Opening up the "black box": Metabolic phenotyping and metabolome-wide association studies in epidemiology

Magda Bictash, Timothy M. Ebbels, Queenie Chan, Ruey Leng Loo, Ivan K.S. Yap, Ian J. Brown, Maria De Iorio, Martha L. Daviglus, Elaine Holmes, Jeremiah Stamler, Jeremy K. Nicholson, Paul Elliott

Research output: Contribution to journalReview articlepeer-review

118 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)970-979
Number of pages10
JournalJournal of Clinical Epidemiology
Issue number9
StatePublished - Sep 2010


  • Biomarkers
  • Metabolic phenotyping
  • Metabonomics
  • NMR spectroscopy

ASJC Scopus subject areas

  • Epidemiology


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