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Effect of Suboptimal Sampling and Handling Conditions on Urinary Metabolic Profiles

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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 (1H NMR) spectroscopy. Multivariate modelling revealed clear differences between the two sampling conditions for both LC–MS and 1H 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.

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Authors and Affiliations

  1. Center for Proteomics and Metabolomics, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands

    Judit Morello, Ekaterina Nevedomskaya, Tiziana Pacchiarotta, Bart Schoemaker, Rico Derks, Axel Meissner, André M. Deelder & Oleg A. Mayboroda

  2. Laboratory of Molecular Biology, Department of Infectious Diseases, Hospital Carlos III, Madrid, Spain

    Judit Morello

  3. Department of Neurology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

    Baziel G. M. van Engelen

  4. Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

    Nicoline B. M. Voet

Authors
  1. Judit Morello
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  2. Ekaterina Nevedomskaya
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  3. Tiziana Pacchiarotta
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  4. Bart Schoemaker
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  5. Rico Derks
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  6. Nicoline B. M. Voet
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  7. Axel Meissner
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  8. André M. Deelder
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  9. Baziel G. M. van Engelen
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  10. Oleg A. Mayboroda
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Corresponding author

Correspondence to Oleg A. Mayboroda.

Additional information

Published in the topical collection Recent Developments in Clinical Omics with guest editors Martin Giera and Manfred Wuhrer.

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Morello, J., Nevedomskaya, E., Pacchiarotta, T. et al. Effect of Suboptimal Sampling and Handling Conditions on Urinary Metabolic Profiles. Chromatographia 78, 429–434 (2015). https://doi.org/10.1007/s10337-014-2778-6

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  • DOI: https://doi.org/10.1007/s10337-014-2778-6

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