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Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in pe...

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Autores principales: Feyaerts, Dorien, Hédou, Julien, Gillard, Joshua, Chen, Han, Tsai, Eileen S., Peterson, Laura S., Ando, Kazuo, Manohar, Monali, Do, Evan, Dhondalay, Gopal K.R., Fitzpatrick, Jessica, Artandi, Maja, Chang, Iris, Snow, Theo T., Chinthrajah, R. Sharon, Warren, Christopher M., Wittman, Rich, Meyerowitz, Justin G., Ganio, Edward A., Stelzer, Ina A., Han, Xiaoyuan, Verdonk, Franck, Gaudillière, Dyani K., Mukherjee, Nilanjan, Tsai, Amy S., Rumer, Kristen K., Jiang, Sizun, Valdés Ferrer, Sergio Iván, Kelly, J. Daniel, Furman, David, Aghaeepour, Nima, Angst, Martin S., Boyd, Scott D., Pinsky, Benjamin A., Nolan, Garry P., Nadeau, Kari C., Gaudillière, Brice, McIlwain, David R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885914/
https://www.ncbi.nlm.nih.gov/pubmed/33594362
http://dx.doi.org/10.1101/2021.02.09.430269
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author Feyaerts, Dorien
Hédou, Julien
Gillard, Joshua
Chen, Han
Tsai, Eileen S.
Peterson, Laura S.
Ando, Kazuo
Manohar, Monali
Do, Evan
Dhondalay, Gopal K.R.
Fitzpatrick, Jessica
Artandi, Maja
Chang, Iris
Snow, Theo T.
Chinthrajah, R. Sharon
Warren, Christopher M.
Wittman, Rich
Meyerowitz, Justin G.
Ganio, Edward A.
Stelzer, Ina A.
Han, Xiaoyuan
Verdonk, Franck
Gaudillière, Dyani K.
Mukherjee, Nilanjan
Tsai, Amy S.
Rumer, Kristen K.
Jiang, Sizun
Valdés Ferrer, Sergio Iván
Kelly, J. Daniel
Furman, David
Aghaeepour, Nima
Angst, Martin S.
Boyd, Scott D.
Pinsky, Benjamin A.
Nolan, Garry P.
Nadeau, Kari C.
Gaudillière, Brice
McIlwain, David R.
author_facet Feyaerts, Dorien
Hédou, Julien
Gillard, Joshua
Chen, Han
Tsai, Eileen S.
Peterson, Laura S.
Ando, Kazuo
Manohar, Monali
Do, Evan
Dhondalay, Gopal K.R.
Fitzpatrick, Jessica
Artandi, Maja
Chang, Iris
Snow, Theo T.
Chinthrajah, R. Sharon
Warren, Christopher M.
Wittman, Rich
Meyerowitz, Justin G.
Ganio, Edward A.
Stelzer, Ina A.
Han, Xiaoyuan
Verdonk, Franck
Gaudillière, Dyani K.
Mukherjee, Nilanjan
Tsai, Amy S.
Rumer, Kristen K.
Jiang, Sizun
Valdés Ferrer, Sergio Iván
Kelly, J. Daniel
Furman, David
Aghaeepour, Nima
Angst, Martin S.
Boyd, Scott D.
Pinsky, Benjamin A.
Nolan, Garry P.
Nadeau, Kari C.
Gaudillière, Brice
McIlwain, David R.
author_sort Feyaerts, Dorien
collection PubMed
description The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUC(training) = 0.799, p-value = 4.2e–6; multi-class AUC(validation) = 0.773, p-value = 7.7e−6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression.
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spelling pubmed-78859142021-02-17 Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19 Feyaerts, Dorien Hédou, Julien Gillard, Joshua Chen, Han Tsai, Eileen S. Peterson, Laura S. Ando, Kazuo Manohar, Monali Do, Evan Dhondalay, Gopal K.R. Fitzpatrick, Jessica Artandi, Maja Chang, Iris Snow, Theo T. Chinthrajah, R. Sharon Warren, Christopher M. Wittman, Rich Meyerowitz, Justin G. Ganio, Edward A. Stelzer, Ina A. Han, Xiaoyuan Verdonk, Franck Gaudillière, Dyani K. Mukherjee, Nilanjan Tsai, Amy S. Rumer, Kristen K. Jiang, Sizun Valdés Ferrer, Sergio Iván Kelly, J. Daniel Furman, David Aghaeepour, Nima Angst, Martin S. Boyd, Scott D. Pinsky, Benjamin A. Nolan, Garry P. Nadeau, Kari C. Gaudillière, Brice McIlwain, David R. bioRxiv Article The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUC(training) = 0.799, p-value = 4.2e–6; multi-class AUC(validation) = 0.773, p-value = 7.7e−6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression. Cold Spring Harbor Laboratory 2021-02-10 /pmc/articles/PMC7885914/ /pubmed/33594362 http://dx.doi.org/10.1101/2021.02.09.430269 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
Feyaerts, Dorien
Hédou, Julien
Gillard, Joshua
Chen, Han
Tsai, Eileen S.
Peterson, Laura S.
Ando, Kazuo
Manohar, Monali
Do, Evan
Dhondalay, Gopal K.R.
Fitzpatrick, Jessica
Artandi, Maja
Chang, Iris
Snow, Theo T.
Chinthrajah, R. Sharon
Warren, Christopher M.
Wittman, Rich
Meyerowitz, Justin G.
Ganio, Edward A.
Stelzer, Ina A.
Han, Xiaoyuan
Verdonk, Franck
Gaudillière, Dyani K.
Mukherjee, Nilanjan
Tsai, Amy S.
Rumer, Kristen K.
Jiang, Sizun
Valdés Ferrer, Sergio Iván
Kelly, J. Daniel
Furman, David
Aghaeepour, Nima
Angst, Martin S.
Boyd, Scott D.
Pinsky, Benjamin A.
Nolan, Garry P.
Nadeau, Kari C.
Gaudillière, Brice
McIlwain, David R.
Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title_full Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title_fullStr Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title_full_unstemmed Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title_short Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
title_sort integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885914/
https://www.ncbi.nlm.nih.gov/pubmed/33594362
http://dx.doi.org/10.1101/2021.02.09.430269
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