Epigenomics in Environmental Health

This review considers the emerging relationships between environmental factors and epigenetic alterations and the application of genome-wide assessments to better define these relationships. First we will briefly cover epigenetic programming in development, one-carbon metabolism, and exposures that may disrupt normal developmental programming of epigenetic states. In addition, because a large portion of epigenetic research has focused on cancer, we discuss exposures associated with carcinogenesis including asbestos, alcohol, radiation, arsenic, and air pollution. Research on other exposures that may affect epigenetic states such as endocrine disruptors is also described, and we also review the evidence for epigenetic alterations associated with aging that may reflect cumulative effects of exposures. From this evidence, we posit potential mechanisms by which exposures modify epigenetic states, noting that understanding the true effect of environmental exposures on the human epigenome will require additional research with appropriate epidemiologic studies and application of novel technologies. With a more comprehensive understanding of the affects of exposures on the epigenome, including consideration of genetic background, the prediction of the toxic potential of new compounds may be more readily achieved, and may lead to the development of more personalized disease prevention and treatment strategies

Let-7 MicroRNA-Binding-Site Polymorphism in the 3′UTR of KRAS and Colorectal Cancer Outcome: A Systematic Review and Meta-Analysis

There is a small but growing body of literature regarding the predictive utility of a Let-7 microRNA-binding-site polymorphism in the 30 -untranslated region (UTR) of KRAS (KRAS-LCS6) for colorectal cancer outcome, although the results are conflicting. We performed a review and meta-analysis in an attempt to better clarify this relationship. A PubMed search was conducted to identify all studies reporting on KRAS let-7 microRNA-binding site polymorphism (LCS6; rs61764370) and colorectal cancer outcome. Hazard ratios (HR) and corresponding 95% confidence intervals (CI) were extracted or estimated from each manuscript. Log HRs and log CIs were combined across studies using the inverse-variance weight to calculate fixed- and random-effects summary estimates and corresponding 95% CIs for overall and progression-free survival. We did not observe any significant association between overall or progression-free survival, neither when considering all colorectal cancer patients nor for subgroup analyses (metastatic, anti-EGFR [epidermal growth factor receptor] treatment, or KRAS wild type). There was substantial heterogeneity across studies, overall and among subgroups analyzed. We have found no clear evidence to support an association between the KRAS-LCS6 genotype and overall or progression-free survival among colorectal cancer patients, even after conducting subgroup analyses by stage and anti-EGFR treatment status. This information helps to clarify the confusing body of literature regarding the clinical implications of the KRAS-LCS6 genetic variant on colorectal cancer outcomes, indicating that it should not be used at the present time to personalize therapeutic strategies (PROSPERO registration number: CRD42013005325)

A New Timepiece: An Epigenetic Mitotic Clock

A new mitotic clock and mathematical approach that incorporates DNA methylation biology common among human cell types provides a new tool for cancer epigenetics research

Absence of an embryonic stem cell DNA methylation signature in human cancer.

BackgroundDifferentiated cells that arise from stem cells in early development contain DNA methylation features that provide a memory trace of their fetal cell origin (FCO). The FCO signature was developed to estimate the proportion of cells in a mixture of cell types that are of fetal origin and are reminiscent of embryonic stem cell lineage. Here we implemented the FCO signature estimation method to compare the fraction of cells with the FCO signature in tumor tissues and their corresponding nontumor normal tissues.MethodsWe applied our FCO algorithm to discovery data sets obtained from The Cancer Genome Atlas (TCGA) and replication data sets obtained from the Gene Expression Omnibus (GEO) data repository. Wilcoxon rank sum tests, linear regression models with adjustments for potential confounders and non-parametric randomization-based tests were used to test the association of FCO proportion between tumor tissues and nontumor normal tissues. P-values of < 0.05 were considered statistically significant.ResultsAcross 20 different tumor types we observed a consistently lower FCO signature in tumor tissues compared with nontumor normal tissues, with 18 observed to have significantly lower FCO fractions in tumor tissue (total n = 6,795 tumor, n = 922 nontumor, P < 0.05). We replicated our findings in 15 tumor types using data from independent subjects in 15 publicly available data sets (total n = 740 tumor, n = 424 nontumor, P < 0.05).ConclusionsThe results suggest that cancer development itself is substantially devoid of recapitulation of normal embryologic processes. Our results emphasize the distinction between DNA methylation in normal tightly regulated stem cell driven differentiation and cancer stem cell reprogramming that involves altered methylation in the service of great cell heterogeneity and plasticity

