Plasma metabolomic biomarkers of mixed nuts exposure inversely correlate with severity of metabolic syndrome

Molecular Nutrition and Food Research

Volumn 59, Issue 12, 2015, Pages 2480-2490

  Mora Cubillos, Ximena ^a   Tulipani, Sara ^a,b   Garcia Aloy, Mar ^a   Bulló, Mònica ^c,d   Tinahones, Francisco J ^b,d   Andres Lacueva, Cristina ^a  

^a UNIVERSITY OF BARCELONA   (Spain)

^b UNIVERSITY OF MÁLAGA   (Spain)

^c UNIVERSITAT ROVIRA I VIRGILI   (Spain)

^d Instituto de Salud Carlos III   (Spain)

Author keywords

Adiposity; Biomarkers of nuts; Gut microbiota; Metabolomics; Plasma human

Indexed keywords

3,8-DIHYDROXY-6H-DIBENZO(B,D)PYRAN-6-ONE GLUCURONIDE; BIOLOGICAL MARKER; COUMARIN DERIVATIVE; FATTY ACID; GLUCURONIDE; POLYPHENOL;

BLOOD; CONTROLLED STUDY; DIET; DIET THERAPY; FEMALE; HUMAN; INTESTINE FLORA; MALE; METABOLIC SYNDROME X; METABOLISM; METABOLOMICS; MICROBIOLOGY; MIDDLE AGED; NUT; OBESITY; PHYSIOLOGY; PROCEDURES; RANDOMIZED CONTROLLED TRIAL; WAIST CIRCUMFERENCE;

ADIPOSITY; BIOMARKERS; COUMARINS; DIET; FATTY ACIDS; FEMALE; GASTROINTESTINAL MICROBIOME; GLUCURONIDES; HUMANS; MALE; METABOLIC SYNDROME X; METABOLOMICS; MIDDLE AGED; NUTS; POLYPHENOLS; WAIST CIRCUMFERENCE;

EID: 84954381324     PISSN: 16134125     EISSN: 16134133     Source Type: Journal    
DOI: 10.1002/mnfr.201500549     Document Type: Article

References (60)

1. Estruch, R., Ros, E., Salas-Salvado, J., Covas, M. I. et al., Primary prevention of cardiovascular disease with a Mediterranean diet. N. Engl. J. Med. 2013, 368, 1279-1290.
2. Mithril, C., Dragsted, L. O., Meyer, C., Tetens, I. et al., Dietary composition and nutrient content of the New Nordic diet. Public Health Nutr. 2013, 16, 777-785.
3. U.S. Department of Agriculture, U.S. Department of Health and Human Services, Scientific Report of the 2015 Dietary Guidelines Advisor Committee Government Printing Office: First Print. Available from: http://health.gov/dietaryguidelines/2015-scientific-report/ (accessed September 7, 2015).
4. Salas-Salvado, J., Guasch-Ferre, M., Bullo, M., Sabate, J., Nuts in the prevention and treatment of metabolic syndrome. Am. J. Clin. Nutr. 2014, 100, 399S-407S.
5. Blanco Mejia, S., Kendall, C. W., Viguiliouk, E., Augustin, L. S. et al., Effect of tree nuts on metabolic syndrome criteria: a systematic review and meta-analysis of randomised controlled trials. BMJ Open 2014, 4, e004660.
6. O'Neil, C. E., Keast, D. R., Nicklas, T. A., Fulgoni, V. L., 3rd, Nut consumption is associated with decreased health risk factors for cardiovascular disease and metabolic syndrome in U.S. adults: NHANES 1999-2004. J. Am. Coll. Nutr. 2011, 30, 502-510.
7. Fernandez-Montero, A., Bes-Rastrollo, M., Beunza, J. J., Barrio-Lopez, M. T. et al., Nut consumption and incidence of metabolic syndrome after 6-year follow-up: the SUN (Seguimiento Universidad de Navarra, University of Navarra follow-up) cohort. Public Health Nutr. 2013, 16, 2064-2072.
8. Ibarrola-Jurado, N., Bullo, M., Guasch-Ferre, M., Ros, E. et al., Cross-sectional assessment of nut consumption and obesity, metabolic syndrome and other cardiometabolic risk factors: the PREDIMED study. PLoS One 2013, 8, e57367.
9. Jackson, C. L., Hu, F. B., Long-term associations of nut consumption with body weight and obesity. Am. J. Clin. Nutr. 2014, 100, 408S-411S.
10. Guo, K., Zhou, Z., Jiang, Y., Li, W. et al., Meta-analysis of prospective studies on the effects of nut consumption on hypertension and type 2 diabetes mellitus. J. Diabetes 2015, 7, 202-212.
11. Ros, E., Martinez-Gonzalez, M. A., Estruch, R., Salas-Salvado, J. et al., Mediterranean diet and cardiovascular health: teachings of the PREDIMED study. Adv. Nutr. 2014, 5, 330S-336S.
12. Ros, E., Health benefits of nut consumption. Nutrients 2010, 2, 652-682.
13. Luo, C., Zhang, Y., Ding, Y., Shan, Z. et al., Nut consumption and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a systematic review and meta-analysis. Am. J. Clin. Nutr. 2014, 100, 256-269.
14. Casas-Agustench, P., Lopez-Uriarte, P., Bullo, M., Ros, E. et al., Effects of one serving of mixed nuts on serum lipids, insulin resistance and inflammatory markers in patients with the metabolic syndrome. Nutr. Metab. Cardiovasc. Dis. 2011, 21, 126-135.
15. Lopez-Uriarte, P., Nogues, R., Saez, G., Bullo, M. et al., Effect of nut consumption on oxidative stress and the endothelial function in metabolic syndrome. Clin. Nutr. 2010, 29, 373-380.
16. Tulipani, S., Urpi-Sarda, M., Garcia-Villalba, R., Rabassa, M. et al., Urolithins are the main urinary microbial-derived phenolic metabolites discriminating a moderate consumption of nuts in free-living subjects with diagnosed metabolic syndrome. J. Agric. Food Chem. 2012, 60, 8930-8940.
17. Garcia-Munoz, C., Vaillant, F., Metabolic fate of ellagitannins: implications for health, and research perspectives for innovative functional foods. Crit. Rev. Food Sci. Nutr. 2014, 54, 1584-1598.
18. Selma, M. V., Beltran, D., Garcia-Villalba, R., Espin, J. C. et al., Description of urolithin production capacity from ellagic acid of two human intestinal Gordonibacter species. Food Funct. 2014, 5, 1779-1784.
19. Selma, M. V., Tomas-Barberan, F. A., Beltran, D., Garcia-Villalba, R. et al., Gordonibacter urolithinfaciens sp. nov., an urolithin-producing bacterium isolated from human gut. Int. J. Syst. Evol. Microbiol. 2014, 64, 2346-2352.
20. Hartstra, A. V., Bouter, K. E., Backhed, F., Nieuwdorp, M., Insights into the role of the microbiome in obesity and type 2 diabetes. Diabetes Care 2015, 38, 159-165.
21. Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C. et al., The food metabolome: a window over dietary exposure. Am. J. Clin. Nutr. 2014, 99, 1286-1308.
22. Ussar, S., Griffin, N. W., Bezy, O., Fujisaka, S. et al., Interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and metabolic syndrome. Cell Metab. 2015, 22, 516-530.
23. van Ravenzwaay, B., Cunha, G. C., Leibold, E., Looser, R. et al., The use of metabolomics for the discovery of new biomarkers of effect. Toxicol. Lett. 2007, 172, 21-28.
24. Llorach, R., Garcia-Aloy, M., Tulipani, S., Vazquez-Fresno, R. et al., Nutrimetabolomic strategies to develop new biomarkers of intake and health effects. J. Agric. Food Chem. 2012, 60, 8797-8808.
25. Nicholson, J. K., Holmes, E., Kinross, J. M., Darzi, A. W. et al., Metabolic phenotyping in clinical and surgical environments. Nature 2012, 491, 384-392.
26. Rappaport, S. M., Barupal, D. K., Wishart, D., Vineis, P. et al., The blood exposome and its role in discovering causes of disease. Environ. Health Perspect. 2014, 122, 769-774.
27. Tulipani, S., Llorach, R., Jauregui, O., Lopez-Uriarte, P. et al., Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption. J. Proteome Res. 2011, 10, 5047-5058.
28. Grundy, S. M., Cleeman, J. I., Daniels, S. R., Donato, K. A. et al., Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation 2005, 112, 2735-2752.
29. Alberti, K. G., Eckel, R. H., Grundy, S. M., Zimmet, P. Z. et al., Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009, 120, 1640-1645.
30. Krauss, R. M., Eckel, R. H., Howard, B., Appel, L. J. et al., AHA Dietary Guidelines: revision 2000: a statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 2000, 102, 2284-2299.
31. Tulipani, S., Llorach, R., Urpi-Sarda, M., Andres-Lacueva, C., Comparative analysis of sample preparation methods to handle the complexity of the blood fluid metabolome: when less is more. Anal. Chem. 2013, 85, 341-348.
32. Tulipani, S., Mora-Cubillos, X., Jauregui, O., Llorach, R. et al., New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics. The not-so-simple process of method performance evaluation. Anal. Chem. 2015, 87, 2639-2647.
33. Rothwell, J. A., Fillatre, Y., Martin, J. F., Lyan, B. et al., New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects. PLoS One 2014, 9, e93474.
34. Llorach, R., Garrido, I., Monagas, M., Urpi-Sarda, M. et al., Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D.A. Webb) skin polyphenols. J. Proteome Res. 2010, 9, 5859-5867.
35. Fernandez-Albert, F., Llorach, R., Andres-Lacueva, C., Perera, A., An R package to analyze LC/MS metabolomic data: MAIT (Metabolite Automatic Identification Toolkit). Bioinformatics 2014, 30, 1937-1939.
36. Fernandez-Albert, F., Llorach, R., Andres-Lacueva, C., Perera-Lluna, A., Peak aggregation as an innovative strategy for improving the predictive power of LC-MS metabolomic profiles. Anal. Chem. 2014, 86, 2320-2325.
37. Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M. et al., HMDB 3.0-the human metabolome database in 2013. Nucleic Acids Res. 2013, 41, D801-D807.
38. Wagele, B., Witting, M., Schmitt-Kopplin, P., Suhre, K., MassTRIX reloaded: combined analysis and visualization of transcriptome and metabolome data. PLoS One 2012, 7, e39860.
39. Horai, H., Arita, M., Kanaya, S., Nihei, Y. et al., MassBank: a public repository for sharing mass spectral data for life sciences. J. Mass Spectrom. 2010, 45, 703-714.
40. Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H. et al., Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 2007, 3, 211-221.
41. Xia, J., Broadhurst, D. I., Wilson, M., Wishart, D. S., Translational biomarker discovery in clinical metabolomics: an introductory tutorial. Metabolomics 2013, 9, 280-299.
42. Robin, X., Turck, N., Hainard, A., Tiberti, N. et al., pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011, 12, 77.
43. Jenab, M., Sabate, J., Slimani, N., Ferrari, P. et al., Consumption and portion sizes of tree nuts, peanuts and seeds in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts from 10 European countries. Br. J. Nutr. 2006, 96, S12-S23.
44. Tomas-Barberan, F., Garcia-Villalba, R., Gonzalez-Sarrias, A., Selma, M. V. et al., Ellagic acid metabolism by human gut microbiota: consistent observation of three urolithin phenotypes in intervention trials, independent of food source, age and health status. J. Agric. Food Chem. 2014, 62, 6535-6538.
45. Espin, J. C., Larrosa, M., Garcia-Conesa, M. T., Tomas-Barberan, F., Biological significance of urolithins, the gut microbial ellagic acid-derived metabolites: the evidence so far. Evid. Based Complement. Alternat. Med. 2013, 2013, 270418.
46. Pfundstein, B., Haubner, R., Wurtele, G., Gehres, N. et al., Pilot walnut intervention study of urolithin bioavailability in human volunteers. J. Agric. Food Chem. 2014, 62, 10264-10273.
47. Seeram, N. P., Henning, S. M., Zhang, Y., Suchard, M. et al., Pomegranate juice ellagitannin metabolites are present in human plasma and some persist in urine for up to 48 hours. J. Nutr. 2006, 136, 2481-2485.
48. Puupponen-Pimia, R., Seppanen-Laakso, T., Kankainen, M., Maukonen, J. et al., Effects of ellagitannin-rich berries on blood lipids, gut microbiota, and urolithin production in human subjects with symptoms of metabolic syndrome. Mol. Nutr. Food Res. 2013, 57, 2258-2263.
49. Dembitsky, V. M., Goldshlag, P., Srebnik, M., Occurrence of dicarboxylic (dioic) acids in some Mediterranean nuts. Food Chem. 2002, 76, 469-473.
50. Mingrone, G., Castagneto, M., Medium-chain, even-numbered dicarboxylic acids as novel energy substrates: an update. Nutr. Rev. 2006, 64, 449-456.
51. Eckel, R. H., Jakicic, J. M., Ard, J. D., de Jesus, J. M. et al., 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J. Am. Coll. Cardiol. 2014, 63, 2960-2984.
52. Mingrone, G., Castagneto-Gissey, L., Mace, K., Use of dicarboxylic acids in type 2 diabetes. Br. J. Clin. Pharmacol. 2013, 75, 671-676.
53. Storlien, L., Oakes, N. D., Kelley, D. E., Metabolic flexibility. Proc. Nutr. Soc. 2004, 63, 363-368.
54. Greco Md, A. V., Mingrone Md, P. G., Capristo Md, E., Benedetti Md, G. et al., The metabolic effect of dodecanedioic acid infusion in non-insulin-dependent diabetic patients. Nutrition 1998, 14, 351-357.
55. Salinari, S., Bertuzzi, A., Gandolfi, A., Greco, A. V. et al., Dodecanedioic acid overcomes metabolic inflexibility in type 2 diabetic subjects. Am. J. Physiol. Endocrinol. Metab. 2006, 291, E1021-E1058.
56. Wang, M., Yang, X., Ren, L., Li, S. et al., Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets. J. Proteome Res. 2014, 13, 4131-4142.
57. Kolvraa, S., Gregersen, N., In vitro studies on the oxidation of medium-chain dicarboxylic acids in rat liver. Biochim. Biophys. Acta 1986, 876, 515-525.
58. Nieman, D. C., Shanely, R. A., Luo, B., Meaney, M. P. et al., Metabolomics approach to assessing plasma 13- and 9-hydroxy-octadecadienoic acid and linoleic acid metabolite responses to 75-km cycling. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2014, 307, R68-R74.
59. Garcia-Aloy, M., Llorach, R., Urpi-Sarda, M., Tulipani, S. et al., Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study. J. Proteome Res. 2014, 13, 3476-3483.
60. Garcia-Villalba, R., Beltran, D., Espin, J. C., Selma, M. V. et al., Time course production of urolithins from ellagic acid by human gut microbiota. J. Agric. Food Chem. 2013, 61, 8797-8806.