Shuang Li, Zhigang Wang, Yake Zheng, Yunqing Ma, Zhi Huang, Yajun Lian
{"title":"Integrated Transcriptomic Analysis Provided Diagnostic and Pathophysiological Insights for Epilepsy.","authors":"Shuang Li, Zhigang Wang, Yake Zheng, Yunqing Ma, Zhi Huang, Yajun Lian","doi":"10.1155/jimr/5925485","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> 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. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusion:</b> This study successfully identified four key genes linked to epilepsy, contributing to the molecular diagnosis of epilepsy.</p>","PeriodicalId":15952,"journal":{"name":"Journal of Immunology Research","volume":"2025 ","pages":"5925485"},"PeriodicalIF":3.6000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12283209/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Immunology Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/jimr/5925485","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
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.
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.