Mechanistic insights into the anti-depressant effect of quercetin: an integrated bibliometrics, bioinformatics, and animal experimentation

Objectives: Accumulating clinical evidence demonstrates the therapeutic potential of Traditional Chinese Medicine (TCM) in mitigating depressive disorders. This research focuses on quercetin, a principal bioactive constituent shared among five classical TCM antidepressant formulations, to systematically decode its multi-target mechanisms via an integrative framework combining neuroinflammatory modulation and synaptic plasticity regulation. Methods: A tripartite experimental design was implemented. Firstly, bibliometric analysis systematically screened antidepressant TCM prescriptions and their bioactive components. Secondly, network pharmacology delineated the therapeutic mechanisms of quercetin - a key phytochemical identified through prior analysis. Finally, we established a chronic unpredictable mild stress (CUMS)-induced depression-like behavior model in mice for validation. Results: were the most commonly used herbs, while Quercetin was identified as the shared bioactive nexus across these prescriptions. Network pharmacology analysis revealed that quercetin may be closely related to PI3K/AKT pathway in depression. And results of animal experimentation showed that quercetin could improve depression-like behaviors and restore neurotransmitters levels. Concurrently, quercetin may inhibit neuroinflammation and ameliorate synaptic ultrastructural by PI3K/AKT pathway. Conclusion: The present study elucidated the mechanism of quercetin, an active ingredient in TCM prescriptions, in the treatment of depression through data mining, network pharmacology prediction, and experimental validation. This integrated research method will provide a new perspective for the development of TCM.