Details

Autor(en) / Beteiligte

• MENNI, Cristina
• FAUMAN, Eric
• WEI YUAN
• MILBURN, Mike
• PALMER, Colin N. A
• FRAYLING, Timothy M
• TRIMMER, Jeff
• BELL, Jordana T
• GIEGER, Christian
• MOHNEY, Rob P
• BROSNAN, Mary Julia
• SUHRE, Karsten
• ERTE, Idil
• SORANZO, Nicole
• SPECTOR, Tim D
• PERRY, John R. B
• KASTENMÜLLER, Gabi
• SHIN, So-Youn
• PETERSEN, Ann-Kristin
• HYDE, Craig
• PSATHA, Maria
• WARD, Kirsten J

Titel

Biomarkers for Type 2 Diabetes and Impaired Fasting Glucose Using a Nontargeted Metabolomics Approach

Ist Teil von

• Diabetes (New York, N.Y.), 2013-12, Vol.62 (12), p.4270-4276

Ort / Verlag

Alexandria, VA: American Diabetes Association

Erscheinungsjahr

2013

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Using a nontargeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycemia in a large population-based cohort of 2,204 females (115 type 2 diabetic [T2D] case subjects, 192 individuals with impaired fasting glucose [IFG], and 1,897 control subjects) from TwinsUK. Forty-two metabolites from three major fuel sources (carbohydrates, lipids, and proteins) were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain keto-acid metabolite 3-methyl-2-oxovalerate was the strongest predictive biomarker for IFG after glucose (odds ratio [OR] 1.65 [95% CI 1.39-1.95], P = 8.46 × 10(-9)) and was moderately heritable (h(2) = 0.20). The association was replicated in an independent population (n = 720, OR 1.68 [ 1.34-2.11], P = 6.52 × 10(-6)) and validated in 189 twins with urine metabolomics taken at the same time as plasma (OR 1.87 [1.27-2.75], P = 1 × 10(-3)). Results confirm an important role for catabolism of branched-chain amino acids in T2D and IFG. In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of nontargeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.