Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients.
Blood transcriptomics
COVID-19
Co-expression analysis
Drug repurposing
Granulocytes
Molecular disease phenotypes
Neutrophils
Stratification
Transcriptome
Journal
Genome medicine
ISSN: 1756-994X
Titre abrégé: Genome Med
Pays: England
ID NLM: 101475844
Informations de publication
Date de publication:
13 01 2021
13 01 2021
Historique:
received:
15
07
2020
accepted:
18
12
2020
entrez:
14
1
2021
pubmed:
15
1
2021
medline:
22
1
2021
Statut:
epublish
Résumé
The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.
Sections du résumé
BACKGROUND
The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.
METHODS
In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.
RESULTS
Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.
CONCLUSIONS
Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.
Identifiants
pubmed: 33441124
doi: 10.1186/s13073-020-00823-5
pii: 10.1186/s13073-020-00823-5
pmc: PMC7805430
doi:
Substances chimiques
Antiviral Agents
0
RNA
63231-63-0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7Investigateurs
Janine Altmüller
(J)
Angel Angelov
(A)
Robert Bals
(R)
Alexander Bartholomäus
(A)
Anke Becker
(A)
Michael Bitzer
(M)
Ezio Bonifacio
(E)
Peer Bork
(P)
Nicolas Casadei
(N)
Thomas Clavel
(T)
Maria Colome-Tatche
(M)
Andreas Diefenbach
(A)
Alexander Dilthey
(A)
Nicole Fischer
(N)
Konrad Förstner
(K)
Sören Franzenburg
(S)
Julia-Stefanie Frick
(JS)
Gisela Gabernet
(G)
Julien Gagneur
(J)
Tina Ganzenmüller
(T)
Siri Göpel
(S)
Alexander Goesmann
(A)
Torsten Hain
(T)
André Heimbach
(A)
Michael Hummel
(M)
Angelika Iftner
(A)
Thomas Iftner
(T)
Stefan Janssen
(S)
Jörn Kalinowski
(J)
René Kallies
(R)
Birte Kehr
(B)
Andreas Keller
(A)
Sarah Kim-Hellmuth
(S)
Christoph Klein
(C)
Oliver Kohlbacher
(O)
Karl Köhrer
(K)
Jan Korbel
(J)
Denise Kühnert
(D)
Ingo Kurth
(I)
Markus Landthaler
(M)
Yang Li
(Y)
Kerstin Ludwig
(K)
Oliwia Makarewicz
(O)
Manja Marz
(M)
Alice McHardy
(A)
Christian Mertes
(C)
Markus Nöthen
(M)
Peter Nürnberg
(P)
Uwe Ohler
(U)
Stephan Ossowski
(S)
Jörg Overmann
(J)
Klaus Pfeffer
(K)
Anna R Poetsch
(AR)
Alfred Pühler
(A)
Nikolaus Rajewsky
(N)
Markus Ralser
(M)
Olaf Rieß
(O)
Stephan Ripke
(S)
Ulisses Nunes da Rocha
(U)
Philip Rosenstiel
(P)
Antoine-Emmanuel Saliba
(AE)
Leif Erik Sander
(LE)
Birgit Sawitzki
(B)
Philipp Schiffer
(P)
Wulf Schneider
(W)
Eva-Christina Schulte
(EC)
Joachim L Schultze
(JL)
Alexander Sczyrba
(A)
Yogesh Singh
(Y)
Michael Sonnabend
(M)
Oliver Stegle
(O)
Jens Stoye
(J)
Fabian Theis
(F)
Janne Vehreschild
(J)
Jörg Vogel
(J)
Max von Kleist
(M)
Andreas Walker
(A)
Jörn Walter
(J)
Dagmar Wieczorek
(D)
Sylke Winkler
(S)
John Ziebuhr
(J)
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