Evidence map›Paper›PMID 35208267›Full record

ReviewMetabolites2022

The Potential of Metabolomics in Biomedical Applications.

Vanessa Gonzalez-Covarrubias, Eduardo Martínez-Martínez, Laura Del Bosque-Plata

Abstract readReview
In one paragraph

Review in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
119citing papers in PubMed, 2 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

119 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Observational
  6. Article
  7. Review
  8. Article
  9. Impact of Daily Rhythms and Postprandial Responses on the Plasma Metabolome.International journal of molecular sciences · 2026
    Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Review
  18. Article
  19. GMC-DMA: GNN-Mamba Co-Contrastive Optimization for Disease-Metabolite Association Prediction.Interdisciplinary sciences, computational life sciences · 2026
    Article
  20. Article

59 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

3 authors.

Vanessa Gonzalez-CovarrubiasPharmacogenomics Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.ORCID 0000-0003-2072-2847
Eduardo Martínez-MartínezLaboratory of Cell Communication and Extracellular Vesicles, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.ORCID 0000-0002-9020-559X
Laura Del Bosque-PlataLaboratory of Nutrigenetics and Nutrigenomics, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.ORCID 0000-0003-3224-378X

Funding

Consejo Nacional de Ciencia y Tecnología 2096211
6 · The paper itself

Abstract

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.

Indexed as

diabetesexposomeextracellular vesicleslongevitymetabolomicsneurodegenerative diseasesobesitypharmacometabolomics

Identifiers

PMID35208267
PMCPMC8880031

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.