Social Environment and Epigenetics

Our social environment, from the microscopic to the macro-social, affects us for the entirety of our lives. One integral line of research to examine how interpersonal and societal environments can get "under the skin" is through the lens of epigenetics. Epigenetic mechanisms are adaptations made to our genome in response to our environment which include tags placed on and removed from the DNA itself to how our DNA is packaged, affecting how our genes are read, transcribed, and interact. These tags are affected by social environments and can persist over time; this may aid us in responding to experiences and exposures, both the enriched and the disadvantageous. From memory formation to immune function, the experience-dependent plasticity of epigenetic modifications to micro- and macro-social environments may contribute to the process of learning from comfort, pain, and stress to better survive in whatever circumstances life has in store.

Exploring the genetic basis of human population differences in DNA methylation and their causal impact on immune gene regulation

BACKGROUND

DNA methylation is influenced by both environmental and genetic factors and is increasingly thought to affect variation in complex traits and diseases. Yet, the extent of ancestry-related differences in DNA methylation, their genetic determinants, and their respective causal impact on immune gene regulation remain elusive.

RESULTS

We report extensive population differences in DNA methylation between 156 individuals of African and European descent, detected in primary monocytes that are used as a model of a major innate immunity cell type. Most of these differences (~ 70%) are driven by DNA sequence variants nearby CpG sites, which account for ~ 60% of the variance in DNA methylation. We also identify several master regulators of DNA methylation variation in trans, including a regulatory hub nearby the transcription factor-encoding CTCF gene, which contributes markedly to ancestry-related differences in DNA methylation. Furthermore, we establish that variation in DNA methylation is associated with varying gene expression levels following mostly, but not exclusively, a canonical model of negative associations, particularly in enhancer regions. Specifically, we find that DNA methylation highly correlates with transcriptional activity of 811 and 230 genes, at the basal state and upon immune stimulation, respectively. Finally, using a Bayesian approach, we estimate causal mediation effects of DNA methylation on gene expression in ~ 20% of the studied cases, indicating that DNA methylation can play an active role in immune gene regulation.

CONCLUSION

Using a system-level approach, our study reveals substantial ancestry-related differences in DNA methylation and provides evidence for their causal impact on immune gene regulation.

Prenatal Alcohol Exposure: Profiling Developmental DNA Methylation Patterns in Central and Peripheral Tissues

Background: Prenatal alcohol exposure (PAE) can alter the development of neurobiological systems, leading to lasting neuroendocrine, neuroimmune, and neurobehavioral deficits. Although the etiology of this reprogramming remains unknown, emerging evidence suggests DNA methylation as a potential mediator and biomarker for the effects of PAE due to its responsiveness to environmental cues and relative stability over time. Here, we utilized a rat model of PAE to examine the DNA methylation profiles of rat hypothalami and leukocytes at four time points during early development to assess the genome-wide impact of PAE on the epigenome and identify potential biomarkers of PAE. Our model of PAE resulted in blood alcohol levels of ~80-150 mg/dl throughout the equivalent of the first two trimesters of human pregnancy. Hypothalami were analyzed on postnatal days (P) 1, 8, 15, 22 and leukocytes at P22 to compare central and peripheral markers. Genome-wide DNA methylation analysis was performed by methylated DNA immunoprecipitation followed by next-generation sequencing. Results: PAE resulted in lasting changes to DNA methylation profiles across all four ages, with 118 differentially methylated regions (DMRs) displaying persistent alterations across the developmental period at a false-discovery rate (FDR) < 0.05. In addition, 299 DMRs showed the same direction of change in the hypothalamus and leukocytes of P22 pups at an FDR < 0.05, with some genes overlapping with the developmental profile findings. The majority of these DMRs were located in intergenic regions, which contained several computationally-predicted transcription factor binding sites. Differentially methylated genes were generally involved in immune function, epigenetic remodeling, metabolism, and hormonal signaling, as determined by gene ontology analyses. Conclusions: Persistent DNA methylation changes in the hypothalamus may be associated with the long-term physiological and neurobehavioral alterations in observed in PAE. Furthermore, correlations between epigenetic alterations in peripheral tissues and those in the brain will provide a foundation for the development of biomarkers of fetal alcohol spectrum disorder (FASD). Finally, findings from studies of PAE provide important insight into the etiology of neurodevelopmental and mental health disorders, as they share numerous phenotypes and comorbidities.

