The Second People's Hospital of Lishui, Lishui, 323000, China.
Cell Mol Biol (Noisy-le-grand). 2020 May 15;66(2):118-124.
In neurodegenerative disease, Parkinson's disease is the second most common one. Current demographic trends tell that by 2030, the risk of prevalence is close to 4% and the incidence is expected to double. Understanding the detailed process of Parkinson's disease can help us to figure out new biomarkers and candidate therapeutic targets for the diagnosis and progression of PD. This study is based on modularity for in-depth analysis and exploration of critical genes in the pathogenesis of Parkinson's disease, intended to identify the molecular processes of Parkinson's disease. According to the hypergeometric test, by performing differential analysis, enrichment analysis, co-expression module analysis, network connectivity analysis and finally, the ncRNA (non-coding RNA) and transcription factor that regulate the module were predicted. Based on the above methods, we obtained ten co-expression modules, including 2180 differential genes. Among them, RB1, IL7, and other genes were significantly differentially expressed in PD patients, and they had existing regulation in dysfunction modules, which was identified as Key genes in PD. The biological processes involved in the modular genes, for example, regulate lymphocyte activation, signal release, cellular calcium homeostasis, regulation of inflammatory responses, and regulation of exocytosis. This behavior significantly regulates signaling pathways such as cytokine-cytokine receptor interactions. Further, we identified ncRNA pivot including miR-25-3p. Also, transcription Factors pivot such as RELA, STAT1 significantly regulate dysfunction modules. This study can help to reveal all Parkinson's core dysfunction modules and potential regulatory factors as well as essential genes and the study assists to improve our understanding of its pathogenesis. The study can also be used to determine treatment goals and measure the effectiveness of interventions to provide predictive biomarkers and candidate therapeutic targets.
在神经退行性疾病中，帕金森病是第二常见的疾病。目前的人口趋势表明，到 2030 年，患病率的风险接近 4%，发病率预计将翻一番。了解帕金森病的详细发病过程有助于我们发现新的生物标志物和候选治疗靶点，用于 PD 的诊断和进展。本研究基于模块性，深入分析和探索帕金森病发病机制中的关键基因，旨在确定帕金森病的分子过程。根据超几何检验，通过进行差异分析、富集分析、共表达模块分析、网络连通性分析，最终预测调节模块的 ncRNA（非编码 RNA）和转录因子。基于上述方法，我们获得了十个共表达模块，包括 2180 个差异基因。其中，RB1、IL7 等基因在帕金森病患者中差异表达显著，且在功能失调模块中有现有的调节作用，被鉴定为 PD 的关键基因。模块基因涉及的生物学过程，例如，调节淋巴细胞激活、信号释放、细胞钙稳态、炎症反应调节和胞吐调节。这种行为显著调节细胞因子-细胞因子受体相互作用等信号通路。此外，我们还鉴定了 ncRNA 枢纽，包括 miR-25-3p。此外，转录因子枢纽，如 RELA、STAT1 显著调节功能失调模块。本研究有助于揭示所有帕金森核心功能失调模块和潜在的调节因子以及关键基因，有助于加深对其发病机制的理解。该研究还可用于确定治疗目标和衡量干预措施的效果，提供预测性生物标志物和候选治疗靶点。
