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Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia

Authors :
Mirjam Lutz
Ekaterina Friebel
Roland S. Liblau
Antoine Roquilly
Guillaume Martin-Blondel
Manfred Claassen
Benjamin Gaborit
Manuel Kauffmann
Sepideh Babaei
Donatella De Feo
Nicolás Gonzalo Núñez
Nisar P. Malek
Chiara Alberti
Sally Al-Hajj
Susanne Unger
Siri Goepel
Ikram Ayoub
Helene A. Häberle
Jakob Nilsson
Nicole Puertas Jurado
Peter Rosenberger
Stefanie Kreutmair
Sinduya Krishnarajah
Burkhard Becher
Michael Bitzer
Florian Ingelfinger
Pistre, Karine
Universität Zürich [Zürich] = University of Zurich (UZH)
German Cancer Consortium [Heidelberg] (DKTK)
German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ)
Institute of Experimental Immunology [Zurich]
Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen
Service d'anesthésie et réanimation chirurgicale [Nantes]
Hôtel-Dieu-Centre hospitalier universitaire de Nantes (CHU Nantes)
German Center for Infectious Research - partner site Tübingen [Tübingen, Allemagne] (DZIF)
Institut Toulousain des Maladies Infectieuses et Inflammatoires (Infinity)
Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
University hospital of Zurich [Zurich]
University of Zurich
Becher, Burkhard
Source :
Immunity, Immunity, 2021, 54 (7), pp.1578-1593.e5. ⟨10.1016/j.immuni.2021.05.002⟩
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

Immune profiling of COVID-19 patients has identified numerous alterations in both innate and adaptive immunity. However, whether those changes are specific to SARS-CoV-2 or driven by a general inflammatory response shared across severely ill pneumonia patients remains unknown. Here, we compared the immune profile of severe COVID-19 with non-SARS-CoV-2 pneumonia ICU patients using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided analysis. COVID-19 and non-SARS-CoV-2 pneumonia both showed increased emergency myelopoiesis and displayed features of adaptive immune paralysis. However, pathological immune signatures suggestive of T cell exhaustion were exclusive to COVID-19. The integration of single-cell profiling with a predicted binding capacity of SARS-CoV-2-petides to the patients’ HLA profile further linked the COVID-19 immunopathology to impaired virus recognition. Towards clinical translation, circulating NKT cell frequency was identified as a predictive biomarker for patient outcome. Our comparative immune map serves to delineate treatment strategies to interfere with the immunopathologic cascade exclusive to severe COVID-19.<br />Graphical Abstract<br />The pathogen-specific immune alterations in severe COVID-19 remain unknown. Using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided comparison of COVID-19 vs. non-SARS-CoV-2-pneumonia patient samples, Kreutmair et al. identify T and NK cell immune signatures specific to SARS-CoV-2. They furthermore reveal NKT cell frequency as a predictive biomarker for COVID-19 outcome prediction and link impaired virus recognition to HLA genetics.

Subjects

Subjects :
0301 basic medicine
CD4-Positive T-Lymphocytes
Male
MESH: CD4-Positive T-Lymphocytes / immunology
MESH: Biomarkers / blood
[SDV]Life Sciences [q-bio]
MESH: HLA Antigens / genetics
MESH: COVID-19 / pathology
10263 Institute of Experimental Immunology
Hospital-acquired pneumonia
Severity of Illness Index
0302 clinical medicine
MESH: Pneumonia / immunology
HLA Antigens
T-Lymphocyte Subsets
peptide binding strength
Immunopathology
Immunology and Allergy
MESH: Pneumonia / pathology
MESH: T-Lymphocyte Subsets / metabolism
COVID
high-dimensional single cell analysis
Antigen Presentation
MESH: Middle Aged
spectral flow cytometry
immune profiling
MESH: SARS-CoV-2 / immunology
Middle Aged
Acquired immune system
MESH: HLA Antigens / immunology
3. Good health
[SDV] Life Sciences [q-bio]
Infectious Diseases
HLA typing
030220 oncology & carcinogenesis
MESH: T-Lymphocyte Subsets / immunology
2723 Immunology and Allergy
MESH: SARS-CoV-2 / pathogenicity
Biomarker (medicine)
Cytokines
biomarker
[SDV.IMM]Life Sciences [q-bio]/Immunology
Female
MESH: Immunity, Innate
Angiotensin-Converting Enzyme 2
Adult
[SDV.IMM] Life Sciences [q-bio]/Immunology
MESH: Immunophenotyping
Immunology
Antigen presentation
610 Medicine & health
Human leukocyte antigen
Biology
Article
03 medical and health sciences
MESH: Natural Killer T-Cells / immunology
Immune system
immunophenotyping
MESH: CD4-Positive T-Lymphocytes / metabolism
MESH: Angiotensin-Converting Enzyme 2 / metabolism
MESH: Severity of Illness Index
medicine
Humans
2403 Immunology
SARS-CoV-2
COVID-19
GM-CSF
2725 Infectious Diseases
Pneumonia
biochemical phenomena, metabolism, and nutrition
medicine.disease
MESH: COVID-19 / immunology
Immunity, Innate
030104 developmental biology
MESH: Antigen Presentation
10033 Clinic for Immunology
570 Life sciences
biology
Natural Killer T-Cells
Biomarkers

Details

Language :
English
ISSN :
10747613
Database :
OpenAIRE
Journal :
Immunity, Immunity, 2021, 54 (7), pp.1578-1593.e5. ⟨10.1016/j.immuni.2021.05.002⟩
Accession number :
edsair.doi.dedup.....7a70271704dd1c2b9bc69005e3664513
Full Text :
https://doi.org/10.1016/j.immuni.2021.05.002