The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Nutritional Metabonomics: Applications and Perspectives
Abstract
Nowadays, nutrition focuses on improving health of individuals through diet. Current nutritional research aims at health promotion, disease prevention, and performance improvement. Modern analytical platforms allow the simultaneous measurement of multiple metabolites providing new insights in the understanding of the functionalities of cells and whole organisms. Metabonomics, "the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modifications", provides a systems approach to understanding global metabolic regulations of organisms. This concept has arisen from various applications of NMR and MS spectroscopies to study the multicomponent metabolic composition of biological fluids, cells, and tissues. The generated metabolic profiles are processed by multivariate statistics to maximize the recovery of information to be correlated with well-determined stimuli such as dietary intervention or with any phenotypic data or diet habits. Metabonomics is thus uniquely suited to assess metabolic responses to deficiencies or excesses of nutrients and bioactive components. Furthermore, metabonomics is used to characterize the metabolic phenotype of individuals integrating genetic polymorphism, metabolic interactions with commensal and symbiotic partners such as gut microflora, as well as environmental and behavioral factors including dietary preferences. This paper reports several experimental key aspects in nutritional metabonomics, reviews its applications employing targeted and holistic approach analysis for the study of the metabolic responses following dietary interventions. It also reports the assessment of intra- and inter-individual variability in animal and human populations. The potentialities of nutritional metabonomics for the discovery of new biomarkers and the characterization of metabolic phenotypes are discussed in a context of their possible utilizations for personalized nutrition to provide health maintenance at the individual level.
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Jaenisch, R., & Bird, A. (2003) · Nature Genetics · doi:10.1038/ng1089 · Cited by 6,325
Dumas, M.-E., Barton, R. H., Toye, A., Cloarec, O., Blancher, C., Rothwell, A., Fearnside, J., Tatoud, R., Blanc, V., Lindon, J. C., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601056103 · Cited by 1,042
Pharmaco-metabonomic phenotyping and personalized drug treatment
Andrew Clayton, T., Lindon, J. C., Cloarec, O., Antti, H., Charuel, C., Hanton, G., Provost, J.-P., Le Net, J.-L., Baker, D., Walley, R. J., et al. (2006) · Nature · doi:10.1038/nature04648 · Cited by 824
Susceptibility of Human Metabolic Phenotypes to Dietary Modulation
Stella, C., Beckwith-Hall, B., Cloarec, O., Holmes, E., Lindon, J. C., Powell, J., van der Ouderaa, F., Bingham, S., Cross, A. J., & Nicholson, J. K. (2006) · Journal of Proteome Research · doi:10.1021/pr060265y · Cited by 376
Cited by
New hypotheses for the health-protective mechanisms of whole-grain cereals: what is beyond fibre?
Fardet, A. (2010) · Nutrition Research Reviews · doi:10.1017/s0954422410000041 · Cited by 1,030
The role of methionine on metabolism, oxidative stress, and diseases
Martínez, Y., Li, X., Liu, G., Bin, P., Yan, W., Más, D., Valdivié, M., Hu, C.-A. A., Ren, W., & Yin, Y. (2017) · Amino Acids · doi:10.1007/s00726-017-2494-2 · Cited by 583
Scalbert, A., Brennan, L., Fiehn, O., Hankemeier, T., Kristal, B. S., van Ommen, B., Pujos-Guillot, E., Verheij, E., Wishart, D., & Wopereis, S. (2009) · Metabolomics · doi:10.1007/s11306-009-0168-0 · Cited by 565
Vuckovic, D. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6039-y · Cited by 532
The food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519
Metadata
- Authors
- Rezzi, S., Ramadan, Z., Fay, L. B., & Kochhar, S.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-01-11
- Volume
- 6
- Issue
- 2
- Pages
- 513-525
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2050135062
- Cited by
- 269
- References
- 4
- FWCI
- 8.98
- Type
- journal article
- Language
- en
- Open access
- closed
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