Interaction between prenatal pesticide exposure and a common polymorphism in the PON1 gene on DNA methylation in genes associated with cardio-metabolic disease risk—an exploratory study

Abstract

BackgroundPrenatal environmental conditions may influence disease risk in later life. We previously found a gene-environment interaction between the paraoxonase 1 (PON1) Q192R genotype and prenatal pesticide exposure leading to an adverse cardio-metabolic risk profile at school age. However, the molecular mechanisms involved have not yet been resolved. It was hypothesized that epigenetics might be involved. The aim of the present study was therefore to investigate whether DNA methylation patterns in blood cells were related to prenatal pesticide exposure level, PON1 Q192R genotype, and associated metabolic effects observed in the children.MethodsWhole blood DNA methylation patterns in 48 children (6–11 years of age), whose mothers were occupationally unexposed or exposed to pesticides early in pregnancy, were determined by Illumina 450 K methylation arrays.ResultsA specific methylation profile was observed in prenatally pesticide exposed children carrying the PON1 192R-allele. Differentially methylated genes were enriched in several neuroendocrine signaling pathways including dopamine-DARPP32 feedback (appetite, reward pathways), corticotrophin releasing hormone signaling, nNOS, neuregulin signaling, mTOR signaling, and type II diabetes mellitus signaling. Furthermore, we were able to identify possible candidate genes which mediated the associations between pesticide exposure and increased leptin level, body fat percentage, and difference in BMI Z score between birth and school age.ConclusionsDNA methylation may be an underlying mechanism explaining an adverse cardio-metabolic health profile in children carrying the PON1 192R-allele and prenatally exposed to pesticides.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-017-0336-4) contains supplementary material, which is available to authorized users.

Insights into the multifactorial causation of obesity by integrated genetic and epigenetic analysis

“…Remarkably, recent GWASs and EWASs highlight crosstalk of many obesity‐associated genetic variants and environmental factors (diet, pesticides, smoking, alcohol consumption, physical activity, and medication) with DNA methylation changes at proximal promoters and enhancers. We observed a strong correlation between prenatal pesticide exposure, paraoxonase 1 polymorphism rs662:T > C, and adverse epigenetic reprogramming of neuroendocrine pathways; children carrying the C allele and prenatally exposed to pesticides showed DNA methylation changes of genes involved in cardiometabolic health with higher body fat content and serum leptin levels as outcome (childhood obesity) 90 . Moreover, Koh et al 123 disclosed an association of obesity‐related physical and biochemical traits with cg07814318 Kruppel‐like Factor‐13 methylation depending on sequencing variations within this gene.…”

“…Mounting evidence suggests that DNA methylation might contribute to the multifactorial pathogenesis of obesity; different studies have demonstrated methylation changes in promotors of genes that are implicated in food intake, obesity, insulin signalling, immunity, and circadian rhythms 88–92 . Studies of the Dutch Hunger Winter during World War II focused on periconceptional environmental exposures and the long‐term effect on health status of the offspring.…”

Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing

“…The strong performance of the covariate "mean" is somewhat unexpected and may be explained by two reasons, which are related to the prior null probability and statistical power, respectively. First, DMPs are enriched in certain regions such as the promoters [30,31], where the methylation levels are similar-either low or high (Additional file 6: Figure S3A). Second, the statistical power to detect DMPs in the middle of the methylation spectrum is higher than those in the two ends, where the methylation changes are constrained (Additional file 6: Figure S3B).…”

“…For EWAS data, besides the association p values, we have plenty of auxiliary covariates, which could be informative of the null probability or statistical power of the CpG-specific hypotheses. For example, differentially methylated CpG positions (DMPs) have been found to be enriched in specific genomic regions, such as promoters [30,31], CpG islands [20], shores [32], a specific chromosome [33], and DNase I hypersensitive sites [32,34]. In addition, some studies found that DMPs tend to change in the same direction, especially in cancer, where genomewide hypomethylation or hypermethylation has been frequently observed [10].…”

Epigenetic Effects of Exposure to Insecticide on Early Differentiation of Mouse Embryonic Stem Cells

“…Therefore, the evaluation of both global and gene-specific DNA methylation provides important insights into developmental toxicity and the associated toxicities of environmental chemicals. Evidences indicated that insecticides induce developmental neurotoxicity (Declerck et al 2017) and carcinogenesis (Zhang et al 2012) through changes in DNA methylation patterns. DNA methylation exhibits its greatest vulnerability to environmental factors during embryogenesis, (Foley et al 2009, Relton and Davey Smith 2010), resulting in adverse health outcomes in children.…”