Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

German COVID-19 Omics Initiative (DeCOI)(German Center for Neurodegenerative Diseases), Anna C. Aschenbrenner(University of Bonn), Maria Mouktaroudi(National and Kapodistrian University of Athens), Benjamin Krämer(University of Bonn), Marie Oestreich(University of Bonn), Nikolaos Antonakos(University of Bonn), Melanie Nuesch-Germano(University of Bonn), Konstantina Gkizeli(University of Bonn), Lorenzo Bonaguro(University of Bonn), Nico Reusch(University of Bonn), Kevin Baßler(University of Bonn), Maria Saridaki(University of Bonn), Rainer Knoll(University of Bonn), Tal Pecht(University of Bonn), Theodore S. Kapellos(University of Bonn), Sarandia Doulou(University of Bonn), Charlotte Kröger(University of Bonn), Miriam Herbert(University of Bonn), Lisa Holsten(University of Bonn), Arik Horne(University of Bonn), Ioanna D. Gemünd(University of Bonn), Νikoletta Ρovina(University of Bonn), Shobhit Agrawal(University of Bonn), K. Dahm(University of Bonn), Martina van Uelft(University of Bonn), Anna Drews(University of Bonn), Lena Lenkeit(University of Bonn), Niklas Bruse(Radboud University Nijmegen), Jelle Gerretsen(University of Bonn), Jannik Gierlich(University of Bonn), Matthias Becker(University of Bonn), Kristian Händler(University of Bonn), Michael Kraut(University of Bonn), Heidi Theis(University of Bonn), Simachew Mengiste(University of Bonn), Elena De Domenico(University of Bonn), Eva C. Schulte(University of Bonn), Lea Seep(University of Bonn), Jan Raabe(University Hospital Bonn), Christoph Hoffmeister(University Hospital Bonn), Michael ToVinh(University Hospital Bonn), Verena Keitel(University Hospital Bonn), Gereon Rieke(University Hospital Bonn), Valentina Talevi(University Hospital Bonn), Dirk Skowasch(University Hospital Bonn), N. Ahmad Aziz(University of Bonn), Peter Pickkers(Radboud University Nijmegen), Frank L. van de Veerdonk(Radboud University Nijmegen), Mihai G. Netea(University of Bonn), Joachim L. Schultze(University of Bonn), Matthijs Kox(Radboud University Nijmegen), Monique M.B. Breteler(University of Bonn), Jacob Nattermann(National and Kapodistrian University of Athens), Antonia Koutsoukou(National and Kapodistrian University of Athens), Evangelos J. Giamarellos‐Bourboulis(University of Bonn), Thomas Ulas(University of Bonn)
Genome Medicine
January 13, 2021
Cited by 277Open Access
Full Text

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.


Related Papers

No related papers found

Powered by citation graph analysis