Literature DB >> 12771369

Genomics and metabolomics as markers for the interaction of diet and health: lessons from lipids.

J Bruce German1, Matthew-Alan Roberts, Steven M Watkins.   

Abstract

Foods are not purified compounds acting on single molecular targets, but complex mixtures of molecules that modulate many biochemical pathways simultaneously. Diet affects the probability of developing various diseases. Nevertheless, specific recommendations for individual diets are not simple. Recommending nutrient intakes above and beyond those needed to provide adequacy requires scientific knowledge and regulatory scrutiny to ensure the efficacy and safety even of essential nutrients. Designing a diet to improve metabolic health is a bold and ambitious goal. It is possible to design foods that will alter metabolism, but what change will make everyone who is otherwise healthy even healthier? Changing one aspect of metabolism to lower the risk of one disease does not improve overall health if it comes at the expense of disrupting another aspect of metabolism that increases the risk of another disease. This issue has: 1) frustrated nutritional recommendations that could provide benefits to the health of large subsets of the population, 2) caused the recall of drugs with many beneficial effects and 3) caused harm by implying that single nutrients/foods could be healthy for everyone. An individualized system for metabolic assessment would establish the efficacy and safety of nutrients such as amino acids or fatty acids when these are designed to be consumed at levels providing improved metabolic health. The need to document the lack of an adverse effect of a food or drug on physiology necessitates a global, i.e. metabolomic approach.

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Year:  2003        PMID: 12771369     DOI: 10.1093/jn/133.6.2078S

Source DB:  PubMed          Journal:  J Nutr        ISSN: 0022-3166            Impact factor:   4.798


  18 in total

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Review 5.  Online tools for bioinformatics analyses in nutrition sciences.

Authors:  Sridhar A Malkaram; Yousef I Hassan; Janos Zempleni
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6.  Self-similarity in NMR Spectra: An Application in Assessing the Level of Cysteine.

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7.  Lipidomics reveals associations between rice quality traits.

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Journal:  Metabolomics       Date:  2020-04-18       Impact factor: 4.290

Review 8.  Nutritional metabolomics: progress in addressing complexity in diet and health.

Authors:  Dean P Jones; Youngja Park; Thomas R Ziegler
Journal:  Annu Rev Nutr       Date:  2012-04-23       Impact factor: 11.848

9.  Microneedle Biosensor: A Method for Direct Label-free Real Time Protein Detection.

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Journal:  Sens Actuators B Chem       Date:  2013-02       Impact factor: 7.460

10.  Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics?

Authors:  Gaëlle Favé; M E Beckmann; J H Draper; J C Mathers
Journal:  Genes Nutr       Date:  2009-04-02       Impact factor: 5.523

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