Chi Jieshan, Xie Qizhi, Jia Jingjing, Liu Xiaoma, Sun Jingjing, Deng Yuanfei, Yi Li
Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, China.
Department of Clinical Medicine, Shantou University Medical College, Shantou, China.
Front Aging Neurosci. 2018 Jun 18;10:178. doi: 10.3389/fnagi.2018.00178. eCollection 2018.
Parkinson's disease (PD) is a quite common neurodegenerative disorder with a prevalence of approximately 1:800-1,000 in subjects over 60 years old. The aim of our study was to determine the candidate target genes in PD through meta-analysis of multiple gene expression arrays datasets and to further combine mRNA and miRNA expression analyses to identify more convincing biological targets and their regulatory factors. Six included datasets were obtained from the Gene Expression Omnibus database by systematical search, including five mRNA datasets (150 substantia nigra samples in total) and one miRNA dataset containing 32 peripheral blood samples. A chip meta-analysis of five microarray data was conducted by using the metaDE package and 94 differentially expressed (DE) mRNAs were comprehensively obtained. And 19 deregulated DE miRNAs were obtained through the analysis of one miRNAs dataset by Qlucore Omics Explorer software. An interaction network formed by DE mRNAs, DE miRNAs, and important pathways was discovered after we analyzed the functional enrichment, protein-protein interactions, and miRNA targetome prediction analysis. In conclusion, this study suggested that five significantly downregulated mRNAs (MAPK8, CDC42, NDUFS1, COX4I1, and SDHC) and three significantly downregulated miRNAs (miR-126-5p, miR-19-3p, and miR-29a-3p) were potentially useful diagnostic markers in clinic, and lipid metabolism (especially non-alcoholic fatty liver disease pathway) and mitochondrial dysregulation may be the keys to biochemically detectable molecular defects. However, the role of these new biomarkers and molecular mechanisms in PD requires further experiments and and further clinical evidence.
帕金森病(PD)是一种相当常见的神经退行性疾病,在60岁以上的人群中患病率约为1:800 - 1000。我们研究的目的是通过对多个基因表达阵列数据集进行荟萃分析来确定帕金森病的候选靶基因,并进一步结合mRNA和miRNA表达分析,以识别更具说服力的生物学靶点及其调控因子。通过系统搜索从基因表达综合数据库获得了六个纳入数据集,包括五个mRNA数据集(总共150个黑质样本)和一个包含32个外周血样本的miRNA数据集。使用metaDE软件包对五个微阵列数据进行芯片荟萃分析,全面获得了94个差异表达(DE)mRNA。通过Qlucore Omics Explorer软件对一个miRNA数据集进行分析,获得了19个失调的DE miRNA。在我们对功能富集、蛋白质 - 蛋白质相互作用和miRNA靶标预测分析后,发现了由DE mRNA、DE miRNA和重要通路形成的相互作用网络。总之,本研究表明五个显著下调的mRNA(MAPK8、CDC42、NDUFS1、COX4I1和SDHC)和三个显著下调的miRNA(miR - 126 - 5p、miR - 19 - 3p和miR - 29a - 3p)可能是临床上有用的诊断标志物,脂质代谢(特别是非酒精性脂肪性肝病通路)和线粒体失调可能是生化可检测分子缺陷的关键。然而,这些新生物标志物和分子机制在帕金森病中的作用需要进一步的实验和临床证据。