DNA Methylation Arrays as Surrogate Measures of Cell mixture Distribution

There has been a long-standing need in biomedical research for a method that quantifies the normally mixed composition of leukocytes beyond what is possible by simple histological or flow cytometric assessments. The latter is restricted by the labile nature of protein epitopes, requirements for cell processing, and timely cell analysis. In a diverse array of diseases and following numerous immune-toxic exposures, leukocyte composition will critically inform the underlying immuno-biology to most chronic medical conditions. Emerging research demonstrates that DNA methylation is responsible for cellular differentiation, and when measured in whole peripheral blood, serves to distinguish cancer cases from controls

A Coding Variant in TMC8 (EVER2) Is Associated with High Risk HPV Infection and Head and Neck Cancer Risk

HPV infection is a causal agent in many epithelial cancers, yet our understanding of genetic susceptibility to HPV infection and resultant cancer risk is limited. Epidermodysplasia Verruciformis is a rare condition of extreme susceptibility to cutaneous HPV infection primarily attributable to mutations in TMC6 and TMC8. Genetic variation in the TMC6/TMC8 region has been linked to beta-type HPV infection and squamous cell carcinoma of the skin, cervical cancer, HPV persistence and progression to cervical cancer. Here, we have tested the hypothesis that the common TMC8 SNP rs7208422 is associated with high-risk HPV infection and risk of head and neck squamous cell carcinoma (HNSCC). Seropositivity to the HPV L1 protein (HPV16, 18, 11, 31, 33, 35, 45, 52, 58) was measured in 514 cases and 452 population-based controls. Genotype was significantly associated with seropositivity to HPV18 L1 (OR TT vs AA = 0.48, 95% CI = 0.22–0.99) and borderline significantly associated with HPV16 L1 (OR TT vs AA = 0.58, 95% CI = 0.22–1.17). There was a consistent inverse association between TMC8 genotype and infection with other HPV types, including statistically significant associations for HPV31 and HPV52. Consistent with these results, the variant T genotype was associated with a reduced risk of HNSCC (ORAT: 0.63, 95% CI 0.45–0.89, ORTT: 0.54, 95% CI 0.36–0.81), even among subjects seronegative for all HPV types (ORAT: 0.71, 95% CI 0.45–1.11, ORTT: 0.54, 95% CI 0.31–0.93). Our data indicate that common genetic variation in TMC8 is associated with high-risk HPV infection and HNSCC etiology

MedZIM: Mediation analysis for Zero-Inflated Mediators with applications to microbiome data

The human microbiome can contribute to the pathogenesis of many complex diseases such as cancer and Alzheimer's disease by mediating disease-leading causal pathways. However, standard mediation analysis is not adequate in the context of microbiome data due to the excessive number of zero values in the data. Zero-valued sequencing reads, commonly observed in microbiome studies, arise for technical and/or biological reasons. Mediation analysis approaches for analyzing zero-inflated mediators are still lacking largely because of challenges raised by the zero-inflated data structure: (a) disentangling the mediation effect induced by the point mass at zero; and (b) identifying the observed zero-valued data points that are actually not zero (i.e., false zeros). We develop a novel mediation analysis method under the potential-outcomes framework to fill this gap. We show that the mediation effect of the microbiome can be decomposed into two components that are inherent to the two-part nature of zero-inflated distributions. The first component corresponds to the mediation effect attributable to a unit-change over the positive relative abundance and the second component corresponds to the mediation effect attributable to discrete binary change of the mediator from zero to a non-zero state. With probabilistic models to account for observing zeros, we also address the challenge with false zeros. A comprehensive simulation study and the applications in two real microbiome studies demonstrate that our approach outperforms existing mediation analysis approaches.Comment: Corresponding: Zhigang L

Genome-wide characterization of cytosine-specific 5-hydroxymethylation in normal breast tissue.

