Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identification of immune correlates of fatal outcomes in critically ill COVID-19 patients

ABSTRACT: Identification of immune correlates of fatal outcomes in critically ill COVID-19 patients

PROVIDER: PRJNA738888 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Identification of immune correlates of fatal outcomes in critically ill COVID-19 patients

Project description:Single-cell RNA-sequencing reveals a shift from focused IFN alpha-driven signals in COVID-19 ICU patients who survive to broad pro-inflammatory responses in fatal COVID-19 – a feature not observed in severe influenza. We conclude that fatal COVID-19 infection is driven by uncoordinated inflammatory responses that drive a hierarchy of T cell activation, elements of which can serve as prognostic indicators and potential targets for immune intervention.

2021-06-18 | GSE178404 | GEO

Transcriptomic clustering of critically-ill COVID-19 patients

Project description:Transcriptomic clustering of critically-ill COVID-19 patients

| PRJNA809558 | ENA

The impact of tobacco smoke exposure and environmental exposures on the pulmonary microbiome of critically ill children

Project description:This project evaluates the effects of tobacco smoke exposure (TSE) on the pediatric lung microbiome in critically ill children. The impact of TSE on the airway microbiome of critically ill, mechanically ventilated pediatric patients will be determined by through clinical outcomes and analysis of urinary and plasma metabolomes to identify other environmental exposures contributing to the alteration of the pediatric microbiome.

2019-06-25 | ST001262 | MetabolomicsWorkbench

Identification of immune correlates of fatal outcomes in critically ill COVID-19 patients.

Project description: Not available

| S-EPMC8445447 | biostudies-literature

Transcriptomic clustering of critically-ill COVID-19 patients [miRNA-Seq]

Project description:Transcriptomic clustering of critically-ill COVID-19 patients [miRNA-Seq]

| PRJNA809566 | ENA

Microarray Analysis of MicroRNA Expression in Peripheral Blood Mononuclear Cells of critically ill Patients with Influenza A (H1N1)

Project description:To determine whether differential expression of cellular microRNAs plays a role in the host response to Influenza A (H1N1) infection, we have employed the Agilent miRNA microarray (V3) as a discovery platform to identify microRNAs between the critically ill Patients with Influenza A (H1N1) and the healthy controls. Five critically ill patients with a diagnosis of 2009 Inflluenza A (H1N1) and three healthy controls were included in the study. The Peripheral Blood Mononuclear Cells (PBMCs) were isolated and total RNA was extracted respectively.

2012-12-28 | E-GEOD-24956 | biostudies-arrayexpress

Transcriptomic clustering of critically-ill COVID-19 patients [Day 1-RNA-Seq]

Project description:Transcriptomic clustering of critically-ill COVID-19 patients [Day 1-RNA-Seq]

| PRJNA809356 | ENA

Transcriptomic clustering of critically-ill COVID-19 patients [Day 4 RNAseq]

Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.

2023-04-29 | GSE206264 | GEO

Transcriptomic clustering of critically-ill COVID-19 patients [Day 1-RNA-Seq]

2022-02-28 | GSE197204 | GEO

Transcriptomic clustering of critically-ill COVID-19 patients [Day 1-miRNA-Seq]

2022-02-28 | GSE197258 | GEO