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Updated: Dec 21, 2025
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Untargeted metabolomics predicts the functional outcome of ischemic stroke
Nai-Fang Chi1, Tzu-Hao Chang2, Chen-Yang Lee3
1Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan; Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Neurology, Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
Background/Purpose:
Metabolites in blood have been found associated with the occurrence of vascular diseases, but its role in the functional recovery of stroke is unclear. The aim of this study is to investigate whether the untargeted metabolomics at the acute stage of ischemic stroke is able to predict functional recovery.
Methods:
One hundred and fifty patients with acute ischemic stroke were recruited and followed up for 3 months. Fasting blood samples within 7 days of stroke were obtained, liquid chromatography and mass spectrometry were applied to identify outcome-associated metabolites. The patients' clinical characteristics and identified metabolites were included for constructing the outcome prediction model using machine learning approaches.
Results:
By using multivariate analysis, 220 differentially expressed metabolites (DEMs) were discovered between patients with favorable outcomes (modified Rankin Scale, mRS ≤ 2 at 3 months, n = 77) and unfavorable outcomes (mRS ≥ 3 at 3 months, n = 73). After feature selection, 63 DEMs were chosen for constructing the outcome prediction model. The predictive accuracy was below 0.65 when including patients' clinical characteristics, and could reach 0.80 when including patients' clinical characteristics and 63 selected DEMs. The functional enrichment analysis identified platelet activating factor (PAF) as the strongest outcome-associated metabolite, which involved in proinflammatory mediators release, arachidonic acid metabolism, eosinophil degranulation, and production of reactive oxygen species.
Conclusion:
Metabolomics is a potential method to explore the blood biomarkers of acute ischemic stroke. The patients with unfavorable outcomes had a lower PAF level compared to those with favorable outcomes.
