The pattern of lung function development from pre-adolescence to adulthood plays a significant role in the pathogenesis of respiratory diseases. Inconsistent findings in genetic studies on lung function trajectories, the importance of DNA methylation (DNA-M), and the critical role of adolescence in lung function development motivated the present study of pre-adolescent DNA-M with lung function trajectories. This study investigated epigenome-wide associations of DNA-M at cytosine-phosphate-guanine dinucleotide sites (CpGs) at childhood with lung function trajectories from childhood to young adulthood.

The extent to which genetic influences on cardiovascular disease risk are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits. We identified ten genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits after multiple-testing correction. Bivariate fine mapping provided evidence that the individual variants responsible for the observed effects on cardiovascular traits at the ADCY3 and ADIPOQ loci were potentially mediated through changes in DNA methylation, although we highlight that we are unable to reliably separate causality from horizontal pleiotropy. Estimates of causal effects were replicated with results from large-scale consortia. Genetic variants and CpG sites identified in this study were enriched for histone mark peaks in relevant tissue types and gene promoter regions. Integrating our results with expression quantitative trait loci data, we provide evidence that variation at these regulatory regions is likely to also influence gene expression levels at these loci.

We have undertaken a systematic Mendelian randomization (MR) study using methylation quantitative trait loci (meQTL) as genetic instruments to assess the relationship between genetic variation, DNA methylation and 139 complex traits. Using two-sample MR, we identified 1148 associations across 61 traits where genetic variants were associated with both proximal DNA methylation (i.e. cis-meQTL) and complex trait variation (P < 1.39 × 10-08). Joint likelihood mapping provided evidence that the genetic variant which influenced DNA methylation levels for 348 of these associations across 47 traits was also responsible for variation in complex traits. These associations showed a high rate of replication in the BIOS QTL and UK Biobank datasets for 14 selected traits, as 101 of the attempted 128 associations survived multiple testing corrections (P < 3.91 × 10-04). Integrating expression quantitative trait loci (eQTL) data suggested that genetic variants responsible for 306 of the 348 refined meQTL associations also influence gene expression, which indicates a coordinated system of effects that are consistent with causality. CpG sites were enriched for histone mark peaks in tissue types relevant to their associated trait and implicated genes were enriched across relevant biological pathways. Though we are unable to distinguish mediation from horizontal pleiotropy in these analyses, our findings should prove valuable in prioritizing candidate loci where DNA methylation may influence traits and help develop mechanistic insight into the aetiology of complex disease.

An adequate intake of vitamin B12 during pregnancy plays an important role in offspring neurodevelopment, potentially via epigenetic processes. We used a two-step Mendelian randomization approach to assess whether DNA methylation plays a mediating and causal role in associations between maternal vitamin B12 status and offspring's cognition. Firstly, we estimated the causal effect of maternal vitamin B12 levels on cord blood DNA methylation using the maternal FUT2 genotypes rs492602:A > G and rs1047781:A > T as proxies for circulating vitamin B12 levels in the Avon Longitudinal Study of Parents and Children (ALSPAC) and we tested the observed associations in a replication cohort. Secondly, we estimated the causal effect of DNA methylation on IQ using the offspring genotype at sites close to the methylated CpG site as a proxy for DNA methylation in ALSPAC and in a replication sample. The first step Mendelian randomization estimated that maternal vitamin B12 had a small causal effect on DNA methylation in offspring at three CpG sites, which was replicated for one of the sites. The second step Mendelian randomization found weak evidence of a causal effect of DNA methylation at two of these sites on childhood performance IQ which was replicated for one of the sites. The findings support a causal effect of maternal vitamin B12 levels on cord blood DNA methylation, and a causal effect of vitamin B12-responsive DNA methylation changes on children's cognition. Some limitations were identified and future studies using a similar approach should aim to overcome such issues.

Human height is strongly influenced by genetics but the contribution of modifiable epigenetic factors is under-explored, particularly in low and middle-income countries (LMIC). We investigate links between blood DNA methylation and child height in four LMIC cohorts (n = 1927) and identify a robust association at three CpGs in the suppressor of cytokine signaling 3 (SOCS3) gene which replicates in a high-income country cohort (n = 879). SOCS3 methylation (SOCS3m)-height associations are independent of genetic effects. Mendelian randomization analysis confirms a causal effect of SOCS3m on height. In longitudinal analysis, SOCS3m explains a maximum 9.5% of height variance in mid-childhood while the variance explained by height polygenic risk score increases from birth to 21 years. Children's SOCS3m is associated with prenatal maternal folate and socio-economic status. In-vitro characterization confirms a regulatory effect of SOCS3m on gene expression. Our findings suggest epigenetic modifications may play an important role in driving child height in LMIC.