Research Paper Volume 11, Issue 5 pp 1486—1500

Integrated DNA methylation and gene expression analysis in the pathogenesis of coronary artery disease

Liu Miao 1, , Rui-Xing Yin 1, 2, 3, , Qing-Hui Zhang 1, , Xi-Jiang Hu 1, , Feng Huang 1, 2, 3, , Wu-Xian Chen 1, , Xiao-Li Cao 2, 3, 4, , Jin-Zhen Wu 1, ,

  • 1 Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning 530021, Guangxi, China
  • 2 Guangxi Key Laboratory Base of Precision Medicine in Cardio-cerebrovascular Disease Control and Prevention, Nanning 530021, Guangxi, China
  • 3 Guangxi Clinical Research Center for Cardio-cerebrovascular Diseases, Nanning 530021, Guangxi, China
  • 4 Department of Neurology, the First Affiliated Hospital, Guangxi Medical University, Nanning 530021, Guangxi, China

received: December 6, 2018 ; accepted: February 22, 2019 ; published: March 7, 2019 ;

https://doi.org/10.18632/aging.101847
How to Cite

Copyright: Miao et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

To evaluate DNA methylation sites and gene expression associated with coronary artery disease (CAD) and the possible pathological mechanism involved, we performed (1) genome-wide DNA methylation and mRNA expression profiling in peripheral blood datasets from the Gene Expression Omnibus repository of CAD samples and controls; (2) functional enrichment analysis and differential methylation gene regulatory network construction; (3) validation tests of 11 differential methylation positions of interest and the corresponding gene expression; and (4) correlation analysis for DNA methylation and mRNA expression data. A total of 669 differentially expressed mRNAs were matched to differentially methylated genes. After disease ontology, Kyoto Encyclopedia of Genes and Genomes pathway, gene ontology, protein-protein interaction and network construction and module analyses, 11 differentially methylated positions (DMPs) corresponding to 11 unique genes were observed: BDNF – cg26949694, BTRC - cg24381155, CDH5 - cg02223351, CXCL12 - cg11267527, EGFR - cg27637738, IL-6 - cg13104385, ITGB1 - cg20545410, PDGFRB - cg25613180, PIK3R1- cg00559992, PLCB1 - cg27178677 and PTPRC - cg09247619. After validation tests of 11 DMPs of interest and the corresponding gene expression, we found that CXCL12 was less hypomethylated in the CAD group, whereas the relative expression of ITGB1, PDGFRB and PIK3R1 was lower in CAD samples, and CXCL12 and ITGB1 methylation was negatively correlated with their expression. This study identified the correlation between DNA methylation and gene expression and highlighted the importance of CXCL12 in CAD pathogenesis.

Abbreviations

Apo: apolipoprotein; BDNF: brain-derived neurotrophic factor; BMI: body mass index; BTRC: beta-transducing repeat containing E3 ubiquitin protein ligase; CAD: coronary artery disease; CAMs: Cell adhesion molecules; CDH5: cadherin 5; CXCL12: C-X-C motif chemokine ligand 12; DEGs: differentially expressed genes; DMaGs: differential methylation and matched differential expression of genes; DMGs: differentially methylated genes; DMPs: differentially methylated positions; DO: disease ontology; EGFR: epidermal growth factor receptor; FDR: false discovery rate; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GEO: Gene Expression Omnibus; GO: gene ontology; GWAS: Genome-wide association study; HDL-C: high-density lipoprotein cholesterol; IL-6: interleukin-6; ITGB1: integrin subunit beta 1; KEGG: Kyoto Encyclopedia of Genes and genomes; LDL-C: low-density lipoprotein cholesterol; MAPK: Mitogen-activated protein kinase; MCODE: molecular complex detection; MI: myocardial infarction; M-MLV: moloney murine leukemia virus; MSP: methylationspecific PCR; PBMCs: peripheral blood mononuclear cells; PCA: principal component analysis; PDGFRB: platelet derived growth factor receptor beta; PI3K-Akt: phosphatidylinositol 3' -kinase-Akt; PIK3R1: phosphoinositide-3-kinase regulatory subunit 1; PLCB1: phospholipase C beta 1; PPI: protein-protein interaction; PTPRC: protein tyrosine phosphatase receptor type C; qRT-PCR: quantitative real-time PCR; RMA: robust multi-array; SPCs: smooth muscle progenitor cells; TC: total cholesterol; TG: triglyceride; TRP: transient receptor potential.