A Standardized Strategy for Simultaneous Quantification of Urine Metabolites to Validate Development of a Biomarker Panel Allowing Comprehensive Assessment of Dietary Exposure

Beckmann, Manfred; Wilson, Thomas; Zubair, Hassan; Lloyd, Amanda J.; Lyons, Laura; Phillips, Helen; Tailliart, Kathleen; Gregory, Nicholas S.; Thatcher, Rhys; García-Pérez, Isabel; Frost, Gary; Mathers, John M.; Draper, John

doi:10.1002/mnfr.202000517

Cited by 7 publications

(10 citation statements)

References 45 publications

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“…A comprehensive list of potential urinary BFIs based on a literature analysis ( 53 ) of putative dietary exposure biomarkers in various human biofluids is presented in Supporting Data 2 . The present biomarker panel strategy aimed to assess habitual diet in individuals and populations; key to this objective was the need to use spot urine samples, specifically urine samples collected just before bedtime and FMV urines, that would be informative of overall food consumption ( 1 , 62 ).…”

Section: Resultsmentioning

confidence: 99%

“…Previous analysis of published literature revealed that the great majority of dietary exposure biomarker candidates were detected and quantified using LC-MS technology ( 53 ). Chemical classification of putative biomarkers showed great structural diversity that included metabolites from 17 Chemical Classes representative of 7 Chemical Super-Classes ( Figure 4A ).…”

Section: Resultsmentioning

confidence: 99%

“…1- and 3-Methyl-xanthine (4 and 7) and Epicatechin(–) (28; a marker for general polyphenol-rich foods) detected exposure to cocoa products on Menu Day 1, whilst Acesulphame-K ( 8 ) was associated with exposure to a diet soft drink on the same day. Sulphoraphane derivatives (18 and 19; D,L-Sulphoraphane L-cysteine and D,L-Sulphoraphane-N-acetyl-L-cysteine) were highly explanatory of exposure to coleslaw (containing cabbage) on Menu Day 3, whilst trigonelline ( 53 ) and N-(2-Furoyl)glycine (39; a strongly heated food marker) reflected exposure to coffee on the same day. Tartrate ( 51 ) and the calystegines (12 and 13; A 3 and B 2 /B 1 ) contributed strongly to the clustering of urine samples from Menu Days 2 and 3 away from Menu Day 1 samples when grape products and potato products were not consumed.…”

Section: Resultsmentioning

confidence: 99%

“…It has been shown previously that the distributions of biomarker concentrations are comparable between post-dinner spot samples, overnight cumulative samples, and 24 h urines ( 62 ). We demonstrated recently ( 53 ) that more than 50 different potential BFIs were detectable in FMV urine the day after the consumption of targeted foods. In the present study, we show that for many, but not all, BFIs there is a relatively linear correlation between concentration in 24 h and FMV urine and suggest that only those with an R 2 approaching 0.2 may be suitable for accurate quantification when using a comprehensive biomarker panel to monitor habitual diet.…”

Section: Discussionmentioning

confidence: 96%

“…Although metabolites distinctive of dietary exposure to particular foods have been described, it is not uncommon to discover subsequently that putative biomarkers are not necessarily specific for individual foods and therefore much rigour needs to be applied during validation of their utility to monitor habitual dietary intake ( 51 ). For application in the real world, the use of multi-metabolite biomarker panels may provide more reliable estimation of dietary exposure than a single-biomarker approach [reviewed by ( 52 )]; such panels need to have comprehensive coverage and to be extendable ( 53 ). For this reason, in the future it will be important to evaluate biomarker performance in the context of complex exposures to multiple foods, with different food formulations, cooking, and processing methods and within complex meals, in eating patterns the target study population is likely to experience ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

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Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations—A Perspective

et al. 2020

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Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in “real world” situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations—A Perspective

et al. 2020

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Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data

et al. 2022

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Introduction Flow infusion electrospray high resolution mass spectrometry (FIE-HRMS) fingerprinting produces complex, high dimensional data sets which require specialist in-silico software tools to process the data prior to analysis. Objectives Present spectral binning as a pragmatic approach to post-acquisition procession of FIE-HRMS metabolome fingerprinting data. Methods A spectral binning approach was developed that included the elimination of single scan m/z events, the binning of spectra and the averaging of spectra across the infusion profile. The modal accurate m/z was then extracted for each bin. This approach was assessed using four different biological matrices and a mix of 31 known chemical standards analysed by FIE-HRMS using an Exactive Orbitrap. Bin purity and centrality metrics were developed to objectively assess the distribution and position of accurate m/z within an individual bin respectively. Results The optimal spectral binning width was found to be 0.01 amu. 80.8% of the extracted accurate m/z matched to predicted ionisation products of the chemical standards mix were found to have an error of below 3 ppm. The open-source R package binneR was developed as a user friendly implementation of the approach. This was able to process 100 data files using 4 Central Processing Units (CPU) workers in only 55 seconds with a maximum memory usage of 1.36 GB. Conclusion Spectral binning is a fast and robust method for the post-acquisition processing of FIE-HRMS data. The open-source R package binneR allows users to efficiently process data from FIE-HRMS experiments with the resources available on a standard desktop computer.

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Dietary biomarkers—an update on their validity and applicability in epidemiological studies

Landberg,

Karra,

Hoobler

et al. 2023

Nutrition Reviews

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The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

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A Standardized Strategy for Simultaneous Quantification of Urine Metabolites to Validate Development of a Biomarker Panel Allowing Comprehensive Assessment of Dietary Exposure

Cited by 7 publications

References 45 publications

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations—A Perspective

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations—A Perspective

Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data

Dietary biomarkers—an update on their validity and applicability in epidemiological studies

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