Literature DB >> 32420683

Discovery of Intake Biomarkers of Lentils, Chickpeas, and White Beans by Untargeted LC-MS Metabolomics in Serum and Urine.

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.   

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.
© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  biomarkers; dietary assessment; legumes; metabolomics; nutrimetabolomics

Mesh:

Substances:

Year:  2020        PMID: 32420683     DOI: 10.1002/mnfr.201901137

Source DB:  PubMed          Journal:  Mol Nutr Food Res        ISSN: 1613-4125            Impact factor:   5.914


  7 in total

1.  PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

Authors:  Nils Paulhe; Cécile Canlet; Annelaure Damont; Lindsay Peyriga; Stéphanie Durand; Catherine Deborde; Sandra Alves; Stephane Bernillon; Thierry Berton; Raphael Bir; Alyssa Bouville; Edern Cahoreau; Delphine Centeno; Robin Costantino; Laurent Debrauwer; Alexis Delabrière; Christophe Duperier; Sylvain Emery; Amelie Flandin; Ulli Hohenester; Daniel Jacob; Charlotte Joly; Cyril Jousse; Marie Lagree; Nadia Lamari; Marie Lefebvre; Claire Lopez-Piffet; Bernard Lyan; Mickael Maucourt; Carole Migne; Marie-Francoise Olivier; Estelle Rathahao-Paris; Pierre Petriacq; Julie Pinelli; Léa Roch; Pierrick Roger; Simon Roques; Jean-Claude Tabet; Marie Tremblay-Franco; Mounir Traïkia; Anna Warnet; Vanessa Zhendre; Dominique Rolin; Fabien Jourdan; Etienne Thévenot; Annick Moing; Emilien Jamin; François Fenaille; Christophe Junot; Estelle Pujos-Guillot; Franck Giacomoni
Journal:  Metabolomics       Date:  2022-06-14       Impact factor: 4.747

Review 2.  Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review.

Authors:  Talha Rafiq; Sandi M Azab; Koon K Teo; Lehana Thabane; Sonia S Anand; Katherine M Morrison; Russell J de Souza; Philip Britz-McKibbin
Journal:  Adv Nutr       Date:  2021-12-01       Impact factor: 8.701

3.  Serum metabolomic signatures of plant-based diets and incident chronic kidney disease.

Authors:  Hyunju Kim; Bing Yu; Xin Li; Kari E Wong; Eric Boerwinkle; Sara B Seidelmann; Andrew S Levey; Eugene P Rhee; Josef Coresh; Casey M Rebholz
Journal:  Am J Clin Nutr       Date:  2022-07-06       Impact factor: 8.472

4.  The Gut Microbiome and Abiotic Factors as Potential Determinants of Postprandial Glucose Responses: A Single-Arm Meal Study.

Authors:  Nathalie Nestel; Josephine D Hvass; Martin I Bahl; Lars H Hansen; Lukasz Krych; Dennis S Nielsen; Lars Ove Dragsted; Henrik M Roager
Journal:  Front Nutr       Date:  2021-01-14

5.  Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective.

Authors:  Manfred Beckmann; Thomas Wilson; Amanda J Lloyd; Duarte Torres; Ana Goios; Naomi D Willis; Laura Lyons; Helen Phillips; John C Mathers; John Draper
Journal:  Front Nutr       Date:  2020-11-25

6.  Plasma Metabolites Associated with a Protein-Rich Dietary Pattern: Results from the OmniHeart Trial.

Authors:  Hyunju Kim; Alice H Lichtenstein; Karen White; Kari E Wong; Edgar R Miller; Josef Coresh; Lawrence J Appel; Casey M Rebholz
Journal:  Mol Nutr Food Res       Date:  2022-02-05       Impact factor: 6.575

7.  Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

Authors:  Naomi D Willis; Amanda J Lloyd; Long Xie; Martina Stiegler; Kathleen Tailliart; Isabel Garcia-Perez; Edward S Chambers; Manfred Beckmann; John Draper; John C Mathers
Journal:  Front Nutr       Date:  2020-10-21
  7 in total

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