An NMR metabolomics approach reveals a combined-biomarkers model in a wine interventional trial with validation in free-living individuals of the ... View Full Text


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Article Info

DATE

2014-10-11

AUTHORS

Rosa Vázquez-Fresno, Rafael Llorach, Mireia Urpi-Sarda, Olha Khymenets, Mònica Bulló, Dolores Corella, Montserrat Fitó, Miguel Angel Martínez-González, Ramon Estruch, Cristina Andres-Lacueva

ABSTRACT

The development of robust biomarkers of consumption would improve the classification of participants with regard to their dietary exposure. In addition, validation of them in free-living individuals remains an important challenge. The aim of this study is to assess wine intake biomarkers using an NMR metabolomic approach to measure the utility of these biomarkers in a wine interventional study (WIS, n = 56) and also to evaluate them in a free-living individuals (PREDIMED study, n = 91). Nine metabolites showed a significantly higher presence in urinary excretion in WIS after wine intake: five food metabolome metabolites (tartrate, ethyl glucuronide [EtG], 2,3-butanediol, mannitol, and ethanol); one related to the endogenous response to wine exposure (3-methyl-2-oxovalerate) and three unidentified compounds. Receiver operating characteristic (ROC) curve for each single metabolite were evaluated and exhibited areas under the curves (AUC) between 67.4 and 86.3 % when they were evaluated individually. Then, a logistic regression model was fitted to generate a combined-biomarkers model using these metabolites. The model generated which included tartrate-EtG, showed an AUC of 90.7 % in WIS. Similarly, the AUC in the PREDIMED study was 92.4 %. Results showed that a model combining tartrate-EtG is more useful for evaluating exposure to wine than single biomarkers, both in interventional studies and epidemiological data. To our knowledge, this is the first time that a combined-biomarker model using an NMR platform in wine biomarkers’ research has been generated and reproduced in a free-living population. More... »

PAGES

797-806

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11306-014-0735-x

DOI

http://dx.doi.org/10.1007/s11306-014-0735-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045526430


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