Systemic metabolic reprogramming within 24 h predicts delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

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Background Delayed cerebral ischemia (DCI) remains a major determinant of poor outcomes after aneurysmal subarachnoid hemorrhage (aSAH), yet early risk stratification is challenging. Methods A retrospective cohort of 44 aSAH patients was analyzed (DCI, n = 22; non-DCI, n = 22). Serum collected within 24 h of admission underwent untargeted liquid chromatography–tandem mass spectrometry metabolomics. Between-group separation was evaluated using supervised multivariate modeling with permutation testing. Differential metabolites were identified using a combined multivariate and univariate strategy (two-sided P < 0.05), followed by pathway enrichment analysis. Independent clinical predictors were assessed using multivariate logistic regression, and aneurysm morphology was quantified on admission CT angiography using radiomics-derived parameters. Results The DCI group was older, had a higher proportion of females, worse admission neurological status, higher vasospasm incidence, and lower hemoglobin. Vasospasm and age were independent predictors. Aneurysm morphological parameters showed no between-group differences. Metabolic profiles showed clear separation, supported by permutation testing ( R 2 = 0.6485; Q 2 intercept = −0.4173). A total of 110 differential metabolites were identified (39 upregulated and 71 downregulated in DCI). Representative changes included increased sphinganine, 2-octenoylcarnitine, guanidoacetic acid, and 5-aminopentanoic acid, with decreased lysophosphatidylcholine 16:0, lysophosphatidylethanolamine 16:0, xanthine, and dehydroepiandrosterone sulfate. Enrichment highlighted coordinated alterations in energy-related, amino-acid, and nucleotide-related pathways. Conclusion Early serum metabolomics within 24 h after aSAH revealed a DCI-associated systemic metabolic signature, supporting the identification of exploratory serum metabolic features associated with DCI in a Chinese cohort, which may inform future biomarker development following targeted validation.

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