Tobacco smoke exposure dramatically alters DNA methylation in blood cells and may mediate smoking-associated complex diseases through effects on immune cell function. However, knowledge of smoking effects in specific leukocyte subtypes is limited. To better characterize smoking–associated methylation changes in whole blood and leukocyte subtypes, we used Illumina 450K arrays and Reduced Representation Bisulfite Sequencing (RRBS) to assess genome-wide DNA methylation. Differential methylation analysis in whole blood DNA from 172 smokers and 81 nonsmokers revealed 738 CpGs, including 616 previously unreported CpGs, genome-wide significantly associated with current smoking (p <1.2x10-7, Bonferroni correction). Several CpGs (MTSS1, NKX6-2, BTG2) were associated with smoking duration among heavy smokers (>22 cigarettes/day, n = 86) which might relate to long-term heavy-smoking pathology. In purified leukocyte subtypes from an independent group of 20 smokers and 14 nonsmokers we further examined methylation and gene expression for selected genes among CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, and CD2+ T cells. In 10 smokers and 10 nonsmokers we used RRBS to fine map differential methylation in CD4+ T cells, CD8+ T cells, CD14+, CD15+, CD19+, and CD56+ natural killer cells. Distinct cell-type differences in smoking-associated methylation and gene expression were identified. AHRR (cg05575921), ALPPL2 (cg21566642), GFI1 (cg09935388), IER3 (cg06126421) and F2RL3 (cg03636183) showed a distinct pattern of significant smoking-associated methylation differences across cell types: granulocytes> monocytes>> B cells. In contrast GPR15 (cg19859270) was highly significant in T and B cells and ITGAL (cg09099830) significant only in T cells. Numerous other CpGs displayed distinctive cell-type responses to tobacco smoke exposure that were not apparent in whole blood DNA. Assessing the overlap between these CpG sites and differential methylated regions (DMRs) with RRBS in 6 cell types, we confirmed cell-type specificity in the context of DMRs. We identified new CpGs associated with current smoking, pack-years, duration, and revealed unique profiles of smoking-associated DNA methylation and gene expression among immune cell types, providing potential clues to hematopoietic lineage-specific effects in disease etiology.

The most common form of genetic variation, single nucleotide polymorphisms or SNPs, can affect the way an individual responds to the environment and modify disease risk. Although most of the millions of SNPs have little or no effect on gene regulation and protein activity, there are many circumstances where base changes can have deleterious effects. Non-synonymous SNPs that result in amino acid changes in proteins have been studied because of their obvious impact on protein activity. It is well known that SNPs within regulatory regions of the genome can result in disregulation of gene transcription. However, the impact of SNPs located in putative regulatory regions, or rSNPs, is harder to predict for two primary reasons. First, the mechanistic roles of non-coding genomic sequence remain poorly defined. Second, experimental validation of the functional consequences of rSNPs is often slow and laborious. In this review, we summarize traditional and novel methodologies for candidate rSNPs selection, in particular in silico techniques that aid in candidate rSNP selection. Additionally we will discuss molecular biological techniques that assess the impact of rSNPs on binding of regulatory machinery, as well as functional consequences on transcription. Standard techniques such as EMSA and luciferase reporter constructs are still widely used to assess effects of rSNPs on binding and gene transcription; however, these protocols are often bottlenecks in the discovery process. Therefore, we highlight novel and developing high-throughput protocols that promise to aid in shortening the process of rSNP validation. Given the large amount of genomic information generated from a multitude of re-sequencing and genome-wide SNP array efforts, future focus should be to develop validation techniques that will allow greater understanding of the impact these polymorphisms have on human health and disease.

Background Tobacco smoke contains numerous agonists of the aryl-hydrocarbon receptor (AhR) pathway, and activation of the AhR pathway was shown to promote atherosclerosis in mice. Intriguingly, cigarette smoking is most strongly and robustly associated with DNA modifications to an AhR pathway gene, the aryl-hydrocarbon receptor repressor (AHRR). We hypothesized that altered AHRR methylation in monocytes, a cell type sensitive to cigarette smoking and involved in atherogenesis, may be a part of the biological link between cigarette smoking and atherosclerosis. Methods and Results DNA methylation profiles of AHRR in monocytes (542 CpG sites ± 150kb of AHRR, using Illumina 450K array) were integrated with smoking habits and ultrasound-measured carotid plaque scores from 1,256 participants of the Multi-Ethnic Study of Atherosclerosis (MESA). Methylation of cg05575921 significantly associated (p = 6.1×10−134) with smoking status (current vs. never). Novel associations between cg05575921 methylation and carotid plaque scores (p = 3.1×10−10) were identified, which remained significant in current and former smokers even after adjusting for self-reported smoking habits, urinary cotinine, and well-known CVD risk factors. This association replicated in an independent cohort using hepatic DNA (n = 141). Functionally, cg05575921 was located in a predicted gene expression regulatory element (enhancer), and had methylation correlated with AHRR mRNA profiles (p = 1.4×10−17) obtained from RNA sequencing conducted on a subset (n = 373) of the samples. Conclusions These findings suggest AHRR methylation may be functionally related to AHRR expression in monocytes, and represents a potential biomarker of subclinical atherosclerosis in smokers.

The p53 tumor suppressor protein is a master regulatory transcription factor that coordinates cellular responses to DNA damage and cellular stress. Besides mutations in p53, or in proteins involved in the p53 response pathway, genetic variation in promoter response elements (REs) of p53 target genes is expected to alter biological responses to stress. To identify SNPs in p53 REs that may modify p53-controlled gene expression, we developed an approach that combines a custom bioinformatics search to identify candidate SNPs with functional yeast and mammalian cell assays to assess their effect on p53 transactivation. Among Ϸ2 million human SNPs, we identified >200 that seem to disrupt functional p53 REs. Eight of these SNPs were evaluated in functional assays to determine both the activity of the putative RE and the impact of the candidate SNPs on transactivation. All eight candidate REs were functional, and in every case the SNP pair exhibited differential transactivation capacities. Additionally, six of the eight genes adjacent to these SNPs are induced by genotoxic stress or are activated directly by transfection with p53 cDNA. Thus, this strategy efficiently identifies SNPs that may differentially affect gene expression responses in the p53 regulatory pathway.bioinformatics ͉ single nucleotide polymorphism ͉ yeast ͉ regulatory sequences ͉ gene expression