综合转录组学分析为癫痫的诊断和病理生理学提供了见解。

IF 3.6 3区 医学 Q2 IMMUNOLOGY
Journal of Immunology Research Pub Date : 2025-07-15 eCollection Date: 2025-01-01 DOI:10.1155/jimr/5925485
Shuang Li, Zhigang Wang, Yake Zheng, Yunqing Ma, Zhi Huang, Yajun Lian
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引用次数: 0

摘要

背景:癫痫是一种常见的神经系统疾病,涉及多种基因和分子通路。研究与癫痫相关的差异表达基因(DEGs)和中枢基因有助于揭示癫痫的病理生理基础,提高潜在的诊断和治疗策略。方法:从Gene Expression Omnibus (GEO)数据库中收集两个癫痫数据集(GSE143272和GSE32534)的转录组数据和单细胞测序数据(GSE201048)。使用Limma R软件包进行差异表达分析,使用STRING数据库和Cytoscape软件对中心基因进行鉴定和分析。利用clusterProfiler R软件包进行基因功能富集分析,并利用中心基因构建癫痫诊断模型。根据受试者工作特征(ROC)曲线评价模型的性能。结果:确定了与癫痫相关的多个deg,并揭示了两个数据集之间的20个共同deg。通过蛋白-蛋白相互作用(PPI)网络分析,鉴定出11个与癫痫密切相关的枢纽基因。CD3D、CD3G、CTSW和JCHAIN在GSE143272和GSE32534数据集中一致表达,在癫痫样本中均呈低表达。特别是,用这四个基因建立的诊断模型在两个数据集中都表现出很强的区分能力(所有曲线下面积(AUC)均为bb0 0.7)。功能富集和单细胞分析显示,这些关键基因与T细胞功能密切相关,提示它们可能在癫痫的免疫调节中发挥重要作用。结论:本研究成功鉴定出4个与癫痫相关的关键基因,有助于癫痫的分子诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated Transcriptomic Analysis Provided Diagnostic and Pathophysiological Insights for Epilepsy.

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.

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来源期刊
CiteScore
6.90
自引率
2.40%
发文量
423
审稿时长
15 weeks
期刊介绍: Journal of Immunology Research is a peer-reviewed, Open Access journal that provides a platform for scientists and clinicians working in different areas of immunology and therapy. The journal publishes research articles, review articles, as well as clinical studies related to classical immunology, molecular immunology, clinical immunology, cancer immunology, transplantation immunology, immune pathology, immunodeficiency, autoimmune diseases, immune disorders, and immunotherapy.
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