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Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories.

Shin Nishiumi1, Yoshihiro Izumi2, Akiyoshi Hirayama3

  • 1Department of Omics Medicine, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya-city, Hyogo 663-8501, Japan.

Metabolites
|February 25, 2022
PubMed
Summary

Inter-laboratory differences in metabolomics are primarily due to measurement and data analysis, not sample preparation. This finding helps address variability in multi-lab metabolomic studies.

Keywords:
hydrophilic metabolitehydrophobic metaboliteinter-laboratory comparisonmass spectrometrymetabolomicsrelative quantification

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Biotechnology

Background:

  • Mass spectrometry-based metabolomics faces challenges due to variations in analytical results across different laboratories and machines.
  • Unique analytical methods employed by each facility contribute to inter-laboratory discrepancies in metabolomic data.

Purpose of the Study:

  • To evaluate the extent to which analytical methods, excluding sample pretreatment, contribute to inter-laboratory differences in metabolomic analysis.
  • To understand the reality of inter-laboratory variations in metabolomics research.

Main Methods:

  • Nine facilities participated in an inter-laboratory comparison using identical dried human and mouse plasma samples.
  • Metabolites were measured using 11 methods for hydrophilic and 7 methods for hydrophobic compounds, excluding laboratory-specific pretreatment.
  • Acquired metabolomic data from each laboratory were integrated and analyzed for differences.

Main Results:

  • Less than 50% of detected metabolites showed no substantial difference in relative quantitative data (human/mouse) between laboratories.
  • Hydrophilic metabolites exhibited fewer inter-laboratory differences compared to hydrophobic metabolites.
  • A slightly high proportion of quantitatively guaranteed metabolites showed no significant inter-laboratory differences.

Conclusions:

  • Inter-laboratory differences in metabolomic data are mainly attributable to measurement and data analysis procedures, rather than sample preparation.
  • While resolving all inter-laboratory differences is challenging due to varying analytical environments, this study clarifies the primary sources of variation.
  • The findings will aid in understanding and mitigating problems in multi-laboratory metabolomics studies.