Weighted gene co expression network analysis (WGCNA) with key pathways and hub‐genes related to micro RNAs in ischemic stroke. Issue 3 (20th April 2021)

• Record Type: Journal Article
• Authors: Qu, Xiang; Wu, Shuang; Gao, Jinggui; Qin, Zhenxiu; Zhou, Zhenhua; Liu, Jingli
• Is Part Of: IET systems biology. Volume 15:Issue 3(2021)
• Page Start: 93
• Page End: 100
• Publication Date: 2021-04-20
• Subjects: Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/syb2.12016
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract: Ischemic stroke (IS) is one of the major causes of death and disability worldwide. However, the specific mechanism of gene interplay and the biological function in IS are not clear. Therefore, more research into IS is necessary. Dataset GSE110993 including 20 ischemic stroke (IS) and 20 control specimens are used to establish both groups and the raw RNA‐seq data were analysed. Weighted gene co‐expression network analysis (WGCNA) was used to screen the key micro‐RNA modules. The centrality of key genes were determined by module membership (mm) and gene significance (GS). The key pathways were identified by enrichment analysis with Kyoto Protocol Gene and Genome Encyclopedia (KEGG), and the key genes were validated by protein‐protein interactions network. Result: Upon investigation, 1185 up‐ and down‐regulated genes were gathered and distributed into three modules in response to their degree of correlation to clinical traits of IS, among which the turquoise module show a trait‐correlation of 0.77. The top 140 genes were further identified by GS and MM. KEGG analysis showed two pathways may evolve in the progress of IS. Discussion: CXCL12 and EIF2a may be important biomarkers for the accurate diagnosis and treatment in IS.