Similar Datasets
Project description:IL-13 neutralization effect on COVID-19 severity
| PRJNA748702 | ENA
Project description:The causative organism, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical manifestations in disease-ridden patients. Differences in the severity of COVID-19 ranges from asymptomatic infections and mild cases to the severe form, leading to acute respiratory distress syndrome (ARDS) and multiorgan failure with poor survival. MiRNAs can regulate various cellular processes, including proliferation, apoptosis, and differentiation, by binding to the 3′UTR of target mRNAs inducing their degradation, thus serving a fundamental role in post-transcriptional repression. Alterations of miRNA levels in the blood have been described in multiple inflammatory and infectious diseases, including SARS-related coronaviruses. We used microarrays to delineate the miRNAs and snoRNAs signature in the peripheral blood of severe COVID-19 cases (n=9), as compared to mild (n=10) and asymptomatic (n=10) patients, and identified differentially expressed transcripts in severe versus asymptomatic, and others in severe versus mild COVID-19 cases. A cohort of 29 male age-matched patients were selected. All patients were previously diagnosed with COVID-19 using TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Waltham, Massachusetts), or Cobas SARS-CoV-2 Test (Roche Diagnostics, Rotkreuz, Switzerland), with a CT value < 30. Additional criterion for selection was age between 35 and 75 years. Participants were grouped into severe, mild and asymptomatic. Classifying severe cases was based on requirement of high-flow oxygen support and ICU admission (n=9). Whereas mild patients were identified based on symptoms and positive radiographic findings with pulmonary involvement (n=10). Patients with no clinical presentation were labelled as asymptomatic cases (n=10).
2022-03-01 | E-MTAB-10970 | biostudies-arrayexpress
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
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
Project description:Coronavirus disease 2019 (COVID-19) has been threatening public health for the last 3 years globally. So far, the pathophysiology of the disease and therapeutic strategies have not clearly known yet. In this project, performing label-free plasma proteomics analysis, we aimed at identifying severity biomarkers for COVID-19 prognosis and proposing potential drugs against the disease symptoms by building the signaling network of significantly regulated proteins and finding the corresponding virus-host interactions. A total of 38 plasma samples from 13 COVID-19 PCR positive individuals and 5 plasma samples from healthy individuals were collected for the analysis. According to the WHO criteria, the severity of our patients was categorized as moderate (n=4), severe (n=3), and critical (n=6). Also, blood samples were collected in different time points after the symptom onset: (1) 1-5 day (± 2 days); early infection, (2) 5-15 days (± 2 days); inflammatory response, and after 15 days (± 2 days); recovery which shows the first PCR negative result from a nasal swab. In summary, we found significantly regulated proteins between COVID-19 patients and uninfected individuals and proposed some critical patient-specific prognostic biomarkers, which can be used as an early predictor of the disease severity. Also, we created a COVID-19 related plasma protein network modulated by SARS-CoV2 viral proteins and indicated clinically significant targets for the disease symptoms.
2023-03-11 | PXD031813 | Pride
Project description:Viral strains, age, and host factors including genetics and proteins are associated with variable immune responses against SARS-CoV-2 and disease severity. We hypothesized that unique proteins/pathways are associated with COVID-19 disease severity in Puerto Rican Hispanics. A total of 121 men and women aged 21-80 years-old were recruited in Puerto Rico. Plasma samples were collected from unvaccinated COVID-19 infected subjects during acute disease (n=39) and compared to COVID-19 negative individuals (n=56) during acute disease using proteomics and cytokine expression. Infected individuals were stratified based on symptomatology as follows: mild (n=18), moderate (n=13), and severe (n=8). Quantitative proteomics was performed in plasma samples using Tandem Mass Tag (TMT) labeling. Cytokines in plasma were quantified using a human cytokine array. Proteomics analyses revealed 56 differentially regulated proteins and the top 3 pathways that were predicted to be inhibited in severe patients including LXR/RXR signaling, Production of NO and ROS in macrophages, and Synaptogenesis signaling. Decreased cadherin-13 validated by ELISA, which participates in synaptogenesis, is a novel protein is a novel protein not previously reported in other studies of COVID-19 severity and validated by ELISA. Cytokine analyses showed that TNF⍺ levels decreased with disease severity. This study uncovers potential host predictors of COVID-19 severity and new avenues for treatment in Puerto Rican Hispanics.
2024-06-16 | PXD046103 | Pride
Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.
2020-08-29 | GSE157103 | GEO
Project description:Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.
2022-12-18 | GSE221234 | GEO
Project description:The SARS-CoV-2 outbreak started on December 2019 in China and rapidly spread worldwide. Clinical manifestations of Coronavirus-disease 2019 (COVID-19) vary broadly, ranging from asymptomatic infection to acute respiratory failure and death, yet the underlying mechanisms and predictive biomarkers for this high variability are still unknown. Emerging evidence has shown that circulating extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of physiologic and pathologic processes. To test the hypothesis that these extracellular components are a key determinant of severity in COVID-19, we collected 31 serum samples from mild COVID-19 patients at admission in single center. After standard therapy without corticosteroids, 9 of 31 patients became severe COVID-19. We analyzed exRNA profiles from the 31 serums and 10 healthy controls for predicting COVID-19 severity value.
2022-03-31 | GSE158877 | GEO
Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress