Integrated bioinformatics analysis to determine the impact of SARS-CoV-2 infections to Heart Failure patients (preprint)

ABSTRACT

Background: COVID-19, the highly contagious respiratory disease, has become a major threat to humanity, and its extrapulmonary effects were also evident. Heart failure (HF) may be the result of myocardial damage associated with COVID-19. Methods: To understand the relationship between SARS-COV-2 and HF, we used bioinformatics analysis to identify common pathways and molecular biomarkers for HF and COVID-19. In this study, two datasets (GSE152418, GSE57338) from Gene Expression Omnibus (GEO) were used to identify differentially expressed genes (DEGs) of SARS-COV-2 infection in HF patients to find common pathways and drug candidates. Results: A total of 123 common DEGs were identified in the two datasets. Using a variety of bioinformatics tools, we first constructed protein-protein interactions (PPI) and then identified hub genes that could be served as potential biomarkers or novel therapeutic strategies. In addition, some common associations between HF and the progression of COVID-19 infection were found by using functional under ontological terms and pathway analysis. Through the datasets, we also identified transcription factor-gene interactions, protein-drug interactions, and co-regulatory network of DEGs-miRNAs with common DEGs. We built gene-disease association network to represent diseases associated with mutual DEGs. Conclusions: Our study has identified the candidate hub genes and drugs that might become a new therapeutic target for novel coronavirus vaccine development and treatment in COVID-19 and HF.