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阿尔茨海默病中的微小RNA-靶标相互作用调控网络

MicroRNA-Target Interaction Regulatory Network in Alzheimer's Disease.

作者信息

Turk Aleksander, Kunej Tanja, Peterlin Borut

机构信息

Department of Animal Science, Biotechnical Faculty, University of Ljubljana, 1230 Domžale, Slovenia.

Clinical Institute of Genomic Medicine, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia.

出版信息

J Pers Med. 2021 Dec 2;11(12):1275. doi: 10.3390/jpm11121275.

Abstract

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia; however, early diagnosis of the disease is challenging. Research suggests that biomarkers found in blood, such as microRNAs (miRNA), may be promising for AD diagnostics. Experimental data on miRNA-target interactions (MTI) associated with AD are scattered across databases and publications, thus making the identification of promising miRNA biomarkers for AD difficult. In response to this, a list of experimentally validated AD-associated MTIs was obtained from miRTarBase. Cytoscape was used to create a visual MTI network. STRING software was used for protein-protein interaction analysis and mirPath was used for pathway enrichment analysis. Several targets regulated by multiple miRNAs were identified, including: , , , , , and . The miRNA with the highest numbers of interactions in the network were: miR-9, miR-16, miR-34a, miR-106a, miR-107, miR-125b, miR-146, and miR-181c. The analysis revealed seven subnetworks, representing disease modules which have a potential for further biomarker development. The obtained MTI network is not yet complete, and additional studies are needed for the comprehensive understanding of the AD-associated miRNA targetome.

摘要

阿尔茨海默病(AD)是一种进行性神经退行性疾病,也是痴呆最常见的病因;然而,该疾病的早期诊断具有挑战性。研究表明,血液中发现的生物标志物,如微小RNA(miRNA),可能有望用于AD的诊断。与AD相关的miRNA-靶标相互作用(MTI)的实验数据分散在数据库和出版物中,因此难以识别有前景的AD相关miRNA生物标志物。针对这一情况,从miRTarBase获得了一份经实验验证的AD相关MTI列表。利用Cytoscape创建了一个可视化的MTI网络。使用STRING软件进行蛋白质-蛋白质相互作用分析,使用mirPath进行通路富集分析。鉴定出了几个受多个miRNA调控的靶标,包括: , , , , ,和 。网络中相互作用数量最多的miRNA为:miR-9、miR-16、miR-34a、miR-106a、miR-107、miR-125b、miR-146和miR-181c。分析揭示了七个子网,代表了具有进一步开发生物标志物潜力的疾病模块。所获得的MTI网络尚未完整,需要进一步的研究来全面了解与AD相关的miRNA靶标组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f085/8708198/a3a852a3deff/jpm-11-01275-g001.jpg

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