Demichev, V;
Tober-Lau, P;
Lemke, O;
Nazarenko, T;
Thibeault, C;
Whitwell, H;
Röhl, A;
... Kurth, F; + view all
(2021)
A time-resolved proteomic and prognostic map of COVID-19.
Cell Systems
10.1016/j.cels.2021.05.005.
(In press).
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Abstract
COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
| Type: | Article |
|---|---|
| Title: | A time-resolved proteomic and prognostic map of COVID-19. |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.cels.2021.05.005 |
| Publisher version: | https://doi.org/10.1016/j.cels.2021.05.005 |
| Language: | English |
| Additional information: | © 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | COVID-19, biomarkers, clinical disease progression, disease prognosis, longitudinal profiling, machine learning, patient trajectories, physiological parameters, proteomics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Womens Cancer |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10131117 |
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