LncRNAs related key pathways and genes in ischemic stroke by weighted gene co-expression network analysis (WGCNA)

Autor: Lijuan Wang, Liyuan Pu, Shuo Li, Lina Jin, Tianyu Feng, Mengzi Sun, Pingping Zheng, Kexin Li, Yan Yao, Min Wang
Rok vydání: 2020
Předmět:
Zdroj: Genomics. 112:2302-2308
ISSN: 0888-7543
DOI: 10.1016/j.ygeno.2020.01.001
Popis: Background Ischemic stroke (IS) was a significant public health concern and long-chain noncoding RNAs (lncRNAs) were gaining particular importance in stroke biology, however, the potential mechanism of lncRNAs in IS was not fully understood. Methods In this study, three diagnosed patients with IS and three controls were selected to establish the lncRNA library. Weighted gene co-expression network analysis (WGCNA) was applied to screen key lncRNA modules associated with IS. The key lncRNAs were identified by module membership (MM) and gene significance (GS). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways and protein-protein interaction (PPI) network method was used to identify the key genes. Results A total of 3627 lncRNAs were investigated, followed by an analysis of 17 modules, and only one module was highly associated with the IS. The top 10 lncRNAs were identified based on GS and MM. KEGG pathways analysis revealed the top two pathways of the Human T cell Lymphotropic Virus-1 (HTLV-1) infection and the mTOR signaling pathway might influence the progress of IS. Further, genes meeting the top two degree (AKT1 and MAPK14) were selected as the hub genes in the PPI network. Conclusion To summarize, this study identified the key pathways and genes, which might serve as biomarkers and targets for precise diagnosis and treatment of IS in the future.
Databáze: OpenAIRE
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