Sepehrinezhad Ali, Shahbazi Ali, Bozorgmehr Ali, Kateb Babak, Yamamoto Vicky, Negah Sajad Sahab
Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran.
Neuroscience Research Center, Mashhad University of Medical Sciences, Mashhad 9919991766, Iran.
J Pers Med. 2022 Jun 26;12(7):1043. doi: 10.3390/jpm12071043.
There are no data available on the levels of genetic networks between obsessive-compulsive disorder (OCD) and multiple sclerosis (MS). To this point, we aimed to investigate common mechanisms and pathways using bioinformatics approaches to find novel genes that may be involved in the pathogenesis of OCD in MS. To obtain gene-gene interactions for MS and OCD, the STRING database was used. Cytoscape was then used to reconstruct and visualize graphs. Then, ToppGene and Enrichr were used to identify the main pathological processes and pathways involved in MS-OCD novel genes. Additionally, to predict transcription factors and microRNAs (miRNAs), the Enrichr database and miRDB database were used, respectively. Our bioinformatics analysis showed that the signal transducer and the activator of transcription 3 () and neurotrophic receptor tyrosine kinase 2 () genes had connections with 32 shared genes between MS and OCD. Furthermore, and had the greatest enrichment parameters (i.e., molecular function, cellular components, and signaling pathways) among ten hub genes. To summarize, data from our bioinformatics analysis showed that there was a significant overlap in the genetic components of MS and OCD. The findings from this study make two contributions to future studies. First, predicted mechanisms related to and in the context of MS and OCD can be investigated for pharmacological interventions. Second, predicted miRNAs related to and can be tested as biomarkers in MS with OCD comorbidity. However, our study involved bioinformatics research; therefore, considerable experimental work (e.g., postmortem studies, case-control studies, and cohort studies) will need to be conducted to determine the etiology of OCD in MS from a mechanistic view.
目前尚无关于强迫症(OCD)和多发性硬化症(MS)之间基因网络水平的数据。就此而言,我们旨在使用生物信息学方法研究共同的机制和途径,以寻找可能参与MS中OCD发病机制的新基因。为了获得MS和OCD的基因-基因相互作用,使用了STRING数据库。然后使用Cytoscape重建并可视化图形。接着,使用ToppGene和Enrichr来识别MS-OCD新基因所涉及的主要病理过程和途径。此外,分别使用Enrichr数据库和miRDB数据库来预测转录因子和微小RNA(miRNA)。我们的生物信息学分析表明,信号转导子和转录激活因子3()以及神经营养受体酪氨酸激酶2()基因与MS和OCD之间的32个共享基因有联系。此外,在十个枢纽基因中, 和 具有最大的富集参数(即分子功能、细胞成分和信号通路)。总之,我们生物信息学分析的数据表明,MS和OCD的遗传成分存在显著重叠。本研究的结果为未来的研究做出了两点贡献。首先,可以研究在MS和OCD背景下与 和 相关的预测机制,以进行药物干预。其次,与 和 相关的预测miRNA可以作为MS合并OCD的生物标志物进行测试。然而,我们的研究涉及生物信息学研究;因此,需要进行大量的实验工作(例如尸检研究、病例对照研究和队列研究),以便从机制角度确定MS中OCD的病因。