Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2010 Sep;63(9):970-9.
doi: 10.1016/j.jclinepi.2009.10.001. Epub 2010 Jan 8.

Opening up the "Black Box": metabolic phenotyping and metabolome-wide association studies in epidemiology

Magda Bictash  1 , 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
Affiliations
Review

Opening up the "Black Box": metabolic phenotyping and metabolome-wide association studies in epidemiology

Magda Bictash et al. J Clin Epidemiol. 2010 Sep.

Abstract

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.

PubMed Disclaimer

Conflict of interest statement

Statement of conflict of interest: The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Large scale metabonomic screening of human populations. Scores plot for a PCA model derived from the 1H NMR urine data from INTERMAP (n=4,630 participants) colored by population sample
The 1H NMR measurement for a given urine specimen is plotted as a single point. The plot shows four outlying phenotypes based on latent information extracted from the spectral data sets, attributable to high urinary glucose, trimethylamine-N-oxide, ethanol and acetaminophen. Representative spectra of participants with characteristic spectral profiles for these metabolites are also highlighted.
Figure 2
Figure 2. Flow chart of the data pre-processing and data analysis strategy for large-scale population studies
See this image and copyright information in PMC

References

    1. Nicholson JK, Wilson I. High resolution proton magnetic resonance spectroscopy of biological fluids. Prog NMR Spect. 1989;21:449–501.
    1. Nicholson JK, Lindon JC, Holmes E. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica. 1999;29(11):1181–9. - PubMed
    1. Nicholson JK, Connelly J, Lindon JC, Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov. 2002;1(2):153–61. - PubMed
    1. Nicholson JK, Lindon JC. Systems biology: Metabonomics. Nature. 2008;455(7216):1054–6. - PubMed
    1. Gavaghan McKee CL, Holmes E, Lenz E, Wilson ID, Nicholson JK. An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: application to the C57BL10J and Alpk:ApfCD mouse. FEBS Lett. 2000;484(3):169–74. - PubMed

Publication types