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Diabetes Care. 2009 Nov;32(11):2116-9. doi: 10.2337/dc09-0197. Epub 2009 Aug 31.

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

Author information

1
Public Health Nutrition Unit, Technische Universität München, Freising, Germany. matthias.schulze@wzw.tum.de

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.

PMID:
19720844
PMCID:
PMC2768223
DOI:
10.2337/dc09-0197
[Indexed for MEDLINE]
Free PMC Article
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