Evidence map›Paper›PMID 40860967›Full record

SynthesisFrontiers in neurology2025

Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.

Lu Ding, Meiling Zhang, Baochao Fan, Fuyuan Deng, Zhenyuan Li, Yixuan Han, Yifan Wu, Jingchun Zeng, Liming Lu

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Blood-Based Biomarkers for Post-Stroke Cognitive Impairment.Current issues in molecular biology · 2026
    Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Review
  12. Review
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

9 authors.

Lu Ding *Department of Traditional Chinese Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Meiling Zhang *Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
Baochao FanClinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
Fuyuan DengClinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
Zhenyuan LiMedical Department, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China.
Yixuan HanSchool of European Languages and Cultures, Beijing Foreign Studies University, Beijing, China.
Yifan WuCollege of Physical Education and Public Health, Guangzhou University of Chinese Medicine, Guangzhou, China.
Jingchun ZengDepartment of Rehabilitation, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China.
Liming LuClinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To systematically collate and evaluate metabolomics-based biomarkers of ischemic stroke (IS) to guide clinical diagnosis and treatment. Methods: Comprehensive literature searches were conducted in PubMed, Embase, and Web of Science using "IS" and "metabolomics" as core keywords, covering publications up through February 2024. Any original metabolomic research related to IS was selected. Key information such as study demographics, study type, objectives, metabolomic analysis methods, and main findings were extracted and analyzed. Frequently mentioned metabolites were subjected to enrichment analysis using the MetaboAnalyst 6.0 platform. Results: A total of 51 studies were included. Quality assessment revealed that 54.8% of the diagnostic studies and 69.2% of the prognostic studies were high-quality, with most controlling for confounding factors. Metabolite analysis revealed associations between decreased proline, isoleucine, valine, and alanine levels with IS. Increased tyrosine, glutamine, phenylalanine, sphingomyelin, glutamate, lactate and glucose, and decreased LysoPC (18:2), histidine, and methionine levels were linked to IS onset. Specific metabolite combinations, such as serine, isoleucine, betaine, PC (5:0/5:0), and LysoPE (18:2), showed high precision in predicting acute ischemic stroke (AIS) (training set AUC = 0.988, test set AUC = 0.971). Glycine-serine-threonine and valine-leucine-isoleucine pathways were significant in diagnosing IS and AIS, and in differentiating ischemic and hemorrhagic strokes, as well as identifying post-stroke depression and cognitive impairment. Conclusion: This study confirms the potential diagnostic and prognostic value of changes in amino acids and lipids, as well as other metabolites and metabolic pathways, in IS. These findings highlight the promise of metabolomics in IS diagnosis, differential diagnosis, risk assessment, and complication identification. However, further validation is needed due to the varying quality of the included studies. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier CRD42022335505.

Indexed as

biomarkersdiagnosisischemic strokemetabolomicsprognosisrisk prediction

Identifiers

PMID40860967
PMCPMC12370529

What OpenQuestion holds

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Registered trials

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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.