Identification of Hub Genes and Pathways Associated With Idiopathic Pulmonary Fibrosis via Bioinformatics Analysis

Hanxi Wan; Hanxi Wan; Xinwei Huang; Peilin Cong; Peilin Cong; Mengfan He; Mengfan He; Aiwen Chen; Tingmei Wu; Tingmei Wu; Danqing Dai; Danqing Dai; Wanrong Li; Wanrong Li; Xiaofei Gao; Xiaofei Gao; Li Tian; Li Tian; Li Tian; Huazheng Liang; Huazheng Liang; Lize Xiong; Lize Xiong; Lize Xiong

Identification of Hub Genes and Pathways Associated With Idiopathic Pulmonary Fibrosis via Bioinformatics Analysis

2021

Idiopathic pulmonary fibrosis (IPF) is a progressive disease whose etiology remains unknown. The purpose of this study was to explore hub genes and pathways related to IPF development and prognosis. Multiple gene expression datasets were downloaded from the Gene Expression Omnibus database. Weighted correlation network analysis (WGCNA) was performed and differentially expressed genes (DEGs) identified to investigate Hub modules and genes correlated with IPF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network analysis were performed on selected key genes. In the PPI network and cytoHubba plugin, 11 hub genes were identified, including ASPN, CDH2, COL1A1, COL1A2, COL3A1, COL14A1, CTSK, MMP1, MMP7, POSTN, and SPP1. Correlation between hub genes was displayed and validated. Expression levels of hub genes were verified using quantitative real-time PCR (qRT-PCR). Dysregulated expression of these genes and their crosstalk might impact the development of IPF through modulating IPF-related biological processes and signaling pathways. Among these genes, expression levels of COL1A1, COL3A1, CTSK, MMP1, MMP7, POSTN, and SPP1 were positively correlated with IPF prognosis. The present study provides further insights into individualized treatment and prognosis for IPF.

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