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Clin Chem. 2018 Aug;64(8):1158-1182. doi: 10.1373/clinchem.2018.287045. Epub 2018 Jun 19.

Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative).

Author information

1
Berlin Institute of Health, Berlin, Germany; vidya.velagapudi@helsinki.fi jennifer.kirwan@mdc-berlin.de.
2
Max Delbrück Center for Molecular Medicine, Berlin-Buch, Germany.
3
UCD School of Agriculture and Food Science, Institute of Food and Health, UCD, Dublin, Ireland.
4
School of Science, Edith Cowan University, Perth, Australia.
5
NIH West Coast Metabolomics Center, UC Davis, Davis, CA.
6
Department of Biochemistry and Molecular Biomedicine and IBUB, Universitat de Barcelona, Barcelona and Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBER-EHD), Madrid, Spain.
7
School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK.
8
Advanced Pattern Analysis and Countermeasures Group, Research Innovation Center, Colorado State University, Fort Collins, CO.
9
Sovaris Aerospace, LLC, Boulder, CO.
10
Metabolomics Unit, Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, Helsinki, Finland. vidya.velagapudi@helsinki.fi jennifer.kirwan@mdc-berlin.de.

Abstract

BACKGROUND:

The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data.

CONTENT:

This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices.

SUMMARY:

Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.

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