Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking

Abstract

Abstract Background Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). Results We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the “immunosuppression” pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. Conclusions In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.