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Open AccessJournal ArticleDOI

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

TLDR
This article 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.
Abstract
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.

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Journal ArticleDOI

COVID-19 and the human innate immune system.

TL;DR: In this article, a conceptual framework for the interaction of the human innate immune system with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was provided to link the clinical observations with experimental findings that have been made during the first year of the pandemic.
Journal ArticleDOI

Swarm Learning for decentralized and confidential clinical machine learning.

TL;DR: Wang et al. as mentioned in this paper proposed Swarm Learning, a decentralized machine learning approach that unifies edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator.
Journal ArticleDOI

Neutrophils in COVID-19.

TL;DR: In this article, the authors highlight the observed immune deviation of neutrophils in COVID-19 and summarize several promising therapeutic attempts to precisely target neutrophILS and their reactivity in patients with COVID19.
Journal ArticleDOI

Monocytes and Macrophages in COVID-19.

TL;DR: In this article, the authors outline current knowledge on monocytes and macrophages in homeostasis and viral infections and summarize concepts and key findings on their role in COVID-19.
References
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Journal ArticleDOI

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