Wang Dong, Song Xixiao, Wang Yan, Li Xia, Jia Shanshan, Wang Zhijing
Department of Neurology, Xi'an Children's Hospital, Xi'an, Shaanxi 710003, China.
ScientificWorldJournal. 2014;2014:731091. doi: 10.1155/2014/731091. Epub 2014 May 12.
Epilepsy is a common chronic neurological disorder. We aim to investigate the underlying mechanism of epilepsy with partial least squares- (PLS-) based gene expression analysis, which is more sensitive than routine variance/regression analysis.
Two microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database. PLS analysis was used to identify differentially expressed genes. Gene ontology and network analysis were also implemented.
A total of 752 genes were identified to be differentially expressed, including 575 depressed and 177 overexpressed genes in patients. For GO enrichment analysis, except for processes related to the nervous system, we also identified overrepresentation of dysregulated genes in angiogenesis. Network analysis revealed two hub genes, CUL3 and EP300, which may serve as potential targets in further therapeutic studies.
Our results here may provide new understanding for the underlying mechanisms of epilepsy pathogenesis and will offer potential targets for producing new treatments.
癫痫是一种常见的慢性神经疾病。我们旨在通过基于偏最小二乘法(PLS)的基因表达分析来探究癫痫的潜在机制,该方法比常规的方差/回归分析更为灵敏。
从基因表达综合数据库(GEO)下载了两个微阵列数据集。采用PLS分析来鉴定差异表达基因。还进行了基因本体论和网络分析。
共鉴定出752个差异表达基因,其中患者中有575个基因表达下调,177个基因表达上调。对于基因本体富集分析,除了与神经系统相关的过程外,我们还发现血管生成中失调基因的过度表达。网络分析揭示了两个枢纽基因CUL3和EP300,它们可能作为进一步治疗研究的潜在靶点。
我们的研究结果可能为癫痫发病机制的潜在机制提供新的认识,并为开发新的治疗方法提供潜在靶点。