Dynamics of gene expression profiling by RNA-Seq and identification of high-risk patients for severe COVID-19 [RNA-Seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA877667 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Although most SARS-CoV-2-infected individuals experience mild COVID-19, some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation. To identify factors driving severe progression of COVID-19, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from healthy donors, patients with mild or severe COVID-19, and patients with severe influenza. Patients with COVID-19 exhibited hyper-inflammatory signatures across all types of cells among PBMCs, particularly upregulation of the TNF/IL-1beta-driven inflammatory response as compared to severe influenza. In classical monocytes from patients with severe COVID-19, type I IFN response co-existed with the TNF/IL-1beta-driven inflammation, and this was not seen in patients with milder COVID-19 infection. Based on this, we propose that the type I IFN response exacerbates inflammation in patients with severe COVID-19 infection.
2020-07-06 | GSE149689 | GEO
Project description:Individuals infected with the SARS-CoV-2 virus present with a wide variety of phenotypes ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe COVID-19 phenotype. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the severe COVID-19 phenotype. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform an locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify 4 introgressed alleles that are strong functional candidates for driving the association between this locus and the severe COVID-19. These variants likely drive the locus’ impact on severity by putatively modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.
2023-02-09 | GSE176233 | GEO
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel viral pathogen that causes a clinical disease called coronavirus disease 2019 (COVID-19). Approximately 20% of infected patients experience a severe manifestation of the disease, causing bilateral pneumonia and acute respiratory distress syndrome. Severe COVID-19 patients also have a pronounced coagulopathy with approximately 30% of patients experiencing thromboembolic complications. However, the cellular etiology driving the coagulopathy remains unknown. Here, we explore whether the prominent neutrophilia seen in severe COVID-19 patients contributes to inflammation-associated coagulation. We found in severe patients the emergence of a CD16Int low-density inflammatory band (LDIB) neutrophil population that trends over time with changes in disease status. These cells demonstrated spontaneous neutrophil extracellular trap (NET) formation, higher phagocytic capacity, enhanced cytokine production, and associated clinically with D-dimer, ferritin, and systemic IL-6 and TNF-α levels. Strikingly, LDIB neutrophils are the major immune cells within the bronchoalveolar lavage (BAL) fluid with increased CXCR3 and loss of CD44 and CD38 expression. We conclude that the LDIB subset contributes to COVID- 19-associated coagulopathy (CAC) and systemic inflammation and could be used as an adjunct clinical marker to monitor disease status and progression. Identifying patients who are trending towards LDIB crisis and implementing early, appropriate treatment could improve all-cause mortality rates for severe COVID-19 patients.
2021-07-20 | GSE154311 | GEO
Project description:Manuscript describes the daily dynamics of transcriptional responses in whole blood, from acute to convalescent phase, in severe and non-severe COVID-19 patients.
2020-12-31 | E-MTAB-9721 | biostudies-arrayexpress
Project description:The clinical course of Coronavirus disease 2019 (COVID-19) displays a wide variability, ranging from completely asymptomatic forms to diseases associated with severe clinical outcomes. To reduce the incidence COVID-19 severe outcomes, innovative molecular biomarkers are needed to improve the stratification of patients at the highest risk of mortality and to better customize therapeutic strategies. MicroRNAs associated with COVID-19 outcomes could allow quantifying the risk of severe outcomes and developing models for predicting outcomes, thus helping to customize the most aggressive therapeutic strategies for each patient. Here, we analyzed the circulating miRNA profiles in a set of 12 hospitalized patients with severe COVID-19, with the aim to identify miRNAs associated with in-hospital mortality.
2021-11-24 | GSE189506 | GEO
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
Project description:Many clinical risk factors for severe COVID-19, such as diabetes, hypertension, and high body mass index have been reported. However, searching for additional risk factors should be continued to predict the progression of severe COVID-19 more accurately. We suppose that clonal hematopoiesis of indeterminate potential (CHIP) can also be regarded as one of risk factors. To identify the influence of CHIP in COVID-19 pathogenesis, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from severe COVID-19 patient with CHIP and integrate the data with other published COVID-19 scRNA seq data (GSE149689). After clustering and annotating cell types, we compare the expression profiles between CHIP vs non-CHIP COVID-19 severe patient.
2022-10-19 | GSE182123 | GEO
Project description:The study aims at investigating the specifical transcriptional signatures of severe COVID-19
2021-01-15 | GSE164805 | GEO
Project description:Red blood cells (RBC) depleted whole blood from COVID-19 patients and controls was harvested and processed in order to performed 10X single cell RNA-seq. For COVID-19 patients 2 samples 10 days a part were analyzed.
2020-08-21 | E-MTAB-9221 | biostudies-arrayexpress
Project description:Single-cell RNA-seq of PBMCs from severe COVID-19 patients
| PRJNA634090 | ENA