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Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

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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–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.

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References

  • Adhikari, K. B., Laursen, B. B., Gregersen, P. L., et al. (2013). Absorption and metabolic fate of bioactive dietary benzoxazinoids in humans. Molecular Nutrition and Food Research, 57, 1847–1858.

    CAS  PubMed  Google Scholar 

  • Andersen, M. B., Rinnan, A., Manach, C., et al. (2014). Untargeted metabolomics as a screening tool for estimating compliance to a dietary pattern. Journal of Proteome Research, 13, 1405–1418.

    Article  CAS  PubMed  Google Scholar 

  • Bach-Faig, A., Berry, E. M., Lairon, D., et al. (2011). Mediterranean diet pyramid today. Science and cultural updates. Public Health Nutrition, 14, 2274–2284.

    Article  PubMed  Google Scholar 

  • 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.

  • Bautista-Castano, I., & Serra-Majem, L. (2012). Relationship between bread consumption, body weight, and abdominal fat distribution: Evidence from epidemiological studies. Nutrition Reviews, 70, 218–233.

    Article  PubMed  Google Scholar 

  • Beckmann, M., Lloyd, A. J., Haldar, S., et al. (2013). Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread. Molecular Nutrition and Food Research, 57, 1859–1873.

    CAS  PubMed  Google Scholar 

  • Bondia-Pons, I., Barri, T., Hanhineva, K., et al. (2013). UPLC–QTOF/MS metabolic profiling unveils urinary changes in humans after a whole grain rye versus refined wheat bread intervention. Molecular Nutrition and Food Research, 57, 412–422.

    Article  CAS  PubMed  Google Scholar 

  • Bondia-Pons, I., Nordlund, E., Mattila, I., et al. (2011). Postprandial differences in the plasma metabolome of healthy Finnish subjects after intake of a sourdough fermented endosperm rye bread versus white wheat bread. Nutrition Journal, 10, 116.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Depeint, F., Bruce, W. R., Shangari, N., et al. (2006). Mitochondrial function and toxicity: Role of the B vitamin family on mitochondrial energy metabolism. Chemico-Biological Interactions, 163, 94–112.

    Article  CAS  PubMed  Google Scholar 

  • Dong, H., Zhang, A., Sun, H., et al. (2012). Ingenuity pathways analysis of urine metabolomics phenotypes toxicity of Chuanwu in Wistar rats by UPLC–Q-TOF-HDMS coupled with pattern recognition methods. Molecular Biosystems, 8, 1206–1221.

    Article  CAS  PubMed  Google Scholar 

  • Estruch, R., Ros, E., Salas-Salvado, J., et al. (2013). Primary prevention of cardiovascular disease with a Mediterranean diet. New England Journal of Medicine, 368, 1279–1290.

    Article  CAS  PubMed  Google Scholar 

  • Fernandez-Ballart, J. D., Pinol, J. L., Zazpe, I., et al. (2010). Relative validity of a semi-quantitative food-frequency questionnaire in an elderly Mediterranean population of Spain. British Journal of Nutrition, 103, 1808–1816.

    Article  CAS  PubMed  Google Scholar 

  • Gil, A., Ortega, R. M., & Maldonado, J. (2011). Wholegrain cereals and bread: A duet of the Mediterranean diet for the prevention of chronic diseases. Public Health Nutrition, 14, 2316–2322.

    Article  PubMed  Google Scholar 

  • Hellwig, M., & Henle, T. (2012). Quantification of the Maillard reaction product 6-(2-formyl-1-pyrrolyl)-l-norleucine (formyline) in food. European Food Research and Technology, 235, 99–106.

    Article  CAS  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 

  • Jiang, D., & Peterson, D. G. (2013). Identification of bitter compounds in whole wheat bread. Food Chemistry, 141, 1345–1353.

    Article  CAS  PubMed  Google Scholar 

  • Johansson-Persson, A., Barri, T., Ulmius, M., et al. (2013). LC–QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake. Analytical and Bioanalytical Chemistry, 405, 4799–4809.

    Article  CAS  PubMed  Google Scholar 

  • Lankinen, M., Schwab, U., Seppanen-Laakso, T., et al. (2011). Metabolomic analysis of plasma metabolites that may mediate effects of rye bread on satiety and weight maintenance in postmenopausal women. Journal of Nutrition, 141, 31–36.

