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Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death
End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differ...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064756/ https://www.ncbi.nlm.nih.gov/pubmed/33704068 http://dx.doi.org/10.7554/eLife.64827 |
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author | Gisby, Jack Clarke, Candice L Medjeral-Thomas, Nicholas Malik, Talat H Papadaki, Artemis Mortimer, Paige M Buang, Norzawani B Lewis, Shanice Pereira, Marie Toulza, Frederic Fagnano, Ester Mawhin, Marie-Anne Dutton, Emma E Tapeng, Lunnathaya Richard, Arianne C Kirk, Paul DW Behmoaras, Jacques Sandhu, Eleanor McAdoo, Stephen P Prendecki, Maria F Pickering, Matthew C Botto, Marina Willicombe, Michelle Thomas, David C Peters, James E |
author_facet | Gisby, Jack Clarke, Candice L Medjeral-Thomas, Nicholas Malik, Talat H Papadaki, Artemis Mortimer, Paige M Buang, Norzawani B Lewis, Shanice Pereira, Marie Toulza, Frederic Fagnano, Ester Mawhin, Marie-Anne Dutton, Emma E Tapeng, Lunnathaya Richard, Arianne C Kirk, Paul DW Behmoaras, Jacques Sandhu, Eleanor McAdoo, Stephen P Prendecki, Maria F Pickering, Matthew C Botto, Marina Willicombe, Michelle Thomas, David C Peters, James E |
author_sort | Gisby, Jack |
collection | PubMed |
description | End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte–endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets. |
format | Online Article Text |
id | pubmed-8064756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-80647562021-04-30 Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death Gisby, Jack Clarke, Candice L Medjeral-Thomas, Nicholas Malik, Talat H Papadaki, Artemis Mortimer, Paige M Buang, Norzawani B Lewis, Shanice Pereira, Marie Toulza, Frederic Fagnano, Ester Mawhin, Marie-Anne Dutton, Emma E Tapeng, Lunnathaya Richard, Arianne C Kirk, Paul DW Behmoaras, Jacques Sandhu, Eleanor McAdoo, Stephen P Prendecki, Maria F Pickering, Matthew C Botto, Marina Willicombe, Michelle Thomas, David C Peters, James E eLife Immunology and Inflammation End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte–endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets. eLife Sciences Publications, Ltd 2021-03-11 /pmc/articles/PMC8064756/ /pubmed/33704068 http://dx.doi.org/10.7554/eLife.64827 Text en © 2021, Gisby et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Immunology and Inflammation Gisby, Jack Clarke, Candice L Medjeral-Thomas, Nicholas Malik, Talat H Papadaki, Artemis Mortimer, Paige M Buang, Norzawani B Lewis, Shanice Pereira, Marie Toulza, Frederic Fagnano, Ester Mawhin, Marie-Anne Dutton, Emma E Tapeng, Lunnathaya Richard, Arianne C Kirk, Paul DW Behmoaras, Jacques Sandhu, Eleanor McAdoo, Stephen P Prendecki, Maria F Pickering, Matthew C Botto, Marina Willicombe, Michelle Thomas, David C Peters, James E Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title | Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title_full | Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title_fullStr | Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title_full_unstemmed | Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title_short | Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death |
title_sort | longitudinal proteomic profiling of dialysis patients with covid-19 reveals markers of severity and predictors of death |
topic | Immunology and Inflammation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064756/ https://www.ncbi.nlm.nih.gov/pubmed/33704068 http://dx.doi.org/10.7554/eLife.64827 |
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