Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE161678 | GEO | 2020/12/11

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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

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

| PRJNA679334 | ENA

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

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-12-11 | GSE161778 | GEO

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]

| PRJNA679336 | ENA

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

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

| PRJNA679331 | ENA

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.

| S-EPMC7689306 | biostudies-literature

Clonal landscape of autoantibody-secreting plasmablasts in COVID-19 patients

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.

2024-09-11 | GSE233522 | GEO

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

Project description:Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design and personalized medicine approaches for COVID-19.

2022-02-22 | PXD023175 | Pride

Linear epitope-specific IgG responses to SARS-CoV-2 and related human coronaviruses in human COVID-19 convalescent sera

Project description:The on-going COVID-19 pandemic requires a deeper understanding of the long-term antibody responses that persist following SARS-CoV-2 infection. To that end, we determined epitope-specific IgG antibody responses in COVID-19 convalescent sera collected at 5 months post-diagnosis and compared that to sera from naïve individuals. Each serum sample was reacted with a high-density peptide microarray representing the complete proteome of SARS-CoV-2 as 15 mer peptides with 11 amino acid overlap and homologs of spike glycoprotein, nucleoprotein, membrane protein, and envelope small membrane protein from related human coronaviruses. Binding signatures were compared between COVID-19 convalescent patients and naïve individuals using the web service tool EPIphany.

2022-02-05 | E-MTAB-10740 | biostudies-arrayexpress

Genome-wide DNA methylation analysis of COVID-19 severity

Project description:Genome-wide DNA methylation analysis of COVID-19 severity using the Illumina HumanMethylationEPIC microarray platform to analyze over 850,000 methylation sites, comparing COVID-19 patients with patients presenting with respiratory symptoms, but negative for COVID-19, using whole blood tissue.

2021-05-31 | GSE174818 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data