Abstract
This review summarizes recent advances in applying metabolomics to autoimmune hepatitis (AIH). AIH is a chronic liver disease characterized by immune-mediated hepatocellular injury, with complex pathogenesis involving genetic, immunological, and environmental factors. Metabolomics, a system-wide approach analyzing small molecule metabolites, offers potential in early diagnosis, prognosis, and therapeutic evaluation of AIH. Current studies identify alterations in amino acid, lipid, carbohydrate, and bile acid metabolism, as well as changes in the gut microbiome and specific metabolite markers that distinguish AIH from other liver diseases. Techniques such as liquid chromatography-mass spectrometry (LC-MS), and bioinformatics facilitate biomarker discovery and enhance understanding of disease mechanisms. Despite challenges such as standardization and data integration, metabolomics holds promise for developing personalized treatment strategies and advancing disease management. Future prospects include combining multi-omics approaches, large-scale cohort studies, and artificial intelligence (AI)-based data analysis to deepen insights into AIH pathology and improve clinical outcomes.