Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure

Lloyd, Amanda J.; Beckmann, Manfred; Haldar, Sumanto; Seal, Chris; Brandt, Kirsten; Draper, John

doi:10.3945/ajcn.112.048033

Cited by 57 publications

(74 citation statements)

References 48 publications

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“…In these studies, the analysis of diet diary or FFQ information allowed classification of individuals in terms of their frequency of consumption of specific diet constituents. In the present paper, we illustrate these approaches for biomarker discovery with particular reference to two studies carried out by the authors (20,(25)(26)(27) . The presence of substantial inter-and intra-individual variability in human metabolite profiles (36) provides a challenge for both biofluid sampling and subsequent data normalisation in metabolomics studies seeking information on habitual diet.…”

Section: Dietary Exposure: Metabolite Fingerprinting: Ffq: Multivariamentioning

confidence: 99%

“…As part of the MEDE project (11) , twenty-four healthy participants consumed a 'test' breakfast, in which the cereal component of a standardised breakfast was replaced by one of four foods of high public health importance, followed by the collection of postprandial urine samples for metabolome analysis (20,25) . Once candidate food biomarkers had been identified (25,26) there was then the opportunity to validate their potential usefulness to monitor habitual diet in the independent GrainMark study (http://www.ncl.ac.uk/afrd/ research/project/2287) (27) . This large-scale dietary intervention study, involving free-living individuals, aimed to discover potential biomarkers of dietary wholegrain exposure.…”

Section: Dietary Exposure: Metabolite Fingerprinting: Ffq: Multivariamentioning

confidence: 99%

“…Thus, the identity of both of these potential biomarkers could be linked directly to the previous chemical analysis of each food. Although hippuric acids (presumably derived from colonic fermentation of the hydroxycinnamic acid content of tomato fruits (48) ) were indicative of tomato exposure, many highly ranked signals (26)(27) . Statistic ranges from the GrainMark study in positive ionisation mode.…”

Section: Exposure To Citrus Foods Has Provided a Paradigm For Discovementioning

confidence: 99%

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Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

et al. 2013

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Although robust associations between dietary intake and population health are evident from conventional observational epidemiology, the outcomes of large-scale intervention studies testing the causality of those links have often proved inconclusive or have failed to demonstrate causality. This apparent conflict may be due to the well-recognised difficulty in measuring habitual food intake which may lead to confounding in observational epidemiology. Urine biomarkers indicative of exposure to specific foods offer information supplementary to the reliance on dietary intake self-assessment tools, such as FFQ, which are subject to individual bias. Biomarker discovery strategies using non-targeted metabolomics have been used recently to analyse urine from either short-term food intervention studies or from cohort studies in which participants consumed a freely-chosen diet. In the latter, the analysis of diet diary or FFQ information allowed classification of individuals in terms of the frequency of consumption of specific diet constituents. We review these approaches for biomarker discovery and illustrate both with particular reference to two studies carried out by the authors using approaches combining metabolite fingerprinting by MS with supervised multivariate data analysis. In both approaches, urine signals responsible for distinguishing between specific foods were identified and could be related to the chemical composition of the original foods. When using dietary data, both food distinctiveness and consumption frequency influenced whether differential dietary exposure could be discriminated adequately. We conclude that metabolomics methods for fingerprinting or profiling of overnight void urine, in particular, provide a robust strategy for dietary exposure biomarker-lead discovery.

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Section: Dietary Exposure: Metabolite Fingerprinting: Ffq: Multivariamentioning

confidence: 99%

Section: Dietary Exposure: Metabolite Fingerprinting: Ffq: Multivariamentioning

confidence: 99%

Section: Exposure To Citrus Foods Has Provided a Paradigm For Discovementioning

confidence: 99%

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Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

et al. 2013

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“…Several biomarkers of coffee intake have previously been proposed, including trigonelline, 2-furoylglycine, caffeine and several polyphenols (Heinzmann, S. S., et al, 2015;Ito, H., et al, 2005;Lang, R., et al, 2011;Lloyd, A. J., et al, 2013;Rothwell, J. A., et al, 2014;Stalmach, A., et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Impact of chlorogenic acids from coffee on urine metabolome in healthy human subjects

