Author: Rabiul Auwul, Md.; Zhang, Chongqi; Rezanur Rahman, Md.; Shahjaman, Md.; Alyami, Salem A.; Ali Moni, Mohammad
                    Title: Network-Based Transcriptomic Analysis Identifies the Genetic Effect of COVID-19 to Chronic Kidney Disease Patients: A Bioinformatics Approach  Cord-id: xfpdgh17  Document date: 2021_6_10
                    ID: xfpdgh17
                    
                    Snippet: COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD by systems biology analysis. We analyzed transcriptomic data obtained from peripheral blood mononuclear cells (PBMC) infected with SARS-CoV-2 and PBMC of CKD patients. We identified 49 differentially expressed genes (DEGs) which were common betw
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD by systems biology analysis. We analyzed transcriptomic data obtained from peripheral blood mononuclear cells (PBMC) infected with SARS-CoV-2 and PBMC of CKD patients. We identified 49 differentially expressed genes (DEGs) which were common between COVID-19 and CKD. The gene ontology and pathways analysis showed the DEGs were associated with “platelet degranulationâ€, “regulation of wound healingâ€, “platelet activationâ€, “focal adhesionâ€, “regulation of actin cytoskeleton†and “PI3K-Akt signalling pathwayâ€. The protein-protein interaction (PPI) network encoded by the common DEGs showed ten hub proteins (EPHB2, PRKAR2B, CAV1, ARHGEF12, HSP90B1, ITGA2B, BCL2L1, E2F1, TUBB1, and C3). Besides, we identified significant transcription factors and microRNAs that may regulate the common DEGs. We investigated protein-drug interaction analysis and identified potential drugs namely, aspirin, estradiol, rapamycin, and nebivolol. The identified common gene signature and pathways between COVID-19 and CKD may be therapeutic targets in COVID-19 patients with CKD comorbidity.
 
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