Integrated Transcriptomic Analysis Provided Diagnostic and Pathophysiological Insights for Epilepsy

整合转录组分析为癫痫的诊断和病理生理学提供了见解

阅读:1

Abstract

Background: Epilepsy is a common neurological disorder involving multiple genes and molecular pathways. Study of differentially expressed genes (DEGs) and hub genes related to epilepsy can help reveal the pathophysiologic basis and improve potential diagnostic and therapeutic strategies. Methods: Transcriptome data of two epilepsy datasets (GSE143272 and GSE32534) and single-cell sequencing data (GSE201048) were collected from the Gene Expression Omnibus (GEO) database. Differential expression analysis was performed using Limma R package, and the hub genes were identified and analyzed utilizing STRING database and Cytoscape software. The clusterProfiler R package was used to perform gene function enrichment analysis and an epilepsy diagnostic model was constructed with the hub genes. The model performance was assessed according to receiver operating characteristic (ROC) curves. Results: Multiple DEGs linked to epilepsy were identified and 20 common DEGs between the two datasets were revealed. Eleven hub genes closely associated with epilepsy were identified by protein-protein interaction (PPI) network analysis. CD3D, CD3G, CTSW, and JCHAIN were consistently expressed in the GSE143272 and GSE32534 datasets and all showed a low expression in epilepsy samples. In particular, the diagnostic model developed with the four genes demonstrated a strong discriminatory ability in both datasets (all area under curve (AUC) > 0.7). Functional enrichment and single-cell analysis revealed that these key genes were closely related to T cell function, suggesting that they may play an important role in the immune regulation of epilepsy. Conclusion: This study successfully identified four key genes linked to epilepsy, contributing to the molecular diagnosis of epilepsy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。