Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients
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Abstract
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.
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A reverse transcriptomics analysis of patient blood immune cells flagged dexamethasone and other corticosteroids as possibly helpful for some severe cases.
“Reverse transcriptomics of blood immune cells derived from COVID-19 patients predicted the broadly anti-inflammatory drug dexamethasone and other corticosteroids as potentially beneficial for a subgroup of severely ill COVID-19 patients (Aschenbrenner et al., 2021).”
From COVID-19 and the human innate immune system (2021) · cites this paper as Aschenbrenner et al., 2021
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Research works printed but not linked: 1
- [101]Walsh EE, Frenck RW, Falsey AR, Kitchin N, Absalon J, Gurtman A, et al. Safety and immunogenicity of two RNA-based covid-19 vaccine candidates. N Engl J Med. 2020;383(25):2439–50. PMC7583697 33053279
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Swarm Learning for decentralized and confidential clinical machine learning
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Self-citationCOVID-19 and the human innate immune system
Schultze, J. L., & Aschenbrenner, A. C. (2021) · Cell · doi:10.1016/j.cell.2021.02.029 · Cited by 714 · see citing works
Self-citationLocal and systemic responses to SARS-CoV-2 infection in children and adults
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- Authors
- (DeCOI), G. C.-1. O. I., Aschenbrenner, A. C., Mouktaroudi, M., Krämer, B., Oestreich, M., Antonakos, N., Nuesch-Germano, M., Gkizeli, K., Bonaguro, L., Reusch, N., Baßler, K., Saridaki, M., Knoll, R., Pecht, T., Kapellos, T. S., Doulou, S., Kröger, C., Herbert, M., Holsten, L., Horne, A., Gemünd, I. D., Rovina, N., Agrawal, S., Dahm, K., van Uelft, M., Drews, A., Lenkeit, L., Bruse, N., Gerretsen, J., Gierlich, J., Becker, M., Händler, K., Kraut, M., Theis, H., Mengiste, S., De Domenico, E., Schulte-Schrepping, J., Seep, L., Raabe, J., Hoffmeister, C., ToVinh, M., Keitel, V., Rieke, G., Talevi, V., Skowasch, D., Aziz, N. A., Pickkers, P., van de Veerdonk, F. L., Netea, M. G., Schultze, J. L., Kox, M., Breteler, M. M. B., Nattermann, J., Koutsoukou, A., Giamarellos-Bourboulis, E. J., & Ulas, T.
- Affiliations
- German Center for Neurodegenerative Diseases (DE)
- University of Bonn (DE)
- National and Kapodistrian University of Athens (GR)
- Radboud University Nijmegen (NL)
- University Hospital Bonn (DE)
- Corresponding author
- Ulas, Thomas
- ORCID
- Aschenbrenner, Anna C.
- Mouktaroudi, Maria
- Krämer, Benjamin
- Oestreich, Marie
- Antonakos, Nikolaos
- Nuesch-Germano, Melanie
- Gkizeli, Konstantina
- Bonaguro, Lorenzo
- Reusch, Nico
- Baßler, Kevin
- Saridaki, Maria
- Knoll, Rainer
- Pecht, Tal
- Kapellos, Theodore S.
- Doulou, Sarandia
- Kröger, Charlotte
- Herbert, Miriam
- Holsten, Lisa
- Horne, Arik
- Gemünd, Ioanna D.
- Rovina, Nikoletta
- Dahm, Kilian
- Drews, Anna
- Lenkeit, Lena
- Bruse, Niklas
- Gerretsen, Jelle
- Becker, Matthias
- Händler, Kristian
- Theis, Heidi
- Mengiste, Simachew
- Seep, Lea
- Raabe, Jan
- Hoffmeister, Christoph
- ToVinh, Michael
- Keitel, Verena
- Rieke, Gereon
- Talevi, Valentina
- Skowasch, Dirk
- Aziz, N. Ahmad
- Pickkers, Peter
- Netea, Mihai G.
- Schultze, Joachim L.
- Kox, Matthijs
- Breteler, Monique M. B.
- Nattermann, Jacob
- Koutsoukou, Antonia
- Ulas, Thomas
- Venue
- Genome Medicine
- Published
- 2021-01-13
- Volume
- 13
- Issue
- 1
- Pages
- 7-7
- ISSN
- 1756-994X (ISSN-L)
- PMC
- PMC7805430
- OpenAlex
- W3120994437
- Cited by
- 255
- References
- 137
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 32 · 2023: 50 · 2022: 80 · 2021: 57 · 2020: 6
- FWCI
- 17.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
- Funders
- Deutsches Zentrum für Infektionsforschung
- Francis Crick Institute (10134)
- Deutsche Forschungsgemeinschaft (SFBTR57, SPP193 7, SFB 704, EXC 2151, GRK 2168, SCHU 950/8-1, 390873048)
- Bundesministerium für Bildung und Forschung (01EA1809C, EXC2151, SPP1937, 01EA1410C, 390873048)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (833247)
- National and Kapodistrian University of Athens
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Immunology and Microbiology › Immunology › Inflammation biomarkers and pathways
- Keywords
- COVID-19 pandemic, SARS-CoV-2, disease severity, neutrophil activation, whole blood transcriptome, granulocytes, immune response, gene expression signatures, patient stratification, drug target prediction, drug candidates, viral infection, inflammatory diseases
- MeSH terms
- COVID-19, COVID-19 Drug Treatment, Antiviral Agents, Humans, Neutrophils, Phenotype, RNA, Severity of Illness Index, Down-Regulation, Up-Regulation, Case-Control Studies, Sequence Analysis, RNA, Principal Component Analysis, Drug Repositioning, Transcriptome
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