ABSTRACT
Chronic obstructive pulmonary disease (COPD) is closely related to innate and adaptive inflammatory immune responses. It is increasingly becoming evident that metabolic syndrome (MetS) affects a significant portion of COPD patients. Through this investigation, we identify shared immune-related candidate biological markers. The Weighted Gene Co-Expression Network Analysis (WGCNA) was utilized to reveal the co-expression modules linked to COPD and MetS. The commonly expressed genes in the COPD and MetS were utilized to conduct an enrichment analysis. We adopted machine-learning to screen and validate hub genes. We also assessed the relationship between hub genes and immune cell infiltration in COPD and MetS, respectively. Moreover, associations across hub genes and metabolic pathways were also explored. Finally, we chose a single-cell RNA sequencing (scRNA-seq) dataset to investigate the hub genes and shared mechanisms at the level of the cells. We also applied cell trajectory analysis and cell-cell communication analysis to focus on the vital immune cell we were interested in. As a result, we selected and validated 13 shared hub genes for COPD and MetS. The enrichment analysis and immune infiltration analysis illustrated strong associations between hub genes and immunology. Additionally, we applied metabolic pathway enrichment analysis, indicating the significant role of reactive oxygen species (ROS) in COPD with MetS. Through scRNA-seq analysis, we found that ROS might accumulate the most in the alveolar macrophages. In conclusion, the 13 hub genes related to the immune response and metabolism may serve as diagnostic biomarkers and treatment targets of COPD with MetS.
Subject(s)
Metabolic Syndrome , Pulmonary Disease, Chronic Obstructive , Humans , Metabolic Syndrome/genetics , Reactive Oxygen Species , Cell Communication , Pulmonary Disease, Chronic Obstructive/genetics , Sequence Analysis, RNAABSTRACT
BACKGROUND: The present study aimed to explore the mechanism of the modified Bushen Yiqi formula (MBYF) in the treatment of chronic obstructive pulmonary disease (COPD) based on network pharmacology and molecular docking. METHODS: First, the active ingredients and corresponding targets in MBYF were mined through the Traditional Chinese Medicine Systems Pharmacology database. Subsequently, Online Mendelian Inheritance in Man, DrugBank, and GeneCard were used to screen COPD-related targets. Cytoscape was used to construct a network of candidate components of MBYF in COPD treatment. The overlapping targets of COPD and MBYF were used to treat COPD, and then CytoHubba and CytoNAC plug-ins in Cytoscape were used for topology analysis to build the core network. In addition, core targets were used for Gene Ontology analysis and enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes. Finally, AutoDock Vina software was used to conduct a molecular docking study on the core active ingredients and core targets to verify the above network pharmacological analysis. RESULTS: Seventy-nine active components of MBYF were screened and 261 corresponding targets were found. At the same time, 1307 related targets corresponding to COPD were screened and 111 overlapping targets were matched. By bioinformatics analysis, 10 core targets were identified, and subsequently, enrichment analysis revealed 385 BP, two CC, eight MF and 78 related signaling pathways. The binding of the core active components in MBYF to the core target was further verified by molecular docking, and all showed good binding. CONCLUSIONS: The active components of MBYF, such as quercetin, kaempferol, luteolin, and baicalein, may be the material basis for the treatment of chronic obstructive pulmonary disease. They affect the expression of inflammatory cells and inflammatory factors, protein phosphorylation, and smooth muscle hyperplasia through tumor necrosis factor, interleukin-17, mitogen-activated protein kinase, nuclear factor-kappa B and other signaling pathways.
