An NMR-based metabolomics approach reveals a combined-biomarkers model in a wine interventional trial with validation in free-living individuals of the PREDIMED study

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 NM...

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Published in:Metabolomics 2014-08
Main Authors: Vázquez Fresno, Rosa, Llorach, Rafael, Urpí Sardà, Mireia, Khymenets, Olha, Bulló, Mònica, Corella Piquer, Dolores, Fitó Colomer, Montserrat, Martínez-González, Miguel Ángel, 1957, Estruch Riba, Ramon, Andrés Lacueva, Ma. Cristina
Format: Article
Language:English
Subjects:
Biochemical markers
Marcadors bioquímics
Metabolites
Metabòlits
Nuclear magnetic resonance
Nutrició
Nutrition
Ressonància magnètica nuclear
Wine
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Summary: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.
ISSN:1573-3882