Qian Kai, Xu Jia-Xin, Deng Yi, Peng Hao, Peng Jun, Ou Chun-Mei, Liu Zu, Jiang Li-Hong, Tai Yong-Hang
Faculty of Life and Biotechnology, Kunming University of Science and Technology, Kunming, China.
Department of Thoracic Surgery, Institute of The First People's Hospital of Yunnan Province, Kunming, China.
Gland Surg. 2020 Dec;9(6):1933-1944. doi: 10.21037/gs-20-39.
Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disorder causing muscle weakness and characterized by a defect in synaptic transmission at the neuromuscular junction. The pathogenesis of this disease remains unclear. We aimed to predict the key signaling pathways of genetic variants and miRNAs in the pathogenesis of MG, and identify the key genes among them.
We searched published information regarding associated single nucleotide polymorphisms (SNPs) and differentially-expressed miRNAs in MG cases. We search of SNPs and miRNAs in literature databases about MG, then we used bioinformatic tools to predict target genes of miRNAs. Moreover, functional enrichment analysis for key genes was carried out utilizing the Cytoscape-plugin, known as ClueGO. These key genes were mapped to STRING database to construct a protein-protein interaction (PPI) network. Then a miRNA-target gene regulatory network was established to screen key genes.
Five genes containing SNPs associated with MG risk were involved in the inflammatory bowel disease (IBD) signaling pathway, and was the key gene. and were predicted to be targeted by the 18 miRNAs and to act as the key genes in adherens, junctions, apoptosis, or cancer-related pathways respectively. These five key genes containing SNPs or targeted by miRNAs were found to be involved in negative regulation of T cell differentiation.
We speculate that SNPs cause the genes to be defective or the miRNAs to downregulate the factors that subsequently negatively regulate regulatory T cells and trigger the onset of MG.
重症肌无力（MG）是一种慢性自身免疫性神经肌肉疾病，可导致肌肉无力，其特征是神经肌肉接头处的突触传递存在缺陷。该疾病的发病机制尚不清楚。我们旨在预测基因变异和微小RNA（miRNA）在MG发病机制中的关键信号通路，并确定其中的关键基因。
我们检索了已发表的关于MG病例中相关单核苷酸多态性（SNP）和差异表达miRNA的信息。我们在关于MG的文献数据库中搜索SNP和miRNA，然后使用生物信息学工具预测miRNA的靶基因。此外，利用Cytoscape插件ClueGO对关键基因进行功能富集分析。将这些关键基因映射到STRING数据库以构建蛋白质-蛋白质相互作用（PPI）网络。然后建立miRNA-靶基因调控网络以筛选关键基因。
五个含有与MG风险相关SNP的基因参与炎症性肠病（IBD）信号通路，且 是关键基因。 和 分别被预测为18个miRNA的靶基因，并分别在黏着连接、凋亡或癌症相关通路中作为关键基因发挥作用。发现这五个含有SNP或被miRNA靶向的关键基因参与T细胞分化的负调控。
我们推测SNP导致基因缺陷或miRNA下调随后对调节性T细胞产生负调控并触发MG发病的因子。
