Literature DB >> 28556565

Demonstration of the utility of biomarkers for dietary intake assessment; proline betaine as an example.

Helena Gibbons1, Charlotte J R Michielsen1, Milena Rundle2, Gary Frost2, Breige A McNulty1, Anne P Nugent1, Janette Walton3, Albert Flynn3, Michael J Gibney1, Lorraine Brennan1.   

Abstract

SCOPE: There is a dearth of studies demonstrating the use of dietary biomarkers for determination of food intake. The objective of this study was to develop calibration curves for use in quantifying citrus intakes in an independent cohort. METHODS AND
RESULTS: Participants (n = 50) from the NutriTech food-intake study consumed standardized breakfasts for three consecutive days over three consecutive weeks. Orange juice intake decreased over the weeks. Urine samples were analyzed by NMR-spectroscopy and proline betaine was quantified and normalized to osmolality. Calibration curves were developed and used to predict citrus intake in an independent cohort; the Irish National Adult Nutrition Survey (NANS) (n = 565). Proline betaine displayed a dose-response relationship to orange juice intake in 24 h and fasting samples (p < 0.001). In a test set, predicted orange juice intakes displayed excellent agreement with true intake. There were significant associations between predicted intake measured in 24 h and fasting samples and true intake (r = 0.710-0.919). Citrus intakes predicted for the NANS cohort demonstrated good agreement with self-reported intake and this agreement improved following normalization to osmolality.
CONCLUSION: The developed calibration curves successfully predicted citrus intakes in an independent cohort. Expansion of this approach to other foods will be important for the development of objective intake measurements.
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Citrus fruit; Dietary assessment; Dose-response; Metabolomics; Proline betaine

Mesh:

Substances:

Year:  2017        PMID: 28556565     DOI: 10.1002/mnfr.201700037

Source DB:  PubMed          Journal:  Mol Nutr Food Res        ISSN: 1613-4125            Impact factor:   5.914


  12 in total

1.  Nutriome-metabolome relationships provide insights into dietary intake and metabolism.

Authors:  Joram M Posma; Isabel Garcia-Perez; Gary Frost; Ghadeer S Aljuraiban; Queenie Chan; Linda Van Horn; Martha Daviglus; Jeremiah Stamler; Elaine Holmes; Paul Elliott; Jeremy K Nicholson
Journal:  Nat Food       Date:  2020-06-22

2.  Serum nonesterified fatty acids have utility as dietary biomarkers of fat intake from fish, fish oil, and dairy in women.

Authors:  Sandi M Azab; Russell J de Souza; Koon K Teo; Sonia S Anand; Natalie C Williams; Jordan Holzschuher; Chris McGlory; Stuart M Philips; Philip Britz-McKibbin
Journal:  J Lipid Res       Date:  2020-03-31       Impact factor: 5.922

Review 3.  Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review.

Authors:  Talha Rafiq; Sandi M Azab; Koon K Teo; Lehana Thabane; Sonia S Anand; Katherine M Morrison; Russell J de Souza; Philip Britz-McKibbin
Journal:  Adv Nutr       Date:  2021-12-01       Impact factor: 8.701

4.  Biomarkers of dietary patterns: a systematic review of randomized controlled trials.

Authors:  Shuang Liang; Reeja F Nasir; Kim S Bell-Anderson; Clémence A Toniutti; Fiona M O'Leary; Michael R Skilton
Journal:  Nutr Rev       Date:  2022-07-07       Impact factor: 6.846

Review 5.  Personalised Interventions-A Precision Approach for the Next Generation of Dietary Intervention Studies.

Authors:  Baukje de Roos; Lorraine Brennan
Journal:  Nutrients       Date:  2017-08-09       Impact factor: 5.717

6.  Ultra-Performance Liquid Chromatography-Ion Mobility Separation-Quadruple Time-of-Flight MS (UHPLC-IMS-QTOF MS) Metabolomics for Short-Term Biomarker Discovery of Orange Intake: A Randomized, Controlled Crossover Study.

Authors:  Leticia Lacalle-Bergeron; Tania Portolés; Francisco J López; Juan Vicente Sancho; Carolina Ortega-Azorín; Eva M Asensio; Oscar Coltell; Dolores Corella
Journal:  Nutrients       Date:  2020-06-29       Impact factor: 5.717

7.  A Metabolomics Approach to the Identification of Urinary Biomarkers of Pea Intake.

Authors:  Pedapati S C Sri Harsha; Roshaida Abdul Wahab; Catalina Cuparencu; Lars Ove Dragsted; Lorraine Brennan
Journal:  Nutrients       Date:  2018-12-04       Impact factor: 5.717

8.  Social, demographic, and economic correlates of food and chemical consumption measured by wastewater-based epidemiology.

Authors:  Phil M Choi; Benjamin Tscharke; Saer Samanipour; Wayne D Hall; Coral E Gartner; Jochen F Mueller; Kevin V Thomas; Jake W O'Brien
Journal:  Proc Natl Acad Sci U S A       Date:  2019-10-07       Impact factor: 11.205

Review 9.  A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019.

Authors:  Eriko Shibutami; Toru Takebayashi
Journal:  Nutrients       Date:  2021-10-24       Impact factor: 5.717

10.  Mendelian Randomization Identifies the Potential Causal Impact of Dietary Patterns on Circulating Blood Metabolites.

Authors:  Nele Taba; Hanna-Kristel Valge; Andres Metspalu; Tõnu Esko; James F Wilson; Krista Fischer; Nicola Pirastu
Journal:  Front Genet       Date:  2021-11-01       Impact factor: 4.599

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