Litcius/Paper detail

Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach

Md. Rabiul Auwul, Chongqi Zhang, Md Rezanur Rahman, Md. Shahjaman, Salem A. Alyami, Mohammad Ali Moni

2021Saudi Journal of Biological Sciences18 citationsDOIOpen Access PDF

Abstract

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 degranulation", "regulation of wound healing", "platelet activation", "focal adhesion", "regulation of actin cytoskeleton" and "PI3K-Akt signalling pathway". 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.

Topics & Concepts

TranscriptomeBiologyKEGGKidney diseaseBioinformaticsTranscription factorE2F1Platelet activationmicroRNAActin cytoskeletonGeneComputational biologyMedicineImmunologyGene expressionGeneticsPlateletCellCytoskeletonEndocrinologyCOVID-19 Clinical Research StudiesChronic Kidney Disease and DiabetesHealth Systems, Economic Evaluations, Quality of Life
Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach | Litcius