Author, as appears in the article.: Garcia-Aloy, Mar; Llorach, Rafael; Urpi-Sarda, Mireia; Jauregui, Olga; Corella, Dolores; Ruiz-Canela, Miguel; Salas-Salvado, Jordi; Fito, Montserrat; Ros, Emilio; Estruch, Ramon; Andres-Lacueva, Cristina;
Department: Bioquímica i Biotecnologia
URV's Author/s: Salas Salvadó, Jorge / Urpi Sarda, Mireia
Keywords: biomarker model cocoa hplc-q-tof-ms metabolomics Biomarker model Cocoa Hplc-q-tof-ms Metabolomics Nutrition
Abstract: The aim of the current study was to apply an untargeted metabolomics strategy to characterize a model of cocoa intake biomarkers in a free-living population.An untargeted HPLC-q-ToF-MS based metabolomics approach was applied to human urine from 32 consumers of cocoa or derived products (CC) and 32 matched control subjects with no consumption of cocoa products (NC). The multivariate statistical analysis (OSC-PLS-DA) showed clear differences between CC and NC groups. The discriminant biomarkers identified were mainly related to the metabolic pathways of theobromine and polyphenols, as well as to cocoa processing. Consumption of cocoa products was also associated with reduced urinary excretions of methylglutarylcarnitine, which could be related to effects of cocoa exposure on insulin resistance. To improve the prediction of cocoa consumption, a combined urinary metabolite model was constructed. ROC curves were performed to evaluate the model and individual metabolites. The AUC values (95% CI) for the model were 95.7% (89.8-100%) and 92.6% (81.9-100%) in training and validation sets, respectively, whereas the AUCs for individual metabolites were <90%.The metabolic signature of cocoa consumption in free-living subjects reveals that combining different metabolites as biomarker models improves prediction of dietary exposure to cocoa.© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Thematic Areas: Astronomia / física Biotechnology Biotecnología Ciência de alimentos Ciências agrárias i Ciências biológicas i Ciências biológicas ii Educação física Farmacia Food science Food science & technology Interdisciplinar Medicina i Medicina ii Medicina veterinaria Nutrição Química Saúde coletiva
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: jordi.salas@urv.cat mireia.urpi@urv.cat
ISSN: 16134125
Author identifier: 0000-0003-2700-7459
Record's date: 2023-02-18
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://onlinelibrary.wiley.com/doi/epdf/10.1002/mnfr.201400434
Papper original source: Molecular Nutrition & Food Research. 59 (2): 212-220
APA: Garcia-Aloy, Mar; Llorach, Rafael; Urpi-Sarda, Mireia; Jauregui, Olga; Corella, Dolores; Ruiz-Canela, Miguel; Salas-Salvado, Jordi; Fito, Montserrat; (2015). A metabolomics-driven approach to predict cocoa product consumption by designing a multimetabolite biomarker model in free-living subjects from the PREDIMED study. Molecular Nutrition & Food Research, 59(2), 212-220. DOI: 10.1002/mnfr.201400434
Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
Article's DOI: 10.1002/mnfr.201400434
Entity: Universitat Rovira i Virgili
Journal publication year: 2015
Publication Type: Journal Publications
Repositori URV