NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition

Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug...

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Bibliographic Details
Published inNMR in biomedicine Vol. 18; no. 3; pp. 143 - 162
Main Authors Bollard, Mary E., Stanley, Elizabeth G., Lindon, John C., Nicholson, Jeremy K., Holmes, Elaine
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.05.2005
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Summary:Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug‐induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1H NMR spectroscopic‐based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter‐animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time‐course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information‐rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues. Copyright © 2004 John Wiley & Sons, Ltd.
Bibliography:ark:/67375/WNG-6BVR4HCC-H
ArticleID:NBM935
istex:D2598EE759B5B3BCDC0E0DDB3B8E38DD16682A5D
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0952-3480
1099-1492
DOI:10.1002/nbm.935