    Article  CAS  PubMed  Google Scholar 

  • Li, F., Pang, X., Krausz, K. W., et al. (2013). Stable isotope- and mass spectrometry-based metabolomics as tools in drug metabolism: A study expanding tempol pharmacology. Journal of Proteome Research, 12, 1369–1376.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Llorach, R., Garcia-Aloy, M., Tulipani, S., et al. (2012). Nutrimetabolomic strategies to develop new biomarkers of intake and health effects. Journal of Agriculture and Food Chemistry, 60, 8797–8808.

    Article  CAS  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.

    Article  CAS  PubMed  Google Scholar 

  • Llorach, R., Urpi-Sarda, M., Jauregui, O., et al. (2009). An LC–MS-based metabolomics approach for exploring urinary metabolome modifications after cocoa consumption. Journal of Proteome Research, 8, 5060–5068.

    Article  CAS  PubMed  Google Scholar 

  • Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., et al. (2012). Diversity, stability and resilience of the human gut microbiota. Nature, 489, 220–230.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Magnus, V., Simaga, S., Iskric, S., & Kveder, S. (1982). Metabolism of tryptophan, indole-3-acetic acid, and related compounds in parasitic plants from the genus Orobanche. Plant Physiology, 69, 853–858.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Martinez-Gonzalez, M. A., Corella, D., Salas-Salvado, J., et al. (2012). Cohort profile: Design and methods of the PREDIMED study. International Journal of Epidemiology, 41, 377–385.

    Article  PubMed  Google 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 

  • McKeown, N. M., Meigs, J. B., Liu, S., et al. (2002). Whole-grain intake is favorably associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study. American Journal of Clinical Nutrition, 76, 390–398.

    CAS  PubMed  Google Scholar 

  • Michalska, A., Amigo-Benavent, M., Zielinski, H., & del Castillo, M. D. (2008). Effect of bread making on formation of Maillard reaction products contributing to the overall antioxidant activity of rye bread. Journal of Cereal Science, 48, 123–132.

    Article  CAS  Google Scholar 

  • Moazzami, A. A., Bondia-Pons, I., Hanhineva, K., et al. (2012). Metabolomics reveals the metabolic shifts following an intervention with rye bread in postmenopausal women—A randomized control trial. Nutrition Journal, 11, 88.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Moco, S., Martin, F. P., & Rezzi, S. (2012). Metabolomics view on gut microbiome modulation by polyphenol-rich foods. Journal of Proteome Research, 11, 4781–4790.

    Article  CAS  PubMed  Google Scholar 

  • Moraes, M. C., Birkett, M. A., Gordon-Weeks, R., et al. (2008). cis-Jasmone induces accumulation of defence compounds in wheat, Triticum aestivum. Phytochemistry, 69, 9–17.

    Article  CAS  PubMed  Google Scholar 

  • Nielsen, K. L., Hartvigsen, M. L., Hedemann, M. S., et al. (2014). Similar metabolic responses in pigs and humans to breads with different contents and compositions of dietary fibers: A metabolomics study. American Journal of Clinical Nutrition, 99, 941–949.

    Article  CAS  PubMed  Google Scholar 

  • Pujos-Guillot, E., Hubert, J., Martin, J. F., et al. (2013). Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: Citrus fruit as a case study. Journal of Proteome Research, 12, 1645–1659.

    Article  CAS  PubMed  Google Scholar 

  • Qi, Y., Li, P., Zhang, Y., et al. (2012). Urinary metabolite markers of precocious puberty. Molecular and Cellular Proteomics, 11: M111.011072.

  • Quilez, J., & Salas-Salvado, J. (2012). Salt in bread in Europe: Potential benefits of reduction. Nutrition Reviews, 70, 666–678.

    Article  PubMed  Google Scholar 

  • R Core Team. (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org/.

  • Robin, X., Turck, N., Hainard, A., et al. (2011). pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics, 12, 77.

    Article  PubMed Central  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • Sofi, F., Abbate, R., Gensini, G. F., & Casini, A. (2010). Accruing evidence on benefits of adherence to the Mediterranean diet on health: An updated systematic review and meta-analysis. American Journal of Clinical Nutrition, 92, 1189–1196.

    Article  CAS  PubMed  Google 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.

  • Sumner, L. W., Amberg, A., Barrett, D., et al. (2007). Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics, 3, 211–221.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Tousoulis, D., Antoniades, C., Tentolouris, C., et al. (2002). l-Arginine in cardiovascular disease: Dream or reality? Vascular Medicine, 7, 203–211.

