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

Abstract

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, 24h-urine samples were collected and analyzed by 1 H-NMR. According to the results of an 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 which 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.

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

“…Two metabolites previously described associated with dealcoholized wine (Vázquez-Fresno et al, 2012) and derived from gut microbiota were hippurate and 4-hydroxyphenylacetate. These two metabolites were also tested with wine versus baseline participants showing no significant association after logistic regression analysis (p>0.05).…”

“…A procedure based on previous published methodology ( Vázquez-Fresno et al, 2012) was applied for the metabolomics analysis. The urine samples were thawed, vortexed, and centrifuged at 13 200 rpm for 5 min.…”

“…Significant metabolites from WIS study which were tested in ROC curve analysis were those previously found (Vázquez-Fresno et al, 2012) and those significant after Bonferroni correction. ROC curves for each metabolite that was statistically significant were calculated (each ROC curve was constructed using a dichotomous variable of wine consumption).Then, a logistic regression model was generated by forward stepwise selection procedures as previously described (BahadoSingh et al, 2012;Murabito et al, 2009).…”

Urinary metabolomic fingerprinting after consumption of a probiotic strain in women with mastitis

“…The supernatant (600 µl) from each urine sample was mixed with an internal standard solution [120 μL, consisting of 0.1% TSP (3-(trimethylsilyl)-proprionate-2,2,3,3-d4, chemical shift reference), 2 mM of sodium azide (NaN3, bacteriostatic agent) and 1.5M KH 2 PO 4 , in 99% deuterium water (D2O)]. The optimized pH of the buffer was set at 7.0, with a potassium deuteroxide solution, to minimize variations in the chemical shifts of the NMR resonances [20]. This mixture was transferred to a 5 mm NMR tube.…”

“…FIDs were collected into 32 K data points (128 scans) with a spectral width of 14 ppm, an acquisition time of 2 s, relaxation delay of 5 s, and a mixing time of 100 ms [20]. A 0.3 Hz line broadening function was applied to raw FIDs prior to Fourier transformation.…”