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

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

PROVIDER: PRJNA819994 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR18486129_1.fastq.gz	Fastqsanger.gz
	SRR18486129_2.fastq.gz	Fastqsanger.gz
	SRR18486130_1.fastq.gz	Fastqsanger.gz
	SRR18486130_2.fastq.gz	Fastqsanger.gz
	SRR18486131_1.fastq.gz	Fastqsanger.gz

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

Project description: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.

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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.

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