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Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

ABSTRACT: Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have investigated potential biomarkers for single foods only, this study considered the whole diet by using menus that delivered a wide range of foods in meals that emulated conventional UK eating patterns. Fifty-one healthy participants (range 19-77 years; 57% female) followed a uniquely designed, randomized controlled dietary intervention, and provided spot urine samples suitable for discovery of BFIs within a real-world context. Free-living participants prepared and consumed all foods and drinks in their own homes and were asked to follow the protocols for meal consumption and home urine sample collection. This study also assessed the robustness, and impact on data quality, of a minimally invasive urine collection protocol. Overall the study design was well-accepted by participants and concluded successfully without any drop outs. Compliance for urine collection, adherence to menu plans, and observance of recommended meal timings, was shown to be very high. Metabolome analysis using mass spectrometry coupled with data mining demonstrated that the study protocol was well-suited for BFI discovery and validation. Novel, putative biomarkers for an extended range of foods were identified including legumes, curry, strongly-heated products, and artificially sweetened, low calorie beverages. In conclusion, aspects of this study design would help to overcome several current challenges in the development of BFI technology. One specific attribute was the examination of BFI generalizability across related food groups and across different preparations and cooking methods of foods. Furthermore, the collection of urine samples at multiple time points helped to determine which spot sample was optimal for identification and validation of BFIs in free-living individuals. A further valuable design feature centered on the comprehensiveness of the menu design which allowed the testing of biomarker specificity within a biobank of urine samples.

SUBMITTER: Willis ND

PROVIDER: S-EPMC7609501 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

Willis Naomi D ND Lloyd Amanda J AJ Xie Long L Stiegler Martina M Tailliart Kathleen K Garcia-Perez Isabel I Chambers Edward S ES Beckmann Manfred M Draper John J Mathers John C JC

Frontiers in nutrition 20201021

Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have inve ...[more]

PMID: 33195362

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Project description:BackgroundIncreasing interest in diets excluding meat and other products of animal origin emphasizes the importance of objective and reliable methods to measure dietary exposure, to evaluate associations and causation between diet and health, and to quantify nutrient intakes in different diets.ObjectivesThis study aimed to investigate if NMR analysis of urine samples can serve as an objective method to discriminate vegan, vegetarian with or without fish, and omnivore diets. A secondary aim was to assess the influence of dietary nutrient intake on the metabolomics results.MethodsHealthy individuals (43 men and 75 women, age 19-57 y) complying with habitual vegan (n = 42), vegetarian (n = 25), vegetarian + fish (n = 13), or omnivore (n = 38) diets were enrolled. Data were collected on clinical phenotype and lifestyle including a 4-d weighed food diary. Urine was analyzed for metabolites by NMR spectroscopy and data normalized using probabilistic quotient normalization and Pareto-scaled before multivariate analysis. Before orthogonal projections to latent structures with discriminant analysis, participants were assigned as meat consumers or nonmeat consumers (vegans and vegetarians), vegans or nonvegans (omnivores, vegetarian, and vegetarian + fish).ResultsThe main results showed that it was possible to discriminate meat and nonmeat consumers (91% correctly classified), but discrimination between vegans and nonvegans was less rigorous (75% correctly classified). Secondary outcomes showed that reported intake of protein was higher in omnivores, and saturated fat lower and fiber higher in vegans, compared with the other groups. Discriminating metabolites were mainly related to differences in protein intake.ConclusionsNMR urine metabolomics appears suitable to objectively identify and predict habitual intake of meat in healthy individuals, but results should be interpreted with caution because not only food groups but also specific foods contribute to the patterns.This trial was registered at clinicaltrials.gov as NCT02039609.

Project description:BackgroundLittle is known about the capacity of overnight and spot urine samples to estimate changes in mean salt intake over time. The objective of this review was to compare the estimates of change in mean population salt intake based on 24-h urine and overnight/spot urine samples.MethodsStudies were systematically identified through searches of peer-reviewed databases (Medline, Embase, Global Health, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews) and grey literature. Studies that reported estimates of mean salt intake for at least two time points based on both 24-h and overnight/spot urines were deemed eligible. The capacity of overnight/spot urine samples to estimate the change in mean salt intake was assessed both at the individual-study level and overall through random-effects meta-analyses. The level of heterogeneity was assessed through the I2 statistic. Subgroup and sensitivity analyses were conducted to explore possible sources of heterogeneity, and check the robustness of the findings from the primary analysis.ResultsA total of 1244 records were identified, 50 were assessed as full text, and 14 studies met the criteria, capturing data on 7291 participants from seven countries. Nine and five studies collected overnight and spot urines, respectively. The comparison of the change in mean salt intake between 24-h and overnight/spot urines showed some inconsistencies at the individual study-level. The pooled mean change in salt intake was - 0.43 g/day (95% CI - 1.16 to 0.30; I2 = 95%) using 24-h urines, and - 0.22 g/day (- 0.65 to 0.20; I2 = 87%) using overnight/spot urines, with a pooled difference-in-differences between the two methods of 0.27 g/day (- 0.23 to 0.77; I2 = 89%). Subgroup analyses showed substantial heterogeneity for most subgroups. Sensitivity analyses did not change the effect observed in the primary analysis.ConclusionThe evidence for the capacity of overnight/spot urines to estimate changes in mean salt intake over time is uncertain. More research where overnight/spot urines are collected in parallel with 24-h urines is needed to enable a more in-depth evaluation of these alternative approaches to estimating change in mean salt intake.

Project description:The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time frame allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive "fingerprint" of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together with 81 urine samples including negative controls and positive samples obtained from recent users of either fentanyl or "traditional" drugs, were subjected to untargeted analysis using both UHPLC reverse phase and HILIC chromatography combined with QTOF mass spectrometry. Data independent acquisition was performed by SWATH in order to obtain a comprehensive profile of the urinary metabolome. After extensive processing, the resulting datasets were initially subjected to unsupervised exploration by principal component analysis (PCA), yielding clear separation of the fentanyl positive samples with respect to both controls and samples positive to other drugs. The urine datasets were then systematically investigated by supervised classification models based on soft independent modeling by class analogy (SIMCA) algorithms, with the end goal of identifying fentanyl users. A final single-class SIMCA model based on an RP dataset and five PCs yielded 96% sensitivity and 74% specificity. The distinguishable metabolic patterns produced by fentanyl in comparison to other opioids opens up new perspectives in the interpretation of the biological activity of fentanyl.

Dataset Information

Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

Publications

Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

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