Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients

In this study, we aimed to explore the molecular mechanism, disease association, and possible health risks in convalescent COVID-19 patients. Gene expression data from a human convalescent COVID-19 data set was compared with a data set from healthy normal individuals in order to identify differentially expressed genes (DEGs). To determine biological function and potential pathway alterations, the GO and KEGG databases were used to analyze the DEGs. Disease association, tissue, and organ-specific analyses were used to identify possible health effects. A total of 250 DEGs were identified between healthy and convalescent COVID-19 subjects. The biological function alterations identified revealed cytokine interactions and increased inflammation through NF-κB1, RELA, JUN, STAT3, and SP1. Interestingly, the most significant pathways were cytokine-cytokine receptor interaction, altered lipid metabolism, and atherosclerosis that play a crucial role in convalescent COVID-19. In addition, we also found pneumonitis, dermatitis, and autoimmune diseases. Based on our study, convalescent COVID-19 is associated with inflammation in a variety of organs that could lead to autoimmune and inflammatory diseases, as well as atherosclerosis. These findings are a first step toward fully exploring the disease mechanisms in depth to understand the relationship between post-COVID-19 infection and potential health risks. This is necessary for the development of appropriate strategies for the prevention...
Source: Bioinformatics and Biology Insights - Category: Bioinformatics Authors: Source Type: research