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Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach
Authors:Md. Rabiul Auwul  Chongqi Zhang  Md Rezanur Rahman  Md. Shahjaman  Salem A. Alyami  Mohammad Ali Moni
Affiliation:1. School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China;2. Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh;3. Department of Biochemistry and Biotechnology, School of Biomedical Science, Khwaja Yunus Ali University, Enayetpur, Sirajganj 6751, Bangladesh;4. Department of Statistics, Begum Rokeya University, Rangpur 5400, Bangladesh;5. Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University, Saudi Arabia;6. WHO Collaborating Centre on eHealth, UNSW Digital Health, School of Public Health and Community Medicine, Faculty of Medicine, UNSW Sydney, Australia;7. The Garvan Institute of Medical Research, Healthy Ageing Theme, Darlinghurst, NSW 2010, Australia
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.
Keywords:COVID-19  Chronic kidney disease  SARS-CoV-2  Systems biology  Transcriptional signature  Protein-protein interaction  Molecular pathways
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