DNA methylation signatures as biomarkers of prior environmental exposures

Assessing marine ecosystem health using multi-omic analysis of blue mussel liquid biopsies: A case study within a national marine park

Marine ecosystems are under escalating threats from myriad environmental stressors, necessitating a deeper understanding of their impact on biodiversity and the health of sentinel organisms. In this study, we carried out a spatiotemporal multi-omic analysis of liquid biopsies collected from mussels (Mytilus spp.) in marine ecosystems of a national park. We delved into the epigenomic, transcriptomic, glycomic, proteomic, and microbiomic profiles to unravel the intricate interplay between ecosystem biodiversity and mussels' biological response to their environments. Our analysis revealed temporal fluctuations in the alpha diversity of the circulating microbiome associated with human activities. Analysis of the hemolymphatic circulating cell-free DNA (ccfDNA) provided information on the biodiversity and the presence of potential pathogens. Epigenomic analysis revealed widespread hypomethylation sites within the mitochondrial (mtDNA). Comparative transcriptomic and glycomic analyses highlighted differences in metabolic pathways and genes associated with immune and wound healing functions. This study demonstrates the potential of multi-omic analysis of liquid biopsy in sentinel to provide a holistic view of human activities' environmental impacts on marine coastal ecosystems. Overall, this approach has the potential to enhance the effectiveness and efficiency of various conservation efforts, leading to more informed decision-making and better outcomes for biodiversity and ecosystem conservation.

Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program

BACKGROUND

Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established.

OBJECTIVE

Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost.

METHODS

We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 .

RESULTS

Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ).

DISCUSSION

To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.

Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection

The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies. The broader scientific community was invited to review and provide feedback on the preliminary recommendation of the Working Group. Fourteen selected protocols for measuring smoking cessation, harm reduction, and biomarkers research associated with smoking cessation were released in the PhenX Toolkit ( https://www.phenxtoolkit.org) in February 2021. These protocols complement existing PhenX Toolkit content related to tobacco regulatory research, substance use and addiction research, and other measures of smoking-related health outcomes. Adopting well-established protocols enables consistent data collection and facilitates comparing and combining data across studies, potentially increasing the scientific impact of individual studies.

Prenatal airborne polycyclic aromatic hydrocarbon exposure, altered regulation of peroxisome proliferator-activated receptor gamma (Ppar)γ, and links with mammary cancer

Environmental exposure to polycyclic aromatic hydrocarbons (PAH) has been shown to be associated with chronic disease outcomes through multiple mechanisms including altered regulation of the transcription factor peroxisome proliferator-activated receptor gamma (Ppar) γ. Because PAH exposure and Pparγ each have been associated with mammary cancer, we asked whether PAH would induce altered regulation of Pparγ in mammary tissue, and whether this association may underlie the association between PAH and mammary cancer. Pregnant mice were exposed to aerosolized PAH at proportions that mimic equivalent human exposures in New York City air. We hypothesized that prenatal PAH exposure would alter Pparγ DNA methylation and gene expression and induce the epithelial to mesenchymal transition (EMT) in mammary tissue of offspring (F1) and grandoffspring (F2) mice. We also hypothesized that altered regulation of Pparγ in mammary tissue would associate with biomarkers of EMT, and examined associations with whole body weight. We found that prenatal PAH exposure lowered Pparγ mammary tissue methylation among grandoffspring mice at postnatal day (PND) 28. However, PAH exposure did not associate with altered Pparγ gene expression or consistently with biomarkers of EMT. Finally, lower Pparγ methylation, but not gene expression, was associated with higher body weight among offspring and grandoffspring mice at PND28 and PND60. Findings suggest additional evidence of multi-generational adverse epigenetic effects of prenatal PAH exposure among grandoffspring mice.

Genes and the Environment in Cancer: Focus on Environmentally Induced DNA Methylation Changes

Cancer has traditionally been viewed as a genetic disorder resulting from the accumulation of gene mutations, chromosomal rearrangements, and aneuploidies in somatic cells [...].

