Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Small RNA-seq analysis of serum miRNAs in patients with severe COVID-19

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE189506 | GEO | 2021/11/24

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

SARS-CoV-2 RNAemia and proteomic biomarker trajectory inform prognostication in COVID-19 patients admitted to intensive care

Project description:Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples (n = 474) from hospitalized COVID-19 patients (n = 123), non-COVID-19 ICU sepsis patients (n = 25) and healthy controls (n = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia was associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22–2.77] adjusted for age and sex). In longitudinal comparisons, COVID-19 ICU patients had a distinct proteomic trajectory associated with RNAemia and mortality. Among COVID-19-enriched proteins, galectin-3 binding protein (LGALS3BP) and proteins of the complement system were identified as interaction partners of SARS-CoV-2 spike glycoprotein. Finally, machine learning identified ‘Age, RNAemia’ and ‘Age, pentraxin-3 (PTX3)’ as the best binary signatures associated with 28-day ICU mortality.

2021-04-26 | PXD024026 | Pride

SARS-CoV-2 RNAemia and proteomic biomarker trajectory inform prognostication in COVID-19 patients admitted to intensive care

2021-04-26 | PXD024089 | Pride

Plasma gradient of soluble urokinase-type plasminogen activator receptor is linked to pathogenic plasma proteome and immune transcriptome and is a prognostic biomarker for severe COVID-19

Project description:The disease caused by the novel coronavirus of 2019 (COVID-19) has resulted in significant morbidity and mortality world-wide. A systemic hyper-inflammation characterizes the severe COVID-19 disease often associated with acute respiratory distress syndrome (ARDS). Bloodbiomarkers with prognostic relevance are of great importance in effective triage and critical care of severe COVID-19 patients. In the present study we report higher plasma abundance of soluble urokinase-type plasminogen activator receptor (sUPAR), shown to be expressed by an abnormally expanded circulating myeloid cell population, in severe COVID-19 patients with acute respiratory distress syndrome. SUPAR level was found to be linked to a characteristic proteomic signature of plasma. A receiver operator characteristics curve analysis identified a cut-off value of sUPAR at 2000pg/ml, which was linked to characteristic differential expression in the immune transcriptome as well as clinical outcomes in our patient cohort. Thus we identified sUPAR as a biomarker with strong predictive potential for clinical outcomes in severe COVID-19.

2023-07-17 | PXD026510 | Pride

Longitudinal characterization of circulating neutrophils uncovers phenotypes associated with severity in hospitalized COVID-19 patients

Project description:Mechanisms of neutrophil involvement in severe COVID-19 remain incompletely understood. Here we collect longitudinal blood samples from 306 hospitalized COVID-19+ patients and 86 controls, and perform bulk RNA-sequencing of enriched neutrophils, plasma proteomics, and high-throughput antibody profiling to investigate relationships between neutrophil states and disease severity. We identify dynamic switches between 6 distinct neutrophil subtypes. At days 3 and 7 post-hospitalization, patients with severe disease display a granulocytic myeloid-derived suppressor cell-like gene expression signature, while patients with resolving disease show a neutrophil progenitor-like signature. Humoral responses are identified as potential drivers of neutrophil effector functions, with elevated SARS-CoV-2-specific IgG1-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirm that while patient-derived IgG antibodies induce phagocytosis in healthy donor neutrophils, IgA antibodies predominantly induce neutrophil cell death. Overall, our study demonstrates a dysregulated myelopoietic response in severe COVID-19 and a potential role for IgA-dominant responses contributing to mortality.

2022-08-28 | GSE212041 | GEO

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals.

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

Multi-omic approach identifies a transcriptional network coupling innate immune response to proliferation in the blood of COVID-19 cancer patients

Project description:Clinical outcomes of COVID-19 patients are worsened by the presence of co-morbidities, especially cancer for which mortality rate in cancer patients affected by COVID-19 is elevated. SARS-CoV-2 infection is known to alter immune system homeostasis. Whether cancer patients developing COVID-19 present alterations of immune functions which might contribute to worse outcomes has been so far poorly investigated. We conducted a multi-omic analysis of immunological parameters in COVID-19 patients with and without cancer. We found that 8 pro-inflammatory factors out of 27 analysed serum cytokines were modulated in COVID-19 patients irrespective of cancer status. Diverse subpopulations of T lymphocytes such as CD8+ T, CD4+ T central memory, Mucosal associated invariant T cells (MAIT) NKT and  T cells were reduced while B memory cells, plasmablasts, late NK and plasmacytoid dendritic cells were expanded in COVID-19 cancer patients. A 19 gene expression signature of peripheral blood cells was able to discriminate COVID-19 cancer and without cancer patients. Gene set enrichment analysis highlights an increased gene expression in Interferon  response and signalling which paired with aberrant cell cycle regulation in cancer patients. Ten out of these 19 genes were specific of COVID-19 cancer patients. Our findings illustrate a repertoire of aberrant alterations of gene expression in circulating immune cells of COVID-19 cancer patients that might contribute to decipher their higher frequency of severe events. We also unveil a transcriptional network involving gene regulators of both inflammation response and proliferation in PBMCs of COVID-19 cancer patients. This might also lead to design of novel therapeutic strategies for COVID-19 cancer patients.

2021-11-10 | GSE164571 | GEO

Whole blood transciptome analysis in severe Covid-19 patients and healthy donors

Project description:The identification of COVID-19 patients with high-risk of severe disease is a challenge in routine care. We performed blood RNA-seq gene expression analyses in severe hospitalized patients compared to healthy donors. Supervised and unsupervised analyses revealed a high abundance of CD177, a specific neutrophil activation marker, contributing to the clustering of severe patients. Gene abundance correlated with high serum levels of CD177 in severe patients. These results highlight neutrophil activation as a hallmark of severe disease and CD177 assessment as a reliable prognostic marker for routine care.

2021-05-27 | GSE171110 | GEO

Clinical and immunological signatures of severe COVID-19 in previously healthy patients with clonal hematopoiesis

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

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

People critically ill with COVID-19 exhibit peripheral immune profiles predictive of mortality and reflective of SARS-CoV-2 lung viral burden

Project description:There remains an urgent need to delinate immune cell states that contribute to mortality in critially ill COVID-19 patients. To better understand determinants of mortality, we performed high dimensional profiling of blood and respiratory samples from critially ill COVID-19 patients. Single-cell RNAseq based characterization of peripheral immune states reveal distinct expression profiles that were predictive of COVID-19 mortality. Temporal analysis revealed a that persistently elevated levels of inflammatory monocyte signatures and persistent interferon signaling preceeded concerted upregulation of inflammatory cytokines. Interrogation of lower respiratory tract saples revelaed that infected myeliod cells upregulated CXCL10, and elevated levels of CXCL10 in plasma were associated with a high risk of death. Overall, our data suggest a pivotal role for myeloid cell states in severe COVID-19 and may faciliate discovery of new diagnostics and therapeutics.

2021-12-08 | GSE180578 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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