Skip to main content
Log in

A strategy for advancing for population-based scientific discovery using the metabolome: the establishment of the Metabolomics Society Metabolomic Epidemiology Task Group

  • Review Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

Metabolomic Epidemiology is a growing area of research within the metabolomics research community. In response to this, we describe the establishment of the Metabolomics Society Metabolomic Epidemiology Task Group. The overall mission of this group is to promote the growth and understanding of metabolomic epidemiology as an independent research discipline and to drive collaborative efforts that can shape the field. In this article we define metabolomic epidemiology and identify the key challenges that need to be addressed in order to advance population-based scientific discovery in metabolomics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  • Beger, R. D., Dunn, W. B., Bandukwala, A., Bethan, B., Broadhurst, D., Clish, C. B., Dasari, S., Derr, L., Evans, A., Fischer, S., Flynn, T., Hartung, T., Herrington, D., Higashi, R., Hsu, P. C., Jones, C., Kachman, M., Karuso, H., Kruppa, G., … Lippa, K. (2019). Towards quality assurance and quality control in untargeted metabolomics studies. Metabolomics, 15, 4.

    Article  Google Scholar 

  • Brindle, J. T., Antti, H., Holmes, E., Tranter, G., Nicholson, J. K., Bethell, H. W., Clarke, S., Schofield, P. M., McKilligin, E., Mosedale, D. E., & Grainger, D. J. (2002). Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabolomics. Nature Medicine, 8, 1439–1444.

    Article  CAS  Google Scholar 

  • Brindle, J. T., Nicholson, J. K., Schofield, P. M., Grainger, D. J., & Holmes, E. (2003). Application of chemometrics to 1H NMR spectroscopic data to investigate a relationship between human serum metabolic profiles and hypertension. The Analyst, 128, 32–36.

    Article  CAS  Google Scholar 

  • Celentano, D. D., & Szklo, M. (2018). Gordis epidemiology. . Elsevier.

    Google Scholar 

  • Dunn, W. B., Wilson, I. D., Nicholls, A. W., & Broadhurst, D. (2012). The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. Bioanalysis, 4, 2249–2264.

    Article  CAS  Google Scholar 

  • Dunn, W. B., Lin, W., Broadhurst, D., Begley, P., Brown, M., Zelena, E., Vaughan, A. A., Halsall, A., Harding, N., Knowles, J. D., Francis-Mcintyre, S., Tseng, A., Ellis, D. I., O’Hagan, S., Aarons, G., Benjamin, B., Chew-Graham, S., Moseley, C., Potter, P., … Winder, C. L. (2015). Molecular phenotyping of a UK population: Defining the human serum metabolome. Metabolomics, 11, 9–26.

    Article  CAS  Google Scholar 

  • Evans, A. M., O’donovan, C., Playdon, M., Beecher, C., Beger, R. D., Bowden, J. A., Broadhurst, D., Clish, C. B., Dasari, S., Dunn, W. B., Griffin, J. L., Hartung, T., Hsu, P. C., Huan, T., Jans, J., Jones, C. M., Kachman, M., Kleensang, A., Lewis, M. R., … Metabolomics Quality Assurance, Quality Control Consortium (mQACC). (2020). Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners. Metabolomics, 16, 113.

    Article  CAS  Google Scholar 

  • Holmes, E., Loo, R. L., Stamler, J., Bictash, M., Yap, I. K., Chan, Q., Ebbels, T., de Iorio, M., Brown, I. J., Veselkov, K. A., Daviglus, M. L., Kesteloot, H., Ueshima, H., Zhao, L., Nicholson, J. K., & Elliott, P. (2008). Human metabolic phenotype diversity and its association with diet and blood pressure. Nature, 453, 396–400.

    Article  CAS  Google Scholar 

  • Kaddurah-Daouk, R., Weinshilboum, R. M., & Pharmacometabolomics Research Network. (2014). Pharmacometabolomics: Implications for clinical pharmacology and systems pharmacology. Clinical Pharmacology and Therapeutics, 95, 154–167.

    Article  CAS  Google Scholar 

  • Kirwan, J. A., Brennan, L., Broadhurst, D., Fiehn, O., Cascante, M., Dunn, W. B., Schmidt, M. A., & Velagapudi, V. (2018). 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). Clinical Chemistry, 64, 1158–1182.

