AUTHOR=Zhou Lintao , Sun Huifang , Li Xiang , Han Qing 

TITLE=Untargeted metabolomic profiling in acute ischemic stroke patients with cerebral microbleeds

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1656974

DOI=10.3389/fneur.2025.1656974

ISSN=1664-2295

ABSTRACT=BackgroundAcute ischemic stroke (AIS) is a common cerebrovascular condition. Cerebral microbleeds (CMBs) are frequently observed in AIS patients and are closely associated with poor prognosis and potential therapeutic implications. Understanding the distinct metabolic profiles in AIS patients with CMBs is critical for uncovering the underlying pathophysiological mechanisms and identifying novel biomarkers.MethodsAn untargeted metabolomics approach using liquid chromatography–mass spectrometry (LC–MS) was employed to compare the metabolic profiles of 30 AIS patients with CMBs (CMB group) and 30 AIS patients without CMBs (the Non CMB group, abbreviated as NCMB group). Raw MS data were processed using MS-DIAL and metabolites were identified by comparison with public and in-house databases. Both univariate and multivariate analyses (PCA, OPLS-DA) were used to identify differential metabolites, followed by KEGG pathway enrichment analysis.ResultsThe LC–MS platform demonstrated robust stability and high data quality. Multivariate statistical modeling successfully distinguished between the two groups, revealing distinct metabolic phenotypes. A total of 156 significantly altered metabolites were identified, including 103 upregulated and 53 downregulated metabolites. Pathway analysis revealed significant perturbations in lipid metabolism, amino acid metabolism, and energy metabolism.ConclusionThis study identified unique metabolic signatures in AIS patients with CMBs. The metabolites such as N-ethylglycine, aspartyl-glutamate, and oleamide were significantly elevated, while metabolites like PC (16:0/18:1) and PC (18:0/20:4) were significantly reduced, and other metabolites implicated disruptions in energy and lipid metabolism. These findings suggest potential biomarker candidates for diagnosis, prognosis, and therapeutic intervention in this high-risk population.