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首页> 外文期刊>BMC Medical Genomics >A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson’s disease
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A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson’s disease

机译：对公共微阵列数据的荟萃分析确定了帕金森氏病的生物调控网络

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Parkinson’s disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation. We examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network. Our results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3′-untranslated region of genes and are controlled by several miRNAs. Our study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our study can determine whether a genetic variant is associated with PD. Overall, these findings will help guide our study of the complex molecular mechanism of PD.
机译：帕金森氏病（PD）是由环境和遗传因素引起的长期退化性疾病。控制PD进程和发展的基因网络及其调控因子需要进一步阐明。我们通过荟萃分析检查了几种PD血液和黑质（SN）微阵列数据集中的常见差异表达基因（DEG）。此外，我们使用GCBI从常见的DEG中筛选了PD特异性基因。接下来，我们使用了一系列生物信息学软件来分析与常见的PD特异性基因相关的miRNA，lncRNA和SNP，然后确定mTF-miRNA-gene-gTF网络。我们的研究结果确定了PD血液研究中的36种常见DEG和PD SN研究中的17种常见DEG，并且先前已知其中5个基因与PD相关。与常见的PD特异性基因相关的调控miRNA的进一步研究显示，在我们的研究中有14种PD特异性miRNA。对有关PD特定基因的mTF-miRNA-gTF网络的分析揭示了两个前馈回路：一个涉及SPRK2基因hsa-miR-19a-3p和SPI1，另一个涉及SPRK2基因hsa-miR。 -17-3p和SPI。长期的非编码RNA（lncRNA）介导的调控网络确定了与PD特异性基因和PD特异性miRNA相关的lncRNA。此外，PD特异性基因的单核苷酸多态性（SNP）分析确定了两个重要的SNP，神经退行性疾病特异性基因的SNP分析确定了七个重要的SNP。这些SNP中的大多数都存在于基因的3'-非翻译区，并受几种miRNA的控制。我们的研究确定了PD患者中共53个常见的DEG，而血液和大脑数据集中的健康对照组与这些健康人相比，其中五个基因以前与PD相关。监管网络分析确定了PD特异性miRNA，相关的长非编码RNA和前馈环，这些有助于我们对PD潜在机制的理解。在我们的研究中鉴定出的SNP可以确定遗传变异是否与PD相关。总体而言，这些发现将有助于指导我们对PD复杂分子机制的研究。

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