Affiliation:
1. School of Pharmacy, Dali University, Dali 671000, China
Abstract
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.
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).
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.
Publisher
Bentham Science Publishers Ltd.
Subject
Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine
Cited by
2 articles.
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