Practical Approach for the Identification and Isomer Elucidation of Biomarkers Detected in a Metabonomic Study for the Discovery of Individuals at Risk for Diabetes by Integrating the Chromatographic and Mass Spectrometric Information
Authors:
- Xinjie ZhaoXZXinjie Zhao
- Jens FritscheJFJens Fritsche
- Peiyuan YinPYPeiyuan Yin
- Philippe Schmitt-KopplinPhilippe Schmitt-Kopplin
- Wenzhao WangWWWenzhao Wang
- Xin LuXLXin Lu
- Hans Ulrich HäringHHHans Ulrich Häring
- Erwin D. SchleicherESErwin D. Schleicher
- Rainer LehmannRLRainer Lehmann
- Guowang XuGXGuowang Xu
- 15 January 2008
- journal article
- research article
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 80 (4) , 1280-1289
Abstract
Sensitive and high-resolution chromatographic-driven metabonomomics studies experienced major growth with the aid of new analytical technologies and bioinformatics software packages. Hence, data collections by LC−MS and data analyses by multivariate statistical methods are by far the most straightforward steps, and the detection of biomarker candidates can easily be achieved. However, the unequivocal identification of the detected metabolite candidates, including isomer elucidation, is still a crux of current metabonomics studies. Here we present a comprehensive analytical strategy for the elucidation of the molecular structure of metabolite biomarkers detected in a metabonomics study, exemplified analyzing spot urine of a cohort of healthy, insulin sensitive subjects and clinically well characterized prediabetic, insulin resistant individuals. An integrated approach of LC−MS fingerprinting, multivariate statistic analysis, LC−MSn experiments, micro preparation, FTICR-MS, GC retention index, database search, and generation of an isotope labeled standard was applied. Overall, we could demonstrate the efficiency of our analytical approach by the unambiguous elucidation of the molecular structure of an isomeric biomarker candidate detected in a complex human biofluid. The proposed strategy is a powerful new analytical tool, which will allow the definite identification of physiologically important molecules in metabonomics studies from basic biochemistry to clinical biomarker discovery.Keywords
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