Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death
eLife, 2021
Gisby J., Clarke C., Medjeral-Thomas N., Malik T., Papadaki A., Mortimer P., Buang N., Lewis S., Pereira M., Toulza F., Fagnano E., Mawhin M., Dutton E., Tapeng L., Richard A., Kirk P., Behmoaras J., Sandhu E., McAdoo S., Prendecki M., Pickering M., Botto M., Willicombe M., Thomas D., Peters J.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Infectious Diseases | Pathophysiology Patient Stratification | Plasma Serum | O Olink Target 96 |
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. 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.