COVID-19 multi-omics
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB55909 | ENA |
REPOSITORIES: ENA
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Project description:Background: The outbreak of coronavirus disease 2019 (COVID-19) poses a considerable health threat to humanity, with potential implications for the ovarian microenvironment remaining uncertain. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Conclusions: By integrating untargeted metabolomic and lipidomic features, we identified biomarkers indicative of oocyte competency influenced by COVID-19.
2024-12-25 | GSE282892 | GEO
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: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:Multi-omics single-cell profiling of surface proteins, gene expression and lymphocyte immune receptors from hospitalised COVID-19 patient peripheral blood immune cells and healthy controls donors. Identification of the coordinated immune cell compositional and state changes in response to SARS-CoV-2 infection or LPS challenge, compared to healthy control immune cells.
2021-03-17 | E-MTAB-10026 | biostudies-arrayexpress
Project description:Background: The outbreak of coronavirus disease 2019 (COVID-19) poses a considerable health threat to humanity, with potential implications for the ovarian microenvironment remaining uncertain. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Conclusions: By integrating untargeted metabolomic and lipidomic features, we identified biomarkers indicative of oocyte competency influenced by COVID-19.
2025-05-07 | PXD058234 | Pride
Project description:We performed RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities. Over 17,000 transcripts, proteins, metabolites, and lipids were quantified and associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a comparative analysis with published data and a machine learning approach for prediction of COVID-19 severity.
2020-07-08 | MSV000085703 | MassIVE
Project description:COVID-19 induces profound B-cell dysregulation, notably a marked expansion of plasmablasts (PB), whose functional role remains unclear. This study aimed to characterize PB dynamics and functions in COVID-19 and their association with disease severity. We performed longitudinal immune profiling in a prospective cohort of 50 patients with COVID-19 (cohort 1), including flow cytometry-based B-cell immunophenotyping and multiplex cytokine analysis at days 1, 7, 14, and 30. A second retrospective cohort of 282 corticosteroid-naïve patients (cohort 2) was used to validate PB dynamics, model PB trajectories, and perform transcriptomic profiling of sorted PB. PB expansion occurred early in COVID-19 and was positively correlated with maximal disease severity (r=0.53, p<0.0001). Two distinct PB expansion trajectories were identified: one rapidly resolving, and one persistent and amplified, the latter being associated with higher severity scores and 30-day mortality (31% vs. 5%, p<0.001). In cohort 1, BAFF levels at day 7 correlated positively with both PB proportion (r=0.59, p=0.002) and maximal disease severity (r=0.74, p<0.001). Transcriptomic profiling of PB in cohort 2 revealed severity-specific signatures: in severe cases, early PB upregulated genes related to purine metabolism and CD39 expression, suggesting a pro-inflammatory role. In non-severe cases, PB expressed interferon-related and CIITA-mediated MHC-II programs, indicative of antiviral function. PB display dual functional profiles in COVID-19, acting either as regulators of antiviral immunity or as amplifiers of inflammation in severe disease. These findings support exploring therapeutic strategies targeting the BAFF-PB axis in severe COVID-19.
2025-07-01 | E-MTAB-15068 | biostudies-arrayexpress
Project description:Circulating microRNAs (miRNAs) have been shown to be excellent disease diagnostic or prognostic biomarkers in a wide range of chronic and acute inflammatory and infectious diseases including viral respiratory infection. Crucially, circulating miRNA levels are thought to reflect the state of the diseased tissue. Despite their proven value as mechanism-based clinical stratification indicators, miRNAs have only started being explored in the context of COVID-19. here, we aimed to explore whether integrating miRNA with other clinical and biological measurements would reveal more accurate correlates of COVID-19 severity and outcome, and to identify severity-specific correlations of miRNAs with COVID-19-associated inflammatory mediators, clinical parameters, and otucome.
2021-12-09 | GSE189610 | GEO
Project description:Matched samples from individuals before they contracted COVID-19 and after they were diagnosed with it were used for TMT-based relative quantitation of their plasma proteome and glycoproteome to study the effects of this infectious disease. Twenty one COVID-19 patients whose pre-COVID-19 plasma samples were also available were selected for this study. These patients had varied courses of illness and were classified based on WHO guidelines into outpatients and those with severe and critical illness. 21 matched sample pairs were divided into 3 sets for 3 TMTPro 16-plex-based mass spectrometry experiments with 8 (set01), 8 (set02), and 5 (set03) patients each. Plasma-derived tryptic peptides from each sample were TMT-labeled, and each pooled set was used for separate experiments for total proteomics and glycoproteomics. A pooled aliquot from each set was used to enrich glycopeptides by size exclusion chromatography and another aliquot was used to fractionate all peptides by basic pH reversed phase liquid chromatography. Enriched glycopeptides were analyzed by LC-MS/MS and quantified across samples using TMT reporter ion intensities. Fold changes (intensity of protein or glycopeptide from a patient with COVID-19/that from the same patient before they had COVID-19) for each protein and glycopeptide were calculated for all patients to assess changes in the proteome that may be attributable to this illness. We detected 1,520 proteins, of which 472 were detected in all patients. 3,892 glycopeptides were identified at 1% FDR at peptide, glycan and glycopeptides levels and their reporter ion intensities were quantified. 732 glycopeptides from 232 glycoproteins were detected in all patients.
2022-08-12 | PXD029376 | Pride
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