(1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors

• Published in: Electrophoresis Vol. 33; no. 15; pp. 2345 - 2354
• Main Authors: Vázquez-Fresno, Rosa, Llorach, Rafael, Alcaro, Francesca, Rodríguez, Miguel Ángel, Vinaixa, Maria, Chiva-Blanch, Gemma, Estruch, Ramon, Correig, Xavier, Andrés-Lacueva, Cristina
• Format: Journal Article
• Language: English
• Published: Germany Wiley-VCH 01.08.2012
• Subjects: Alcohol Drinking - metabolism; Alcohol Drinking - urine; Analysis of Variance; Biochemical markers; Biomarkers - metabolism; Biomarkers - urine; Cardiovascular diseases; Cardiovascular Diseases - metabolism; Cardiovascular Diseases - urine; Consum d'alcohol; Cross-Over Studies; Drinking of alcoholic beverages; Ethanol - administration & dosage; Ethanol - metabolism; Flavonoids - administration & dosage; Flavonoids - metabolism; Humans; Malalties cardiovasculars; Male; Marcadors bioquímics; Metabolism; Metabolisme; Metabolites; Metabolome - drug effects; Metabolomics; Metabòlits; Metagenome; Middle Aged; Nuclear magnetic resonance; Nuclear Magnetic Resonance, Biomolecular - methods; Phenols - administration & dosage; Phenols - metabolism; Prospective Studies; Ressonància magnètica nuclear; Risk Factors; Wine
• ISSN: 0173-0835; 1522-2683
• DOI: 10.1002/elps.201100646

Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake.