Literature DB >> 26269369

Polyphenol metabolome in human urine and its association with intake of polyphenol-rich foods across European countries.

William Mb Edmands1, Pietro Ferrari1, Joseph A Rothwell1, Sabina Rinaldi1, Nadia Slimani1, Dinesh K Barupal1, Carine Biessy1, Mazda Jenab1, Françoise Clavel-Chapelon2, Guy Fagherazzi2, Marie-Christine Boutron-Ruault2, Verena A Katzke3, Tilman Kühn3, Heiner Boeing4, Antonia Trichopoulou5, Pagona Lagiou6, Dimitrios Trichopoulos7, Domenico Palli8, Sara Grioni9, Rosario Tumino10, Paolo Vineis11, Amalia Mattiello12, Isabelle Romieu1, Augustin Scalbert13.   

Abstract

BACKGROUND: An improved understanding of the contribution of the diet to health and disease risks requires accurate assessments of dietary exposure in nutritional epidemiologic studies. The use of dietary biomarkers may improve the accuracy of estimates.
OBJECTIVE: We applied a metabolomic approach in a large cohort study to identify novel biomarkers of intake for a selection of polyphenol-containing foods. The large chemical diversity of polyphenols and their wide distribution over many foods make them ideal biomarker candidates for such foods.
DESIGN: Metabolic profiles were measured with the use of high-resolution mass spectrometry in 24-h urine samples from 481 subjects from the large European Prospective Investigation on Cancer and Nutrition cohort. Peak intensities were correlated to acute and habitual dietary intakes of 6 polyphenol-rich foods (coffee, tea, red wine, citrus fruit, apples and pears, and chocolate products) measured with the use of 24-h dietary recalls and food-frequency questionnaires, respectively.
RESULTS: Correlation (r > 0.3, P < 0.01 after correction for multiple testing) and discriminant [pcorr (1) > 0.3, VIP > 1.5] analyses showed that >2000 mass spectral features from urine metabolic profiles were significantly associated with the consumption of the 6 selected foods. More than 80 polyphenol metabolites associated with the consumption of the selected foods could be identified, and large differences in their concentrations reflecting individual food intakes were observed within and between 4 European countries. Receiver operating characteristic curves showed that 5 polyphenol metabolites, which are characteristic of 5 of the 6 selected foods, had a high predicting ability of food intake.
CONCLUSION: Highly diverse food-derived metabolites (the so-called food metabolome) can be characterized in human biospecimens through this powerful metabolomic approach and screened to identify novel biomarkers for dietary exposures, which are ultimately essential to better understand the role of the diet in the cause of chronic diseases.
© 2015 American Society for Nutrition.

Entities:  

Keywords:  EPIC; citrus fruits; coffee; dietary biomarkers; flavonoids; food metabolome; phenolic acids; polyphenols; red wine; tea

Mesh:

Substances:

Year:  2015        PMID: 26269369     DOI: 10.3945/ajcn.114.101881

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  50 in total

1.  Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation.

Authors:  Jeremy P Koelmel; Nicholas M Kroeger; Emily L Gill; Candice Z Ulmer; John A Bowden; Rainey E Patterson; Richard A Yost; Timothy J Garrett
Journal:  J Am Soc Mass Spectrom       Date:  2017-03-06       Impact factor: 3.109

2.  Untargeted Metabolomics Analytical Strategy Based on Liquid Chromatography/Electrospray Ionization Linear Ion Trap Quadrupole/Orbitrap Mass Spectrometry for Discovering New Polyphenol Metabolites in Human Biofluids after Acute Ingestion of Vaccinium myrtillus Berry Supplement.

Authors:  Claudia Ancillotti; Marynka Ulaszewska; Fulvio Mattivi; Massimo Del Bubba
Journal:  J Am Soc Mass Spectrom       Date:  2018-11-30       Impact factor: 3.109

3.  Coffee and tea drinking in relation to the risk of differentiated thyroid carcinoma: results from the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

