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Competitive Endogenous RNA Network and Pathway-Based Analysis of LncRNA Single-Nucleotide Polymorphism in Myasthenia Gravis

Scientific Reports(2021)

Department of Neurology

Cited 4|Views21
Abstract
Myasthenia gravis (MG) is a complex neurological autoimmune disease with a pathogenetic mechanism that has yet to be elucidated. Emerging evidence has revealed that genes, non-coding RNAs and genetic variants play significant roles in the pathogenesis of MG. However, the molecular mechanisms of single nucleotide polymorphisms (SNPs) located on lncRNAs could disturb lncRNA-mediated ceRNA regulatory functions still unclear in MG. In this study, we collated 276 experimentally confirmed MG risk genes and 192 MG risk miRNAs. We then constructed a lncRNA-mediated ceRNA network for MG based on multi-step computational strategies. Next, we systematically integrated risk pathways and identified candidate SNPs in lncRNAs for MG based on data acquired from public databases. In addition, we constructed a pathway-based lncRNA-SNP mediated network (LSPN) that contained 128 lncRNAs targeting 8 MG risk pathways. By analyzing network, we propose a latent mechanism for how the "lncRNA-SNP-mRNA-pathway" axis affects the pathogenesis of MG. Moreover, 25 lncRNAs and 51 SNPs on lncRNAs were extracted from the "lncRNA-SNP-mRNA-pathway" axis. Finally, functional analyses demonstrated lncRNA-SNPs mediated ceRNA regulation pairs associated with MG participated in the MAPK signaling pathway. In summary, we constructed MG-specific lncRNA-SNPs mediated ceRNA regulatory networks based on pathway in the present study, which was helpful to elucidate the roles of lncRNA-SNPs in the pathogenesis of MG and provide novel insights into mechanism of lncRNA-SNPs as potential genetic risk biomarkers of MG.
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Key words
Data mining,Neurological disorders,Science,Humanities and Social Sciences,multidisciplinary
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