Network-based Approach to Identify Pathways and Macromolecule Interactions that Mediate Influences of COVID-19 on the Progression of Respiratory System Diseases

Abstract

COVID-19 is an infectious illness concerning coronavirus that is transmitted through droplets propagated by an infected person exhales, coughs, or sneezes. People affected by coronavirus have a risk to occur respiratory diseases (RDs). The longevity of COVID-19 may appear a vital risk of manifesting RDs. To address these issues, we explored transcriptomic data to identify the genetic effects of COVID-19 on the development of RDs such as Bronchitis (BC), Asthma (AT), Lung cancer (LC), and Pulmonary Edema (PE). We explored GEO datasets from NCBI for COVID-19, BC, AT, LC, PE case, and control subjects. We identified COVID-19 is associated with RDs by sharing 16, 19, 27, and 59 commonly DEGs accordingly. By using these genes we performed some bioinformatics analysis and constructed diseasome networks, identified functional and ontological pathways. We formed PPIs networks and PDIs network. On the basis of PPIs and PDIs, we have identified hub proteins and constructed hub proteins network. We have successfully developed a quantitative model to identify the genetic effects of COVID-19 on the progression of RDs. We also validated our investigations through gold-benchmark datasets. Our results are an effective resource to mark out the most important influences on the development of RDs for COVID-19.