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Depression and metabolic dysfunction-associated steatotic liver disease (MASLD) frequently co-occur, and their bidirectional pathological interactions complicate clinical management. Liver-brain crosstalk provides a systematic framework for understanding these multi-organ connections. Xiaoyaosan (XYS), a classical formula for soothing the liver and relieving depression, has been investigated for its therapeutic potential in both conditions; however, most available evidence remains preclinical. We systematically reviewed 158 original studies graded by evidence level and synthesized the pharmacological mechanisms of XYS. The available evidence suggests that XYS may restore liver-brain communication through vagal, humoral, and gut microbiota pathways. At the vagal pathway level, XYS has been reported to inhibit aberrant afferent transmission of intestinal pro-inflammatory signals to the central nervous system while concurrently enhancing cholinergic anti-inflammatory efferent output, thereby potentially restoring the afferent-efferent balance of autonomic innervation. At the humoral pathway level, XYS may restore the negative feedback function of the hypothalamic-pituitary-adrenal (HPA) axis, redirect tryptophan metabolic flux away from excessive diversion toward the kynurenine pathway, and alleviate neuroinflammation through upregulation of monoamine neurotransmitters and inhibition of microglial M1 polarization. At the gut microbiota pathway level, XYS may reshape microbial community structure and its metabolic profile, restore the microecological barrier and intestinal mucosal permeability by increasing the abundance of short-chain fatty acid-producing bacteria and reducing enterogenous endotoxin load. Two integrative nodes, namely the serotonergic redirection of tryptophan flux and the systematic restoration of gut microbiota, are proposed to underlie the dual efficacy. These nodes may form a bidirectional closed loop that links peripheral metabolic signals with central neuroplasticity. Current evidence has notable limitations, including poor clinical relevance of disease models, insufficient causal inference, questionable dose extrapolation, and lack of temporal dynamics. Future studies should prioritize randomized controlled trials in comorbid populations, multi-omics biomarker discovery, and temporal causal network analysis to facilitate clinical translation.
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Chu et al. (2026) studied this question.
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