Integrated network pharmacology and in vivo experiments to reveal the anti-inflammatory mechanism of Qinghuo Rougan Formula in uveitis

Changying Jing¹Yaqi Sun²Hongsheng Bi³Junguo Guo³Cong Ren³Jike Song³Beibei Wang³Qingmei Tian³Dadong Guo³Pengjuan He⁴Lijie Li⁵Xiaofeng Xie^3*

• ¹Helmholtz Center München, Helmholtz Association of German Research Centres (HZ), Neuherberg, Germany
• ²LMU Munich University Hospital, Munich, Bavaria, Germany
• ³Eye Institute of Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
• ⁴Shandong Maternal and Child Health Hospital, Jinan, Shandong Province, China
• ⁵Shandong Endocrinology and Metabolic Disease Hospital, Jinan, Shandong Province, China

Background: Uveitis is a complex intraocular inflammatory disease and pathology results from the continuous production of proinflammatory cytokines in the optical axis. Qinghuo Rougan Formula (QHRGF), a traditional Chinese medicine (TCM) is now used to treat uveitis with desirable effect. However, the mechanism of action is still unclear. This study aimed to explore the potential diagnostic and therapeutic biomarkers for uveitis using systems biology methods, including network pharmacology and weighted gene co-expression network analysis (WGCNA).Methods: A molecular drug-compound-target-uveitis interaction network was established using network pharmacology. Functional enrichment analyses were performed to screen potential signaling pathways. The uveitis gene expression dataset from the Gene Expression Omnibus database was subjected to WGCNA to identify gene co-expression modules related to uveitis and explore the potential hub genes. The least absolute shrinkage and selection operator (LASSO) model was used to identify the hub genes. Additionally, molecular docking was performed to verify the accuracy and stability of the model. Finally, the suppressive effects of QHRGF on uveitis were experimentally verified in vivo.Results: Network pharmacology and functional enrichment analysis showed that 18 targets and immune/inflammation-related pathways were associated with the QHRGF-targeted pathway network. The yellow module contained 120 genes had a strong correlation with uveitis using WGCNA. In total, 12 putative targets of QHRGF, differentially expressed genes, and yellow module genes were determined. Six hub genes were identified using LASSO model and the receiving operating characteristic curve analysis demonstrated the model can serve as biomarkers for uveitis. The advantages of these genes were approved using molecular docking. Finally, in vivo experiments provided evidence confirming that QHRGF was identified as the key target of the anti-inflammatory effect of uveitis.In conclusion, this research revealed that QHRGF can be used to treat uveitis through multiple components and targets. Meanwhile, the potential anti-inflammatory action of QHRGF in the treatment of uveitis was verified by combining network pharmacology and in vivo experiments, suggesting its potential as a quite prospective agent for the therapy of uveitis.