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=13
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).
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.