Artificial Cells, Nanomedicine, and Biotechnology (Jan 2020)

Identification of potential key pathways, genes and circulating markers in the development of intracranial aneurysm based on weighted gene co-expression network analysis

  • Guojia Du,
  • Dangmurenjiafu Geng,
  • Kai Zhou,
  • Yandong Fan,
  • Riqing Su,
  • Qingjiu Zhou,
  • Bo Liu,
  • Serick Duysenbi

DOI
https://doi.org/10.1080/21691401.2020.1770264
Journal volume & issue
Vol. 48, no. 1
pp. 999 – 1007

Abstract

Read online

AbstractBackground 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.

Keywords