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Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients
The global coronavirus disease 2019 (COVID-19) pandemic has lasted for over 2 years now and has already caused millions of deaths. In COVID-19, leukocyte pyroptosis has been previously associated with both beneficial and detrimental effects, so its role in the development of this disease remains con...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343985/ https://www.ncbi.nlm.nih.gov/pubmed/35928821 http://dx.doi.org/10.3389/fimmu.2022.888661 |
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author | Tang, Yingkui Zhang, Peidong Liu, Qiuyu Cao, Luyang Xu, Jingsong |
author_facet | Tang, Yingkui Zhang, Peidong Liu, Qiuyu Cao, Luyang Xu, Jingsong |
author_sort | Tang, Yingkui |
collection | PubMed |
description | The global coronavirus disease 2019 (COVID-19) pandemic has lasted for over 2 years now and has already caused millions of deaths. In COVID-19, leukocyte pyroptosis has been previously associated with both beneficial and detrimental effects, so its role in the development of this disease remains controversial. Using transcriptomic data (GSE157103) of blood leukocytes from 126 acute respiratory distress syndrome patients (ARDS) with or without COVID-19, we found that COVID-19 patients present with enhanced leukocyte pyroptosis. Based on unsupervised clustering, we divided 100 COVID-19 patients into two clusters (PYRcluster1 and PYRcluster2) according to the expression of 35 pyroptosis-related genes. The results revealed distinct pyroptotic patterns associated with different leukocytes in these PYRclusters. PYRcluster1 patients were in a hyperinflammatory state and had a worse prognosis than PYRcluster2 patients. The hyperinflammation of PYRcluster1 was validated by the results of gene set enrichment analysis (GSEA) of proteomic data (MSV000085703). These differences in pyroptosis between the two PYRclusters were confirmed by the PYRscore. To improve the clinical treatment of COVID-19 patients, we used least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model based on differentially expressed genes between PYRclusters (PYRsafescore), which can be applied as an effective prognosis tool. Lastly, we explored the upstream transcription factors of different pyroptotic patterns, thereby identifying 112 compounds with potential therapeutic value in public databases. |
format | Online Article Text |
id | pubmed-9343985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93439852022-08-03 Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients Tang, Yingkui Zhang, Peidong Liu, Qiuyu Cao, Luyang Xu, Jingsong Front Immunol Immunology The global coronavirus disease 2019 (COVID-19) pandemic has lasted for over 2 years now and has already caused millions of deaths. In COVID-19, leukocyte pyroptosis has been previously associated with both beneficial and detrimental effects, so its role in the development of this disease remains controversial. Using transcriptomic data (GSE157103) of blood leukocytes from 126 acute respiratory distress syndrome patients (ARDS) with or without COVID-19, we found that COVID-19 patients present with enhanced leukocyte pyroptosis. Based on unsupervised clustering, we divided 100 COVID-19 patients into two clusters (PYRcluster1 and PYRcluster2) according to the expression of 35 pyroptosis-related genes. The results revealed distinct pyroptotic patterns associated with different leukocytes in these PYRclusters. PYRcluster1 patients were in a hyperinflammatory state and had a worse prognosis than PYRcluster2 patients. The hyperinflammation of PYRcluster1 was validated by the results of gene set enrichment analysis (GSEA) of proteomic data (MSV000085703). These differences in pyroptosis between the two PYRclusters were confirmed by the PYRscore. To improve the clinical treatment of COVID-19 patients, we used least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model based on differentially expressed genes between PYRclusters (PYRsafescore), which can be applied as an effective prognosis tool. Lastly, we explored the upstream transcription factors of different pyroptotic patterns, thereby identifying 112 compounds with potential therapeutic value in public databases. Frontiers Media S.A. 2022-07-19 /pmc/articles/PMC9343985/ /pubmed/35928821 http://dx.doi.org/10.3389/fimmu.2022.888661 Text en Copyright © 2022 Tang, Zhang, Liu, Cao and Xu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Tang, Yingkui Zhang, Peidong Liu, Qiuyu Cao, Luyang Xu, Jingsong Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title | Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title_full | Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title_fullStr | Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title_full_unstemmed | Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title_short | Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients |
title_sort | pyroptotic patterns in blood leukocytes predict disease severity and outcome in covid-19 patients |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343985/ https://www.ncbi.nlm.nih.gov/pubmed/35928821 http://dx.doi.org/10.3389/fimmu.2022.888661 |
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