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Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study

Item Type:Article
Title:Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study
Creators Name:Schulze, M.B. and Weikert, C. and Pischon, T. and Bergmann, M.M. and Al-Hasani, H. and Schleicher, E. and Fritsche, A. and Haering, H.U. and Boeing, H. and Joost, H.G.
Abstract:OBJECTIVE: We investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors. RESEARCH DESIGN AND METHODS: A case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2 diabetes cases identified in the cohort during 7 years of follow-up, 579 remained for analyses after exclusions. Prediction models were compared by receiver operatoring characteristic (ROC) curve and integrated discrimination improvement. RESULTS: Case-control discrimination by the lifestyle characteristics (ROC-AUC: 0.8465) improved with plasma glucose (ROC-AUC: 0.8672, P < 0.001) and A1C (ROC-AUC: 0.8859, P < 0.001). ROC-AUC further improved with HDL cholesterol, triglycerides, gamma-glutamyltransferase, and alanine aminotransferase (0.9000, P = 0.002). Twenty SNPs did not improve discrimination beyond these characteristics (P = 0.69). CONCLUSIONS: Metabolic markers, but not genotyping for 20 diabetogenic SNPs, improve discrimination of incident type 2 diabetes beyond lifestyle risk factors.
Keywords:Alanine Transaminase, Area Under Curve, Biological Markers, Blood Glucose, Case-Control Studies, HDL Cholesterol, Cohort Studies, Type 2 Diabetes Mellitus, Genetic Markers, Genotype, Germany, Glycosylated Hemoglobin A, Single Nucleotide Polymorphism, Predictive Value of Tests, Prospective Studies, ROC Curve, Risk Assessment, {gamma}-Glutamyltransferase
Source:Diabetes Care
ISSN:0149-5992
Publisher:American Diabetes Association
Volume:32
Number:11
Page Range:2116-2119
Date:November 2009
Official Publication:https://doi.org/10.2337/dc09-0197
PubMed:View item in PubMed

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