Abstract：
This study employed systems biology and high-throughput technologies to analyze complex molecular components of MS pathophysiology, combining data from multiple omics sources to identify potential biomarkers and propose therapeutic targets and repurposed drugs for MS treatment. This study analyzed GEO microarray datasets and MS proteomics data using geWorkbench, CTD, and COREMINE to identify differentially expressed genes associated with MS disease. Protein-protein interaction networks were constructed using Cytoscape and its plugins, and functional enrichment analysis was performed to identify crucial molecules. A drug-gene interaction network was also created using DGIdb to propose medications. This study identified 592 differentially expressed genes (DEGs) associated with MS disease using GEO, proteomics, and text-mining datasets. 37 DEGs were found to be important by topographical network studies, and 6 were identified as the most significant for MS pathophysiology. Additionally, we proposed six drugs that target these key genes. Crucial molecules identified in this study were dysregulated in MS and likely play a key role in the disease mechanism, warranting further research. Additionally, we proposed repurposing certain FDA-approved drugs for MS treatment. Our in silico results were supported by previous experimental research on some of the target genes and drugs. SIGNIFICANCE: As the long-lasting investigations continue to discover new pathological territories in neurodegeneration, here we apply a systems biology approach to determine multiple sclerosis\'s molecular and pathophysiological origin and identify multiple sclerosis crucial genes that contribute to candidating new biomarkers and proposing new medications.
摘要：
本研究采用系统生物学和高通量技术来分析MS病理生理学的复杂分子成分，结合来自多个组学来源的数据，以确定潜在的生物标志物，并提出治疗靶标和用于MS治疗的药物。本研究使用geWorkbench分析了GEO微阵列数据集和MS蛋白质组学数据，CTD,和COREMINE鉴定与MS疾病相关的差异表达基因。使用Cytoscape及其插件构建蛋白质-蛋白质相互作用网络，并进行功能富集分析以鉴定关键分子。还使用DGIdb创建了药物-基因相互作用网络来提出药物。这项研究使用GEO鉴定了592个与MS疾病相关的差异表达基因(DEGs)，蛋白质组学，和文本挖掘数据集。通过地形网络研究发现37个DEG很重要，和6被确定为MS病理生理学最显著。此外,我们提出了针对这些关键基因的六种药物。在这项研究中确定的关键分子在MS中失调，并且可能在疾病机制中起关键作用。保证进一步的研究。此外,我们建议将某些FDA批准的药物重新用于MS治疗.我们的计算机模拟结果得到了先前对一些靶基因和药物的实验研究的支持。意义：随着长期的调查继续发现神经变性的新病理领域，在这里，我们应用系统生物学方法来确定多发性硬化症的分子和病理生理起源，并确定有助于候选新生物标志物和提出新药物的多发性硬化症关键基因。