DNA methylation signatures as biomarkers of socioeconomic position

This review article provides a framework for the use of deoxyribonucleic acid (DNA) methylation (DNAm) biomarkers to study the biological embedding of socioeconomic position (SEP) and summarizes the latest developments in the area. It presents the emerging literature showing associations between individual- and neighborhood-level SEP exposures and DNAm across the life course. In contrast to questionnaire-based methods of assessing SEP, we suggest that DNAm biomarkers may offer an accessible metric to study questions about SEP and health outcomes, acting as a personal dosimeter of exposure. However, further work remains in standardizing SEP measures across studies and evaluating consistency across domains, tissue types, and time periods. Meta-analyses of epigenetic associations with SEP are offered as one approach to confirm the replication of DNAm loci across studies. The development of DNAm biomarkers of SEP would provide a method for examining its impact on health outcomes in a more robust way, increasing the rigor of epidemiological studies.

Epigenetics as a Biomarker for Early-Life Environmental Exposure

PURPOSE OF REVIEW

There is interest in evaluating the developmental origins of health and disease (DOHaD) which emphasizes the role of prenatal and early-life environments on non-communicable health outcomes throughout the life course. The ability to rigorously assess and identify early-life risk factors for later health outcomes, including those with childhood onset, in large population samples is often limited due to measurement challenges such as impractical costs associated with prospective studies with a long follow-up duration, short half-lives for some environmental toxicants, and lack of biomarkers that capture inter-individual differences in biologic response to external environments.

RECENT FINDINGS

Epigenomic patterns, and DNA methylation in particular, have emerged as a potential objective biomarker to address some of these study design and exposure measurement challenges. In this article, we summarize the literature to date on epigenetic changes associated with specific prenatal and early-life exposure domains as well as exposure mixtures in human observational studies and their biomarker potential. Additionally, we highlight evidence for other types of epigenetic patterns to serve as exposure biomarkers. Evidence strongly supports epigenomic biomarkers of exposure that are detectable across the lifespan and across a range of exposure domains. Current and future areas of research in this field seek to expand these lines of evidence to other environmental exposures, to determine their specificity, and to develop predictive algorithms and methylation scores that can be used to evaluate early-life risk factors for health outcomes across the life span.

Epigenetics and ADHD: Reflections on Current Knowledge, Research Priorities and Translational Potential

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder influenced by both genetic and environmental factors, typically identified in the school-age years but hypothesized to have developmental origins beginning in utero. To improve current strategies for prediction, prevention and treatment, a central challenge is to delineate how, at a molecular level, genetic and environmental influences jointly shape ADHD risk, phenotypic presentation, and developmental course. Epigenetic processes that regulate gene expression, such as DNA methylation, have emerged as a promising molecular system in the search for both biomarkers and mechanisms to address this challenge. In this Current Opinion, we discuss the relevance of epigenetics (specifically DNA methylation) for ADHD research and clinical practice, starting with the current state of knowledge, what challenges we have yet to overcome, and what the future may hold in terms of methylation-based applications for personalized medicine in ADHD. We conclude that the field of epigenetics and ADHD is promising but is still in its infancy, and the potential for transformative translational applications remains a distant goal. Nevertheless, rapid methodological advances, together with the rise of collaborative science and increased availability of high-quality, longitudinal data make this a thriving research area that in future may contribute to the development of new tools for improved prediction, management, and treatment of ADHD.

CpG site-specific methylation as epi-biomarkers for the prediction of health risk in PAHs-exposed populations

Environmental insults can lead to alteration in DNA methylation of specific genes. To address the role of altered DNA methylation in prediction of polycyclic aromatic hydrocarbons (PAHs) exposure-induced genetic damage, we recruited two populations, including diesel engine exhausts (low-level) and coke oven emissions (high-level) exposed subjects. The positive correlation was observed between the internal exposure marker (1-hydroxypyrene) and the extents of DNA damage (P < 0.05). The methylation of representative genes, including TRIM36, RASSF1a, and MGMT in peripheral blood lymphocytes was quantitatively examined by bisulfite-pyrosequencing assay. The DNA methylation of these three genes in response to PAHs exposure were changed in a CpG-site-specific manner. The identified hot CpG site-specific methylation of three genes exhibited higher predictive power for DNA damage than the respective single genes in both populations. Furthermore, the dose-response relationship analysis revealed a nonlinear U-shape curve of TRIM36 or RASSF1a methylation in combined population, which led to determination of the threshold of health risk. Furthermore, we established a prediction model for genetic damage based on the unidirectional-alteration MGMT methylation levels. In conclusion, this study provides new insight into the application of multiple epi-biomarkers for health risk assessment upon PAHs exposure.

