Mar Garcia-Aloy1,2,3, Marynka Ulaszewska4,3, Pietro Franceschi5, Sheila Estruel-Amades1, Christoph H Weinert6, Alba Tor-Roca1,2, Mireia Urpi-Sarda1,2, Fulvio Mattivi3,7, Cristina Andres-Lacueva1,2. 1. Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain. 2. CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, 08028, Spain. 3. Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), San Michele all'Adige, 38010, Italy. 4. IRCCS San Raffaele Scientific Institute, Center for Omics Sciences, Proteomics and Metabolomics Facility - ProMeFa, Milan, 20132, Italy. 5. Computational Biology Unit, Research and Innovation Center, Fondazione Edmund Mach, San Michele all'Adige, 38010, Italy. 6. Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Karlsruhe, 76131, Germany. 7. Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, 38123, Italy.
Abstract
SCOPE: To identify reliable biomarkers of food intake (BFIs) of pulses. METHODS AND RESULTS: A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses. CONCLUSIONS: The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity.
RCT Entities:
SCOPE: To identify reliable biomarkers of food intake (BFIs) of pulses. METHODS AND RESULTS: A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses. CONCLUSIONS: The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity.
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