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Bifurcated monocyte states are predictive of mortality in severe COVID-19
Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations(1), ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality(2,3). Despite extensive analyses, there remains an urgent need to delineate immune cell sta...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885916/ https://www.ncbi.nlm.nih.gov/pubmed/33594364 http://dx.doi.org/10.1101/2021.02.10.430499 |
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author | Cillo, Anthony R. Somasundaram, Ashwin Shan, Feng Cardello, Carly Workman, Creg J. Kitsios, Georgios D. Ruffin, Ayana Kunning, Sheryl Lampenfeld, Caleb Onkar, Sayali Grebinoski, Stephanie Deshmukh, Gaurav Methe, Barbara Liu, Chang Nambulli, Sham Andrews, Lawrence Duprex, W. Paul Joglekar, Alok V. Benos, Panayiotis V. Ray, Prabir Ray, Anuradha McVerry, Bryan J. Zhang, Yingze Lee, Janet S. Das, Jishnu Singh, Harinder Morris, Alison Bruno, Tullia C. Vignali, Dario A.A. |
author_facet | Cillo, Anthony R. Somasundaram, Ashwin Shan, Feng Cardello, Carly Workman, Creg J. Kitsios, Georgios D. Ruffin, Ayana Kunning, Sheryl Lampenfeld, Caleb Onkar, Sayali Grebinoski, Stephanie Deshmukh, Gaurav Methe, Barbara Liu, Chang Nambulli, Sham Andrews, Lawrence Duprex, W. Paul Joglekar, Alok V. Benos, Panayiotis V. Ray, Prabir Ray, Anuradha McVerry, Bryan J. Zhang, Yingze Lee, Janet S. Das, Jishnu Singh, Harinder Morris, Alison Bruno, Tullia C. Vignali, Dario A.A. |
author_sort | Cillo, Anthony R. |
collection | PubMed |
description | Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations(1), ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality(2,3). Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1β) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1β and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics. |
format | Online Article Text |
id | pubmed-7885916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-78859162021-02-17 Bifurcated monocyte states are predictive of mortality in severe COVID-19 Cillo, Anthony R. Somasundaram, Ashwin Shan, Feng Cardello, Carly Workman, Creg J. Kitsios, Georgios D. Ruffin, Ayana Kunning, Sheryl Lampenfeld, Caleb Onkar, Sayali Grebinoski, Stephanie Deshmukh, Gaurav Methe, Barbara Liu, Chang Nambulli, Sham Andrews, Lawrence Duprex, W. Paul Joglekar, Alok V. Benos, Panayiotis V. Ray, Prabir Ray, Anuradha McVerry, Bryan J. Zhang, Yingze Lee, Janet S. Das, Jishnu Singh, Harinder Morris, Alison Bruno, Tullia C. Vignali, Dario A.A. bioRxiv Article Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations(1), ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality(2,3). Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1β) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1β and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics. Cold Spring Harbor Laboratory 2021-02-10 /pmc/articles/PMC7885916/ /pubmed/33594364 http://dx.doi.org/10.1101/2021.02.10.430499 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Cillo, Anthony R. Somasundaram, Ashwin Shan, Feng Cardello, Carly Workman, Creg J. Kitsios, Georgios D. Ruffin, Ayana Kunning, Sheryl Lampenfeld, Caleb Onkar, Sayali Grebinoski, Stephanie Deshmukh, Gaurav Methe, Barbara Liu, Chang Nambulli, Sham Andrews, Lawrence Duprex, W. Paul Joglekar, Alok V. Benos, Panayiotis V. Ray, Prabir Ray, Anuradha McVerry, Bryan J. Zhang, Yingze Lee, Janet S. Das, Jishnu Singh, Harinder Morris, Alison Bruno, Tullia C. Vignali, Dario A.A. Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title | Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title_full | Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title_fullStr | Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title_full_unstemmed | Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title_short | Bifurcated monocyte states are predictive of mortality in severe COVID-19 |
title_sort | bifurcated monocyte states are predictive of mortality in severe covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885916/ https://www.ncbi.nlm.nih.gov/pubmed/33594364 http://dx.doi.org/10.1101/2021.02.10.430499 |
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