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Immune phenotypes that predict COVID-19 severity
Severe COVID-19 causes profound immune perturbations, but pre-infection immune signatures contributing to severe COVID-19 remain unknown. Genome-wide association studies (GWAS) identified strong associations between severe disease and several chemokine receptors and molecules from the type I interfe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8923110/ https://www.ncbi.nlm.nih.gov/pubmed/35291290 http://dx.doi.org/10.21203/rs.3.rs-1378671/v1 |
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author | Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip Roederer, Mario |
author_facet | Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip Roederer, Mario |
author_sort | Liechti, Thomas |
collection | PubMed |
description | Severe COVID-19 causes profound immune perturbations, but pre-infection immune signatures contributing to severe COVID-19 remain unknown. Genome-wide association studies (GWAS) identified strong associations between severe disease and several chemokine receptors and molecules from the type I interferon pathway. Here, we define immune signatures associated with severe COVID-19 using high-dimensional flow cytometry. We measured the peripheral immune system from individuals who recovered from mild, moderate, severe or critical COVID-19 and focused only on those immune signatures returning to steady-state. Individuals that suffered from severe COVID-19 showed reduced frequencies of T cell, MAIT cell and dendritic cell (DCs) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we found reduced frequencies of type I interferon-producing plasmacytoid DCs and altered IFNAR2 expression on several myeloid cells in individuals recovered from severe COVID-19. Thus, these data identify potential immune mechanisms contributing to severe COVID-19. |
format | Online Article Text |
id | pubmed-8923110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-89231102022-03-16 Immune phenotypes that predict COVID-19 severity Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip Roederer, Mario Res Sq Article Severe COVID-19 causes profound immune perturbations, but pre-infection immune signatures contributing to severe COVID-19 remain unknown. Genome-wide association studies (GWAS) identified strong associations between severe disease and several chemokine receptors and molecules from the type I interferon pathway. Here, we define immune signatures associated with severe COVID-19 using high-dimensional flow cytometry. We measured the peripheral immune system from individuals who recovered from mild, moderate, severe or critical COVID-19 and focused only on those immune signatures returning to steady-state. Individuals that suffered from severe COVID-19 showed reduced frequencies of T cell, MAIT cell and dendritic cell (DCs) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we found reduced frequencies of type I interferon-producing plasmacytoid DCs and altered IFNAR2 expression on several myeloid cells in individuals recovered from severe COVID-19. Thus, these data identify potential immune mechanisms contributing to severe COVID-19. American Journal Experts 2022-03-10 /pmc/articles/PMC8923110/ /pubmed/35291290 http://dx.doi.org/10.21203/rs.3.rs-1378671/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Article Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip Roederer, Mario Immune phenotypes that predict COVID-19 severity |
title | Immune phenotypes that predict COVID-19 severity |
title_full | Immune phenotypes that predict COVID-19 severity |
title_fullStr | Immune phenotypes that predict COVID-19 severity |
title_full_unstemmed | Immune phenotypes that predict COVID-19 severity |
title_short | Immune phenotypes that predict COVID-19 severity |
title_sort | immune phenotypes that predict covid-19 severity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8923110/ https://www.ncbi.nlm.nih.gov/pubmed/35291290 http://dx.doi.org/10.21203/rs.3.rs-1378671/v1 |
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