheng,

Eugene P. Rhee,

Thomas J. Wang,

James B. Meigs,

Robert E. Gerszten,

José C. Florez

Publication year - 2014

Publication title -

diabetes care

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 6.636

H-Index - 363

eISSN - 1935-5548

pISSN - 0149-5992

DOI - 10.2337/dc14-0560

Subject(s) - type 2 diabetes , metabolite , medicine , framingham risk score , diabetes mellitus , single nucleotide polymorphism , logistic regression , area under the curve , odds ratio , endocrinology , bioinformatics , oncology , genotype , genetics , biology , disease , gene

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.

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