DataSheet3_Association of DNA Methylation Patterns in 7 Novel Genes With Ischemic Stroke in the Northern Chinese Population.PDF

Background: Ischemic stroke is a highly complex disorder. This study aims to identify novel methylation changes in ischemic stroke.
Methods: We carried out an epigenome-wide study of ischemic stroke using an Infinium HumanMethylation 850K array (cases:controls = 4:4). 10 CpG sites in 8 candidate genes from gene ontology analytics top-ranked pathway were selected to validate 850K BeadChip results (cases:controls = 20:20). We further qualified the methylation level of promoter regions in 8 candidate genes (cases:controls = 188:188). Besides, we performed subgroup analysis, dose-response relationship and diagnostic prediction polygenic model of candidate genes.
Results: In the discovery stage, we found 462 functional DNA methylation positions to be associated with ischemic stroke. Gene ontology analysis highlighted the “calcium-dependent cell-cell adhesion via plasma membrane cell adhesion molecules” item, including 8 candidate genes (CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB6/PCDHB9). In the replication stage, we identified 5 differentially methylated loci in 20 paired samples and 7 differentially methylated genes (CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB9) in 188 paired samples. Subgroup analysis showed that the methylation level of above 7 genes remained significantly different in the male subgroup, large-artery atherosclerosis subgroup and right hemisphere subgroup. The methylation level of each gene was grouped into quartiles, and Q4 groups of the 7 genes were associated with higher risk of ischemic stroke than Q1 groups (p < 0.05). Besides, the polygenic model showed high diagnostic specificity (0.8723), sensitivity (0.883), and accuracy (0.8777).
Conclusion: Our results demonstrate that DNA methylation plays a crucial part in ischemic stroke. The methylation of these 7 genes may be potential diagnostic biomarker for ischemic stroke.

背景：缺血性脑卒中（Ischemic stroke）是一类高度复杂的疾病。本研究旨在识别缺血性脑卒中中新型的甲基化改变。
方法：本研究采用Infinium HumanMethylation 850K芯片（Infinium HumanMethylation 850K array）开展缺血性脑卒中的表观全基因组研究，病例组与对照组样本量比例为4:4。从基因本体分析（Gene Ontology, GO）排名靠前的通路所涉及的8个候选基因中，选取10个CpG位点（CpG site）以验证850K BeadChip微珠芯片的检测结果，该验证阶段病例组与对照组样本量比例为20:20。进一步对8个候选基因的启动子区域甲基化水平进行定量检测，此阶段病例组与对照组样本量比例为188:188。此外，本研究还针对候选基因开展了亚组分析、剂量反应关系分析及诊断预测多基因模型构建。
结果：在发现阶段，本研究共筛选出462个与缺血性脑卒中相关的功能性DNA甲基化位点。基因本体分析聚焦于"经细胞膜细胞黏附分子介导的钙依赖性细胞间黏附"条目，该条目包含8个候选基因（CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB6/PCDHB9）。在复制阶段，本研究在20例配对样本中鉴定出5个差异甲基化位点，在188例配对样本中鉴定出7个差异甲基化基因（CDH2/PCDHB10/PCDHB11/PCDHB14/PCDHB16/PCDHB3/PCDHB9）。亚组分析显示，上述7个基因的甲基化水平在男性亚组、大动脉粥样硬化亚组及右半球亚组中仍存在显著差异。将每个基因的甲基化水平按四分位数分组后发现，7个基因的Q4组较Q1组缺血性脑卒中发病风险更高（P < 0.05）。此外，构建的多基因模型展现出较高的诊断特异性（0.8723）、灵敏度（0.883）及准确度（0.8777）。
结论：本研究结果证实DNA甲基化在缺血性脑卒中的发生发展中发挥关键作用。上述7个基因的甲基化修饰有望成为缺血性脑卒中潜在的诊断生物标志物（biomarker）。