Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

2 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Lipidomics data of cured COVID-19 patients

ABSTRACT: SE vs H and MY vs H data (neg & pos) for statistical analysis

ORGANISM(S): Homo Sapiens

SUBMITTER: Wendong Huang

PROVIDER: PXD023154 | iProX | Tue Dec 15 00:00:00 GMT 2020

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Publications

Lipidomic alteration of plasma in cured COVID-19 patients using ultra high-performance liquid chromatography with high-resolution mass spectrometry.

Bai Yunpeng Y Huang Wendong W Li Yaocai Y Lai Changchun C Huang Sumei S Wang Guangwen G He Yuemei Y Hu Linhui L Chen Chunbo C

Bioscience reports 20210301 3

<h4>Background</h4>The pandemic of novel coronavirus disease 2019 (COVID-19) has become a serious public health crisis worldwide. The symptoms of COVID-19 vary from mild to severe among different age groups, but the physiological changes related to COVID-19 are barely understood.<h4>Methods</h4>In the present study, a high-resolution mass spectrometry (HRMS)-based lipidomic strategy was used to characterize the endogenous plasma lipids for cured COVID-19 patients with different ages and symptoms ...[more]

PMID: 33635316

Similar Datasets

Circulating peptidome is strongly altered in COVID-19 patients

Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease-19 (COVID-19), an infectious disease characterized by a broad spectrum of symptoms, from mild to severe. Even though the COVID-19 impact on the proteome, metabolome, and lipidome has been largely investigated in different bio-fluids, to date the circulating peptidome remains unexplored. Thus, the present study aimed to apply an untargeted peptidomic approach to provide insight into alterations of circulating peptides in the development and severity of SARS-CoV-2 infection. The circulating peptidome from COVID-19 severe and mildly symptomatic patients and negative controls was characterized using LC-MS/MS analysis for identification and quantification purposes. Database search and statistical analysis allowed a complete characterization of the plasma peptidome and the detection of the most significant modulated peptides that were impacted by the infection. Our results highlighted not only that peptide abundance inversely correlates with disease severity but also the involvement of biomolecules belonging to inflammatory, immune-response, and coagulation proteins/processes. Moreover, our data suggested a possible involvement of changes in protein degradation patterns. In the present research, for the first time, the untargeted peptidomic approach enabled the identification of circulating peptides potentially playing a crucial role in the progression of COVID-19.

2023-03-11 | PXD036020 | Pride

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

Project description: Not available

| S-BSST416 | biostudies-other

Effects of Dexamethasone in COVID-19 patients

Project description:Dexamethasone improves the survival of COVID-19 patients in need of supplemental oxygen therapy. Hospitalized COVID-19 patients eligible for dexamethasone therapy were recruited from the general care ward in several centers in Greece and the Netherlands and whole blood transcriptomic analysis was performed before and after starting dexamethasone treatment. Peripheral blood mononuclear cells (PBMCs) were isolated from healthy individuals and COVID-19 patients and stimulated with inactivated SARS-CoV-2 ex vivo in the presence or absence of dexamethasone and their transcriptome was assessed.

2023-07-26 | GSE227585 | GEO

Circulating miRNA Profiles in COVID-19 Patients and Meta-Analysis: Implications for Disease Progression and Prognosis

Project description:We compared circulating miRNA profiles of hospitalized COVID-positive patients (n = 104, 27 with ARDS) and age and gender matched healthy controls (n = 18) to identify miRNA signatures associated with COVID and COVID-induced ARDS. Meta-analysis incorporating data from published studies and our data was performed to identify a set of differentially expressed miRNAs in 1) COVID-positive patients versus healthy controls as well as 2) severe (ARDS+) COVID vs moderate COVID. Gene ontology enrichment analysis of the genes these miRNAs interact with identified terms associated with immune response, such as interferon and interleukin signaling, as well as viral genome activities associated with COVID disease and severity. Additionally, we observed downregulation of a cluster of miRNAs located on chromosome 14 (14q32) among all COVID patients. To predict COVID disease and severity, we developed machine learning models that achieved AUC scores between 0.88–0.93 for predicting disease, and between 0.62–0.81 for predicting severity, even across diverse studies with different sample types (plasma versus serum), collection methods, and library preparations. Our findings provide network and top miRNA feature insights into COVID disease progression and contribute to the development of tools for disease prognosis and management.

2023-12-13 | GSE240888 | 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

Circulating microRNA signatures associated with disease severity and outcome in COVID-19 patients

Project description:In this study, we sought to identify circulating microRNA (miRNA) signatures associated with COVID-19 severity and outcome through small RNA-sequencing of serum samples from 89 COVID-19 patients and 45 healthy controls. As results, a set of miRNAs associated with lung disease, vascular damage and inflammation were upregulated in serum of COVID-19 patients vs controls, while miRNAs that inhibit pro-inflammatory cytokines and chemokines, angiogenesis and stress response were downregulated. In addition, patients with severe COVID-19 vs mild or moderate disease had a circulating miRNA signature associated with sepsis, hearth failure, tissue fibrosis, inflammation, and impairment of type I IFN and antiviral responses. A subset of the differentially expressed miRNAs predicted ICU admission, sequelae and mortality in COVID-19 patients. Investigation of the differentially expressed circulating miRNAs in relevant human cell types in vitro showed that some of these miRNAs were modulated directly by SARS-CoV-2 infection or indirectly by type I IFN stimulation.

2022-05-03 | GSE201790 | 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

Quantitative Proteomics Analysis of COVID-19 Patients

Project description:Treatment of severe cases of Coronavirus disease 2019 (COVID-19) is extremely important to decrease death and end organ damages. Herein, we performed a proteomic analysis of plasma samples from mild, moderate and sever Covid-19 patients. Analysis revealed differentially expressed proteins and different therapeutic potential targets related to innate immune responses

2023-05-02 | PXD037400 | Pride

Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms

Project description: Not available

| S-BSST719 | biostudies-other

Immunologic characterization of COVID-19 patients with hematologic cancer: biologic and clinical significance

Project description:Immunosuppression caused by cancer itself and cytotoxic treatment may pose a challenge to coronavirus disease 2019 (COVID-19) patients with hematological malignancies. Here, we use multidimensional flow cytometry (MFC) to analyze immune profiles in peripheral blood samples of 515 COVID-19 patients at presentation. In 14 cases, deep immunophenotyping of B- and T-cells was performed and six myeloid- and dendritic-cell subsets were FACSorted for transcriptome analysis using RNAseq. Of the 515 patients, 15 and 10 had solid and hematological tumors, respectively. Those with hematological cancer showed significantly higher rates of intensive care (50%) and death (30%) from COVID-19 vs cases with solid cancer and no tumor. Patients with hematological malignancies displayed altered immune profiles with significantly decreased absolute numbers of several subsets of myeloid and lymphoid cells. Myeloid- and dendritic-cell types from hematological cases showed differentially expression of genes coding transcription factors, toll-like receptors and proinflammatory interleukin receptors implicated in response to coronaviruses. The relative distribution of the B-cell compartment was notoriously altered in COVID-19 patients with hematological cancer, and progressively lower numbers of B- and T-cell subsets were observed in deceased cases. Altogether, our results suggest an association between impaired immune responses and poorer outcomes in COVID-19 patients with hematological malignancies.

2020-12-31 | GSE153610 | 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