A time-resolved proteomic and prognostic map of COVID-19.
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.
['Demichev|Vadim|V|', 'Tober-Lau|Pinkus|P|', 'Lemke|Oliver|O|', 'Nazarenko|Tatiana|T|', 'Thibeault|Charlotte|C|', 'Whitwell|Harry|H|', 'Röhl|Annika|A|', 'Freiwald|Anja|A|', 'Szyrwiel|Lukasz|L|', 'Ludwig|Daniela|D|', 'Correia-Melo|Clara|C|', 'Aulakh|Simran Kaur|SK|', 'Helbig|Elisa T|ET|', 'Stubbemann|Paula|P|', 'Lippert|Lena J|LJ|', 'Grüning|Nana-Maria|NM|', 'Blyuss|Oleg|O|', 'Vernardis|Spyros|S|', 'White|Matthew|M|', 'Messner|Christoph B|CB|', 'Joannidis|Michael|M|', 'Sonnweber|Thomas|T|', 'Klein|Sebastian J|SJ|', 'Pizzini|Alex|A|', 'Wohlfarter|Yvonne|Y|', 'Sahanic|Sabina|S|', 'Hilbe|Richard|R|', 'Schaefer|Benedikt|B|', 'Wagner|Sonja|S|', 'Mittermaier|Mirja|M|', 'Machleidt|Felix|F|', 'Garcia|Carmen|C|', 'Ruwwe-Glösenkamp|Christoph|C|', 'Lingscheid|Tilman|T|', 'Bosquillon de Jarcy|Laure|L|', 'Stegemann|Miriam S|MS|', 'Pfeiffer|Moritz|M|', 'Jürgens|Linda|L|', 'Denker|Sophy|S|', 'Zickler|Daniel|D|', 'Enghard|Philipp|P|', 'Zelezniak|Aleksej|A|', 'Campbell|Archie|A|', 'Hayward|Caroline|C|', 'Porteous|David J|DJ|', 'Marioni|Riccardo E|RE|', 'Uhrig|Alexander|A|', 'Müller-Redetzky|Holger|H|', 'Zoller|Heinz|H|', 'Löffler-Ragg|Judith|J|', 'Keller|Markus A|MA|', 'Tancevski|Ivan|I|', 'Timms|John F|JF|', 'Zaikin|Alexey|A|', 'Hippenstiel|Stefan|S|', 'Ramharter|Michael|M|', 'Witzenrath|Martin|M|', 'Suttorp|Norbert|N|', 'Lilley|Kathryn|K|', 'Mülleder|Michael|M|', 'Sander|Leif Erik|LE|', '|||', 'Ralser|Markus|M|', 'Kurth|Florian|F|']
D000367:Age Factors D015415:Biomarkers D001772:Blood Cell Count D001784:Blood Gas Analysis D000086382:COVID-19 D018450:Disease Progression D004789:Enzyme Activation D006801:Humans D007249:Inflammation D000069550:Machine Learning D011379:Prognosis D020543:Proteome D040901:Proteomics D000086402:SARS-CoV-2
proteomics COVID-19 machine learning biomarkers clinical disease progression disease prognosis longitudinal profiling patient trajectories physiological parameters