Browse by author
Lookup NU author(s): Dr Naomi Willis, Dr Long Xie, Professor John Mathers
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2019, The Author(s). Introduction: Dietary exposure monitoring within populations is reliant on self-reported measures such as Food Frequency Questionnaires and diet diaries. These methods often contain inaccurate information due to participant misreporting, non-compliance and bias. Urinary metabolites derived from individual foods could provide additional objective indicators of dietary exposure. For biomarker approaches to have utility it is essential that they cover a wide-range of commonly consumed foods and the methodology works in a real-world environment. Objectives: To test that the methodology works in a real-world environment and to consider the impact of the major sources of likely variance; particularly complex meals, different food formulations, processing and cooking methods, as well as the dynamics of biomarker duration in the body. Methods: We designed and tested a dietary exposure biomarker discovery and validation strategy based on a food intervention study involving free-living individuals preparing meals and collecting urine samples at home. Two experimental periods were built around three consecutive day menu plans where all foods and drinks were provided (n = 15 and n = 36). Results: The experimental design was validated by confirming known consumption biomarkers in urinary samples after the first menu plan. We tested biomarker performance with different food formulations and processing methods involving meat, wholegrain, fruits and vegetables. Conclusion: It was demonstrated that spot urine samples, together with robust dietary biomarkers, despite major sources of variance, could be used successfully for dietary exposure monitoring in large epidemiological studies.
Author(s): Lloyd AJ, Willis ND, Wilson T, Zubair H, Chambers E, Garcia-Perez I, Xie L, Tailliart K, Beckmann M, Mathers JC, Draper J
Publication type: Article
Publication status: Published
Journal: Metabolomics
Year: 2019
Volume: 15
Issue: 5
Online publication date: 02/05/2019
Acceptance date: 19/04/2019
Date deposited: 20/05/2019
ISSN (print): 1573-3882
ISSN (electronic): 1573-3890
Publisher: Springer New York LLC
URL: https://doi.org/10.1007/s11306-019-1532-3
DOI: 10.1007/s11306-019-1532-3
PubMed id: 31049735
Altmetrics provided by Altmetric
