Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort
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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–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 % (69.1–86.4 %) to 93.7 % (89.4–98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6–69.7 %) to 78.4 % (69.8–87.1 %). 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.
KeywordsNutrimetabolomics Food metabolome Biomarkers Bread HPLC–q-TOF-MS Metabolic fingerprinting
- Bautista-Castano, I., Sanchez-Villegas, A., Estruch, R., et al. (2012). Changes in bread consumption and 4-year changes in adiposity in Spanish subjects at high cardiovascular risk. British Journal of Nutrition, 110, 337–346.Google Scholar
- Ismail, N. A., Posma, J. M., Frost, G., et al. (2013). The role of metabonomics as a tool for augmenting nutritional information in epidemiological studies. Electrophoresis, 34, 2276–2286.Google Scholar
- Llorach-Asuncion, R., Jauregui, O., Urpi-Sarda, M., & Andres-Lacueva, C. (2010). Methodological aspects for metabolome visualization and characterization: A metabolomic evaluation of the 24 h evolution of human urine after cocoa powder consumption. Journal of Pharmaceutical and Biomedical Analysis, 51, 373–381.PubMedCrossRefGoogle Scholar
- Martinez-Gonzalez, M. A., Palma, S., & Toledo, E. (2006). Correlación y regresión. In M. A. Martinez-Gonzalez (Ed.), Bioestadística Amigable. Madrid: Díaz de Santos.Google Scholar
- Mataix Verdú, J. (2003). Tabla de Composición de Alimentos. Granada: Universidad de Granada.Google Scholar
- Qi, Y., Li, P., Zhang, Y., et al. (2012). Urinary metabolite markers of precocious puberty. Molecular and Cellular Proteomics, 11: M111.011072.Google Scholar
- R Core Team. (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org/.
- Roux, A., Xu, Y., Heilier, J. F., et al. (2012). Annotation of the human adult urinary metabolome and metabolite identification using ultra high performance liquid chromatography coupled to a linear quadrupole ion trap-Orbitrap mass spectrometer. Analytical Chemistry, 84, 6429–6437.PubMedCrossRefGoogle Scholar
- Spanish Agency for Food Safety and Nutrition. (2011). ENIDE: National Survey of Dietary Intake (2009–2010): Results of consumer data. In AESAN. Retrieved January 23, 2013, from http://www.aesan.msc.es/AESAN/docs/docs/evaluacion_riesgos/datos_consumo/ENIDE.pdf.
- Spanish Food Composition Database (BEDCA). (2010). BEDCA Database v1.0. In RedBEDCA, AESAN. Retrieved January 23, 2013, from http://www.bedca.net.