    Article  PubMed  Google Scholar 

  • Tulipani, S., Llorach, R., Jauregui, O., et al. (2011). Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption. Journal of Proteome Research, 10, 5047–5058.

    Article  CAS  PubMed  Google Scholar 

  • Williams, P. G. (2012). Evaluation of the evidence between consumption of refined grains and health outcomes. Nutrition Reviews, 70, 80–99.

    Article  PubMed  Google Scholar 

  • Xia, J., Broadhurst, D. I., Wilson, M., & Wishart, D. S. (2013). Translational biomarker discovery in clinical metabolomics: An introductory tutorial. Metabolomics, 9, 280–299.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Zhen, Y., Krausz, K. W., Chen, C., et al. (2007). Metabolomic and genetic analysis of biomarkers for peroxisome proliferator-activated receptor alpha expression and activation. Molecular Endocrinology, 21, 2136–2151.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

This research was supported by Spanish National Grants from the Ministry of Economy and Competitiveness (MINECO), as well as FEDER (Fondo Europeo de Desarrollo Regional): AGL2009-13906-C02-01, AGL2010-10084-E, CONSOLIDER INGENIO 2010 Programme: FUN-C-FOOD-CSD2007-063, and ISCIII-CIBEROBN; Merck Serono Research Grants 2010 from Fundación Salud 2000, and by “Pan cada día” open call promoted by the Scientific Committee of Bread and by INCERHPAN. The "CIBER de Fisiopatología de la Obesidad y Nutrición" (CIBEROBN) is an initiative of the Instituto de Salud Carlos III, Madrid, Spain. M. G. A. thanks the Generalitat de Catalunya’s Agency AGAUR for the predoctoral FI-DGR 2011 Fellowship. R. Ll. and M. U. S. thank the “Ramón y Cajal” (RYC-2010–07334 and RYC-2011-09677, respectively) and ST the “Juan de la Cierva” program, both programmes from MINECO and Fondo Social Europeo (FSE). MF was funded by a contract from the Catalan Government and the Instituto de Salud Carlos III FEDER (FIS CP06/00100). None of the funding sources had any involvement in the study or data analysis.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Biomarkers & Nutrimetabolomic Lab., Nutrition and Food Science Department, XaRTA, INSA, Campus Torribera, Pharmacy Faculty, University of Barcelona, Av. Joan XXIII s/n, 08028, Barcelona, Spain

    Mar Garcia-Aloy, Rafael Llorach, Mireia Urpi-Sarda & Cristina Andres-Lacueva

  2. INGENIO-CONSOLIDER Program, Fun-C-Food CSD2007-063, Ministry of Science and Innovation, Barcelona, Spain

    Mar Garcia-Aloy, Rafael Llorach, Mireia Urpi-Sarda, Sara Tulipani & Cristina Andres-Lacueva

  3. Biomedical Research Institute (IBIMA), Service of Endocrinology and Nutrition, Hospital Complex (Virgen de la Victoria), Campus de Teatinos s/n, University of Málaga, 29010, Málaga, Spain

    Sara Tulipani

  4. Human Nutrition Unit, Hospital Universitari de Sant Joan de Reus, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili, Reus, Spain

    Jordi Salas-Salvadó

  5. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain

    Jordi Salas-Salvadó, Miguel Angel Martínez-González, Dolores Corella, Montserrat Fitó, Ramon Estruch & Lluis Serra-Majem

  6. Department of Preventive Medicine and Public Health, Medical School-Clinica, University of Navarra, Pamplona, Spain

    Miguel Angel Martínez-González

  7. Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain

    Dolores Corella

  8. Cardiovascular Risk and Nutrition Research Group, IMIM-Institut de Recerca del Hospital del Mar, Barcelona, Spain

    Montserrat Fitó

  9. Department of Internal Medicine, Hospital Clinic, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain

    Ramon Estruch

  10. Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Lluis Serra-Majem

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  1. Mar Garcia-Aloy
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  2. Rafael Llorach
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  3. Mireia Urpi-Sarda
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  4. Sara Tulipani
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  10. Lluis Serra-Majem
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  11. Cristina Andres-Lacueva
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Corresponding authors

Correspondence to Rafael Llorach or Cristina Andres-Lacueva.

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Garcia-Aloy, M., Llorach, R., Urpi-Sarda, M. et al. Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort. Metabolomics 11, 155–165 (2015). https://doi.org/10.1007/s11306-014-0682-6

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