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Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE161778 | GEO | 2020/12/11

REPOSITORIES: GEO

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Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories [sequencing]

Project description:In order to characterise the temporal dynamics of host response during COVID-19, we performed a longitudinal multi-omics study using a two centre German cohort of 13 patients. Bulk RNA was extracted from peripheral blood sampled at up to 5 time points per patient. At each sample point, a patient’s disease trajectory, “pseudotime”, was categorised according to clinical parameters. Both, whole transcriptome and B cell receptor sequence analysis was used to determine signatures specific to different disease trajectories. We identified coexpression modules that were associated with specific patterns across different COVID-19 disease trajectories. One module identified was related to failing interferon I response at the peak of disease severity. A second module showed biphasic upregulation of transcripts associated with erythropoiesis. Bulk BCR identified expansion of IgA+ and IgG+ cells. In sum, this study demonstrated distinct gene expression dynamics upon SARS-CoV-2 infection.

2020-12-11 | GSE161777 | GEO

Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories [methylation]

Project description:To help characterise the temporal dynamics of host response during COVID-19, we performed a longitudinal DNA methylation analysis in a cohort of 12 patients. DNA was extracted from peripheral blood sampled at up to 5 time points per patient. At each sample point, a patient’s disease trajectory, “pseudotime”, was categorised according to clinical parameters. DNA methylation profiling by Illumina Bead Arrays was performed on each sample. We found CpG sites hypomethylated during COVID-19 were highly enriched in cis of transcripts related to positive regulation of TNF secretion and innate immune signalling, indicating potential long-term regulation of immunological misfiring by epigenetic processes.

2020-12-11 | GSE161678 | GEO

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.

Project description:Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.

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Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories

Project description:Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories

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Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories [methylation]

Project description:Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories [methylation]

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Longitudinal multi-omics identifies responses of megakaryocytes, erythroid cells and plasmablasts as hallmarks of severe COVID-19 trajectories [sequencing]

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Maturation trajectories and transcriptional landscape of plasmablasts and autoreactive B cells in COVID-19.

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Project description:Although severe COVID-19 is often associated with elevated autoantibody titers, the underlying mechanism has been unclear. Here, we investigated repertoires and reactivities of immunoglobulins derived from blood plasmablasts (PBs) in COVID-19 patients. This uncovered robust clonal expansion of PBs secreting cardiolipin (CL)-reactive autoantibodies in humoral response to SARS-CoV-2. About half of the expanded CL-reactive clones were also reactive to SARS-CoV-2 antigens and derived from SARS-CoV-2-specific primary responses as well as seasonal coronavirus-reactive memory responses. One such clone, CoV1804, was reactive to both CL and viral nucleocapsid (N), and exhibited anti-nucleolar activity in human cells. Repertoire analysis identified antibodies sharing genetic features with CoV1804 in COVID-19 patient-derived immunoglobulins from our and other cohorts, thereby constituting a novel public antibody. These public autoantibodies had numerous mutations that enhanced anti-N reactivity. On the other hand, anti-CL reactivity fluctuated through somatic hypermutation, which instead resulted in the acquisition of additional self-reactivities, including anti-nucleolar activity in the progeny. Thus, potentially CL-reactive precursors may have developed multiple reactivities to different self-antigens through clonal expansion driven by viral antigens. Our results unraveled a unique process of autoantibody production during COVID-19 and provide novel insights into the origin of virus-induced autoantibodies.

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