Document Detail

A multivariate screening strategy for investigating metabolic effects of strenuous physical exercise in human serum.
MedLine Citation:
PMID:  17428078     Owner:  NLM     Status:  MEDLINE    
A novel hypothesis-free multivariate screening methodology for the study of human exercise metabolism in blood serum is presented. Serum gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) data was processed using hierarchical multivariate curve resolution (H-MCR), and orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to model the systematic variation related to the acute effect of strenuous exercise. Potential metabolic biomarkers were identified using data base comparisons. Extensive validation was carried out including predictive H-MCR, 7-fold full cross-validation, and predictions for the OPLS-DA model, variable permutation for highlighting interesting metabolites, and pairwise t tests for examining the significance of metabolites. The concentration changes of potential biomarkers were verified in the raw GC/TOFMS data. In total, 420 potential metabolites were resolved in the serum samples. On the basis of the relative concentrations of the 420 resolved metabolites, a valid multivariate model for the difference between pre- and post-exercise subjects was obtained. A total of 34 metabolites were highlighted as potential biomarkers, all statistically significant (p < 8.1E-05). As an example, two potential markers were identified as glycerol and asparagine. The concentration changes for these two metabolites were also verified in the raw GC/TOFMS data. The strategy was shown to facilitate interpretation and validation of metabolic interactions in human serum as well as revealing the identity of potential markers for known or novel mechanisms of human exercise physiology. The multivariate way of addressing metabolism studies can help to increase the understanding of the integrative biology behind, as well as unravel new mechanistic explanations in relation to, exercise physiology.
Elin Pohjanen; Elin Thysell; Pär Jonsson; Caroline Eklund; Anders Silfver; Inga-Britt Carlsson; Krister Lundgren; Thomas Moritz; Michael B Svensson; Henrik Antti
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2007-04-12
Journal Detail:
Title:  Journal of proteome research     Volume:  6     ISSN:  1535-3893     ISO Abbreviation:  J. Proteome Res.     Publication Date:  2007 Jun 
Date Detail:
Created Date:  2007-06-01     Completed Date:  2007-07-18     Revised Date:  2009-11-03    
Medline Journal Info:
Nlm Unique ID:  101128775     Medline TA:  J Proteome Res     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2113-20     Citation Subset:  IM    
Research Group for Chemometrics, Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden.
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MeSH Terms
Biological Markers / blood
Gas Chromatography-Mass Spectrometry*
Multivariate Analysis
Serum / chemistry*,  metabolism*
Reg. No./Substance:
0/Biological Markers

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