ArticleNutrients2017
Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries.
Article in Nutrients, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 34 citations in OpenAlex.
- Targeted Urinary Profiling as a Biomarker of Dietary Flavonoid Intake from Fruits and Vegetables and its Relationship to the Timing of Dietary Assessment.Current developments in nutrition · 2025Article
- Development of a (Poly)phenol Metabolic Signature for Assessing (Poly)phenol-Rich Dietary Patterns.Journal of agricultural and food chemistry · 2024Article
- Exploring Human Metabolome after Wine Intake-A Review.Molecules (Basel, Switzerland) · 2023Review
- Hydroxytyrosol in Foods: Analysis, Food Sources, EU Dietary Intake, and Potential Uses.Foods (Basel, Switzerland) · 2022Review
- Article
- Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review.Advances in nutrition (Bethesda, Md.) · 2021Review
- Article
- A systematic review to identify biomarkers of intake for fermented food products.Genes & nutrition · 2021Review
- Urinary Resveratrol Metabolites Output: Differential Associations with Cardiometabolic Markers and Liver Enzymes in House-Dwelling Subjects Featuring Metabolic Syndrome.Molecules (Basel, Switzerland) · 2020Article
- Dietary Patterns Are Associated with Serum Metabolite Patterns and Their Association Is Influenced by Gut Bacteria among Older German Adults.The Journal of nutrition · 2020Article
- Effects of Polyphenol-Rich Foods on Human Health.Nutrients · 2018Article
Corrections and comments
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Authors and funding
24 authors at 12 institutions in 6 countries.
Funding
Abstract
We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine (
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Registered trials
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