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Resveratrol in the foodomics era: 1:25,000
Author(s) -
Khakimov Bekzod,
Engelsen Søren Balling
Publication year - 2017
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/nyas.13425
Subject(s) - resveratrol , wine , multivariate statistics , spurious relationship , metabolite , multivariate analysis , bioavailability , antioxidant , coronary heart disease , function (biology) , chemistry , pharmacology , food science , biochemistry , medicine , biology , computer science , machine learning , evolutionary biology
Resveratrol is probably the most investigated plant secondary metabolite ever. An epidemiological study known as the French paradox showed a correlation between red wine intake and low mortality due to coronary heart diseases, and the red wine substance resveratrol was claimed to play a key role. Since then, several hundred resveratrol studies have been conducted to demonstrate its antioxidant and other beneficial properties. In the foodomics era, considering a complex foodome including over 25,000 substances that make up the human diet, it appears to be outdated to pursue the hunt for biological activities one function/compound at a time. First, nature is multivariate, and the effect of any one molecule will have to be modulated by its carrying matrix, its bioavailability, and synergies with other molecules. Second, a large number of targeted studies have the tendency to become biased, as they tend to retain only the data that the researchers think are relevant and thus increase the chances of spurious correlations. In this concise review, we retrace the research toward a more inductive, holistic, and multivariate path.