Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

ABSTRACT: Data Access Committee EGAC00001002480

PROVIDER: EGAC00001002480 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

Project description:Data Access Committee EGAC00001003435

| EGAC00001003435 | EGA

COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

Project description:Through thorough exclusion criteria and deep phenotypic characterisation for a Madrid-based population we intend to find enrichment of gene mutations associated to severity. In addition we will look for statistically overrepresented annotation of particular phenotypes (a controlled vocabulary specifically developed for this project) that associate them to affected genes in our patient sample.

| EGAS00001005931 | EGA

Proteomic blood profiling in mild, severe and critical COVID-19 patients

Project description: Not available

| S-BSST416 | biostudies-other

Lung transplantation for patients with severe COVID-19

Project description:Lung transplantation can potentially be a life-saving treatment for patients with non-resolving COVID-19-associated respiratory failure. Concerns limiting transplant include recurrence of SARS-CoV-2 infection in the allograft, technical challenges imposed by viral-mediated injury to the native lung, and potential risk for allograft infection by pathogens associated with ventilator-associated pneumonia in the native lung. Most importantly, the native lung might recover, resulting in long-term outcomes preferable to transplant. Here, we report results of the first successful lung transplantation procedures in patients with non-resolving COVID-19-associated respiratory failure in the United States. We performed sm-FISH to detect both positive and negative strands of SARS-CoV-2 RNA in the explanted lung tissue, extracellular matrix imaging using SHIELD tissue clearance, and single cell RNA-Seq on explant and warm post-mortem lung biopsies from patients who died from severe COVID-19 pneumonia. Lungs from patients with prolonged COVID-19 were free of virus but pathology showed extensive evidence of injury and fibrosis which resembled end-stage pulmonary fibrosis. We used a machine learning approach to project single cell RNA-Seq data from patients with late stage COVID-19 onto a single cell atlas of pulmonary fibrosis, revealing similarities across cell lineages. There was no recurrence of SARS-CoV-2 or pathogens associated with pre-transplant ventilator associated pneumonias following transplantation. Our findings suggest that some patients with severe COVID-19 develop fibrotic lung disease for which lung transplantation is the only option for survival.

2020-10-28 | GSE158127 | GEO

Human gut microbiota, COVID-19 patients with mild or severe symptoms.

Project description:Analysis of COVID-19 hospitalized patients, with different kind of symptoms, by human rectal swabs collection and 16S sequencing approach.

2022-09-22 | E-MTAB-12236 | biostudies-arrayexpress

Case series of the first three severe COVID-19 patients treated with the secretome of hypoxia-mesenchymal stem cells in Indonesia

Project description: Not available

| S-BSST677 | biostudies-other

Characterisation of the blood RNA host response underpinning severity in COVID-19 patients

Project description:Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA-Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups.

2022-07-19 | E-MTAB-10926 | biostudies-arrayexpress

Cohort survey of healthcare workers with COVID-19 infection

Project description: Not available

| S-BSST563 | biostudies-other

Host-viral infection maps at single-cell resolution reveal signatures of severe COVID-19 patients

Project description:Viruses are a constant threat to global health as shown by the current COVID-19 pandemic. Currently, lack of data underlying the biology of the interaction of the human host with SARS-CoV-2 virus is limiting effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped scRNA-seq data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the ability of Viral-Track to detect various viruses from multiple models of infection. Applying Viral-Track to Bronchoalveloar Lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the SARS-CoV-2 virus on the immune system of severe patients as compared to mild cases. The SARS-CoV-2 infection is mainly restricted to epithelial and macrophage subsets. In addition, Viral-Track detects in one of the severe patients an unexpected co-infection of the human MetaPneumoVirus, present mainly in monocytes and strongly dampening their type-I IFN-signaling.

2023-06-01 | GSE148881 | GEO