Perphenazine Attenuates the Pro-Inflammatory Responses in Mouse Models of Th2-Type Allergic Dermatitis

A network medicine-based approach to explore the relationship between depression and inflammation

Background

Depression is widespread global problem that not only severely impacts individuals' physical and mental health but also imposes a heavy disease burden on nations and societies. The role of inflammation in the pathogenesis and pathophysiology of depression has received much attention, but the precise relationship between the two remains unclear. This study aims to investigate the correlation between depression and inflammation using a network medicine approach.

Methods

We utilized a degree-preserving approach to identify the large connected component (LCC) of all depression-related proteins in the human interactome. The LCC was deemed as the disease module for depression. To measure the association between depression and other diseases, we calculated the overlap between these disease protein modules using the Sab algorithm. A smaller Sab value indicates a stronger association between diseases. Building on the results of this analysis, we further explored the correlation between inflammation and depression by conducting enrichment and pathway analyses of critical targets. Finally, we used a network proximity approach to calculate drug-disease proximity to predict the efficacy of drugs for the treatment of depression. We calculated and ranked the distances between depression disease modules and 6,100 drugs. The top-ranked drugs were selected to explore their potential for treating depression based on the hypothesis that their antidepressant effects are related to reducing inflammation.

Results

In the human interactome, all depression-related proteins are clustered into a large connected component (LCC) consisting of 202 proteins and multiple small subgraphs. This indicates that depression-related proteins tend to form clusters within the same network. We used the 202 LCC proteins as the key disease module for depression. Next, we investigated the potential relationships between depression and 299 other diseases. Our analysis identified over 18 diseases that exhibited significant overlap with the depression module. Where S_AB = -0.075 for the vascular disease and depressive disorders module, S_AB = -0.070 for the gastrointestinal disease and depressive disorders module, and S_AB = -0.062 for the endocrine system disease and depressive disorders module. The distance between them S_AB < 0 implies that the pathogenesis of depression is likely to be related to the pathogenesis of its co-morbidities of depression and that potential therapeutic approaches may be derived from the disease treatment libraries of these co-morbidities. Further, considering that the inflammation is ubiquitous in some disease, we calculate the overlap between the collected inflammation module (236 proteins) and the depression module (202 proteins), finding that they are closely related (S_di = -0.358) in the human protein interaction network. After enrichment and pathway analysis of key genes, we identified the HIF-1 signaling pathway, PI3K-Akt signaling pathway, Th17 cell differentiation, hepatitis B, and inflammatory bowel disease as key to the inflammatory response in depression. Finally, we calculated the Z-score to determine the proximity of 6,100 drugs to the depression disease module. Among the top three drugs identified by drug-disease proximity analysis were Perphenazine, Clomipramine, and Amitriptyline, all of which had a greater number of targets in the network associated with the depression disease module. Notably, these drugs have been shown to exert both anti-inflammatory and antidepressant effects, suggesting that they may modulate depression through an anti-inflammatory mechanism. These findings demonstrate a correlation between depression and inflammation at the network medicine level, which has important implications for future elucidation of the etiology of depression and improved treatment outcomes.

Conclusion

Neuroimmune signaling pathways play an important role in the pathogenesis of depression, and many classes of antidepressants exhibiting anti-inflammatory properties. The pathogenesis of depression is closely related to inflammation.

Glycyrrhizic acid suppresses atopic dermatitis-like symptoms by regulating the immune balance

BACKGROUND

Glycyrrhiza is one of the most widely used traditional Chinese medicines in China. Its main bioactive ingredient glycyrrhizic acid (GA) has the potential to be used as a treatment for atopic dermatitis (AD) because it has similar actions to steroids, but with relatively few side effects.

AIMS

The objective of this study was to explore the potential mechanisms of GA on AD mice model.

METHODS

Calcipotriol, a vitamin D3 analogue (MC903) was applied topically to establish AD mouse model. Mice were intraperitoneally administrated with 2 mg/kg dexamethasone (DEX), 25 or 50 mg/kg GA for 15 days. After mice were executed, skin tissues were collected and detected the expression levels of IL-4, IFN-γ, TNF-α and thymic stromal lymphopoietin (TSLP). The percentages of Th1, Th2, Th17, langerhans cells (LCs) in draining lymph nodes (dLNs) were measured by flow cytometry.

RESULTS

Our data demonstrated that GA improved the symptoms of AD by exerting anti-inflammatory and anti-allergic functions in vivo. We found that GA treatment decreased the level of total IgE in serum, suppressed ear swelling, reduced the infiltration of mast cells in skin lesions and decreased expressions of IL-4, IFN-γ, TNF-α and TSLP in skin lesions. Furthermore, our experimental results demonstrated that GA suppressed the Th1/Th2/Th17-immune responses in the dLNs, inhibited the migration of LCs in dLNs.

CONCLUSIONS

In conclusion, our findings suggested potential therapeutic effects of GA against MC903-induced AD-like skin lesions in mice.

Targeting Mast Cells in Allergic Disease: Current Therapies and Drug Repurposing

The incidence of allergic disease has grown tremendously in the past three generations. While current treatments are effective for some, there is considerable unmet need. Mast cells are critical effectors of allergic inflammation. Their secreted mediators and the receptors for these mediators have long been the target of allergy therapy. Recent drugs have moved a step earlier in mast cell activation, blocking IgE, IL-4, and IL-13 interactions with their receptors. In this review, we summarize the latest therapies targeting mast cells as well as new drugs in clinical trials. In addition, we offer support for repurposing FDA-approved drugs to target mast cells in new ways. With a multitude of highly selective drugs available for cancer, autoimmunity, and metabolic disorders, drug repurposing offers optimism for the future of allergy therapy.