Madrid-Gambin

Vázquez-Fresno

Vegas

et al. 2016

Food Research International

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HIGHLIGHTS Acute intake of CGAs from coffee impacts on central energetic metabolism. Sustained intake of CGAs from coffee plays a role in microbiota-derived compounds. Trigonelline is a coffee extract beverage biomarker in short-and long-term. Direct excretion of trigonelline would avoid interindividual variation. The use of uni-and multivariate analyses reinforced the biological effects. ABSTRACTSeveral studies suggest that coffee has some benefits for health; however, little is known about the specific role of the main polyphenol compounds of coffee, chlorogenic acids (CGAs), without caffeine interaction. A 1 H-Nuclear Magnetic Resonance ( 1 H-NMR)-based metabolomics approach was used to assess the effect of CGAs from coffee on the human urine metabolome. Ten male volunteers participated in a dietary crossover randomized intervention study with a rich CGAs coffee extract beverage (CEB: 223 mg/100 ml of CGAs). The study consisted of a daily intake of CEB or a control beverage with equal caffeine dose during 28 days. Fasting urines collected at the first and last days of each period of the study were analyzed using an CGAs untargeted 1 H-NMR approach. Additionally, 4-hour postpandrial urines after the first intake of each beverage were also analyzed. Uni-and multi-variate statistic approaches 2 were used to strengthen the results. Multilevel partial least squares discriminant analysis (ML-PLS-DA) was used to paired comparisons across the crossover design. A further univariate analysis model for crossover studies was performed to assess the significant changes. Acute consumption of CEB resulted in high excretion of 2-furoylglycine, likewise endogenous compounds such as succinic, citric, 3-methyl-2-oxovaleric and isobutyric acids. Sustained consumption of CEB showed an increase of microbiota-derived compounds such as hippuric, 3-(3-Hydroxyphenyl)-3-hydroxypropionic and 3-hydroxyhippuric acids in urine. Moreover, trigonelline was found in urine after both acute and sustained intakes, as well as in the composition of the beverage exhibiting a direct excretion of this biomarker without any biotransformation, suggesting a non-interindividual variation.

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“…Examples include a web-based dietary recall for children, mobile phone photography to instantly record consumed foods, a mobile phone application to record intake with voice recognition, and a wearable device to take pictures of food through image recognition (NIH Genes, Environment, and Health Initiative (GEI) 2013-http://tinyurl.com/oh5lh3v). These innovations, along with improvements in biomarkers of dietary intake including metabolomics and other techniques (Vernocchi et al 2012;Lloyd et al 2013), hold promise for contributing to improved dietary assessment through advanced technology (Tucker et al 2013).…”

Section: Micronutrient Requirements and Food Intake Datamentioning

confidence: 99%

The genomics of micronutrient requirements

2015

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Healthy nutrition is accepted as a cornerstone of public health strategies for reducing the risk of noncommunicable conditions such as obesity, cardiovascular disease, and related morbidities. However, many research studies continue to focus on single or at most a few factors that may elicit a metabolic effect. These reductionist approaches resulted in: (1) exaggerated claims for nutrition as a cure or prevention of disease; (2) the wide use of empirically based dietary regimens, as if one fits all; and (3) frequent disappointment of consumers, patients, and healthcare providers about the real impact nutrition can make on medicine and health. Multiple factors including environment, host and microbiome genetics, social context, the chemical form of the nutrient, its (bio)availability, and chemical and metabolic interactions among nutrients all interact to result in nutrient requirement and in health outcomes. Advances in laboratory methodologies, especially in analytical and separation techniques, are making the chemical dissection of foods and their availability in physiological tissues possible in an unprecedented manner. These omics technologies have opened opportunities for extending knowledge of micronutrients and of their metabolic and endocrine roles. While these technologies are crucial, more holistic approaches to the analysis of physiology and environment, novel experimental designs, and more sophisticated computational methods are needed to advance our understanding of how nutrition influences health of individuals.

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Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure

Abstract: This data-driven strategy can identify urinary metabolites associated with habitual exposure to specific foods. This trial has the UK registration number 4349 and was registered at isrtcn.org as CCT-NAPN-A13175.

Cited by 57 publications

References 48 publications

Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

Impact of chlorogenic acids from coffee on urine metabolome in healthy human subjects

The genomics of micronutrient requirements

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