Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

Mark R. Viant; E. Amstalden; T. Athersuch; M. Bouhifd; S. Camuzeaux; D. M. Crizer; P. Driemert; T. Ebbels; D. Ekman; B. Flick; V. Giri; M. Gómez-Romero; V. Haake; M. Herold; A. Kende; F. Lai; P. E.G. Leonards; P. P. Lim; G. R. Lloyd; J. Mosley; C. Namini; J. R. Rice; S. Romano; C. Sands; M. J. Smith; T. Sobanski; A. D. Southam; L. Swindale; B. van Ravenzwaay; T. Walk; R. J.M. Weber; F. M. Zickgraf; H. Kamp

doi:10.1007/s00204-024-03680-y

Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

Mark R. Viant^*, E. Amstalden, T. Athersuch, M. Bouhifd, S. Camuzeaux, D. M. Crizer, P. Driemert, T. Ebbels, D. Ekman, B. Flick, V. Giri, M. Gómez-Romero, V. Haake, M. Herold, A. Kende, F. Lai, P. E.G. Leonards, P. P. Lim, G. R. Lloyd, J. MosleyC. Namini, J. R. Rice, S. Romano, C. Sands, M. J. Smith, T. Sobanski, A. D. Southam, L. Swindale, B. van Ravenzwaay, T. Walk, R. J.M. Weber, F. M. Zickgraf, H. Kamp

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography–mass spectrometry (LC–MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Original language	English
Pages (from-to)	1111-1123
Number of pages	13
Journal	Archives of Toxicology
Volume	98
Issue number	4
Early online date	18 Feb 2024
DOIs	https://doi.org/10.1007/s00204-024-03680-y
Publication status	Published - Apr 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Funding

We thank the following: Dr Donna O’Neil, Phenome Centre Birmingham, for extracting samples; Dr Douwe Molenaar, Vrije Universiteit Amsterdam, for discussions on statistical analysis; Dr Rosemary Barnett, Dr Tom Lawson and Dr Elena Sostare, Michabo Health Science Limited, for contributing to the University of Birmingham’s grouping analyses; Mr Karl Michael Jessop, Syngenta, for extracting samples; Dr David Cowie, Dr Elizabeth McInnes and Dr Alex Charlton, Syngenta, for peer reviewing the toxicological mode of action predictions; the Cefic Monitoring Team and external advisors for feedback throughout the study; and Mr David Epps, University of Birmingham, for project management. This work was primarily funded by the Cefic Long-range Research Initiative [LRI-C8]. Data were acquired at the National Phenome Centre (Imperial College London), which is supported by the UK Medical Research Council and National Institute for Health Research [grant number MC_PC_12025]; at Phenome Centre Birmingham (University of Birmingham), supported by the Medical Research Council [MR/M009157/1]; additionally, both Phenome Centres' are supported by the Medical Research Council UK Consortium for MetAbolic Phenotyping (MAP UK) [MR/S010483/1].

Funders	Funder number
LRI
Medical Research Council UK Consortium	MR/S010483/1
Medical Research Council	MR/M009157/1
National Institute for Health and Care Research	MC_PC_12025
Imperial College London
University of Birmingham

Keywords

Guidance
Metabolomics
OECD
Reproducibility
Standardisation
Validation

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Viant, M. R., Amstalden, E., Athersuch, T., Bouhifd, M., Camuzeaux, S., Crizer, D. M., Driemert, P., Ebbels, T., Ekman, D., Flick, B., Giri, V., Gómez-Romero, M., Haake, V., Herold, M., Kende, A., Lai, F., Leonards, P. E. G., Lim, P. P., Lloyd, G. R., ... Kamp, H. (2024). Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice. Archives of Toxicology, 98(4), 1111-1123. https://doi.org/10.1007/s00204-024-03680-y

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Viant, MR, Amstalden, E, Athersuch, T, Bouhifd, M, Camuzeaux, S, Crizer, DM, Driemert, P, Ebbels, T, Ekman, D, Flick, B, Giri, V, Gómez-Romero, M, Haake, V, Herold, M, Kende, A, Lai, F, Leonards, PEG, Lim, PP, Lloyd, GR, Mosley, J, Namini, C, Rice, JR, Romano, S, Sands, C, Smith, MJ, Sobanski, T, Southam, AD, Swindale, L, van Ravenzwaay, B, Walk, T, Weber, RJM, Zickgraf, FM & Kamp, H 2024, 'Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice', Archives of Toxicology, vol. 98, no. 4, pp. 1111-1123. https://doi.org/10.1007/s00204-024-03680-y

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Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

Abstract

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