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Plasma untargeted metabolomics identifies pathognomonic amino acid dysregulation discriminating acute ischemic stroke from intracerebral hemorrhage

Year: 2026
Type: article
Abstract: Stroke is a complex neurological disorder defined by the abrupt disruption of cerebral function, with two major subtypes: acute ischemic stroke (AIS), arising from cerebral artery occlusion, and intracerebral hemorrhage (ICH), caused by cerebrovascular rupture. Despite overlapping clinical presentations, the distinct underlying pathophysiological mechanisms of these subtypes demand tailored therapeutic approaches. Currently, there are no clinically applicable biomarkers available to facilitate the rapid differential diagnosis of AIS and ICH. To delineate the metabolic disparities between AIS and ICH patients, we employed untargeted plasma metabolomics based on gas chromatography-mass spectrometry (GC-MS). Plasma samples were collected from 63 AIS patients, 35 ICH patients, and 66 healthy controls, followed by metabolic profiling to identify differentially expressed metabolites. A total of over 50 metabolites, including amino acids, fatty acids, and carbohydrates, were identified from the plasma samples. Multivariate statistical analyses further identified metabolites with differential abundance across the study groups. Pathway enrichment analysis highlighted significant perturbations in amino acid metabolism, with 7 amino acids showing differential expression between AIS and ICH patients. Importantly, all these differentially expressed amino acids were significantly upregulated in the plasma of AIS patients relative to ICH patients. Moreover, application of the Support Vector Machine algorithm to these metabolites demonstrated that several amino acids could serve as key components for the differential diagnosis of AIS and ICH. Our findings uncover distinct amino acid metabolic signatures between AIS and ICH, offering novel insights into the pathophysiological divergence of these two stroke subtypes. Furthermore, the identified differential amino acids represent potential candidate biomarkers for the differential diagnosis and therapeutic targeting of AIS and ICH. This study also emphasizes the value of untargeted metabolomics in elucidating the complex mechanisms underlying cerebrovascular diseases.
Language: English
Open Access status: gold
Estimated APC paid: $3,090
OpenAlex ID: W7225833459
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