1. A time-resolved proteomic and prognostic map of COVID-19
- Author
-
Vadim Demichev, Pinkus Tober-Lau, Oliver Lemke, Tatiana Nazarenko, Charlotte Thibeault, Harry Whitwell, Annika Röhl, Anja Freiwald, Lukasz Szyrwiel, Daniela Ludwig, Clara Correia-Melo, Simran Kaur Aulakh, Elisa T. Helbig, Paula Stubbemann, Lena J. Lippert, Nana-Maria Grüning, Oleg Blyuss, Spyros Vernardis, Matthew White, Christoph B. Messner, Michael Joannidis, Thomas Sonnweber, Sebastian J. Klein, Alex Pizzini, Yvonne Wohlfarter, Sabina Sahanic, Richard Hilbe, Benedikt Schaefer, Sonja Wagner, Mirja Mittermaier, Felix Machleidt, Carmen Garcia, Christoph Ruwwe-Glösenkamp, Tilman Lingscheid, Laure Bosquillon de Jarcy, Miriam S. 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 Lilley, Michael Mülleder, Leif Erik Sander, Markus Ralser, Florian Kurth, Malte Kleinschmidt, Katrin M. Heim, Belén Millet, Lil Meyer-Arndt, Ralf H. Hübner, Tim Andermann, Jan M. Doehn, Bastian Opitz, Birgit Sawitzki, Daniel Grund, Peter Radünzel, Mariana Schürmann, Thomas Zoller, 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 M. Kruse, Carolin Ferse, Roland Körner, Claudia Spies, Andreas Edel, Steffen Weber-Carstens, Alexander Krannich, Saskia Zvorc, Linna Li, Uwe Behrens, Sein Schmidt, Maria Rönnefarth, Chantip Dang-Heine, Robert Röhle, Emma Lieker, Lucie Kretzler, Isabelle Wirsching, Christian Wollboldt, Yinan Wu, Georg Schwanitz, David Hillus, Stefanie Kasper, Nadine Olk, Alexandra Horn, Dana Briesemeister, Denise Treue, Michael Hummel, Victor M. Corman, Christian Drosten, Christof von Kalle, Ralser, Markus [0000-0001-9535-7413], and Apollo - University of Cambridge Repository
- Subjects
Proteomics ,Patient Trajectories ,Histology ,Proteome ,Disease Prognosis ,Clinical Disease Progression ,Inflammation ,Disease ,0601 Biochemistry and Cell Biology ,Bioinformatics ,Asymptomatic ,Article ,Pathology and Forensic Medicine ,Blood cell ,Machine Learning ,03 medical and health sciences ,0302 clinical medicine ,Humans ,Medicine ,030304 developmental biology ,0303 health sciences ,SARS-CoV-2 ,business.industry ,Age Factors ,Cell Biology ,Prognosis ,Blood Cell Count ,Enzyme Activation ,Longitudinal Profiling ,medicine.anatomical_structure ,Infectious disease (medical specialty) ,Cohort ,Disease Progression ,Blood Gas Analysis ,medicine.symptom ,business ,Covid-19 ,Physiological parameters ,030217 neurology & neurosurgery ,Biomarkers - 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., Graphical abstract, Demichev, Tober-Lau et al., present a time-resolved molecular map of the COVID-19, measuring plasma proteomes of patients with COVID-19 along with an extensive panel of clinical diagnostic parameters at 687-time points. They describe the specificity and dynamics, as well as the predictive and prognostic power of the molecular signatures in COVID-19.
- Published
- 2021
- Full Text
- View/download PDF