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1.
Cell ; 2021 Dec 28.
Article in English | MEDLINE | ID: covidwho-1588146

ABSTRACT

Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathology, and it remains unclear whether T cells contribute to disease pathology. Here, we combined single-cell transcriptomics and single-cell proteomics with mechanistic studies to assess pathogenic T cell functions and inducing signals. We identified highly activated CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune-complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Increased generation of C3a in severe COVID-19 induced activated CD16+ cytotoxic T cells. Proportions of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a were associated with fatal outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.

2.
Immunity ; 54(11): 2650-2669.e14, 2021 11 09.
Article in English | MEDLINE | ID: covidwho-1442406

ABSTRACT

Longitudinal analyses of the innate immune system, including the earliest time points, are essential to understand the immunopathogenesis and clinical course of coronavirus disease (COVID-19). Here, we performed a detailed characterization of natural killer (NK) cells in 205 patients (403 samples; days 2 to 41 after symptom onset) from four independent cohorts using single-cell transcriptomics and proteomics together with functional studies. We found elevated interferon (IFN)-α plasma levels in early severe COVD-19 alongside increased NK cell expression of IFN-stimulated genes (ISGs) and genes involved in IFN-α signaling, while upregulation of tumor necrosis factor (TNF)-induced genes was observed in moderate diseases. NK cells exert anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) activity but are functionally impaired in severe COVID-19. Further, NK cell dysfunction may be relevant for the development of fibrotic lung disease in severe COVID-19, as NK cells exhibited impaired anti-fibrotic activity. Our study indicates preferential IFN-α and TNF responses in severe and moderate COVID-19, respectively, and associates a prolonged IFN-α-induced NK cell response with poorer disease outcome.


Subject(s)
COVID-19/immunology , Interferon-alpha/immunology , Killer Cells, Natural/immunology , SARS-CoV-2/immunology , Tumor Necrosis Factor-alpha/metabolism , Base Sequence , Humans , Immunity, Innate/immunology , Inflammation/immunology , Interferon-alpha/blood , Pulmonary Fibrosis/pathology , RNA-Seq , Severity of Illness Index , Transcriptome/genetics , United Kingdom , United States
3.
Nature ; 594(7862): 265-270, 2021 06.
Article in English | MEDLINE | ID: covidwho-1246377

ABSTRACT

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.


Subject(s)
Blockchain , Clinical Decision-Making/methods , Confidentiality , Datasets as Topic , Machine Learning , Precision Medicine/methods , COVID-19/diagnosis , COVID-19/epidemiology , Disease Outbreaks , Female , Humans , Leukemia/diagnosis , Leukemia/pathology , Leukocytes/pathology , Lung Diseases/diagnosis , Machine Learning/trends , Male , Software , Tuberculosis/diagnosis
4.
Front Immunol ; 12: 652470, 2021.
Article in English | MEDLINE | ID: covidwho-1204206

ABSTRACT

Strong evidence has been accumulated since the beginning of the COVID-19 pandemic that neutrophils play an important role in the pathophysiology, particularly in those with severe disease courses. While originally considered to be a rather homogeneous cell type, recent attention to neutrophils has uncovered their fascinating transcriptional and functional diversity as well as their developmental trajectories. These new findings are important to better understand the many facets of neutrophil involvement not only in COVID-19 but also many other acute or chronic inflammatory diseases, both communicable and non-communicable. Here, we 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 COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/immunology , Neutrophils/immunology , Pandemics , SARS-CoV-2/immunology , Humans
5.
Front Immunol ; 12: 652470, 2021.
Article in English | MEDLINE | ID: covidwho-1177980

ABSTRACT

Strong evidence has been accumulated since the beginning of the COVID-19 pandemic that neutrophils play an important role in the pathophysiology, particularly in those with severe disease courses. While originally considered to be a rather homogeneous cell type, recent attention to neutrophils has uncovered their fascinating transcriptional and functional diversity as well as their developmental trajectories. These new findings are important to better understand the many facets of neutrophil involvement not only in COVID-19 but also many other acute or chronic inflammatory diseases, both communicable and non-communicable. Here, we 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 COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/immunology , Neutrophils/immunology , Pandemics , SARS-CoV-2/immunology , Humans
6.
Genome Med ; 13(1): 7, 2021 01 13.
Article in English | MEDLINE | ID: covidwho-1027902

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.


Subject(s)
COVID-19/pathology , Neutrophils/metabolism , Transcriptome , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Case-Control Studies , Down-Regulation , Drug Repositioning , Humans , Neutrophils/cytology , Neutrophils/immunology , Phenotype , Principal Component Analysis , RNA/blood , RNA/chemistry , RNA/metabolism , Sequence Analysis, RNA , Severity of Illness Index , Up-Regulation
7.
STAR Protoc ; 1(3): 100233, 2020 Dec 18.
Article in English | MEDLINE | ID: covidwho-978460

ABSTRACT

In December 2019, a new coronavirus, SARS-CoV-2, which causes the respiratory illness that led to the COVID-19 pandemic, was reported. In the face of such a new pathogen, special precautions must be taken to examine potentially infectious materials due to the lack of knowledge on disease transmissibility, infectivity, and molecular pathogenicity. Here, we present a complete and safe workflow for performing scRNA-seq experiments on blood samples of infected patients from cell isolation to data analysis using the micro-well based BD Rhapsody platform. For complete information on the use and execution of this protocol, please refer to Schulte-Schrepping et al. (2020).

8.
Cell ; 182(6): 1419-1440.e23, 2020 09 17.
Article in English | MEDLINE | ID: covidwho-694631

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.


Subject(s)
Coronavirus Infections/immunology , Myeloid Cells/immunology , Myelopoiesis , Pneumonia, Viral/immunology , Adult , Aged , CD11 Antigens/genetics , CD11 Antigens/metabolism , COVID-19 , Cells, Cultured , Coronavirus Infections/blood , Coronavirus Infections/pathology , Female , HLA-DR Antigens/genetics , HLA-DR Antigens/metabolism , Humans , Male , Middle Aged , Myeloid Cells/cytology , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/pathology , Proteome/genetics , Proteome/metabolism , Proteomics , Single-Cell Analysis
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