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Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples
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: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700777/ https://www.ncbi.nlm.nih.gov/pubmed/36433939 http://dx.doi.org/10.1038/s41467-022-34638-2 |
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author | Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip A. Roederer, Mario |
author_facet | Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip A. 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 measure the cells of 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 show reduced frequencies of T cell, mucosal-associated invariant T cell (MAIT) and dendritic cell (DC) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we find 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-9700777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97007772022-11-27 Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples Liechti, Thomas Iftikhar, Yaser Mangino, Massimo Beddall, Margaret Goss, Charles W. O’Halloran, Jane A. Mudd, Philip A. Roederer, Mario Nat Commun 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 measure the cells of 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 show reduced frequencies of T cell, mucosal-associated invariant T cell (MAIT) and dendritic cell (DC) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we find 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. Nature Publishing Group UK 2022-11-25 /pmc/articles/PMC9700777/ /pubmed/36433939 http://dx.doi.org/10.1038/s41467-022-34638-2 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (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 A. Roederer, Mario Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title | Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title_full | Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title_fullStr | Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title_full_unstemmed | Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title_short | Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples |
title_sort | immune phenotypes that are associated with subsequent covid-19 severity inferred from post-recovery samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700777/ https://www.ncbi.nlm.nih.gov/pubmed/36433939 http://dx.doi.org/10.1038/s41467-022-34638-2 |
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