Evidence map›Paper›PMID 26109927›Full record

ReviewMetabolomics : Official journal of the Metabolomic Society

Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review.

Abdul-Hamid Emwas, Claudio Luchinat, Paola Turano, Leonardo Tenori, Raja Roy, Reza M Salek, Danielle Ryan, Jasmeen S Merzaban, Rima Kaddurah-Daouk, Ana Carolina Zeri and 5 more

Abstract readReview
In one paragraph

Review in Metabolomics : Official journal of the Metabolomic Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

93 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Investigation of pH-dependentInternational journal of obesity (2005) · 2025
    Article
  10. Article
  11. Article
  12. Heliyon · 2024
    Article
  13. Best Practices in NMR Metabolomics: Current State.Trends in analytical chemistry : TRAC · 2024
    Article
  14. Review
  15. Review
  16. Article
  17. Quantitative NMR Methods in Metabolomics.Handbook of experimental pharmacology · 2023
    Article
  18. Practical Aspects of NMR-Based Metabolomics.Handbook of experimental pharmacology · 2023
    Article
  19. Article
  20. Article

33 more citing papers are in PubMed but not listed here.

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

15 authors.

Abdul-Hamid EmwasImaging and Characterization Core Lab, King Abdullah University of Science and Technology, KSA, Thuwal, Saudi Arabia.
Claudio LuchinatCentro Risonanze Magnetiche - CERM, University of Florence, Florence, Italy.
Paola TuranoCentro Risonanze Magnetiche - CERM, University of Florence, Florence, Italy.
Leonardo TenoriFiorGen Foundation, 50019 Sesto Fiorentino, Florence, Italy.
Raja RoyCentre of Biomedical Research, Formerly known as Centre of Biomedical Magnetic Resonance, Sanjay Gandhi Post-Graduate Institute of Medical Sciences Campus, Lucknow, India.
Reza M SalekDepartment of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK ; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD UK.
Danielle RyanSchool of Agricultural and Wine Sciences, Charles Sturt University, Wagga Wagga, Australia.
Jasmeen S MerzabanBiological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, KSA, Thuwal, Saudi Arabia.
Rima Kaddurah-DaoukPharmacometabolomics Center, School of Medicine, Duke University, Durham, USA.
Ana Carolina ZeriBrazilian Biosciences National Laboratory, LNBio, Campinas, SP Brazil.
G A Nagana GowdaDepartment of Anethesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, 850 Republican St., Seattle, WA 98109 USA.
Daniel RafteryDepartment of Anethesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, 850 Republican St., Seattle, WA 98109 USA.
Yulan WangWuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Beijing, China.
Lorraine BrennanInstitute of Food and Health and Conway Institute, School of Agriculture & Food Science, Dublin 4, Ireland.
David S WishartDepartment of Computing Science, University of Alberta, Edmonton, Alberta Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

Indexed as

BiomarkerDiagnosisHuman diseasesMetabolites profilingMetabolomicsMetabonomicsNMRRecommendationsStandardizationUrine

Identifiers

PMID26109927
PMCPMC4475544

What OpenQuestion holds

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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.