    Article  CAS  Google Scholar 

  • Last, J. M. (1988). A dictionary of epidemiology. . Oxford University Press.

    Google Scholar 

  • Lindon, J. C., Nicholson, J. K., Holmes, E., Antti, H., Bollard, M. E., Keun, H., Beckonert, O., Ebbels, T. M., Reily, M. D., Robertson, D., Stevens, G. J., Luke, P., Breau, A. P., Cantor, G. H., Bible, R. H., Niederhauser, U., Senn, H., Schlotterbeck, G., Sidelmann, U. G., … Laursen, S. M. (2003). Contemporary issues in toxicology the role of metabonomics in toxicology and its evaluation by the COMET project. Toxicology and Applied Pharmacology, 187, 137–146.

    Article  CAS  Google Scholar 

  • Liu, X., Hoene, M., Yin, P., Fritsche, L., Plomgaard, P., Hansen, J. S., Nakas, C. T., Niess, A. M., Hudemann, J., Haap, M., Mendy, M., Weigert, C., Wang, X., Fritsche, A., Peter, A., Haring, H. U., Xu, G., & Lehmann, R. (2018). Quality control of serum and plasma by quantification of (4E,14Z)-sphingadienine-C18-1-phosphate uncovers common preanalytical errors during handling of whole blood. Clinical Chemistry, 64, 810–819.

    Article  CAS  Google Scholar 

  • Mendez, K. M., Reinke, S. N., & Broadhurst, D. I. (2019). A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification. Metabolomics, 15, 150.

    Article  Google Scholar 

  • Slupsky, C. M., Rankin, K. N., Wagner, J., Fu, H., Chang, D., Weljie, A. M., Saude, E. J., Lix, B., Adamko, D. J., Shah, S., Greiner, R., Sykes, B. D., & Marrie, T. J. (2007). Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles. Analytical Chemistry, 79, 6995–7004.

    Article  CAS  Google Scholar 

  • Trivedi, D. K., Hollywood, K. A., & Goodacre, R. (2017). Metabolomics for the masses: The future of metabolomics in a personalized world. New Horizons in Translational Medicine, 3, 294–305.

    PubMed  PubMed Central  Google Scholar 

  • Underwood, B. R., Broadhurst, D., Dunn, W. B., Ellis, D. I., Michell, A. W., Vacher, C., Mosedale, D. E., Kell, D. B., Barker, R. A., Grainger, D. J., & Rubinsztein, D. C. (2006). Huntington disease patients and transgenic mice have similar pro-catabolic serum metabolite profiles. Brain, 129, 877–886.

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge that the Metabolomic Epidemiology Task Group was formally established by the Metabolomics Society in September 2019. The task group was founded by the authors of this manuscript and Krista A. Zanetti (National Cancer Institute, Bethesda, Maryland, USA), who is representing the National Institutes of Health’s efforts in the field of metabolomic epidemiology on the Task Group. The task group has met once a month since inception and will continue to operate until the group feels that the tasks described in this document are progressed to a satisfactory endpoint.

Funding

JLS and RK are funded by R01HL123915, R01HL141826, R01 DK125273, and a foundation grant from SFARI. RK is additionally funded by K01HL146980. JLS is additionally funded by 5P01HL132825. CEW is supported by the Swedish Heart Lung Foundation (Grant No. HLF 20180290, HLF 20200693).

Author information

Authors and Affiliations

Authors

Contributions

All authors made substantial contributions to the conception, intellectual content and writing of this manuscript. All authors approved the final manuscript and agree to be accountable for all aspects of this work.

Corresponding author

Correspondence to Jessica Lasky-Su.

Ethics declarations

Conflicts of interest

The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lasky-Su, J., Kelly, R.S., Wheelock, C.E. et al. A strategy for advancing for population-based scientific discovery using the metabolome: the establishment of the Metabolomics Society Metabolomic Epidemiology Task Group. Metabolomics 17, 45 (2021). https://doi.org/10.1007/s11306-021-01789-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11306-021-01789-0

Keywords

Navigation