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Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach
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 tran...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190333/ https://www.ncbi.nlm.nih.gov/pubmed/34127904 http://dx.doi.org/10.1016/j.sjbs.2021.06.015 |
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author | Auwul, Md. Rabiul Zhang, Chongqi Rahman, Md Rezanur Shahjaman, Md. Alyami, Salem A. Moni, Mohammad Ali |
author_facet | Auwul, Md. Rabiul Zhang, Chongqi Rahman, Md Rezanur Shahjaman, Md. Alyami, Salem A. Moni, Mohammad Ali |
author_sort | Auwul, Md. Rabiul |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8190333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-81903332021-06-10 Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach Auwul, Md. Rabiul Zhang, Chongqi Rahman, Md Rezanur Shahjaman, Md. Alyami, Salem A. Moni, Mohammad Ali Saudi J Biol Sci Original Article 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. Elsevier 2021-10 2021-06-10 /pmc/articles/PMC8190333/ /pubmed/34127904 http://dx.doi.org/10.1016/j.sjbs.2021.06.015 Text en © 2021 Published by Elsevier B.V. on behalf of King Saud University. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Auwul, Md. Rabiul Zhang, Chongqi Rahman, Md Rezanur Shahjaman, Md. Alyami, Salem A. Moni, Mohammad Ali Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title | Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title_full | Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title_fullStr | Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title_full_unstemmed | Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title_short | Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach |
title_sort | network-based transcriptomic analysis identifies the genetic effect of covid-19 to chronic kidney disease patients: a bioinformatics approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190333/ https://www.ncbi.nlm.nih.gov/pubmed/34127904 http://dx.doi.org/10.1016/j.sjbs.2021.06.015 |
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