The hypermethylation of FOXP3 gene as an epigenetic marker for the identification of arsenic poisoning risk

Background and Purpose: Arsenic exposure can lead to skin lesions and multiple organ damage, which are not easily reversible and for which there is no effective therapeutics. Identification of reliable epigenetic markers is essential for early recognition of arsenic poisoning risk. Anomalous DNA methylation of immune homeostasis regulator FOXP3 is a critical mechanism for triggering arsenic poisoning. This study aims to explore the value of FOXP3 methylation in the identification of arsenic poisoning risk.Methods: 88 arsenic poisoning subjects and 41 references were recruited. Urinary arsenic contents and FOXP3 methylation in PBLCs was measured by ICP-MS and pyrosequencing, respectively.Results: The results showed that the elevated FOXP3 methylation in PBLCs were associated with the increased levels of urinary arsenic and were positively associated with the increased risk of arsenic poisoning and its progression. The result of mediation analysis revealed that 24.3% of the effect of arsenic exposure on the risk of arsenic poisoning was mediated by increased FOXP3 methylation. Additionally, we constructed a nomogram model with FOXP3 methylation as an epigenetic predictor to assess the probability of individual arsenic poisoning. The model showed a robust ability in the discrimination of arsenic poisoning risk, with an area under receiver operating characteristics curve of 0.897(0.845-0.949) and more than 70% accuracy. The calibration curves and the Harrell concordance index showed that the consistency rate between the probability predicted by the nomogram model and the actual probability is 89.7%.Conclusions: Taken together, we found the great potential of FOXP3 methylation for the identification of arsenic poisoning risk and provided a new approach to the application of epigenetic markers in accurately quantifying the risk of adverse outcomes.

Prenatal Particulate Matter Exposure Is Associated with Saliva DNA Methylation at Age 15: Applying Cumulative DNA Methylation Scores as an Exposure Biomarker

Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 has cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during the three months prior to birth was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n = 749) and 15 (n = 793) was measured using the Illumina HumanMethylation 450 k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by independent meta-analysis effect estimates and standardizing the sums. Using a mixed-effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income-to-needs ratio, nonmartial birth status, and saliva cell-type proportions. Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with a median income-to-needs ratio of 1.4. Mean exposure levels for PM2.5 were 27.9 μg/m³/day (standard deviation: 7.0; 23.7% of observations exceeded safety standards) and for PM10 were 15.0 μg/m³/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 μg/m³/day) was associated with a −0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: −0.0732, 0.0158, p = 0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 μg/m³/day) was associated with a −0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.3038, 0.0095, p = 0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with a −0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.043, −0.005, p = 0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. In utero PM10-associated DNA methylation differences were identified at age 15 in saliva. Benchmarking the timing and cell-type generalizability is critical for epigenetic exposure biomarker assessment.

Using primary teeth and archived dried spots for exposomic studies in children: Exploring new paths in the environmental epidemiology of pediatric cancer

It is estimated that 300,000 children 0-14 years of age are diagnosed with cancer worldwide each year. While the absolute risk of cancer in children is low, it is the leading cause of death due to disease in children in high-income countries. In spite of this, the etiologies of pediatric cancer are largely unknown. Environmental exposures have long been thought to play an etiologic role. However, to date, there are few well-established environmental risk factors for pediatric malignancies, likely due to technical barriers in collecting biological samples prospectively in pediatric populations for direct measurements. In this review, we propose the use of novel or underutilized biospecimens (dried blood spots and teeth) and molecular approaches for exposure assessment (epigenetics, metabolomics, and somatic mutational profiles). Future epidemiologic studies of pediatric cancer should incorporate novel exposure assessment methodologies, data on molecular features of tumors, and a more complete assessment of gene-environment interactions.

Characteristics of epigenetic aging across gestational and perinatal tissues

Background

Epigenetic clocks have been used to indicate differences in biological states between individuals of same chronological age. However, so far, only few studies have examined epigenetic aging in newborns—especially regarding different gestational or perinatal tissues. In this study, we investigated which birth- and pregnancy-related variables are most important in predicting gestational epigenetic age acceleration or deceleration (i.e., the deviation between gestational epigenetic age estimated from the DNA methylome and chronological gestational age) in chorionic villus, placenta and cord blood tissues from two independent study cohorts (ITU, n = 639 and PREDO, n = 966). We further characterized the correspondence of epigenetic age deviations between these tissues.

Results

Among the most predictive factors of epigenetic age deviations in single tissues were child sex, birth length, maternal smoking during pregnancy, maternal mental disorders until childbirth, delivery mode and parity. However, the specific factors related to epigenetic age deviation and the direction of association differed across tissues. In individuals with samples available from more than one tissue, relative epigenetic age deviations were not correlated across tissues.

