Biomarker Study of Oxidative Stress in Chronic Obstructive Pulmonary Disease and Prediction of Chinese medicine
Objective: To explore the role of oxidative stress in chronic obstructive pulmonary disease (COPD) and predict related therapeutic Chinese medicines. Methods: Download the COPD microarray data set GSE10006 from the GEO database, obtain oxidative stress genes from the GeneCards database, and identify differentially expressed oxida-tive stress genes (DEOSGs); perform GO, KEGG and GSEA enrichment analysis on DEOSGs; use the String database and Cytoscape The software constructs a PPI network and selects candidate central genes; uses the independent sample GSE76925 to verify the candidate central genes and determines the central genes; uses CIBERSORTF to evaluate the immune microenvironment of the sample and analyzes the correlation between the central genes and 22 types of im-mune cells; finally, Use the Coremine database to predict Chinese medicines that can target the treatment of COPD and count their related attributes. Results: 13 DEOSGs were obtained, and 2 central genes FN1 and PPARG were identified; immune infiltration assessment showed that unactivated mast cells were significantly up-regulated in COPD tissues, while activated mast cells were significantly down-regulated; it was suggested that ginseng, rhubarb, and araceae 43 traditional Chinese medicines have potential intervention effects on COPD. Conclusion: FN1 and PPARG can be used as diagnostic biomarkers for COPD and can provide potential basis for the diagnosis and treatment of this disease.
万方数据
维普
