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通过异常甲基化差异表达基因与ceRNA网络的整合分析鉴定重症肌无力中的LINC00173

Identification of LINC00173 in Myasthenia Gravis by Integration Analysis of Aberrantly Methylated- Differentially Expressed Genes and ceRNA Networks.

作者信息

Xu Si, Wang Tianfeng, Lu Xiaoyu, Zhang Huixue, Liu Li, Kong Xiaotong, Li Shuang, Wang Xu, Gao Hongyu, Wang Jianjian, Wang Lihua

机构信息

Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.

出版信息

Front Genet. 2021 Sep 16;12:726751. doi: 10.3389/fgene.2021.726751. eCollection 2021.

DOI:10.3389/fgene.2021.726751
PMID:34603387
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8481885/
Abstract

Myasthenia gravis (MG) is an autoimmune disease associated with autoantibody production that leads to skeletal muscle weakness. The molecular mechanisms underlying MG are not fully understood. We analyzed the gene expression profile (GSE85452) and methylation profile (GSE85647) of MG samples from the GEO database to identify aberrantly methylated-differentially expressed genes. By integrating the datasets, we identified 143 hypermethylation-low expression genes and 91 hypomethylation-high expression genes. Then we constructed PPI network and ceRNA networks by these genes. Phosphatase and tensin homolog (PTEN) and Abelson tyrosine-protein kinase (ABL)1 were critical genes in both PPI networks and ceRNA networks. And potential MG associated lncRNAs were selected by comprehensive analysis of the critical genes and ceRNA networks. In the hypermethylation-low expression genes associated ceRNA network, sirtuin (SIRT)1 was the most important gene and the lncRNA HLA complex (HC) P5 had the highest connection degree. Meanwhile, PTEN was the most important gene and the lncRNA LINC00173 had the highest connection degree in the hypomethylation-high expression genes associated ceRNA network. LINC00173 was validated to be upregulated in MG patients by qRT-PCR ( = 0.005), which indicated LINC00173 might be a potential biomarker for MG. These results provide a basis for future studies on the molecular pathogenesis of MG.

摘要

重症肌无力(MG)是一种与自身抗体产生相关的自身免疫性疾病,可导致骨骼肌无力。MG潜在的分子机制尚未完全明确。我们分析了来自基因表达综合数据库(GEO)的MG样本的基因表达谱(GSE85452)和甲基化谱(GSE85647),以鉴定异常甲基化的差异表达基因。通过整合数据集,我们鉴定出143个高甲基化低表达基因和91个低甲基化高表达基因。然后我们利用这些基因构建了蛋白质-蛋白质相互作用(PPI)网络和竞争性内源性RNA(ceRNA)网络。磷酸酶和张力蛋白同源物(PTEN)以及阿贝尔森酪氨酸蛋白激酶(ABL)1在PPI网络和ceRNA网络中均为关键基因。通过对关键基因和ceRNA网络的综合分析,筛选出了潜在的与MG相关的长链非编码RNA(lncRNA)。在与高甲基化低表达基因相关的ceRNA网络中,沉默调节蛋白(SIRT)1是最重要的基因,lncRNA HLA复合体(HC)P5的连接度最高。同时,在与低甲基化高表达基因相关的ceRNA网络中,PTEN是最重要的基因,lncRNA LINC00173的连接度最高。通过实时定量逆转录聚合酶链反应(qRT-PCR)验证,MG患者中LINC00173表达上调(P = 0.005),这表明LINC00173可能是MG的潜在生物标志物。这些结果为未来MG分子发病机制的研究提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acfc/8481885/e32f4c450201/fgene-12-726751-g007.jpg
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