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Harmonizing human plasma metabolite annotation with Plasma Benchmark

Nature Metabolism (2025)Cite this article

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The human plasma metabolome has been extensively characterized: version 5.0 of the Human Metabolome Database (HMDB)1 currently encompasses 37,229 entries for metabolites reported in human blood. Although the analytical coverage of modern LC–MS platforms enables the detection and identification of 1,000–2,000 plasma metabolites, the number of well-known and regularly detected plasma metabolites is considerably smaller: reference values of 144 plasma metabolites in a healthy population2 and 588 lipids in the National Institute of Standards and Technology’s (NIST) reference plasma sample3 have been reported previously. The plasma metabolome also exhibits vast interindividual and intraindividual variability, which is explained by variation in the microbiome, dietary habits and genetics4. Challenges in consistently reporting the human plasma metabolome arise from interlaboratory variation in non-targeted LC–MS methodologies and varying practices and capabilities in the annotation of the metabolites themselves5.

To construct Plasma Benchmark, three participating laboratories analysed the same in-house pooled plasma and the NIST1950 human reference plasma6 in four analytical modes, including reversed-phase and hydrophilic interaction chromatography in the positive and negative ionization modes followed by data matrix generation in MS-DIAL7. We applied a set of inclusion criteria based on signal-to-noise ratio, relative standard deviation, sample-to-blank ratio, and acquisition of MS/MS data and predicted molecular formula to narrow the number of detected molecular features down to 639 robust molecular features that most probably represent actual plasma metabolites. Nearly 88% of the detected molecular features did not fulfil the signal-to-noise ratio and sample-to-blank ratio criteria, probably due to inherent noise and contaminants in LC–MS data but also because of high variability in the detection of many molecular features across laboratories8 (Fig. 1b). Manual curation of the robust molecular features resulted in 288 unique metabolites, whereas the rest of the molecular features were classified as redundant molecular features and in-source fragments. The inclusion of four analytical modes was crucial for an extensive coverage of metabolites because most were detected in only one mode (Fig. 1b).

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Fig. 1: The Plasma Benchmark online tool and database contain reproducibly detected metabolites from human fasting reference plasma.

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Acknowledgements

M. Reponen (University of Eastern Finland), J. Kuparinen (University of Eastern Finland) and N. Robinot (International Agency for Research on Cancer) are acknowledged for technical assistance. S. Keppo (Koponen+Hildén) is acknowledged for the technical development of the Plasma Benchmark visualization tool. The University of Eastern Finland mass spectrometry laboratory is supported by Biocenter Finland and Biocenter Kuopio.

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Author notes

  1. These authors contributed equally: Ville Koistinen, Topi Meuronen.

Authors and Affiliations

  1. Food Sciences Unit, University of Turku, Turku, Finland

    Ville Koistinen, Topi Meuronen, Hany Ahmed & Kati Hanhineva

  2. Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland

    Ville Koistinen & Kati Hanhineva

  3. International Agency for Research on Cancer (IARC), Lyon, France

    Pekka Keski-Rahkonen, Reza Salek & Augustin Scalbert

  4. School of Clinical Medicine and NIHR Cambridge BRC, University of Cambridge, Cambridge, UK

    Reza Salek

  5. Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden

    Otto Savolainen, Carl Brunius & Rikard Landberg

  6. School of Pharmacy, University of Eastern Finland, Kuopio, Finland

    Marko Lehtonen & Seppo Auriola

Authors
  1. Ville Koistinen
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  12. Kati Hanhineva
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Contributions

V.K., P.K.R., R.S., O.S., C.B., R.L., M.L., S.A., A.S. and K.H. conceptualized the study. P.K.R., O.S., H.A. and M.L. designed and carried out the LC–MS experiments. V.K. and T.M. performed the data analysis and manuscript writing. All authors critically reviewed the manuscript.

Corresponding author

Correspondence to Kati Hanhineva.

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Competing interests

V.K., T.M. and K.H. are affiliated with Afekta Technologies. The company did not participate in this study. The remaining authors declare no competing interests.

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Nature Metabolism thanks Domenica Berardi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Koistinen, V., Meuronen, T., Keski-Rahkonen, P. et al. Harmonizing human plasma metabolite annotation with Plasma Benchmark. Nat Metab (2025). https://doi.org/10.1038/s42255-025-01376-w

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