Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Differential expression and correlation analysis of global transcriptome for hemorrhagic transformation after acute ischemic stroke

ABSTRACT: In order to explore the epigenetic characteristics of hemorrhagic transformation(HT) after acute ischemic stroke, we used transcriptome sequencing technology to analyze the global transcriptome expression profile of patients with and without HT after acute ischemic stroke and to study the differential expression of messenger RNA (mRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) between HT group and non-HT group.

ORGANISM(S): Homo sapiens

PROVIDER: GSE199435 | GEO | 2022/03/30

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Single-Cell RNA-Seq reveals cellualr heterogeneity and gene expression difference between ischemic and hemorrhagic stroke brain

Project description:Cluster analysis using nonlinear dimensionality reduction ([tSNE]) revealed the differences in global gene expression profiles of healthy and injured striatum, and identified clusters of cells with unique genetic signatures in both ischemic brain and hemorrhagic brain. Genes with p-value < 0.05 and fold change ≥1.5 were regarded as differentially expressed genes (DEGs). For astrocytes, 135 DEGs were downregulated in hemorrhagic stroke compared to ischemic stroke. The secondary profiling of astrocytic subtypes yielded 10 different subtypes with distinct functional cell identities. For microglia, tSNE map indicated the distribution and proportion of microglia/macrophage were very similar in in the ischemic and hemorrhagic stroke models. We obtained 75 DEGs in total (hemorrhagic stroke vs. ischemic stroke, 54 were upregulated, 21 were downregulated) .

2021-10-31 | GSE167593 | GEO

iTRAQ-based quantitative serum proteomic analysis in ischemic stroke patients

Project description:Hemorrhagic transformation (HT), which occurs with or without reperfusion treatments (thrombolysis and/or thrombectomy), deteriorates the outcomes of ischemic stroke patients. It is essential to find clinically reliable biomarkers that can predict HT. In this study, we screened for potential serum biomarkers from an existing blood bank and database with 243 suspected acute ischemic stroke (AIS) patients. A total of 37 patients were enrolled, who were diagnosed as AIS but did not receive reperfusion treatment. They were divided into two groups based on whether they accompanied with HT or not (5 HT and 32 non-HT). Serum samples were labeled by isobaric tags for relative and absolute quantitation (iTRAQ) and analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and compared under NCBInr database. A total of 647 proteins in sera samples were captured and the levels of 17 proteins (12 up-regulated and 5 down-regulated) were significantly different. These differentially expressed proteins were further categorized with Gene Ontology functional classification annotation and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analysis into biological processes. Further protein-protein interaction analysis using String database discovered that, among the differential expressed proteins, 10 pairs of proteins were found to have crosstalk connections, which may have direct (physical) and indirect (functional) interactions for the development of HT. Our findings suggest that these differentially expressed proteins could serve as potential biomarkers for predicting HT after ischemic stroke.

2021-10-12 | PXD026950 | Pride

Gene expression analysis of peripheral whole blood RNA following ischemic stroke

Project description:The purpose of this project was to elucidate gene expression in the peripheral whole blood of acute ischemic stroke patients to identify a panel of genes for the diagnosis of acute ischemic stroke. Peripheral blood samples were collected in Paxgene Blood RNA tubes from stroke patients who were >18 years of age with MRI diagnosed ischemic stroke and controls who were non-stroke neurologically healthy. The results suggest a panel of genes can be used to diagnose ischemic stroke, and provide information about the biological pathways involved in the response to acute ischemic stroke in humans. Total RNA extracted from whole blood in n=39 ischemic stroke patients compared to n=24 healthy control subjects.

2010-06-08 | E-GEOD-16561 | biostudies-arrayexpress

Differential expression and correlation analysis of global transcriptome for hemorrhagic transformation after acute ischemic stroke

Project description:Differential expression and correlation analysis of global transcriptome for hemorrhagic transformation after acute ischemic stroke

| PRJNA819994 | ENA

Gene expression analysis of peripheral whole blood RNA following ischemic stroke

2010-06-01 | GSE16561 | GEO

LncRNA expression profiling of ischemic stroke patients

Project description:Our study reveals that ischemic stroke can influence the expression of LncRNAs and mRNAs in the peripheral blood at both the acute and subacute stages

2019-02-27 | GSE122709 | GEO

Identification of circulating microRNAs as potential biomarkers for detecting acute ischemic stroke

Project description:In order to determine the serum microRNAs profile from middle-old aged patients with acute ischemic stroke and investigate possible diagnostic value of these differential microRNAs.The blood samples of 117 IS patients and 82 healthy people were collected. Differential miRNAs in serum from IS and control were screened with miRNA microarray analysis, and the expression of selected miRNAs were validated by quantitative reverse-transcriptase polymerase chain reaction assays (qRT-PCR). Results: We discovered 115 differentially expressed miRNAs, among which miR-32-3p, miR-106-5p, miR-532-5p were found be related to IS for the first time. Conclusions: In the present study, we identified the changed expression pattern of miRNAs in IS. Serum miR-32-3p, miR-106-5p, miR-1246 and miR-532-5p may serve as potential diagnostic biomarkers for IS. During the initial screening stage, we divided the serum samples into five groups (10 serum samples were pooled to form a group). Group A1: A denotes thrombotic stroke and 1 denotes hepertension. Group A14: A denotes thrombotic stroke, 1 denotes hepertension and 4 denotes hyperlipidemia. Group B2: B denotes embolic stroke and 2 denotes heart disease. Group B12: B denotes embolic stroke, 1 denotes hepertension and 2 denotes heart disease. Group 0: healthy control group.

2015-08-12 | E-GEOD-60319 | biostudies-arrayexpress

Clinical significance of MSP-RON signaling based on mRNA-microRNA integration analyses in acute severe ischemic stroke patients (mRNA data)

Project description:The roles of mRNA and microRNA (miRNA) are widely known in many diseases including acute ischemic stroke. About 60 % of all human messenger RNAs (mRNAs) are regulated by microRNAs. Integration analysis using mRNA and miRNA are important to elucidate pathogenesis. But the contribution of mRNA and miRNA, especially miRNA targeted mRNA, related with severity of acute ischemic stroke is not remain understood. To clarify the pathway related with the severity of acute ischemic stroke, we examined mRNA and miRNA integration analysis targeted for acute ischemic stroke.

2023-08-11 | GSE202518 | GEO

Expression data from heart tissue after induction of ischemic stroke (occlusion of the middle cerebral artery)

Project description:Stroke is frequently associated with cardiac troponin increase and cardiac complications. 24h and 72h after experimental ischemic stroke of the brain, we harvested the heart to investigate pathways and target genes, involved in cardiac dysfunction after acute ischemic stroke

2018-07-19 | GSE102558 | GEO

Clinical significance of MSP-RON signaling based on mRNA-microRNA integration analyses in acute severe ischemic stroke patients (micro RNA data)

2023-08-11 | GSE202708 | 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