A time-resolved proteomic and prognostic map of COVID-19
Vadim Demichev, Pinkus Tober‐Lau, Oliver Lemke, Tatiana Nazarenko, Charlotte Thibeault, Harry J. Whitwell, Annika Röhl, Anja Freiwald, Łukasz Szyrwiel, Daniela Ludwig, Clara Correia‐Melo, Simran Kaur Aulakh, Elisa T. Helbig, Paula Stubbemann, Lena J. Lippert, Nana‐Maria Grüning, Oleg Blyuss, Spyros I. Vernardis, Matthew White, Christoph B. Messner, Michael Joannidis, Thomas Sonnweber, Sebastian Klein, Alex Pizzini, Yvonne Wohlfarter, Sabina Sahanic, Richard Hilbe, Benedikt Schaefer, Sonja Wagner, Mirja Mittermaier, Felix Machleidt, Carmen García, Christoph Ruwwe‐Glösenkamp, Tilman Lingscheid, Laure Bosquillon de Jarcy, Miriam Stegemann, Moritz Pfeiffer, Linda Jürgens, Sophy Denker, Daniel Zickler, Philipp Enghard, Aleksej Zelezniak, Archie Campbell, Caroline Hayward, David J. Porteous, Riccardo E. Marioni, Alexander Uhrig, Holger Müller-Redetzky, Heinz Zoller, Judith Löffler‐Ragg, Markus A. Keller, Ivan Tancevski, John F. Timms, Alexey Zaikin, Stefan Hippenstiel, Michael Ramharter, Martin Witzenrath, Norbert Suttorp, Kathryn S. Lilley, Michael Mülleder, Leif Erik Sander, Malte Kleinschmidt, Kathrin Heim, Belén Millet, Lil Meyer‐Arndt, Ralf‐Harto Hübner, Tim Andermann, Jan M. Doehn, Bastian Opitz, Birgit Sawitzki, Daniel Grund, Peter Radünzel, Mariana Schürmann, Thomas Zöller, Florian Alius, Philipp Knape, Astrid Breitbart, Yaosi Li, Felix Bremer, Panagiotis Pergantis, Dirk Schürmann, Bettina Temmesfeld‐Wollbrück, Daniel Wendisch, Sophia Brumhard, Sascha S. Haenel, Claudia Conrad, Philipp Georg, Kai‐Uwe Eckardt, Lukas Lehner, Jan Matthias Kruse, Carolin Ferse, Roland Körner, Claudia Spies, Andreas Edel, Steffen Weber‐Carstens, Alexander Krannich, Saskia Zvorc, Linna Li, Uwe D. Behrens, Sein Schmidt
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.