DNA methylation analysis using bisulphite-based amplicon sequencing of individuals exposed to maternal tobacco use during pregnancy, and offspring conduct problems in childhood and adolescence.

Maternal tobacco smoking during pregnancy is a large driver of health inequalities and a higher prevalence of conduct problem (CP) has been observed in exposed offspring. Further, maternal tobacco use during pregnancy can also alter offspring DNA methylation. However, currently, limited molecular evidence has been found to support this observation. Thus we aim to examine the association between maternal tobacco use in pregnancy and offspring CP, to determine whether offspring CP is mediated by tobacco exposure-induced DNA methylation differences. Understanding the etiology of the association between maternal tobacco use and offspring CP will be crucial in the early identification and treatment of CP in children and adolescents. Here, a sub group of N =96 individuals was sourced from the Christchurch Health and Development Study, a longitudinal birth cohort studied for over 40 years in New Zealand. Whole blood samples underwent bisulphite-based amplicon sequencing at 10 loci known to play a role in neurodevelopment, or which had associations with CP phenotypes. We identified significant (P CYP1A1 , ASH2L and MEF2C in individuals with CP who were exposed to tobacco in utero . We conclude that environmentally-induced DNA methylation differences could play a role in the observed link between maternal tobacco use during pregnancy and childhood/adolescent CP. However, larger sample sizes are needed to produce an adequate amount of power to investigate this interaction further.

A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk.

Epidemiological and associative research from humans and animals identifies correlations between the environment and health impacts. The environment-health inter-relationship is effected through an individual's underlying genetic variation and mediated by mechanisms that include the changes to gene regulation that are associated with the diversity of phenotypes we exhibit. However, the causal relationships have yet to be established, in part because the associations are reduced to individual interactions and the combinatorial effects are rarely studied. This problem is exacerbated by the fact that our genomes are highly dynamic; they integrate information across multiple levels (from linear sequence, to structural organisation, to temporal variation) each of which is open to and responds to environmental influence. To unravel the complexities of the genomic basis of human disease, and in particular non-communicable diseases that are also influenced by the environment (e.g., obesity, type II diabetes, cancer, multiple sclerosis, some neurodegenerative diseases, inflammatory bowel disease, rheumatoid arthritis) it is imperative that we fully integrate multiple layers of genomic data. Here we review current progress in integrated genomic data analysis, and discuss cases where data integration would lead to significant advances in our ability to predict how the environment may impact on our health. We also outline limitations which should form the basis of future research questions. In so doing, this review will lay the foundations for future research into the impact of the environment on our health.

Genome-wide DNA methylation analysis of heavy cannabis exposure in a New Zealand longitudinal cohort.

Cannabis use is of increasing public health interest globally. Here we examined the effect of heavy cannabis use, with and without tobacco, on genome-wide DNA methylation in a longitudinal birth cohort (Christchurch Health and Development Study, CHDS). A total of 48 heavy cannabis users were selected from the CHDS cohort, on the basis of their adult exposure to cannabis and tobacco, and DNA methylation assessed from whole blood samples, collected at approximately age 28. Methylation in heavy cannabis users was assessed, relative to non-users (n = 48 controls) via the Illumina Infinium® MethylationEPIC BeadChip. We found the most differentially methylated sites in cannabis with tobacco users were in the AHRR and F2RL3 genes, replicating previous studies on the effects of tobacco. Cannabis-only users had no evidence of differential methylation in these genes, or at any other loci at the epigenome-wide significance level (P < 10-7). However, there were 521 sites differentially methylated at P < 0.001 which were enriched for genes involved in neuronal signalling (glutamatergic synapse and long-term potentiation) and cardiomyopathy. Further, the most differentially methylated loci were associated with genes with reported roles in brain function (e.g. TMEM190, MUC3L, CDC20 and SP9). We conclude that the effects of cannabis use on the mature human blood methylome differ from, and are less pronounced than, the effects of tobacco use, and that larger sample sizes are required to investigate this further.