Evidence map›Paper›PMID 34716906›Full record

SynthesisSports medicine (Auckland, N.Z.)2022

Metabolomics in Exercise and Sports: A Systematic Review.

Kayvan Khoramipour, Øyvind Sandbakk, Ammar Hassanzadeh Keshteli, Abbas Ali Gaeini, David S Wishart, Karim Chamari

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 3 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

77 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Dynamic Metabolic Changes Driven by Exercise Intensity in Acute Swimming.Medicine and science in sports and exercise · 2025
    Trial
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Review
  11. Urinary metabolomic signatures of muscle injury and recovery in elite football players.Metabolomics : Official journal of the Metabolomic Society · 2026
    Observational
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

17 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

6 authors.

Kayvan KhoramipourPhysiology Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran. k.khoramipour@kmu.ac.ir.ORCID http://orcid.org/0000-0003-1598-8640
Øyvind SandbakkDepartment of Neuromedicine and Movement Science, Centre for Elite Sports Research, Norwegian University of Science and Technology, Trondheim, Norway.
Ammar Hassanzadeh KeshteliDepartment of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
Abbas Ali GaeiniDepartment of Exercise Physiology, University of Tehran, Tehran, Iran.
David S WishartDepartment of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
Karim ChamariASPETAR, Qatar Orthopaedic and Sports Medicine Hospital, Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolomics is a field of omics science that involves the comprehensive measurement of small metabolites in biological samples. It is increasingly being used to study exercise physiology and exercise-associated metabolism. However, the field of exercise metabolomics has not been extensively reviewed or assessed.

objectiveThis review on exercise metabolomics has three aims: (1) to provide an introduction to the general workflow and the different metabolomics technologies used to conduct exercise metabolomics studies; (2) to provide a systematic overview of published exercise metabolomics studies and their findings; and (3) to discuss future perspectives in the field of exercise metabolomics.

methodsWe searched electronic databases including Google Scholar, Science Direct, PubMed, Scopus, Web of Science, and the SpringerLink academic journal database between January 1st 2000 and September 30th 2020.

resultsBased on our detailed analysis of the field, exercise metabolomics studies fall into five major categories: (1) exercise nutrition metabolism; (2) exercise metabolism; (3) sport metabolism; (4) clinical exercise metabolism; and (5) metabolome comparisons. Exercise metabolism is the most popular category. The most common biological samples used in exercise metabolomics studies are blood and urine. Only a small minority of exercise metabolomics studies employ targeted or quantitative techniques, while most studies used untargeted metabolomics techniques. In addition, mass spectrometry was the most commonly used platform in exercise metabolomics studies, identified in approximately 54% of all published studies. Our data indicate that biomarkers or biomarker panels were identified in 34% of published exercise metabolomics studies.

conclusionOverall, there is an increasing trend towards better designed, more clinical, mass spectrometry-based metabolomics studies involving larger numbers of participants/patients and larger numbers of metabolites being identified.

Indexed as

MetabolomicsSportsBiomarkersExerciseHumansMetabolomeBiomarkers

Identifiers

PMID34716906

What OpenQuestion holds

Textmetadata
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.