A time-resolved proteomic and prognostic map of COVID-19More about Open Access at the Crick
Authors listVadim Demichev Pinkus Tober-Lau Oliver Lemke Tatiana Nazarenko Charlotte Thibeault Harry Whitwell Annika Röhl Anja Freiwald Lukasz Szyrwiel Daniela Ludwig Clara Correia-Melo Simran Aulakh Elisa T Helbig Paula Stubbemann Lena J Lippert Nana-Maria Grüning Oleg Blyuss Spyros Vernardis Matthew White Christoph 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 PA-COVID-19 Study group Markus Ralser Florian Kurth
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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.
Journal Cell systems
Issue number 8