Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Auwul, Md. Rabiul, Zhang, Chongqi, Rahman, Md Rezanur, Shahjaman, Md., Alyami, Salem A., Moni, Mohammad Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
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
_version_ 1783705664069042176
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
work_keys_str_mv AT auwulmdrabiul networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach
AT zhangchongqi networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach
AT rahmanmdrezanur networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach
AT shahjamanmd networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach
AT alyamisalema networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach
AT monimohammadali networkbasedtranscriptomicanalysisidentifiesthegeneticeffectofcovid19tochronickidneydiseasepatientsabioinformaticsapproach