Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference.

Background: DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data.

Results: By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes.

Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions.

Background: Tobacco smoking is a major risk factor for atherosclerotic disease and has been associated with DNA methylation (DNAm) changes in blood cells. However, whether smoking influences DNAm in the diseased vascular wall is unknown but may prove crucial in understanding the pathophysiology of atherosclerosis. In this study, we associated current tobacco smoking to epigenome-wide DNAm in atherosclerotic plaques from patients undergoing carotid endarterectomy.

Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation.

X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males.

DNA methylation as a mediator of the association between prenatal adversity and risk factors for metabolic disease in adulthood.

Although it is assumed that epigenetic mechanisms, such as changes in DNA methylation (DNAm), underlie the relationship between adverse intrauterine conditions and adult metabolic health, evidence from human studies remains scarce. Therefore, we evaluated whether DNAm in whole blood mediated the association between prenatal famine exposure and metabolic health in 422 individuals exposed to famine in utero and 463 (sibling) controls. We implemented a two-step analysis, namely, a genome-wide exploration across 342,596 cytosine-phosphate-guanine dinucleotides (CpGs) for potential mediators of the association between prenatal famine exposure and adult body mass index (BMI), serum triglycerides (TG), or glucose concentrations, which was followed by formal mediation analysis.

Disease variants alter transcription factor levels and methylation of their binding sites.

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions.

Age-related accrual of methylomic variability is linked to fundamental ageing mechanisms.

Background: Epigenetic change is a hallmark of ageing but its link to ageing mechanisms in humans remains poorly understood. While DNA methylation at many CpG sites closely tracks chronological age, DNA methylation changes relevant to biological age are expected to gradually dissociate from chronological age, mirroring the increased heterogeneity in health status at older ages.

Results: Here, we report on the large-scale identification of 6366 age-related variably methylated positions (aVMPs) identified in 3295 whole blood DNA methylation profiles, 2044 of which have a matching RNA-seq gene expression profile.

An alternative approach to multiple testing for methylation QTL mapping reduces the proportion of falsely identified CpGs.

Introduction: An increasing number of studies investigates the influence of local genetic variation on DNA methylation levels, so-called in cis methylation quantitative trait loci (meQTLs). A common multiple testing approach in genome-wide cis meQTL studies limits the false discovery rate (FDR) among all CpG-SNP pairs to 0.05 and reports on CpGs from the significant CpG-SNP pairs.

MethylAid: visual and interactive quality control of large Illumina 450k datasets.

Unlabelled: The Illumina 450k array is a frequently used platform for large-scale genome-wide DNA methylation studies, i.e. epigenome-wide association studies.