Identification of molecular mechanisms of association amongst comorbidities and COVID-19: An Interactome based Systems Biology Approach
Abstract
Background: Comorbidity has emerged as a major challenge in the last few decades that result from cascades of failures involving complex biochemical and physical interactions of genes, proteins, and metabolites responsible for cellular functions. Various epidemiological and demographic studies conducted since the emergence and global transmission of the SARS-CoV-2 virus have reported that patients having pre-existing medical conditions such as Cardiovascular Disease, Diabetes, Hepatitis, Lung Disease, and Kidney Disease are more prone to coronavirus infection. Objective: The present study was undertaken to elucidate the molecular mechanisms that are common amongst COVID-19 associated-comorbidities using an interactome based network biology approach so as to identify the shared genes/proteins and biological pathways. Methodology: Genes of COVID-19 associated-comorbidity diseases retrieved from disease databases were analyzed using in silico bioinformatics and systems network biology tools STRING and Cytoscape plug-ins CytoHubba and CytoCluster. Results: The shared hub proteins, namely IL1B, ACTB, IL6, MMP2, ALB, AKT1, MAPK3, FN1, TNF, CCL2, VEGFA and TP53, among various pre-existing comorbidities revealed their involvement in immunological pathways. All these proteins were also found to have significant associations with ACE2, TMPRSS2 and CD17/BSG, the entry receptors of COVID-19 virus. Conclusion: Higher risk factor for COVID-19 in patients with pre-existing comorbidities is due to immune dysfunction that results in their higher susceptibility to infection by SARS-CoV-2 via its entry receptors on the host cells. This study provides novel insights about the association between host genetics and consequences of viral infection that is responsible for severity of COVID-19 in patients suffering from pre-existing comorbidities.
Keywords: ComorbiditySARS-CoV-2systems network biologyinteractomeCOVID-19in silicohub genesCytokine storm (CS)Immune dysfunction
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