Evidence map›Paper›PMID 33195362›Full record

ArticleFrontiers in nutrition2020

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.

Naomi D Willis, Amanda J Lloyd, Long Xie, Martina Stiegler, Kathleen Tailliart, Isabel Garcia-Perez, Edward S Chambers, Manfred Beckmann, John Draper, John C Mathers

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 45% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Naomi D WillisHuman Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Amanda J LloydInstitute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom.
Long XieHuman Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Martina StieglerHuman Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Kathleen TailliartInstitute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom.
Isabel Garcia-PerezNutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom.
Edward S ChambersNutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom.
Manfred BeckmannInstitute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom.
John DraperInstitute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom.
John C MathersHuman Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom.
Newcastle University · GBInstitute of Biological, Environmental and Rural Sciences · GBImperial College London · GBAberystwyth University · GB

Funding

Department of Health PDF-2012-05-456Medical Research Council MR/J010308/1Medical Research Council MR/P020941/1
6 · The paper itself

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.

Indexed as

biomarkersdietary intakefree-living participantsmetabolomicsradomized control trial

Identifiers

PMID33195362
PMCPMC7609501
OpenAlexW3093172955

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.