Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/73063
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dc.contributor.authorHernández-Alonso, Pabloen_US
dc.contributor.authorBecerra-Tomás, Nereaen_US
dc.contributor.authorPapandreou, Christopheren_US
dc.contributor.authorBulló, Mònicaen_US
dc.contributor.authorGuasch-Ferré, Martaen_US
dc.contributor.authorToledo, Estefaníaen_US
dc.contributor.authorRuiz-Canela, Miguelen_US
dc.contributor.authorClish, Clary B.en_US
dc.contributor.authorCorella, Doloresen_US
dc.contributor.authorDennis, Courtneyen_US
dc.contributor.authorDeik, Amyen_US
dc.contributor.authorWang, Dong D.en_US
dc.contributor.authorRazquin, Cristinaen_US
dc.contributor.authorDrouin-Chartier, Jean Philippeen_US
dc.contributor.authorEstruch, Ramonen_US
dc.contributor.authorRos, Emilioen_US
dc.contributor.authorFitó, Montserraten_US
dc.contributor.authorArós, Fernandoen_US
dc.contributor.authorFiol, Miquelen_US
dc.contributor.authorSerra Majem, Luisen_US
dc.contributor.authorLiang, Limingen_US
dc.contributor.authorMartínez-González, Miguel A.en_US
dc.contributor.authorHu, Frank B.en_US
dc.contributor.authorSalas-Salvadó, Jordien_US
dc.date.accessioned2020-06-08T09:36:46Z-
dc.date.available2020-06-08T09:36:46Z-
dc.date.issued2020en_US
dc.identifier.issn1613-4125en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/73063-
dc.description.abstractThe plasma metabolomics profiles of protein intake have been rarely investigated. The aim is to identify the distinct plasma metabolomics profiles associated with overall intakes of protein as well as with intakes from animal and plant protein sources. Methods and results: A cross-sectional analysis using data from 1833 participants at high risk of cardiovascular disease is conducted. Associations between 385 identified metabolites and the intake of total, animal protein (AP), and plant protein (PP), and plant-to-animal ratio (PR) are assessed using elastic net continuous regression analyses. A double 10-cross-validation (CV) procedure is used and Pearson correlations coefficients between multi-metabolite weighted models and reported protein intake in each pair of training-validation datasets are calculated. A wide set of metabolites is consistently associated with each protein source evaluated. These metabolites mainly consisted of amino acids and their derivatives, acylcarnitines, different organic acids, and lipid species. Few metabolites overlapped among protein sources (i.e., C14:0 SM, C20:4 carnitine, GABA, and allantoin) but none of them toward the same direction. Regarding AP and PP approaches, C20:4 carnitine and dimethylglycine are positively associated with PP but negatively associated with AP. However, allantoin, C14:0 SM, C38:7 PE plasmalogen, GABA, metronidazole, and trigonelline (N-methylnicotinate) behave contrarily. Ten-CV Pearson correlation coefficients between self-reported protein intake and plasma metabolomics profiles range from 0.21 for PR to 0.32 for total protein. Conclusions: Different sets of metabolites are associated with total, animal, and plant protein intake. Further studies are needed to assess the contribution of these metabolites in protein biomarkers’ discovery and prediction of cardiometabolic alterations.en_US
dc.languageengen_US
dc.relation.ispartofMolecular Nutrition And Food Researchen_US
dc.sourceMolecular Nutrition and Food Research [ISSN 1613-4125], v. 64(12), (Enero 2020)en_US
dc.subject32 Ciencias médicasen_US
dc.subject.otherLipidomicsen_US
dc.subject.otherLiquid Chromatography Tandem Mass Spectrometryen_US
dc.subject.otherMetabolitesen_US
dc.subject.otherMetabolomicsen_US
dc.subject.otherProteinen_US
dc.titlePlasma Metabolomics Profiles are Associated with the Amount and Source of Protein Intake: A Metabolomics Approach within the PREDIMED Studyen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/mnfr.202000178en_US
dc.identifier.scopus85085569275-
dc.contributor.authorscopusid56239477300-
dc.contributor.authorscopusid56416500800-
dc.contributor.authorscopusid36470858000-
dc.contributor.authorscopusid6602243634-
dc.contributor.authorscopusid55110459200-
dc.contributor.authorscopusid7003562288-
dc.contributor.authorscopusid6603417884-
dc.contributor.authorscopusid35460787900-
dc.contributor.authorscopusid7003570538-
dc.contributor.authorscopusid57130114700-
dc.contributor.authorscopusid54880256400-
dc.contributor.authorscopusid57216964292-
dc.contributor.authorscopusid13612519200-
dc.contributor.authorscopusid56397170200-
dc.contributor.authorscopusid7005989830-
dc.contributor.authorscopusid35474202600-
dc.contributor.authorscopusid6602891390-
dc.contributor.authorscopusid7004158382-
dc.contributor.authorscopusid7005315313-
dc.contributor.authorscopusid35596972100-
dc.contributor.authorscopusid57216656850-
dc.contributor.authorscopusid7004290629-
dc.contributor.authorscopusid57208121316-
dc.contributor.authorscopusid7003357665-
dc.identifier.eissn1613-4133-
dc.investigacionCiencias de la Saluden_US
dc.type2Artículoen_US
dc.description.numberofpages12en_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2020en_US
dc.identifier.ulpgcen_US
dc.description.sjr1,495
dc.description.jcr5,914
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IUIBS: Nutrición-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptDepartamento de Ciencias Clínicas-
crisitem.author.orcid0000-0002-9658-9061-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.fullNameSerra Majem, Luis-
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