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Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets
Corona virus disease 2019 (COVID-19) increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The underlying pathophysiological processes are complex, and remain poorly understood. To this end, platelets play important roles in regulating the cardiovascular sy...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008611/ https://www.ncbi.nlm.nih.gov/pubmed/35421970 http://dx.doi.org/10.1186/s12920-022-01222-y |
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author | Alarabi, Ahmed B. Mohsen, Attayeb Mizuguchi, Kenji Alshbool, Fatima Z. Khasawneh, Fadi T. |
author_facet | Alarabi, Ahmed B. Mohsen, Attayeb Mizuguchi, Kenji Alshbool, Fatima Z. Khasawneh, Fadi T. |
author_sort | Alarabi, Ahmed B. |
collection | PubMed |
description | Corona virus disease 2019 (COVID-19) increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The underlying pathophysiological processes are complex, and remain poorly understood. To this end, platelets play important roles in regulating the cardiovascular system, including via contributions to coagulation and inflammation. There is ample evidence that circulating platelets are activated in COVID-19 patients, which is a primary driver of the observed thrombotic outcome. However, the comprehensive molecular basis of platelet activation in COVID-19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID-19. These cluster of genes successfully identify COVID-19 cases, relative to healthy in a separate validation data set using machine learning, thereby validating our findings. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID-19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID-19 disease at the molecular level, which might aid in defining new targets for treatment of COVID-19–induced thrombosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01222-y. |
format | Online Article Text |
id | pubmed-9008611 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90086112022-04-14 Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets Alarabi, Ahmed B. Mohsen, Attayeb Mizuguchi, Kenji Alshbool, Fatima Z. Khasawneh, Fadi T. BMC Med Genomics Research Corona virus disease 2019 (COVID-19) increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The underlying pathophysiological processes are complex, and remain poorly understood. To this end, platelets play important roles in regulating the cardiovascular system, including via contributions to coagulation and inflammation. There is ample evidence that circulating platelets are activated in COVID-19 patients, which is a primary driver of the observed thrombotic outcome. However, the comprehensive molecular basis of platelet activation in COVID-19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID-19. These cluster of genes successfully identify COVID-19 cases, relative to healthy in a separate validation data set using machine learning, thereby validating our findings. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID-19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID-19 disease at the molecular level, which might aid in defining new targets for treatment of COVID-19–induced thrombosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01222-y. BioMed Central 2022-04-14 /pmc/articles/PMC9008611/ /pubmed/35421970 http://dx.doi.org/10.1186/s12920-022-01222-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Alarabi, Ahmed B. Mohsen, Attayeb Mizuguchi, Kenji Alshbool, Fatima Z. Khasawneh, Fadi T. Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title | Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title_full | Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title_fullStr | Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title_full_unstemmed | Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title_short | Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets |
title_sort | co-expression analysis to identify key modules and hub genes associated with covid-19 in platelets |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008611/ https://www.ncbi.nlm.nih.gov/pubmed/35421970 http://dx.doi.org/10.1186/s12920-022-01222-y |
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