Network-based identification genetic effect of SARS-CoV-2 infections to Idiopathic pulmonary fibrosis (IPF) patients

Brief Bioinform. 2021 Mar 22;22(2):1254-1266. doi: 10.1093/bib/bbaa235.


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the cause of coronavirus disease (COVID-19) that causes a major threat to humanity. As the spread of the virus is probably getting out of control on every day, the epidemic is now crossing the most dreadful phase. Idiopathic pulmonary fibrosis (IPF) is a risk factor for COVID-19 as patients with long-term lung injuries are more likely to suffer in the severity of the infection. Transcriptomic analyses of SARS-CoV-2 infection and IPF patients in lung epithelium cell datasets were selected to identify the synergistic effect of SARS-CoV-2 to IPF patients. Common genes were identified to find shared pathways and drug targets for IPF patients with COVID-19 infections. Using several enterprising Bioinformatics tools, protein-protein interactions (PPIs) network was designed. Hub genes and essential modules were detected based on the PPIs network. TF-genes and miRNA interaction with common differentially expressed genes and the activity of TFs are also identified. Functional analysis was performed using gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway and found some shared associations that may cause the increased mortality of IPF patients for the SARS-CoV-2 infections. Drug molecules for the IPF were also suggested for the SARS-CoV-2 infections.

Keywords: SARS-CoV-2; differentially expressed genes; drug molecule; gene ontology; hub gene; idiopathic pulmonary fibrosis; protein–protein interactions.

MeSH terms

  • COVID-19 / complications*
  • COVID-19 / genetics
  • COVID-19 / virology
  • Datasets as Topic
  • Epithelial Cells / virology
  • Gene Ontology
  • Genes, Viral
  • Humans
  • Idiopathic Pulmonary Fibrosis / complications*
  • Lung / cytology
  • Lung / virology
  • SARS-CoV-2 / genetics*
  • Transcriptome