Network Pharmacology Study on the Mechanism of Gastrodin Reversing Depressive Symptoms in Traumatically Stressed Rats

天麻素逆转创伤应激大鼠抑郁症状机制的网络药理学研究

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作者:Ruodan Zhao, Xie Li, Haizhu Zhang, Xubing Chen, Ying Wang

Background

Depression is a typical outcome of the repair of posttraumatic stress disorder (PTSD). Based on network pharmacology and neuropharmacology experiments, this study aimed to explore how gastrodin (GAS) reverses depressive symptoms in traumatically stressed rats.

Conclusion

The effect of GAS on depressive symptoms in SPS rats may be closely related to its reduction of CRF expression in PVN and CeA and inhibition of neuron (NE) synthesis in LC.

Methods

GAS-related targets were predicted by SwissTargetPrediction; depression-related targets were collected from GeneCards and therapeutic target database (TTD); protein-protein interaction (PPI) network was constructed with its action mechanism being predicted by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. The animal model of PTSD was replicated by single prolonged stress (SPS). The antidepressant effect of GAS was investigated by the forced swim test (FST) and tail suspension test (TST). The levels of tyrosine hydroxylase (TH) and corticotropin-releasing factor type I receptor (CRF1) in locus ceruleus (LC) and the expression of corticotropin-releasing factor (CRF) in the paraventricular nucleus of the hypothalamus (PVN) and central amygdala (CeA) were measured by immunofluorescence.

Results

GAS significantly shortened the tail suspension and swimming immobility in SPS rats in TST and FST experiments (p < 0.05 or p < 0.01). The network analysis showed that the critical antidepressant targets of GAS were 86 targets such as GAPDH, CASP3 MMP9, HRAS, DPP4, and TH, which were significantly enriched in the pathways such as pathways neuroactive ligandreceptor interaction. High doses of GAS could significantly reduce the level of TH and CRF in CEA in the brain of rats with depressive symptoms (p < 0.01) and, at the same time, lower the expression of CRF in PVN (p < 0.05).

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