Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530022, China.
Maternal and Child Health Hospital and Obstetrics and Gynecology Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi 530003, China.
Biomed Res Int. 2020 Feb 12;2020:8047146. doi: 10.1155/2020/8047146. eCollection 2020.
The present study identified methylation patterns of schizophrenia- (SCZ-) related genes in different brain regions and used them to construct a novel DNA methylation-based SCZ diagnostic model.
Four DNA methylation datasets representing different brain regions were downloaded from the Gene Expression Omnibus. The common differentially methylated genes (CDMGs) in all datasets were identified to perform functional enrichment analysis. The differential methylation sites of 10 CDMGs involved in the largest numbers of neurological or psychiatric-related biological processes were used to construct a DNA methylation-based diagnostic model for SCZ in the respective datasets.
A total of 849 CDMGs were identified in the four datasets, but the methylation sites as well as degree of methylation differed across the brain regions. Functional enrichment analysis showed CDMGs were significantly involved in biological processes associated with neuronal axon development, intercellular adhesion, and cell morphology changes and, specifically, in PI3K-Akt, AMPK, and MAPK signaling pathways. Four DNA methylation-based classifiers for diagnosing SCZ were constructed in the four datasets, respectively. The sample recognition efficiency of the classifiers showed an area under the receiver operating characteristic curve of 1.00 in three datasets and >0.9 in one dataset.
DNA methylation patterns in SCZ vary across different brain regions, which may be a useful epigenetic characteristic for diagnosing SCZ. Our novel model based on SCZ-gene methylation shows promising diagnostic power.
本研究鉴定了与精神分裂症（SCZ）相关基因在不同脑区的甲基化模式，并利用这些模式构建了一种新的基于 DNA 甲基化的 SCZ 诊断模型。
从基因表达综合数据库中下载了四个代表不同脑区的 DNA 甲基化数据集。鉴定所有数据集中共有的差异甲基化基因（CDMGs），以进行功能富集分析。使用涉及最多神经或精神疾病相关生物学过程的 10 个 CDMG 的差异甲基化位点，在各自的数据集中构建基于 DNA 甲基化的 SCZ 诊断模型。
在四个数据集中共鉴定出 849 个 CDMGs，但不同脑区的甲基化位点和甲基化程度存在差异。功能富集分析表明，CDMGs 显著参与了与神经元轴突发育、细胞间黏附以及细胞形态变化相关的生物学过程，特别是与 PI3K-Akt、AMPK 和 MAPK 信号通路相关。在四个数据集分别构建了四个基于 DNA 甲基化的 SCZ 分类器。分类器的样本识别效率在三个数据集中的受试者工作特征曲线下面积为 1.00，在一个数据集中>0.9。
SCZ 在不同脑区的 DNA 甲基化模式存在差异，这可能是诊断 SCZ 的一种有用的表观遗传特征。我们基于 SCZ 基因甲基化的新型模型显示出有前景的诊断能力。
