Sun Yongsheng, Ji Haonan, Xu Liqin, Gu Ruiyin, Striano Pasquale, Winston Gavin P, Li Bin, Zhou Hui
Department of Pediatrics, The Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China.
Department of Pediatrics, The Affiliated Hospital of Nantong University, Nantong, China.
Transl Pediatr. 2024 Jul 31;13(7):1190-1200. doi: 10.21037/tp-24-211. Epub 2024 Jul 29.
The optimal biomarkers for early diagnosis, treatment, and prognosis of tuberous sclerosis complex (TSC)-associated epilepsy are not yet clear. This study identifies the crucial genes involved in the pathophysiology of TSC-associated epilepsy via a bioinformatics analysis. These genes may serve as novel therapeutic targets.
Gene chip data sets (GSE62019 and GSE16969) comprising the data of patients with TSC-associated epilepsy and healthy control participants were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in the GEO database were identified using the GEO2R gene expression analysis tool. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene Ontology function, and protein-protein interaction (PPI) network analyses were then conducted. The results were analyzed using R language, and are presented in volcano plots, Venn diagrams, heatmaps, and enrichment pathway bubble charts. A gene set enrichment analysis (GSEA), was conducted to examine the KEGG pathways and crucial genes linked to TSC-associated epilepsy. The potential genes were compared with the genes listed in the Online Mendelian Inheritance in Man (OMIM) database and analyzed against the literature to determine their clinical significance. Finally, the expression of the key genes in the TSC-associated epilepsy mice cerebral cortex was examined through immunohistochemical staining.
The intersection of the GSE62019 and GSE16969 data sets revealed 151 commonly upregulated DEGs. The KEGG enrichment analysis indicated that these DEGs affected the occurrence and development of TSC-associated epilepsy by modulating complement and coagulation cascades, glycosaminoglycans in cancer, and extracellular matrix-receptor interactions. Four high-scoring clusters emerged, and podoplanin () was identified as a key gene through the construction of a PPI network of the common DEGs using the Cytoscape software. A GSEA of the DEGs revealed that the common DEG was enriched in both data sets in pathways related to platelet activation, aggregation, and the glycoprotein VI (GPVI)-mediated activation cascade. Immunohistochemical staining revealed a significant elevation in expression in the cerebral cortex of mice with TSC-associated epilepsy. Conversely, the control group mice did not display any significantly positive neurons.
The discovery of these crucial genes and signaling pathways extends understanding of the molecular processes underlying the development of TSC-associated epilepsy. Additionally, our findings may provide a theoretical basis for research into targeted clinical treatments.
结节性硬化症（TSC）相关癫痫的早期诊断、治疗及预后的最佳生物标志物尚不清楚。本研究通过生物信息学分析确定了参与TSC相关癫痫病理生理学的关键基因。这些基因可能成为新的治疗靶点。
从基因表达综合数据库（GEO）获取包含TSC相关癫痫患者和健康对照者数据的基因芯片数据集（GSE62019和GSE16969）。使用GEO2R基因表达分析工具识别GEO数据库中的差异表达基因（DEG）。随后进行京都基因与基因组百科全书（KEGG）通路、基因本体功能和蛋白质-蛋白质相互作用（PPI）网络分析。结果用R语言进行分析，并以火山图、维恩图、热图和富集通路气泡图呈现。进行基因集富集分析（GSEA）以研究与TSC相关癫痫相关的KEGG通路和关键基因。将潜在基因与在线人类孟德尔遗传（OMIM）数据库中列出的基因进行比较，并对照文献进行分析以确定其临床意义。最后，通过免疫组织化学染色检测关键基因在TSC相关癫痫小鼠大脑皮层中的表达。
GSE62019和GSE16969数据集的交集显示有151个共同上调的DEG。KEGG富集分析表明，这些DEG通过调节补体和凝血级联反应、癌症中的糖胺聚糖以及细胞外基质-受体相互作用影响TSC相关癫痫的发生和发展。出现了四个高分簇，通过使用Cytoscape软件构建共同DEG的PPI网络，鉴定出足突蛋白（）为关键基因。对DEG的GSEA显示，共同DEG在两个数据集中均富集于与血小板活化、聚集以及糖蛋白VI（GPVI）介导的活化级联反应相关的通路中。免疫组织化学染色显示，TSC相关癫痫小鼠大脑皮层中的表达显著升高。相反，对照组小鼠未显示任何明显阳性神经元。
这些关键基因和信号通路的发现扩展了对TSC相关癫痫发生发展潜在分子过程的理解。此外，我们的研究结果可能为靶向临床治疗研究提供理论依据。
