Bictash, Magda, Ebbels, Timothy, Chan, Queenie, Loo, Ruey Leng, Yap, Ivan K. S., Brown, Ian J., De Iorio, Maria, Daviglus, Martha L., Holmes, Elaine, Stamler, Jeremiah, and others. (2010) Opening up the "black box": Metabolic phenotyping and metabolome-wide association studies in epidemiology. Journal of Clinical Epidemiology, 63 (9). pp. 970-979. ISSN 0895-4356. (doi:10.1016/j.jclinepi.2009.10.001) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:36451)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.jclinepi.2009.10.001 |
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.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.jclinepi.2009.10.001 |
Uncontrolled keywords: | Biomarkers, INTERMAP, INTERSALT, Metabolic phenotyping, Metabonomics, NMR spectroscopy, false positive result, human, metabolite, metabolome, nuclear magnetic resonance spectroscopy, phenotype, priority journal, review, Biological Markers, Humans, Metabolome, Metabolomics, Molecular Epidemiology, Phenotype, Reproducibility of Results, Risk Assessment |
Subjects: | Q Science |
Divisions: | Divisions > Division of Natural Sciences > Medway School of Pharmacy |
Depositing User: | Rueyleng Loo |
Date Deposited: | 14 Nov 2013 22:27 UTC |
Last Modified: | 05 Nov 2024 10:20 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/36451 (The current URI for this page, for reference purposes) |
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