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基于ceRNA网络的基因组列线图的开发与验证,用于阻塞性睡眠呼吸暂停的综合分析

Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea.

作者信息

Liu Wang, Sun Xishi, Huang Jiewen, Zhang Jinjian, Liang Zhengshi, Zhu Jinru, Chen Tao, Zeng Yu, Peng Min, Li Xiongbin, Zeng Lijuan, Lei Wei, Cheng Junfen

机构信息

The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.

Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.

出版信息

Front Genet. 2023 Mar 10;14:1084552. doi: 10.3389/fgene.2023.1084552. eCollection 2023.

Abstract

Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA. We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes. We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes. Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.

摘要

一些与长链非编码RNA(lncRNA)相关的竞争性内源性RNA(ceRNA)被认为是阻塞性睡眠呼吸暂停(OSA)潜在的诊断和治疗生物标志物。我们旨在鉴定OSA发生发展过程中的潜在关键基因,这将为研究OSA潜在的分子机制以及OSA的诊断和治疗奠定基础。我们收集了OSA患者和健康对照者的血浆样本,使用芯片检测ceRNA。基于lncRNA的差异表达,我们鉴定了与lncRNA结合的微小RNA(miRNA)的靶基因。然后,我们构建了lncRNA相关的ceRNA网络,进行了功能富集分析和蛋白质-蛋白质相互作用分析,并对稳定关键基因的表达水平进行了内部和外部验证。接着,我们对稳定关键基因进行LASSO回归分析,选择相对显著的基因构建一个简单易用的列线图,对列线图进行验证,并构建关键基因的核心ceRNA子网。通过差异分析,我们成功鉴定出282个差异表达的lncRNA和380个差异表达的mRNA,并构建了一个由292个miRNA-lncRNA和41个miRNA-mRNA组成的OSA相关ceRNA网络。通过蛋白质-蛋白质相互作用分析和关键基因筛选,我们又获得了7个稳健的关键基因,即细胞周期蛋白D2(CCND2)、威尔姆斯瘤基因1(WT1)、E2F转录因子2(E2F2)、干扰素调节因子1(IRF1)、溴结构域蛋白2A(BAZ2A)、层粘连蛋白γ1(LAMC1)和Disabled-2蛋白(DAB2)。使用LASSO回归分析,我们创建了一个包含四个预测因子(CCND2、WT1、E2F2和IRF1)的列线图,其曲线下面积(AUC)为1。最后,我们构建了一个由74个miRNA-lncRNA节点和7个miRNA-mRNA节点组成的核心ceRNA子网。我们的研究为阐明lncRNA在OSA中的分子机制以及OSA的诊断和治疗提供了新的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f4f/10036397/6ba356730e0b/fgene-14-1084552-g001.jpg

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