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• W2568649357 abstract "Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils, and beans), spot urine samples from a subcohort from the PREDIMED study were stratified using a validated food frequency questionnaire. Urine samples of nonpulse consumers (≤4 g/day of pulse intake) and habitual pulse consumers (≥25 g/day of pulse intake) were analyzed using a 1H nuclear magnetic resonance (NMR) metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine, and 3-methylhistidine. This model was evaluated by a receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to reported pulse exposure highlighted new candidates for biomarkers of pulse consumption and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings." @default.
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• W2568649357 date "2017-03-16" @default.
• W2568649357 modified "2023-10-16" @default.
• W2568649357 title "Urinary ¹H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a Subcohort from the PREDIMED study" @default.
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• W2568649357 doi "https://doi.org/10.1021/acs.jproteome.6b00860" @default.
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