Despite recent evidence that 5-hydroxymethylcytosine (5hmC) possesses roles in gene regulation distinct from 5-methylcytosine (5mC), relatively little is known regarding the functions of 5hmC in mammalian tissues. To address this issue, we utilized an approach combining both paired bisulfite (BS) and oxidative bisulfite (oxBS) DNA treatment, to resolve genome-wide patterns of 5hmC and 5mC in normal breast tissue from disease-free women. Although less abundant than 5mC, 5hmC was differentially distributed, and consistently enriched among breast-specific enhancers and transcriptionally active chromatin. In contrast, regulatory regions associated with transcriptional inactivity, such as heterochromatin and repressed Polycomb regions, were relatively depleted of 5hmC. Gene regions containing abundant 5hmC were significantly associated with lactate oxidation, immune cell function, and prolactin signaling pathways. Furthermore, genes containing abundant 5hmC were enriched among those actively transcribed in normal breast tissue. Finally, in independent data sets, normal breast tissue 5hmC was significantly enriched among CpG loci demonstrated to have altered methylation in pre-invasive breast cancer and invasive breast tumors. Primarily, our findings identify genomic loci containing abundant 5hmC in breast tissues and provide a genome-wide map of nucleotide-level 5hmC in normal breast tissue. Additionally, these data suggest 5hmC may participate in gene regulatory programs that are dysregulated during breast-related carcinogenesis

Human milk-associated bacterial communities associate with the infant gut microbiome over the first year of life

IntroductionMicrobial communities inhabiting the human infant gut are important for immune system development and lifelong health. One critical exposure affecting the bacterial colonization of the infant gut is consumption of human milk, which contains diverse microbial communities and prebiotics. We hypothesized that human milk-associated microbial profiles are associated with those of the infant gut.MethodsMaternal–infant dyads enrolled in the New Hampshire Birth Cohort Study (n = 189 dyads) contributed breast milk and infant stool samples collected approximately at 6 weeks, 4 months, 6 months, 9 months, and 12 months postpartum (n = 572 samples). Microbial DNA was extracted from milk and stool and the V4-V5 region of the bacterial 16S rRNA gene was sequenced.ResultsClustering analysis identified three breast milk microbiome types (BMTs), characterized by differences in Streptococcus, Staphylococcus, Pseudomonas, Acinetobacter, and microbial diversity. Four 6-week infant gut microbiome types (6wIGMTs) were identified, differing in abundances of Bifidobacterium, Bacteroides, Clostridium, Streptococcus, and Escherichia/Shigella, while two 12-month IGMTs (12mIGMTs) differed primarily by Bacteroides presence. At 6 weeks, BMT was associated with 6wIGMT (Fisher’s exact test value of p = 0.039); this association was strongest among infants delivered by Cesarean section (Fisher’s exact test value of p = 0.0028). The strongest correlations between overall breast milk and infant stool microbial community structures were observed when comparing breast milk samples to infant stool samples collected at a subsequent time point, e.g., the 6-week breast milk microbiome associated with the 6-month infant gut microbiome (Mantel test Z-statistic = 0.53, value of p = 0.001). Streptoccous and Veillonella species abundance were correlated in 6-week milk and infant stool, and 4- and 6-month milk Pantoea species were associated with infant stool Lachnospiraceae genera at 9 and 12  months.DiscussionWe identified clusters of human milk and infant stool microbial communities that were associated in maternal–infant dyads at 6 weeks of life and found that milk microbial communities were more strongly associated with infant gut microbial communities in infants delivered operatively and after a lag period. These results suggest that milk microbial communities have a long-term effect on the infant gut microbiome both through sharing of microbes and other molecular mechanisms