Publication Type Journal Article
Title Effect of Suboptimal Sampling and Handling Conditions on Urinary Metabolic Profiles
Authors Judit Morello Ekaterina Nevedomskaya Tiziana Pacchiarotta Bart Schoemaker Rico Derks Nicoline B. M. Voet Axel Meissner Andre M. Deelder Baziel G. M. van Engelen Oleg A. Mayboroda
Groups
Journal CHROMATOGRAPHIA
Year 2015
Month March
Volume 78
Number 5
Pages 429-434
Abstract Collection and storage of the clinical samples are crucial factors in the metabolomic workflows. However, with the expansion of metabolomics into the clinical domain and towards the large field studies in particular, the high sampling/storage standards practiced in the tightly controlled hospital environment cannot always be guaranteed. Thus, if the samples are exposed to suboptimal conditions and their integrity is compromised should they be discarded? Or such samples retain physiologically relevant information and can be of use? To explore the options we analyzed 117 urine samples that were collected under two different conditions. Part of the samples were collected within a clinical setting under optimal conditions, another part by patients at home and shipped to the hospital by mail. All samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) and proton nuclear magnetic resonance (H-1 NMR) spectroscopy. Multivariate modelling revealed clear differences between the two sampling conditions for both LC-MS and H-1 NMR data sets. However, the differential metabolites appeared to be platform-specific, which clearly emphasizes the complementary nature of both techniques. The analysis of the samples that were exposed to suboptimal conditions revealed that age and body mass index remain as dominant traits of the metabolic profile, although their influence was stronger for LC-MS data. In conclusion, although it is important to ensure adequate sample collection and storage conditions, urine samples that do not fulfil these criteria still retain valuable physiological information and as such thus they could be of use for metabolomic studies when no alternative is available.
DOI http://dx.doi.org/10.1007/s10337-014-2778-6
ISBN
Publisher
Book Title
ISSN 0009-5893
EISSN 1612-1112
Conference Name
Bibtex ID ISI:000350820500012
Observations
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