Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
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. 203 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.
Date Issued
2021-03-11
Date Acceptance
2021-03-10
ISSN
2050-084X
Publisher
eLife Sciences Publications Ltd
Start Page
1
End Page
30
Journal / Book Title
eLife
Volume
10
Issue
1
Copyright Statement
© 2021, Gisby et al. This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
License URL
Sponsor
Medical Research Council (MRC)
Medical Research Council (MRC)
Medical Research Council
Community Jameel Imperial College COVID-19 Excellence Fund
Identifier
https://elifesciences.org/articles/64827
Grant Number
MR/N01121X/1
EP/V520354/1
P87193 COV0226
Subjects
COVID-19
biomarkers
cytokines
end-stage kidney disease
human
immunology
inflammation
longitudinal
medicine
proteomics
0601 Biochemistry and Cell Biology
Publication Status
Published online
Article Number
e64827
Date Publish Online
2021-03-11