Conclusion

Gestational epigenetic age acceleration or deceleration was not related to more favorable or unfavorable factors in one direction in the investigated tissues, and the relative epigenetic age differed between tissues of the same person. This indicates that epigenetic age deviations associate with distinct, tissue specific, factors during the gestational and perinatal period. Our findings suggest that the epigenetic age of the newborn should be seen as a characteristic of a specific tissue, and less as a general characteristic of the child itself.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01080-y.

Melatonin protects against defects induced by Enniatin B1 during porcine early embryo development

Exogenous factors influence embryo development. Enniatin B1 (EB1), one emerging mycotoxin of Fusarium fungi, can cause damage to cells and mouse blastocysts. However, the toxicity of EB1 on porcine embryo development and whether melatonin can eliminate the detrimental effects of EB1 on embryos remain unclear. Here, this work demonstrated that EB1 significantly decreased the cleavage and blastocyst rates and blastocyst cell number of embryos in a dose and time dependent manner. Further study displayed that EB1 obviously destroyed nuclear remodeling dynamics. Importantly, EB1 triggered embryo apoptosis through downregulating the expression of Sod1,Gpx4, Cat and Bcl2l1 while upregulating the transcription of Bax and Caspase3. Moreover, EB1 significantly disrupted the transcription of Dnmt1, Dnmt3a, Tet1 and Tet3, further leading to incomplete DNA demethylation of CenRep, Oct4, Nanog and Sox2, thus, the expression of Eif1a, Oct4, Nanog and Sox2 remarkably decreased. Whereas EB1-exposed embryos were treated with melatonin, these disorders were obviously ameliorated, and the development ability of embryos was also rescued. In conclusion, EB1 exerted detrimental effects on porcine early embryos, while melatonin effectively rescued EB1-mediated defects in embryos. This work provides a novel insight into the improvement of embryo quality and the promotion of human and animal reproduction.

DNA Methylation-Based Biomarkers of Environmental Exposures for Human Population Studies

PURPOSE OF REVIEW

This manuscript orients the reader to the underlying motivations of environmental biomarker development for human population studies and provides the foundation for applying these novel biomarkers in future research. In this review, we focus our attention on the DNA methylation-based biomarkers of (i) smoking, among adults and pregnant women, (ii) lifetime cannabis use, (iii) alcohol consumption, and (iv) cumulative exposure to lead.

RECENT FINDINGS

Prior environmental exposures and lifestyle modulate DNA methylation levels. Exposure-related DNA methylation changes can either be persistent or reversible once the exposure is no longer present, and this combination of both persistent and reversible changes has essential value for biomarker development. Here, we present available biomarkers representing past and cumulative exposures using individual DNA methylation profiles. In the present work, we describe how the field of environmental epigenetics can leverage machine learning algorithms to develop exposure biomarkers and reduce problems of misreporting exposures or limited access technology. We emphasize the crucial role of the individual DNA methylation profiles in those predictions, providing a summary of each biomarker, and highlighting their advantages, and limitations. Future research can cautiously leverage these DNA methylation-based biomarkers to understand the onset and progression of diseases.

DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA

A subset of individuals with type 1 diabetes will develop diabetic kidney disease (DKD). DKD is heritable and large-scale genome-wide association studies have begun to identify genetic factors that influence DKD. Complementary to genetic factors, we know that a person’s epigenetic profile is also altered with DKD. This study reports analysis of DNA methylation, a major epigenetic feature, evaluating methylome-wide loci for association with DKD. Unique features (n = 485,577; 482,421 CpG probes) were evaluated in blood-derived DNA from carefully phenotyped White European individuals diagnosed with type 1 diabetes with (cases) or without (controls) DKD (n = 677 samples). Explicitly, 150 cases were compared to 100 controls using the 450K array, with subsequent analysis using data previously generated for a further 96 cases and 96 controls on the 27K array, and de novo methylation data generated for replication in 139 cases and 96 controls. Following stringent quality control, raw data were quantile normalized and beta values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls; resultant P-values for array-based data were adjusted for multiple testing. Genes with significantly increased (hypermethylated) and/or decreased (hypomethylated) levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways. Twenty-two loci demonstrated statistically significant fold changes associated with DKD and additional support for these associated loci was sought using independent samples derived from patients recruited with similar inclusion criteria. Markers associated with CCNL1 and ZNF187 genes are supported as differentially regulated loci (P < 10^–8), with evidence also presented for AFF3, which has been identified from a meta-analysis and subsequent replication of genome-wide association studies. Further supporting evidence for differential gene expression in CCNL1 and ZNF187 is presented from kidney biopsy and blood-derived RNA in people with and without kidney disease from NephroSeq. Evidence confirming that methylation sites influence the development of DKD may aid risk prediction tools and stimulate research to identify epigenomic therapies which might be clinically useful for this disease.

