Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/63238
Title: Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort
Author: Garcia Aloy, Mar
Llorach, Rafael
Urpí Sardà, Mireia
Tulipani, Sara
Salas Salvadó, Jordi
Martínez-González, Miguel Ángel, 1957-
Corella Piquer, Dolores
Fitó, Montserrat
Estruch Riba, Ramon
Serra Majem, Lluís
Andrés Lacueva, Ma. Cristina
Keywords: Metabòlits
Nutrició
Marcadors bioquímics
Pa
Consum d'aliments
Cromatografia de líquids d'alta resolució
Espectrometria de masses
Metabolites
Nutrition
Biochemical markers
Bread
Food consumption
High performance liquid chromatography
Mass spectrometry
Issue Date: 28-Jun-2014
Publisher: Springer Science + Business Media
Abstract: Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC <br>q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 <br>86.4 %) to 93.7 % (89.4 <br>98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 <br>69.7 %) to 78.4 % (69.8 <br>87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.
Note: Versió postprint del document publicat a: http://dx.doi.org/10.1007/s11306-014-0682-6
It is part of: Metabolomics, 2015, vol. 11, num. 1, p. 155-165
Related resource: http://dx.doi.org/10.1007/s11306-014-0682-6
URI: http://hdl.handle.net/2445/63238
ISSN: 1573-3882
Appears in Collections:Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)
Articles publicats en revistes (Medicina)

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