AUTHOR=Sun Hongwei , Xu Jia , Hu Bifeng , Liu Yue , Zhai Yun , Sun Yanyan , Sun Hongwei , Li Fang , Wang Jiamin , Feng Anqi , Tang Ying , Zhao Jingbo 

TITLE=Association of DNA Methylation Patterns in 7 Novel Genes With Ischemic Stroke in the Northern Chinese Population

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.844141

DOI=10.3389/fgene.2022.844141

ISSN=1664-8021

ABSTRACT=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). 
Conclusions—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.