Early-life socioeconomic disadvantage, not current, predicts accelerated epigenetic aging of monocytes

Low socioeconomic status (SES) in early-life and adulthood independently contribute to increased risk for aging-related chronic diseases. One mechanistic hypothesis for these associations involves faster cellular aging of immune cells, which could plausibly contribute to chronic disease pathogenesis by compromising host resistance and/or up-regulating inflammation. However, little is known about the association between life-course SES and cellular aging. The present study examines the association of early-life and current SES with a novel biomarker of cellular aging termed the "epigenetic clock," in monocytes. Additionally, we examine health behaviors and depressive symptoms as potential explanatory pathways. The study involved 335 participants between the ages of 15 and 55 from Vancouver, Canada and surrounding areas. Enrolled participants had to fit into four life-course SES trajectories, corresponding to low-low, low-high, high-low and high-high combinations of early-life (ages 0 to 5) and current SES respectively. Cellular aging of monocytes was measured using Horvath's DNA methylation derived measure of epigenetic age acceleration. Results indicated that socioeconomic disadvantage during early-life, but not later in life, was associated with accelerated epigenetic aging of monocytes. No early-life SES by current SES interaction was detected, suggesting that socioeconomic mobility is unrelated to epigenetic age acceleration. In path analyses, neither current health behaviors nor current depressive symptoms emerged as mediators of the early-life SES effect. These findings suggest socioeconomic disadvantage in early-life is independently predictive of cellular aging of immune cells, with potential implications for aging-related diseases later in life.

The biological embedding of early-life socioeconomic status and family adversity in children's genome-wide DNA methylation

Aim:

To examine variation in child DNA methylation to assess its potential as a pathway for effects of childhood social adversity on health across the life course.

Materials & methods:

In a diverse, prospective community sample of 178 kindergarten children, associations between three types of social experience and DNA methylation within buccal epithelial cells later in childhood were examined.

Results:

Family income, parental education and family psychosocial adversity each associated with increased or decreased DNA methylation (488, 354 and 102 sites, respectively) within a unique set of genomic CpG sites. Gene ontology analyses pointed to genes serving immune and developmental regulation functions.

Conclusion:

Findings provided support for DNA methylation as a biomarker linking early-life social experiences with later life health in humans.

Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array

BACKGROUND

The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required.

METHODS

DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array.

RESULTS

Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44-3.10 years across preprocessing methods.

CONCLUSIONS

Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.

Cell type-specific DNA methylation in neonatal cord tissue and cord blood: a 850K-reference panel and comparison of cell types

Accounting for cellular heterogeneity is essential in neonatal epigenome-wide association studies (EWAS) performed on heterogeneous tissues, such as umbilical cord tissue (CT) or cord blood (CB). Using a reference-panel-based statistical approach, the cell type composition of heterogeneous tissues can be estimated by comparison of whole tissue DNA methylation profiles with cell type-specific DNA methylation signatures. Currently, there is no adequate DNA methylation reference panel for CT, and existing CB panels have been generated on lower coverage Infinium HumanMethylation450 arrays. In this study, we generate a reference panel for CT and improve available CB panels by using the higher coverage Infinium MethylationEPIC arrays. We performed DNA methylation profiling of 9 cell types isolated from CT and CB samples from 14 neonates. In addition to these cell types, we profiled DNA methylation of unfractionated CT and CB. Cell type composition of these unfractionated tissue samples, as estimated by our reference panels, was in agreement with that obtained by flow cytometry. Expectedly, DNA methylation profiles from CT and CB were distinct, reflecting their mesenchymal and hematopoietic stem cell origins. Variable CpGs from both unfractionated CT and its isolated cell types were more likely to be located in open seas and intronic regions than those in CB. Cell type specific CpGs in CT were enriched in intercellular matrix pathways, while those from CB were enriched in immune-related pathways. This study provides an open source reference panel for estimation and adjustment of cellular heterogeneity in CT and CB, and broadens the scope of tissue utilization assessed in future neonatal EWAS studies.

