Identification of common signatures in pulmonary diseases by bioinformatic analysis

Abstract

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 infection, primarily affects the respiratory system, and various symptoms ranging from asymptomatic to life-threatening depending on gender, age, or presence of certain diseases, have been observed. Pulmonary arterial hypertension (PAH) is a rare but fatal disease of the pulmonary vasculature, and idiopathic pulmonary fibrosis (IPF) is a progressive and debilitating disease that affects lung function, resulting in respiratory failure, which can ultimately lead to death. Several common risk factors for COVID-19, IPF, and PAH were previously reported. However, the molecular mechanisms underlying the crosstalk between these diseases has not been elucidated. Thus, identifying common signatures of these diseases would be invaluable for future development of therapeutic strategies. In the current study, integrated bioinformatic analysis was performed to identify common features of these diseases. Specifically, gene expression data associated with COVID19, IPF, and PAH were comparatively analyzed and differentially expressed genes (DEGs) were identified individually considering the diseased and control states. Then, a physical protein-protein interaction (PPI) network was constructed among common DEGs and hub proteins, which may play an important role in development and progression of these diseases were identified. A total of 91 genes were found as common DEGs, and enrichment analysis revealed significant alterations in immunity and inflammation related processes, and cancer associated pathways. Topological analysis of PPI network revealed seven hub proteins based on degree and betweenness centrality measures. Overall, these findings identified common mechanisms of IPF, PAH and COVID-19 at molecular level and provide new potential molecular targets. Keywords: Transcriptome, Molecular signatures, Pulmonary diseases