Effect of prenatal arsenic exposure on DNA methylation and leukocyte subpopulations in cord blood

Linking the aryl hydrocarbon receptor with altered DNA methylation patterns and developmentally induced aberrant antiviral CD8+ T cell responses

Successfully fighting infection requires a properly tuned immune system. Recent epidemiological studies link exposure to pollutants that bind the aryl hydrocarbon receptor (AHR) during development with poorer immune responses later in life. Yet, how developmental triggering of AHR durably alters immune cell function remains unknown. Using a mouse model, we show that developmental activation of AHR leads to long-lasting reduction in the response of CD8(+) T cells during influenza virus infection, cells critical for resolving primary infection. Combining genome-wide approaches, we demonstrate that developmental activation alters DNA methylation and gene expression patterns in isolated CD8(+) T cells prior to and during infection. Altered transcriptional profiles in CD8(+) T cells from developmentally exposed mice reflect changes in pathways involved in proliferation and immunoregulation, with an overall pattern that bears hallmarks of T cell exhaustion. Developmental exposure also changed DNA methylation across the genome, but differences were most pronounced following infection, where we observed inverse correlation between promoter methylation and gene expression. This points to altered regulation of DNA methylation as one mechanism by which AHR causes durable changes in T cell function. Discovering that distinct gene sets and pathways were differentially changed in developmentally exposed mice prior to and after infection further reveals that the process of CD8(+) T cell activation is rendered fundamentally different by early life AHR signaling. These findings reveal a novel role for AHR in the developing immune system: regulating DNA methylation and gene expression as T cells respond to infection later in life.

Cell-composition effects in the analysis of DNA methylation array data: a mathematical perspective

Background

The impact of cell-composition effects in analysis of DNA methylation data is now widely appreciated. With the availability of a reference data set consisting of DNA methylation measurements on isolated cell types, it is possible to impute cell proportions and adjust for them, but there is increasing interest in methods that adjust for cell composition effects when reference sets are incomplete or unavailable.

Results

In this article we present a theoretical basis for one such method, showing that the total effect of a phenotype on DNA methylation can be decomposed into orthogonal components, one representing the effect of phenotype on proportions of major cell types, the other representing either subtle effects in composition or global effects at focused loci, and that it is possible to separate these two types of effects in a finite data set. We demonstrate this principle empirically on nine DNA methylation data sets, showing that the first few principal components generally contain a majority of the information on cell-type present in the data, but that later principal components nevertheless contain information about a small number of loci that may represent more focused associations. We also present a new method for determining the number of linear terms to interpret as cell-mixture effects and demonstrate robustness to the choice of this parameter.

Conclusions

Taken together, our work demonstrates that reference-free algorithms for cell-mixture adjustment can produce biologically valid results, separating cell-mediated epigenetic effects (i.e. apparent effects arising from differences in cell composition) from those that are not cell mediated, and that in general the interpretation of associations evident from DNA methylation should be carefully considered.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0527-y) contains supplementary material, which is available to authorized users.

Gene-specific differential DNA methylation and chronic arsenic exposure in an epigenome-wide association study of adults in Bangladesh

BACKGROUND

Inorganic arsenic is one of the most common naturally occurring contaminants found in the environment. Arsenic is associated with a number of health outcomes, with epigenetic modification suggested as a potential mechanism of toxicity.

OBJECTIVE

Among a sample of 400 adult participants, we evaluated the association between arsenic exposure, as measured by blood and urinary total arsenic concentrations, and epigenome-wide white blood cell DNA methylation.

METHODS

We used linear regression models to examine the associations between arsenic exposure and methylation at each CpG site, adjusted for sex, age, and batch. Differentially methylated loci were subsequently examined in relation to corresponding gene expression for functional evidence of gene regulation.

RESULTS

In adjusted analyses, we observed four differentially methylated CpG sites with urinary total arsenic concentration and three differentially methylated CpG sites with blood arsenic concentration, based on the Bonferroni-corrected significance threshold of p < 1 × 10(-7). Methylation of PLA2G2C (probe cg04605617) was the most significantly associated locus in relation to both urinary (p = 3.40 × 10(-11)) and blood arsenic concentrations (p = 1.48 × 10(-11)). Three additional novel methylation loci-SQSTM1 (cg01225779), SLC4A4 (cg06121226), and IGH (cg13651690)--were also significantly associated with arsenic exposure. Further, there was evidence of methylation-related gene regulation based on gene expression for a subset of differentially methylated loci.

