Evidence map›Paper›PMID 41469719›Full record

ReviewEuropean journal of medical research2025

Mass spectrometry-based metabolomics in recurrent ischemic stroke: pathophysiological insights, treatment resistance, and synergistic therapies.

Shiyang Liu, Siat Yee Fong, Hui Liu, Peiyang Sun

Abstract readReview
In one paragraph

Review in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

4 authors.

Shiyang LiuDepartment of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
Siat Yee FongDepartment of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
Hui LiuDepartment of Neurology, The Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, People's Republic of China.
Peiyang SunDepartment of Neurology, The Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, People's Republic of China. sunpeiyang2008@aliyun.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recurrent ischemic stroke represents a major unmet clinical challenge, contributing significantly to the global burden of neurological disability and mortality. Despite widespread implementation of guideline-recommended secondary prevention strategies-including antiplatelet therapy, lipid management, and blood pressure control-a substantial proportion of stroke survivors experience subsequent ischemic events (GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Neurology. 2021;20(10):795-820.). This persistent residual risk suggests that current clinical paradigms fail to capture the complex, heterogeneous biological dysregulation driving the recurrent disease state (Hankey in Lancet Neurol 13:178-194, 2014). Ischemic stroke is fundamentally a catastrophic metabolic crisis, involving rapid bioenergetic failure, profound oxidative stress, and prolonged inflammatory cascades (Dirnagl et al. in Trends Neurosci 22:391-397, 1999). Mass spectrometry (MS)-based metabolomics has emerged as a premier technological platform in preclinical and exploratory clinical research, capable of simultaneously quantifying hundreds to thousands of endogenous small-molecule metabolites (Nicholson and Lindon in Nature 455:1054-1056, 2008). By providing a functional readout of cellular phenotypes, MS metabolomics offers a unique window into the dynamic biochemical alterations that precede, accompany, and follow ischemic injury. This review provides a comprehensive synthesis of recent advances in applying MS-based approaches to dissect the pathophysiology of recurrent ischemic stroke. We critically examine strong evidence implicating core metabolic disruptions, including the "sphingolipid rheostat" and blood-brain barrier integrity, the shift toward pro-inflammatory lipid mediators in the inflammation-thrombosis axis, mitochondrial tricarboxylic acid cycle dysfunction, and the complex interplay between gut microbiota-derived metabolites and host vascular health. Furthermore, we explore the emerging field of pharmacometabolomics, detailing how MS profiling is providing mechanistic insights into resistance to standard antiplatelet therapies, particularly involving clopidogrel bioactivation pathways and arachidonic acid shunting in aspirin-treated patients. The potential of metabolomics to elucidate the biological mechanisms of complementary therapies, such as acupuncture, is also reviewed with critical appraisal. Finally, we provide a realistic and sobering assessment of the current translational gap. We highlight that while MS metabolomics offers unparalleled pathophysiological insights, significant technical and validation hurdles-including standardization of protocols, absolute quantification challenges, and the need for large-scale, diverse cohort studies-must be overcome before these metabolic signatures can be translated into viable clinical tools for personalized risk stratification and prevention of recurrent stroke (Wishart in Physiol Rev 99:1819-1875, 2019).

Indexed as

Ischemic StrokeMass SpectrometryMetabolomicsHumansRecurrenceAntiplatelet resistanceBiomarkersGut microbiotaIschemic stroke recurrenceMass spectrometryMetabolomicsPharmacometabolomicsSphingolipids

Identifiers

PMID41469719
PMCPMC12860104

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.