Introduction The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19. Materials and methods Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs. Results A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01). Conclusion Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.
【초록키워드】 COVID-19, coronavirus disease, SARS-CoV-2, coronavirus, pulmonary fibrosis, cytokine, progression, risk factor, dataset, enrichment analysis, SARS-CoV-2 infections, protein-protein interaction, differentially expressed gene, IPF, PPI, Extracellular matrix, Cytoscape, therapeutic target, acute respiratory syndrome, material, DEGs, datasets, GEO database, identifying, Genes, FIVE, Result, predicted, identify, performed, caused, involved, reported, determine, regulated, upregulated, downregulated, candidate drug, 【제목키워드】 pulmonary fibrosis, Bioinformatics analysis, identification, with COVID-19,