CONCLUSIONS

We observed significant associations between arsenic exposure and gene-specific differential white blood cell DNA methylation, suggesting that epigenetic modifications may be an important pathway underlying arsenic toxicity. The specific differentially methylated loci identified may inform potential pathways for future interventions.

Prenatal arsenic exposure and the epigenome: identifying sites of 5-methylcytosine alterations that predict functional changes in gene expression in newborn cord blood and subsequent birth outcomes

Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456-236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424,935 CpG sites representing 18,761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5' untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments.

Arsenic induces polyadenylation of canonical histone mRNA by down-regulating stem-loop-binding protein gene expression

The replication-dependent histone genes are the only metazoan genes whose messenger RNA (mRNA) does not terminate with a poly(A) tail at the 3'-end. Instead, the histone mRNAs display a stem-loop structure at their 3'-end. Stem-loop-binding protein (SLBP) binds the stem-loop and regulates canonical histone mRNA metabolism. Here we report that exposure to arsenic, a carcinogenic metal, decreased cellular levels of SLBP by inducing its proteasomal degradation and inhibiting SLBP transcription via epigenetic mechanisms. Notably, arsenic exposure dramatically increased polyadenylation of canonical histone H3.1 mRNA possibly through down-regulation of SLBP expression. The polyadenylated H3.1 mRNA induced by arsenic was not susceptible to normal degradation that occurs at the end of S phase, resulting in continued presence into mitosis, increased total H3.1 mRNA, and increased H3 protein levels. Excess expression of canonical histones have been shown to increase sensitivity to DNA damage as well as increase the frequency of missing chromosomes and induce genomic instability. Thus, polyadenylation of canonical histone mRNA following arsenic exposure may contribute to arsenic-induced carcinogenesis.

Role of metabolic genes in blood arsenic concentrations of Jamaican children with and without autism spectrum disorder

Arsenic is a toxic metalloid with known adverse effects on human health. Glutathione-S-transferase (GST) genes, including GSTT1, GSTP1, and GSTM1, play a major role in detoxification and metabolism of xenobiotics. We investigated the association between GST genotypes and whole blood arsenic concentrations (BASC) in Jamaican children with and without autism spectrum disorder (ASD). We used data from 100 ASD cases and their 1:1 age- and sex-matched typically developing (TD) controls (age 2-8 years) from Jamaica. Using log-transformed BASC as the dependent variable in a General Linear Model, we observed a significant interaction between GSTP1 and ASD case status while controlling for several confounding variables. However, for GSTT1 and GSTM1 we did not observe any significant associations with BASC. Our findings indicate that TD children who had the Ile/Ile or Ile/Val genotype for GSTP1 had a significantly higher geometric mean BASC than those with genotype Val/Val (3.67 µg/L vs. 2.69 µg/L, p < 0.01). Although, among the ASD cases, this difference was not statistically significant, the direction of the observed difference was consistent with that of the TD control children. These findings suggest a possible role of GSTP1 in the detoxification of arsenic.

Incorporating epigenetic data into the risk assessment process for the toxic metals arsenic, cadmium, chromium, lead, and mercury: strategies and challenges

Exposure to toxic metals poses a serious human health hazard based on ubiquitous environmental presence, the extent of exposure, and the toxicity and disease states associated with exposure. This global health issue warrants accurate and reliable models derived from the risk assessment process to predict disease risk in populations. There has been considerable interest recently in the impact of environmental toxicants such as toxic metals on the epigenome. Epigenetic modifications are alterations to an individual's genome without a change in the DNA sequence, and include, but are not limited to, three commonly studied alterations: DNA methylation, histone modification, and non-coding RNA expression. Given the role of epigenetic alterations in regulating gene and thus protein expression, there is the potential for the integration of toxic metal-induced epigenetic alterations as informative factors in the risk assessment process. In the present review, epigenetic alterations induced by five high priority toxic metals/metalloids are prioritized for analysis and their possible inclusion into the risk assessment process is discussed.