Phenotypic Subtyping and Re-Analysis of Existing Methylation Data from Autistic Probands in Simplex Families Reveal ASD Subtype-Associated Differentially Methylated Genes and Biological Functions

Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to the severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated regions (DMR) and DMR-associated genes (DAGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DAGs in each phenotypic subgroup but not in the combined case group. Moreover, relational gene networks constructed with the DAGs reveal signaling pathways associated with specific functions and comorbidities. In addition, a network comprised of DAGs shared among all ASD subgroups and the combined case group is enriched in genes involved in inflammatory responses, suggesting that neuroinflammation may be a common theme underlying core features of ASD. These findings demonstrate the value of phenotype definition in methylomic analyses of ASD and may aid in the development of subtype-directed diagnostics and therapeutics.

Beyond the looking glass: recent advances in understanding the impact of environmental exposures on neuropsychiatric disease

The etiologic pathways leading to neuropsychiatric diseases remain poorly defined. As genomic technologies have advanced over the past several decades, considerable progress has been made linking neuropsychiatric disorders to genetic underpinnings. Interest and consideration of nongenetic risk factors (e.g., lead exposure and schizophrenia) have, in contrast, lagged behind heritable frameworks of explanation. Thus, the association of neuropsychiatric illness to environmental chemical exposure, and their potential interactions with genetic susceptibility, are largely unexplored. In this review, we describe emerging approaches for considering the impact of chemical risk factors acting alone and in concert with genetic risk, and point to the potential role of epigenetics in mediating exposure effects on transcription of genes implicated in mental disorders. We highlight recent examples of research in nongenetic risk factors in psychiatric disorders that point to potential shared biological mechanisms-synaptic dysfunction, immune alterations, and gut-brain interactions. We outline new tools and resources that can be harnessed for the study of environmental factors in psychiatric disorders. These tools, combined with emerging experimental evidence, suggest that there is a need to broadly incorporate environmental exposures in psychiatric research, with the ultimate goal of identifying modifiable risk factors and informing new treatment strategies for neuropsychiatric disease.

Rationale, Study Design, and Cohort Characteristics for the Markers for Environmental Exposures (MEE) Study

Environmental factors have been linked to many diseases and health conditions, but reliable assessment of environmental exposures is challenging. Developing biomarkers of environmental exposures, rather than relying on self-report, will improve our ability to assess the association of such exposures with disease. Epigenetic markers, most notably DNA methylation, have been identified for some environmental exposures, but identification of markers for additional exposures is still needed. The rationale behind the Markers for Environmental Exposures (MEE) Study was to (1) identify biomarkers, especially epigenetic markers, of environmental exposures, such as pesticides, air/food/water contaminants, and industrial chemicals that are commonly encountered in the general population; and (2) support the study of potential relationships between environmental exposures and health and health-related factors. The MEE Study is a cross-sectional study with potential for record linkage and follow-up. The well-characterized cohort of 400 postmenopausal women has generated a repository of biospecimens, including blood, urine, and saliva samples. Paired data include an environmental exposures questionnaire, a breast health questionnaire, dietary recalls, and a food frequency questionnaire. This work describes the rationale, study design, and cohort characteristics of the MEE Study. In addition to our primary research goals, we hope that the data and biorepository generated by this study will serve as a resource for future studies and collaboration.

Epigenetic Biomarkers for Environmental Exposures and Personalized Breast Cancer Prevention

Environmental and lifestyle factors are believed to account for >80% of breast cancers; however, it is not well understood how and when these factors affect risk and which exposed individuals will actually develop the disease. While alcohol consumption, obesity, and hormone therapy are some known risk factors for breast cancer, other exposures associated with breast cancer risk have not yet been identified or well characterized. In this paper, it is proposed that the identification of blood epigenetic markers for personal, in utero, and ancestral environmental exposures can help researchers better understand known and potential relationships between exposures and breast cancer risk and may enable personalized prevention strategies.