Liao B, Zhou F K, Zhong S X, Zhou Y F, Qin Y S, Zhou M X, Qin C
Department of Neurology, First Affiliated Hospital, Guangxi Medical University, Nanning 530021, China.
Zhonghua Yi Xue Za Zhi. 2019 Feb 19;99(7):525-531. doi: 10.3760/cma.j.issn.0376-2491.2019.07.010.
To analyze the expression microarray data in the public databases of intracranial aneurysms (IA) using bioinformatics, and to provide important information for the study of disease mechanisms. Gene co-expression network was constructed by weighted gene co-expression network analysis (WGCNA) based on the dataset (GSE75436) and pivot genes were identified. Using the online tool DAVID (Database for Annotation, Visualization, and Integrated Discovery) to perform GO function enrichment and KEGG path analysis on modules highly related to IA. Three IA-related modules were screened out, and 14 pivot genes (COL3A1, SPARC, CDH11, COL5A1, HOPX, CLEC11A, GALNT10, ADAMTS2, CEMIP, KIAA1755, COL11A1, ZIC2, CDKN2A, and LINC00460) in the brown module were identified; the analysis of GO showed that the brown module was mainly enriched in extracellular matrix organization, extracellular matrix organization, cell adhesion and other biological processes; the analysis of KEGG indicated that the brown module involved in ECM-receptor interaction, Focal adhesion, protein digestion and absorption, PI3K-Akt signaling pathway. Based on WGCNA, we identified modular and pivotal genes that are critical to the development of IA, and they may become potential biomarkers and/or therapeutic targets.
运用生物信息学方法分析颅内动脉瘤(IA)公共数据库中的表达微阵列数据,为疾病机制研究提供重要信息。基于数据集(GSE75436),通过加权基因共表达网络分析(WGCNA)构建基因共表达网络并鉴定枢纽基因。利用在线工具DAVID(注释、可视化与整合发现数据库)对与IA高度相关的模块进行GO功能富集和KEGG通路分析。筛选出3个与IA相关的模块,鉴定出棕色模块中的14个枢纽基因(COL3A1、SPARC、CDH11、COL5A1、HOPX、CLEC11A、GALNT10、ADAMTS2、CEMIP、KIAA1755、COL11A1、ZIC2、CDKN2A和LINC00460);GO分析表明,棕色模块主要富集于细胞外基质组织、细胞外基质组织、细胞黏附等生物学过程;KEGG分析表明,棕色模块涉及细胞外基质-受体相互作用、黏着斑、蛋白质消化与吸收、PI3K-Akt信号通路。基于WGCNA,我们鉴定出对IA发展至关重要的模块和关键基因,它们可能成为潜在的生物标志物和/或治疗靶点。