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Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

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Clarke, Candice L 
Medjeral-Thomas, Nicholas 
Malik, Talat H 
Papadaki, Artemis 


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.


Funder: The Sidharth Burman endowment


Research Article, Immunology and Inflammation, Medicine, COVID-19, proteomics, longitudinal, biomarkers, cytokines, end-stage kidney disease, Human

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eLife Sciences Publications, Ltd
UK Research and Innovation (COVID-19 Rapid Response Rolling Call (MR/V027638/1))
Imperial College London (Community Jameel and the Imperial President's Excellence Fund)
UK Research and Innovation (UKRI Innovation Fellowship at Health Data Research UK (MR/S004068/2))
Wellcome Trust (Wellcome-Beit Prize Clinical Research Career Development Fellowship (206617/A/17/A))
Wellcome Trust (Wellcome Trust Senior Fellow in Clinical Science (212252/Z/18/Z))
Wellcome Trust (Wellcome Trust and Imperial College London Research Fellowship)
Auchi Renal Research Fund (Auchi Clinical Research Fellowship)
Medical Research Council (MC_UU_00002/13)