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  4. Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients
 
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2023
Journal Article
Title

Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients

Abstract
SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Previous studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited.We addressed the gap of existing knowledge with regard to a differentiated understanding of disease dynamics in SARS-CoV-2 infection while specifically considering disease stage and severity. We biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of the individualized disease phase assignment, proteome analysis revealed a severity dependent general type-2-centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response characterizing severe disease was successfully validated in a second cohort. Together with the regulation of proteins related to SARS-CoV-2-specific symptoms identified by proteome screening, we not only confirmed results from previous studies but provide novel information for biomarker and therapy development.
Author(s)
Bauer, Alina
Helmholtz Zentrum München, Computational Health Department
Pachl, Elisabeth
Helmholtz Zentrum München, Computational Health Department
Hellmuth, Johannes C.
Ludwig-Maximilians-Universität München, University Hospital, Department of Medicine III
Kneidinger, Nikolaus
Helmholtz Zentrum Muenchen, Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive
Motaharehsadat, Heydarian
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Frankenberger, Marion
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Stubbe, Hans C.
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Ryffel, Bernhard
CNRS-University of Orleans and Artimmune, UMR 7355, Laboratory of Experimental and Molecular Immunology and Neurogenetics (INEM)
Petrera, Agnese
Helmholtz Zentrum München, Metabolomics and Proteomics Core
Hauck, Stefanie M.
Helmholtz Zentrum München, Metabolomics and Proteomics Core
Behr, Jürgen
Helmholtz Zentrum Muenchen, Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive
Kaiser, Rainer
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Scherer, Clemens
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Deng, Li
Helmholtz Zentrum München, Computational Health Department
Teupser, Daniel
Ludwig-Maximilians-Universität München, University Hospital, Institute of Laboratory Medicine
Ahmidi, Narges
Fraunhofer-Institut für Kognitive Systeme IKS  
Muenchhoff, Maximilian
Ludwig-Maximilians-Universität München, University Hospital, COVID-19 Registry of the LMU Munich (CORKUM)
Schubert, Benjamin
Helmholtz Zentrum München, Computational Health Department
Hilgendorff, Anne
Helmholtz Zentrum Muenchen, Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive
Journal
Biochimica et biophysica acta. Molecular basis of disease  
Project(s)
Klinische und Omic-basierte Analyse der Trajektorie für COVID-19-Infektion und Genesung  
IKS-Ausbauprojekt  
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie
Open Access
DOI
10.1016/j.bbadis.2022.166592
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie
Keyword(s)
  • biomarker

  • COVID-19

  • immune response

  • NETosis

  • proteomics

  • high-risk patient

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