Use of Multiple Metabolic and Genetic Markers to Improve the Prediction of Type 2 Diabetes: the EPIC-Potsdam Study  

Oleh:

Schulze, Matthias B. ; Weikert, Cornelia ; Pischon, Tobias ; Bergmann, Manuela M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Diabetes Care vol. 32 no. 11 (Nov. 2009), page 2116-2119.
Topik: DIABETES MELLITUS; DIABETES; single nucleotide polymorphisms (SNPs); receiver operatoring characteristic (ROC);

Ketersediaan

Perpustakaan FK Nomor Panggil: D05.K.2009.03 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

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, ?-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.

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