Untargeted metabolomics unveils critical metabolic signatures in novel phenotypes of acute ischemic stroke.

Abstract

This study aimed to identify metabolic footprints associated with distinct phenotypes of acute ischemic stroke (AIS) using untargeted metabolomics. We included 20 samples each from AIS phenotype A (n = 251), B (n = 213), and C (n = 43) groups, along with 20 age- and gender-matched healthy controls (HCs). Plasma metabolic profiles were analyzed using liquid chromatography-mass spectrometry (LC-MS). Weighted gene correlation network analysis (WGCNA) evaluated associations between metabolite clusters and clinical traits, including the National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin Scale (mRS). We identified three, five, and six key differential metabolites for diagnosing phenotypes A, B, and C, respectively, demonstrating high diagnostic performance. These metabolites were focused on fatty acids, sex hormones, amino acids, and their derivatives. WGCNA identified 12 core metabolites involved in phenotype progression. Notably, phenylalanylphenylalanine and phenylalanylleucine were inversely correlated with disease severity and disability. Metabolites related to energy supply and inflammation were common across phenotypes, with additional changes in ionic homeostasis in phenotype A and decreased neurotransmitter release in phenotype C. Biosynthesis of unsaturated fatty acids and the pentose phosphate pathway (PPP) were relevant across all phenotypes, while the folate biosynthesis pathway was linked to phenotype C and clinical scales. Key metabolites, including phenylalanylphenylalanine and phenylalanylleucine, and pathways such as folate biosynthesis, significantly contribute to AIS severity and differentiation of phenotypes. These findings offer new insights into the pathogenesis and mechanisms underlying AIS phenotypes.