Abstract
BACKGROUND: Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, closely associated with neuroinflammation, immune dysregulation, and gut microbiota imbalance. Gut microbiota-derived metabolites may modulate key targets involved in MS pathogenesis. METHODS: This study integrated network pharmacology, machine learning (ML), and single-cell transcriptome analysis to identify MS-related differentially expressed genes (DEGs) and potential targets of gut microbial metabolites. Feature contributions were evaluated using the SHapley Additive exPlanations (SHAP) method, and causal relationships were validated via Mendelian randomization (MR). Single-cell analysis, molecular docking, and assessments of drug-likeness and toxicity were also performed. RESULTS: Caspase-3 (CASP3) was identified as a core target interacting with multiple gut microbial metabolites, including L-isoleucine, aromatic lactic acid derivatives, 3-hydroxyphenethyl alcohol, and D-xylose, potentially regulating neuroimmune responses via TNF, MAPK, IL-17, and galectin pathways. Specific microbial taxa, such as Akkermansia, Bacteroides, and Bifidobacterium, were closely associated with these metabolites. The metabolites exhibited favorable drug-likeness and low predicted toxicity, indicating potential therapeutic value. CONCLUSION: Gut microbial dysbiosis and its metabolites play a significant role in MS onset and progression, providing a theoretical basis for identifying therapeutic targets and gut-CNS axis interventions. Experimental validation is needed to confirm mechanisms and translational potential.