The Untargeted Metabolomics Reveals Differences in Energy Metabolism in Patients with Different Subtypes of Ischemic Stroke.

aimsIschemic stroke (IS) is the most common subtype of stroke. The risk factors and pathogenesis of IS are complex and varied due to different subtypes. Therefore, we used metabolomics technology to investigate the biomarkers and potential pathophysiological mechanisms of different subtypes of IS.

methodsWe included 126 IS patients and divided them into two groups based on the TOAST classification: large-artery atherosclerosis (LAA) group (n = 87) and small-vessel occlusion (SVO) group (n = 39). Plasma metabolomics analysis was performed using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to identify metabolic profiles in LAA and SVO subtype IS patients and to determine metabolic differences between patients with the two subtypes of IS.

resultsWe identified 26 differential metabolites between LAA and SVO subtype IS. A multiple prediction model based on the plasm metabolites had good predictive ability for IS subtyping (AUC = 0.822, accuracy = 77.8%), with 12,13-DHOME being the most important differential metabolite in the model. The differential metabolic pathways between the two subtypes of IS patients included tricarboxylic acid (TCA) cycle, alanine, aspartate and glutamate metabolism, and pyruvate metabolism, mainly focused on energy metabolism.

conclusion12,13-DHOME emerged as the primary discriminatory metabolite between LAA and SVO subtypes of IS. In LAA subtype IS patients, energy metabolism, encompassing pyruvate metabolism and the TCA cycle, exhibited lower activity levels when compared to patients with the SVO subtype IS. The utilization of targeted metabolomics holds the potential to improve diagnostic accuracy for distinguishing stroke subtypes.