【Objective】We aimed to explore the pathogenic genes of Idiopathic pulmonary fibrosis (IPF) by bioinformatics analy? sis and provide a target for further research.【Methods】Gene data sets GSE53845

GSE24206

GSE10667 were downloaded from the Gene Expression Omnibus database and the differential expression genes of normal tissue and IPF were screened with GEO2R analysis tool. GO analysis and KEGG pathway enrichment analysis of differentially expressed genes were performed in DAVID database in or? der to find out the biological function and its focused signal pathway in differentially expressed genes during IPF development. In order to study the relationship between differential genes and proteins

STRING and CYTOSCAPE software were used to construct the pro? tein interaction network and MCODE software was used to extract the sub-network modules in the protein-interacting network.【Re? sults】This study found 110 differentially expressed genes

of which 92 were high expression in IPF and 18 were low expression. GO enrichment analysis showed that the up-regulated genes in IPF mainly affected the biological processes such as cell adhesion

bio-ad? hesion and collagen metabolism. The enriched molecular function was mainly involved in the composition of extracellular matrix struc? ture and the binding of calcium ions. The down-regulated proteins are mainly involved in the sensory regulation of the biological pro? cess in IPF. KEGG pathway analysis showed that the up-regulated genes in IPF were mainly involved in receptor interactions

cell ad? hesion and other signaling pathways. 【Conclusions】This study uses bioinformatics to screen out the differential genes

some of which have been shown to be involved in IPF

and some genes have not been studied

suggesting that it may be a new research target for IPF pathogenesis.