Opening up the “black box”: metabolic phenotyping and metabolome-wide association studies in epidemiology
Open accessAbstract
Background Metabolic phenotyping of humans allows information to be captured on the interactions between dietary, xenobiotic, other lifestyle and environmental exposures, and genetic variation, which together influence the balance between health and disease risks at both individual and population levels.Objectives We describe here the main procedures in large-scale metabolic phenotyping and their application to metabolome-wide association (MWA) studies.Methods By use of high-throughput technologies and advanced spectroscopic methods, application of metabolic profiling to large-scale epidemiologic sample collections, including metabolome-wide association (MWA) studies for biomarker discovery and identification.Discussion Metabolic profiling at epidemiologic scale requires optimization of experimental protocol to maximize reproducibility, sensitivity, and quantitative reliability, and to reduce analytical drift. Customized multivariate statistical modeling approaches are needed for effective data visualization and biomarker discovery with control for false-positive associations since 100s or 1,000s of complex metabolic spectra are being processed.Conclusion Metabolic profiling is an exciting addition to the armamentarium of the epidemiologist for the discovery of new disease-risk biomarkers and diagnostics, and to provide novel insights into etiology, biological mechanisms, and pathways.
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Metabolome-wide association studies (MWASs) have been proposed as useful tools for discovering low-molecular-weight biomarkers predictive of causal exposures or disease progression.
“MWASs have been proposed as useful tools for discovering low-molecular-weight biomarkers that are predictive of either causal exposures or disease progression (59, 165, 166).”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [166]
The INTERMAP metabolite differences suggest important effects of diet and related risk factors, including microbiota, on coronary artery disease and stroke risk.
“The investigators showed that metabolite concentrations differed substantially between Asian and Western populations, suggesting important effects of diet and related risk factors, including the microbiota, on the risk of coronary artery disease and stroke.”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [166]
Three highly discriminating biomarkers were identified in the INTERMAP study: alanine was directly correlated with blood pressure, while formate and hippurate were inversely correlated with blood pressure.
“biomarkers were identified, namely alanine, which was directly correlated with blood pressure, and formate and hippurate, both of which were inversely correlated with blood pressure.”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [166]
In the INTERMAP study, untargeted NMR of more than 4000 urine specimens from geographically diverse populations showed that metabolite concentrations differed substantially between Asian and Western populations.
“The investigators showed that metabolite concentrations differed substantially between Asian and Western populations, suggesting important effects of diet and related risk factors, including the microbiota, on the risk of coronary artery disease and stroke.”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [166]
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- Authors
- Bictash, M., Ebbels, T. M., Chan, Q., Loo, R. L., Yap, I. K. S., Brown, I. J., de Iorio, M., Daviglus, M. L., Holmes, E., Stamler, J., Nicholson, J. K., & Elliott, P.
- Affiliations
- Imperial College London (GB)
- Medway School of Pharmacy (GB)
- Northwestern University (US)
- Corresponding author
- Nicholson, Jeremy K.
- Elliott, Paul
- ORCID
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2010-09
- Volume
- 63
- Issue
- 9
- Pages
- 970-979
- ISSN
- 0895-4356 (ISSN-L)
- PMC
- PMC4048926
- OpenAlex
- W2130686160
- Cited by
- 140
- References
- 74
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 4 · 2023: 5 · 2022: 6 · 2021: 10 · 2020: 6 · 2019: 12 · 2018: 9 · 2017: 10 · 2016: 10 · 2015: 10 · 2014: 11 · 2013: 11 · 2012: 15
- FWCI
- 1.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Murdoch University Research Portal (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Kent Academic Repository (University of Kent) (submittedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology
- National Heart, Lung, and Blood Institute (090357003)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Metabolism and Genetic Disorders
- Keywords
- metabolic phenotyping, metabolome-wide association study, metabolite profiling, biomarker discovery, high-throughput metabolomics, false positive association, multivariate statistical modeling, genetic variation
- MeSH terms
- Humans, Phenotype, Reproducibility of Results, Biomarkers, Molecular Epidemiology, Risk Assessment, Metabolomics, Metabolome
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