Authors:  Raul Zamora-Ros; Muath A Alghamdi; Valerie Cayssials; Silvia Franceschi; Martin Almquist; Joakim Hennings; Maria Sandström; Konstantinos K Tsilidis; Elisabete Weiderpass; Marie-Christine Boutron-Ruault; Bodil Hammer Bech; Kim Overvad; Anne Tjønneland; Kristina E N Petersen; Francesca Romana Mancini; Yahya Mahamat-Saleh; Fabrice Bonnet; Tilman Kühn; Renée T Fortner; Heiner Boeing; Antonia Trichopoulou; Christina Bamia; Georgia Martimianaki; Giovanna Masala; Sara Grioni; Salvatore Panico; Rosario Tumino; Francesca Fasanelli; Guri Skeie; Tonje Braaten; Cristina Lasheras; Elena Salamanca-Fernández; Pilar Amiano; Maria-Dolores Chirlaque; Aurelio Barricarte; Jonas Manjer; Peter Wallström; H Bas Bueno-de-Mesquita; Petra H Peeters; Kay-Thee Khaw; Nicholas J Wareham; Julie A Schmidt; Dagfinn Aune; Graham Byrnes; Augustin Scalbert; Antonio Agudo; Sabina Rinaldi
Journal:  Eur J Nutr       Date:  2018-12-10       Impact factor: 5.614

Review 4.  Coffee, tea and caffeine intake and the risk of non-melanoma skin cancer: a review of the literature and meta-analysis.

Authors:  Saverio Caini; Maria Sofia Cattaruzza; Benedetta Bendinelli; Giulio Tosti; Giovanna Masala; Patrizia Gnagnarella; Melania Assedi; Ignazio Stanganelli; Domenico Palli; Sara Gandini
Journal:  Eur J Nutr       Date:  2016-07-07       Impact factor: 5.614

5.  Nutritional metabolomics and breast cancer risk in a prospective study.

Authors:  Mary C Playdon; Regina G Ziegler; Joshua N Sampson; Rachael Stolzenberg-Solomon; Henry J Thompson; Melinda L Irwin; Susan T Mayne; Robert N Hoover; Steven C Moore
Journal:  Am J Clin Nutr       Date:  2017-06-28       Impact factor: 7.045

6.  GC/MS based metabolite profiling of Indonesian specialty coffee from different species and geographical origin.

Authors:  Sastia Prama Putri; Tomoya Irifune; Eiichiro Fukusaki
Journal:  Metabolomics       Date:  2019-09-18       Impact factor: 4.290

Review 7.  Nutritional Metabolomics in Cancer Epidemiology: Current Trends, Challenges, and Future Directions.

Authors:  Emma E McGee; Rama Kiblawi; Mary C Playdon; A Heather Eliassen
Journal:  Curr Nutr Rep       Date:  2019-09

Review 8.  Use of Metabolomics in Improving Assessment of Dietary Intake.

Authors:  Marta Guasch-Ferré; Shilpa N Bhupathiraju; Frank B Hu
Journal:  Clin Chem       Date:  2017-10-16       Impact factor: 8.327

9.  Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics.

Authors:  Douglas I Walker; Col Timothy M Mallon; Philip K Hopke; Karan Uppal; Young-Mi Go; Patricia Rohrbeck; Kurt D Pennell; Dean P Jones
Journal:  J Occup Environ Med       Date:  2016-08       Impact factor: 2.162

10.  Dietary intake of total polyphenol and polyphenol classes and the risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Authors:  Raul Zamora-Ros; Valerie Cayssials; Mazda Jenab; Joseph A Rothwell; Veronika Fedirko; Krasimira Aleksandrova; Anne Tjønneland; Cecilie Kyrø; Kim Overvad; Marie-Christine Boutron-Ruault; Franck Carbonnel; Yahya Mahamat-Saleh; Rudolf Kaaks; Tilman Kühn; Heiner Boeing; Antonia Trichopoulou; Elissavet Valanou; Effie Vasilopoulou; Giovanna Masala; Valeria Pala; Salvatore Panico; Rosario Tumino; Fulvio Ricceri; Elisabete Weiderpass; Marko Lukic; Torkjel M Sandanger; Cristina Lasheras; Antonio Agudo; Maria-Jose Sánchez; Pilar Amiano; Carmen Navarro; Eva Ardanaz; Emily Sonestedt; Bodil Ohlsson; Lena Maria Nilsson; Martin Rutegård; Bas Bueno-de-Mesquita; Petra H Peeters; Kay-Thee Khaw; Nicholas J Wareham; Kathryn Bradbury; Heinz Freisling; Isabelle Romieu; Amanda J Cross; Paolo Vineis; Augustin Scalbert
Journal:  Eur J Epidemiol       Date:  2018-05-15       Impact factor: 8.082

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