The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies

Abstract

Background

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

Aim of review

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

Key scientific concepts of review

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze–thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

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Funding

This research was supported by NSFC (National Natural Science Fundation of China, Nos. 81972966, 81672091) and BJNSF (Natural Science Fundation of Beijing, No. 7172232).

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LM and LX conceived of the concept of the review. HB and XJ conducted the literature search. XJ and ZG analyzed the search results and wrote the paper. ZG, HB, HL and LX were involved in revision.

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Correspondence to Lulin Ma or Lixiang Xue.

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Bi, H., Guo, Z., Jia, X. et al. The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies. Metabolomics 16, 68 (2020). https://doi.org/10.1007/s11306-020-01666-2

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Keywords

  • Metabolomics
  • Serum
  • Plasma
  • Urine
  • Preprocessing