Effects and potential mechanisms of si-ni-san on animal models of depression: a preclinical systematic review and meta-analysis

Context In Traditional Chinese Medicine depressive disorders are commonly associated with liver qi stagnation syndrome. Si-ni-san (SNS), a classic formula for soothing the liver and relieving qi stagnation, is widely used for its potential antidepressant-like effects. Objective This preclinical systematic review and meta-analysis aimed to evaluate the pharmacological effects of SNS on depression-related behavioral outcomes in animal models and to summarize its mechanisms of action. Methods We conducted a systematic search of seven databases (including PubMed) for records published up to December 2025. Risk of bias was assessed using SYRCLE’s tool. Meta-analyses were performed using STATA 15.0 and RevMan 5.4. Subgroup and leave-one-out sensitivity analyses were conducted to test the robustness of the findings. Publication bias was assessed using funnel plots and Egger’s test. Trim-and-fill analysis was performed to adjust for potential publication bias. The certainty of evidence was evaluated using a modified GRADE approach for preclinical studies. Results A total of 28 studies were included, involving 384 animals and three behavioral tests: sucrose preference test (SPT), forced swim test (FST), and tail suspension test (TST). SNS treatment was associated with increased sucrose preference in the SPT (SMD = 3.18, 95% CI = [2.44, 3.93]), and reduced immobility time in both the FST (SMD = −2.17, 95% CI = [-2.86, −1.49]) and TST (SMD = −2.55, 95% CI = [-3.31, −1.78]). Mechanistically, SNS treatment was associated with increased monoamine neurotransmitters (MNTs), reduced hypothalamic-pituitary-adrenal (HPA) axis hormones, and decreased pro-inflammatory cytokines. Conclusion These findings suggest that SNS is associated with antidepressant-like pharmacological effects in rodent models, with changes in MNTs, HPA axis hormones, and inflammatory markers. However, due to substantial heterogeneity, risk of bias, and inadequate phytochemical characterization, these results should be considered hypothesis-generating and interpreted with caution.