Quantifying neurodegeneration and vulnerable networks with the aid of structural covariance analysis from magnetic resonance imaging.

Major depressive disorder (MDD) is a mental health issue characterized by core features of “depressed mood” and “loss of interest or pleasure” and accompanied by symptoms such as fatigue, neurocognitive impairment, and sleep disturbances (Kennedy, 2008). Approximately 300 million of the global population experience MDD, and the prevalence rate is increasing (Liu et al., 2020; Monroe and Harkness, 2022). Despite the availability of various antidepressant medications, the rates of response are modest and patients may experience severe side effects or remission (Gorzalka and Hill, 2011). Therefore, overcoming the inadequate response to MDD treatment is a critical challenge. Concerns about the limited effectiveness of current depression treatment strategies have prompted a search for emerging drugs and therapies. In this context, traditional Chinese medicine (TCM), with its comparatively high translational value, may offer new possibilities for targeted therapy for MDD. In recent years, the cultivation of Saposhnikoviae Radix (SR) in northeast China has regained momentum because of its high medicinal and dietary value (Yang et al., 2020b). A recent metabolomics study showed that the SR extract holds potential medicinal prospects in neuroinflammatory defense by inhibiting pro-inflammatory genes and upregulating metabolites such as levodopa-dopamine, gamma-hydroxybutyric acid, and 5-hydroxy-L-tryptophan (Zhu et al., 2021). As one of the most abundant components in SR root, 5-O-methylvisammioside (MeV) is a marker compound used to determine the genuineness and quality control of SR in the Chinese Pharmacopoeia (Xu et al., 2024b). Therefore, the medicinal value of MeV has significant pharmacological importance. MeV was shown to have antipyretic and analgesic functions (Yang et al., 2017), and to treat psoriasis-like dermatitis (Fu et al., 2020). Recently, MeV was demonstrated to exert an antidepressant effect by inhibiting the nuclear/cytosolic ratio of nuclear factor kappa beta (NF-κB) and upregulating the levels of brain-derived neurotrophic factor (BDNF) and tropomyosin receptor kinase B (TrkB) in the hippocampus of LPS mice (Sun et al., 2020). MeV also increased superoxide dismutase levels and decreased malondialdehyde content in the hippocampus. Following MeV treatment , the overactivation of BV-2 microglia was inhibited via the NF-κB/inhibitory subunit of NF kappa B alpha (IκBα) pathway (Sun et al., 2020). MeV may also play a neuroprotective role in focal cerebral ischemia in rats by regulating the phosphatidylinositol 3-kinase/protein kinase B signaling pathway in the cerebral cortex (Chang and Wu, 2016). No studies have explored the utility of MeV in treating high-risk mental disorders such as MDD. With the convergence and popularization of bioinformatics and systems biology, network pharmacology has become a more convenient approach for deciphering the intrinsic mechanisms of drug therapy for diseases in the form of visual “network targets” (Gu et al., 2022). The intervention mechanisms of candidate compounds, targets, and diseases are interlinked through network pharmacology, which provides a statistical basis for systematically characterizing how drugs treat diseases (Li and Zhang, 2013). The multi-channel regulatory mechanism emphasized by network pharmacology is similar to the pharmacodynamic characteristics of multi-targets and multi-pathways in TCM (Zhang et al., 2023). Network pharmacology has significantly enhanced the elucidation of the multi-faceted targets of TCM and the anti-depression mechanisms (Zhang et al., 2021; Cao et al., 2023; Chen et al., 2024).