Background
Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung function.
Methods
In the present study, we used weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with lung function in IPF. Three datasets, containing clinical information, were downloaded from Gene Expression Omnibus. WGCNA was performed on the GSE32537 dataset. Differentially expressed gene s (DEGs) between IPF patients and healthy controls were also identified to filter hub genes. The relationship between hub genes and lung function was then validated using the GSE47460 and GSE24206 datasets.
Results
The red module, containing 267 genes, was positively correlated with the St. George’s Respiratory Questionnaire score (r = 0.37, p < 0.001) and negatively correlated with the percent predicted forced vital capacity (FVC% predicted) (r = − 0.46, p < 0.001) and the percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) (r = − 0.42, p < 0.001). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the genes in the red module were primarily involved in inflammation and immune pathways. Based on Module Membership and Gene Significance, 32 candidate hub genes were selected in the red module to construct a protein-protein interaction network . Based on the identified DEGs and the degree of connectivity in the network, we identified three hub genes, including interleukin 6 (IL6), suppressor of cytokine signaling-3 (SOCS3), and serpin family E member 1 (SERPINE1). In the GSE47460 dataset, Spearman correlation coefficients between Dlco% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.32, –0.41, and –0.46, respectively. Spearman correlation coefficients between FVC% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.29, –0.33, and –0.27, respectively. In the GSE24206 dataset, all three hub genes were upregulated in patients with advanced IPF.
Conclusion
We identified three hub genes that negatively correlated with the lung function of IPF patients. Our results provide insights into the pathogenesis underlying the progressive disruption of lung function, and the identified hub genes may serve as biomarkers and potential therapeutictargets for the treatment of IPF patients.
Detection of microRNA expression levels based on microarray analysis for classification of idiopathic pulmonary fibrosis