The regulatory effect of Angelicae Sinensis Radix on neuroendocrine-immune network and sphingolipid metabolism in CUMS-induced model of depression

Conventional antidepressants therapy remains unsatisfactory due to the disadvantages of delayed clinical onset of action and side effects. Traditional Chinese Medicine (TCM) with good efficacy and higher safety have received much attention. Angelicae Sinensis Radix (AS), a well-known TCM, has been proved to exhibit the efficacy of antidepression recently. The purpose of this study was to investigate the potential anti-depressant mechanisms of AS based on chronic unpredictable mild stress (CUMS) rat model. In this study, behavioral experiments, molecular biology techniques, and ultra performance liquid chromatography-triple-time of flight mass spectrometer (UPLC-Triple-TOF/MS) were combined to explore the potential antidepressant mechanisms of AS based on CUMS rat model. The results demonstrated that AS could reduce the contents of serum hypothalamic-pituitary-adrenal (HPA) axis hormones in CUMS rats, including corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol (CORT). In addition, AS regulated the percentage of CD4+ T lymphocytes, the ratio of CD4+/CD8+, and the levels of serum cytokines such as IL-1β, IL-4, IL-6, and TNF-α in CUMS rats. Lipidomics showed that 31 lipids were related to depression and AS could regulate the lipid metabolism alteration induced by CUMS, particularly sphingolipid metabolism. Finally, the key proteins in sphingolipid metabolic pathways in hippocampus of CUMS rats could be back-regulated by AS, including serine palmitoyl transferase (SPTLC2), ceramide synthase (CerS2), sphingomyelinase (SPHK1), and neutral sphingomyelinase (nSMase). AS could alleviate NEI network disorder and restore the levels of sphingolipid metabolites and key proteins in CUMS rats. The underlying mechanism by which AS relieved depression-like behavior in CUMS rats may be through modulation of NEI and disturbances in sphingolipid metabolism.