Autor según el artículo: 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;
Departamento: Bioquímica i Biotecnologia
Autor/es de la URV: Salas Salvadó, Jorge / Urpi Sarda, Mireia
Palabras clave: Nutrition Metabolomics Hplc-q-tof-ms Cocoa Biomarker model metabolomics hplc-q-tof-ms cocoa biomarker model
Resumen: 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.
Áreas temáticas: Saúde coletiva Química Nutrição Medicina veterinaria Medicina ii Medicina i Interdisciplinar Food science & technology Food science Farmacia Educação física Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Biotecnología Biotechnology Astronomia / física
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 16134125
Direcció de correo del autor: mireia.urpi@urv.cat jordi.salas@urv.cat
Identificador del autor: 0000-0003-2700-7459
Fecha de alta del registro: 2024-09-07
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://onlinelibrary.wiley.com/doi/epdf/10.1002/mnfr.201400434
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Molecular Nutrition & Food Research. 59 (2): 212-220
Referencia de l'ítem segons les normes 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
DOI del artículo: 10.1002/mnfr.201400434
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2015
Tipo de publicación: Journal Publications
Repositori URV