Wang Tianfeng, Xu Si, Liu Li, Li Shuang, Zhang Huixue, Lu Xiaoyu, Kong Xiaotong, Li Danyang, Wang Jianjian, Wang Lihua
Department of Neurology, The Second Affiliated Hospital of Harbin Medical University Harbin 150081, Heilongjiang, China.
Am J Transl Res. 2022 Feb 15;14(2):772-787. eCollection 2022.
Multiple sclerosis (MS) is an autoimmune neuroinflammatory disease of the nervous system. However, the precise molecular mechanisms underlying MS have yet to be fully elucidated. In this study, our aim was to provide novel insight into the pathogenesis of MS and provide a resource for identifying new biomarkers and therapeutics for MS.
In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs). Next, we constructed a protein-protein interaction (PPI) network and a MS-specific ceRNA network (MCEN) by integrating expression profiles, interaction pairs of mRNA-miRNAs and lncRNA-miRNAs. Then, according to the modular structure of the PPI network, we identified hub DEmRNAs and generated a ceRNA subnetwork so that we could analyze the key lncRNAs that were associated with MS.
We first identified 4 modules by constructing a PPI network using DEmRNAs. Functional enrichment analysis showed these modules were enriched in immune-related pathways. Then, we constructed the MCEN and the hub gene-associated ceRNA subnetwork using a comprehensive computational approach. We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork. Finally, by analyzing LINC00649-miR-1275-CD20, we identified 6 drugs that may represent novel drugs for MS.
Collectively, our results provide novel insight for the discovery of biomarkers and therapeutics for MS and provide a suitable foundation from which to design future investigations of the pathogenic mechanisms associated with MS.
多发性硬化症（MS）是一种神经系统的自身免疫性神经炎症性疾病。然而，MS潜在的精确分子机制尚未完全阐明。在本研究中，我们的目的是为MS的发病机制提供新的见解，并为鉴定MS的新生物标志物和治疗方法提供资源。
在本研究中，我们分析了从基因表达综合数据库（GEO）下载的MS患者样本的基因表达谱（GSE21942）和微小RNA（miRNA）表达谱（GSE61741），并鉴定了差异表达的信使核糖核酸（mRNAs）和miRNAs（DEmRNAs、DEmiRNAs）。接下来，我们通过整合表达谱、mRNA-miRNA和长链非编码RNA（lncRNA）-miRNA的相互作用对，构建了蛋白质-蛋白质相互作用（PPI）网络和MS特异性竞争性内源RNA网络（MCEN）。然后，根据PPI网络的模块结构，我们鉴定了枢纽DEmRNAs并生成了一个ceRNA子网，以便我们能够分析与MS相关的关键lncRNAs。
我们首先使用DEmRNAs构建PPI网络，鉴定出4个模块。功能富集分析表明这些模块在免疫相关途径中富集。然后，我们使用综合计算方法构建了MCEN和枢纽基因相关的ceRNA子网。我们鉴定出三个关键lncRNAs（LINC00649、TP73-AS1和MALAT1），并在子网内进一步鉴定了关键lncRNA介导的ceRNAs。最后，通过分析LINC00649-miR-1275-CD20，我们鉴定出6种可能代表MS新型药物的药物。
总体而言，我们的结果为MS生物标志物和治疗方法的发现提供了新的见解，并为设计未来与MS相关致病机制的研究提供了合适的基础。
