Cross-Platform Urine Metabolomics of Experimental Hyperglycemia in Type 2 DiabetesLiesbet Temmerman2,3#, Alysha M De Livera1#, Jairus B Bowne1, John R Sheedy1, Damien L Callahan2, Amsha Nahid1, David P De Souza1, Liliane Schoofs3, Dedreia L Tull1, Malcolm J McConville1, Ute Roessner2,6* and John M Wentworth4,5
- *Corresponding Author:
- Ute Roessner
School of Botany
The University of Melbourne
3010 Victoria, Australia
Tel: +61 3 90353635
E-mail: [email protected]
Received date November 26, 2011; Accepted date January 18, 2012; Published date January 23, 2012
Citation: Temmerman L, De Livera AM, Bowne JB, Sheedy JR, Callahan DL, et al. (2012) Cross-Platform Urine Metabolomics of Experimental Hyperglycemia in Type 2 Diabetes. J Diabetes Metab S6:002. doi:10.4172/2155-6156.S6-002
Copyright: © 2012 Temmerman L, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Hyperglycemia causes diabetic nephropathy, a condition for which there are no specific diagnostic markers that predict progression to renal failure. Here we describe a multiplatform metabolomic analysis of urine from individuals with type 2 diabetes, collected before and immediately following experimental hyperglycemia. We used targeted nuclear magnetic resonance spectroscopy (NMR), liquid chromatography - mass spectrometry (LC-MS) and gas chromatography - MS (GC-MS) to identify markers of hyperglycemia. Following optimization of data normalisation and statistical analysis, we identified a reproducible NMR and LC-MS based urine signature of hyperglycemia. Significant increases of alanine, alloisoleucine, isoleucine, leucine, N-isovaleroylglycine, valine, choline, lactate and taurine and decreases of arginine, gamma-aminobutyric acid, hippurate, suberate and N-acetylglutamate were observed. GC-MS analysis identified a number of metabolites differentially present in post-glucose versus baseline urine, but these could not be identified using current metabolite libraries. This analysis is an important first step towards identifying biomarkers of early-stage diabetic nephropathy.