基因共表达网络
基因
生物
NLRC4型
基因表达
计算生物学
小桶
基因调控网络
生物信息学
遗传学
转录组
基因本体论
受体
半胱氨酸蛋白酶1
炎症体
作者
Guojia Du,Dangmurenjiafu Geng,Kai Zhou,Yandong Fan,Riqing Su,Qingjiu Zhou,Bo Liu,Serick Duysenbi
标识
DOI:10.1080/21691401.2020.1770264
摘要
Background Intracranial aneurysm (IA) is a disease resulted from weak brain control, characterized by local expansion or dilation of brain artery. This study aimed to construct a gene co-expression network by Weighted Gene Correlation Network Analysis (WGCNA) to explore the potential key pathways and genes for the development of IA.Method Six IA-related gene expression data sets were downloaded from the Gene Expression Omnibus (GEO) database for identifying differentially expressed genes (DEGs). WGCNA was used to identify modules associated with IA. Functional enrichment analysis was used to explore the potential biological functions. ROC analysis was used to find markers for predicting IA.Results Purple, greenyellow and yellow modules were significantly associated with unruptured intracranial aneurysms, while blue and turquoise modules were significantly associated with ruptured intracranial aneurysms. Functional modules significantly related to IA were enriched in Ribosome, Glutathione metabolism, cAMP signalling pathway, Lysosome, Glycosaminoglycan degradation and other pathways. CD163, FCEREG, FPR1, ITGAM, NLRC4, PDG, and TYROBP were up-regulated ruptured intracranial aneurysms and serum, these genes were potential circulating markers for predicting IA rupture.Conclusions Potential IA-related key pathways, genes and circulating markers were identified for predicting IA rupture by WGCNA analysis.
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