Exposure to childhood abuse is associated with human sperm DNA methylation

Offspring of persons exposed to childhood abuse are at higher risk of neurodevelopmental and physical health disparities across the life course. Animal experiments have indicated that paternal environmental stressors can affect sperm DNA methylation and gene expression in an offspring. Childhood abuse has been associated with epigenetic marks in human blood, saliva, and brain tissue, with statistically significant methylation differences ranging widely. However, no studies have examined the association of childhood abuse with DNA methylation in gametes. We examined the association of childhood abuse with DNA methylation in human sperm. Combined physical, emotional, and sexual abuse in childhood was characterized as none, medium, or high. DNA methylation was assayed in 46 sperm samples from 34 men in a longitudinal non-clinical cohort using HumanMethylation450 BeadChips. We performed principal component analysis and examined the correlation of principal components with abuse exposure. Childhood abuse was associated with a component that captured 6.2% of total variance in DNA methylation (p < 0.05). Next, we investigated the regions differentially methylated by abuse exposure. We identified 12 DNA regions differentially methylated by childhood abuse, containing 64 probes and including sites on genes associated with neuronal function (MAPT, CLU), fat cell regulation (PRDM16), and immune function (SDK1). We examined adulthood health behaviors, mental health, and trauma exposure as potential mediators of an association between abuse and DNAm, and found that mental health and trauma exposure partly mediated the association. Finally, we constructed a parsimonious epigenetic marker for childhood abuse using a machine learning approach, which identified three probes that predicted high vs. no childhood abuse in 71% of participants. Our results suggested that childhood abuse is associated with sperm DNA methylation, which may have implications for offspring development. Larger samples are needed to identify with greater confidence specific genomic regions differentially methylated by childhood abuse.

Children's biobehavioral reactivity to challenge predicts DNA methylation in adolescence and emerging adulthood

A growing body of research has documented associations between adverse childhood environments and DNA methylation, highlighting epigenetic processes as potential mechanisms through which early external contexts influence health across the life course. The present study tested a complementary hypothesis: indicators of children's early internal, biological, and behavioral responses to stressful challenges may also be linked to stable patterns of DNA methylation later in life. Children's autonomic nervous system reactivity, temperament, and mental health symptoms were prospectively assessed from infancy through early childhood, and principal components analysis (PCA) was applied to derive composites of biological and behavioral reactivity. Buccal epithelial cells were collected from participants at 15 and 18 years of age. Findings revealed an association between early life biobehavioral inhibition/disinhibition and DNA methylation across many genes. Notably, reactive, inhibited children were found to have decreased DNA methylation of the DLX5 and IGF2 genes at both time points, as compared to non‐reactive, disinhibited children. Results of the present study are provisional but suggest that the gene's profile of DNA methylation may constitute a biomarker of normative or potentially pathological differences in reactivity. Overall, findings provide a foundation for future research to explore relations among epigenetic processes and differences in both individual‐level biobehavioral risk and qualities of the early, external childhood environment.

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation β-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.

PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

BACKGROUND

Polygenic risk scores (PRS) describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of variance in outcome than single nucleotide polymorphisms (SNPs) alone. However, there is little consensus on the optimal data input for generating PRS, and existing approaches largely preclude the use of imputed posterior probabilities and strand-ambiguous SNPs i.e., A/T or C/G polymorphisms. Our ability to predict complex traits that arise from the additive effects of a large number of SNPs would likely benefit from a more inclusive approach.

RESULTS

We developed PRS-on-Spark (PRSoS), a software implemented in Apache Spark and Python that accommodates different data inputs and strand-ambiguous SNPs to calculate PRS. We compared performance between PRSoS and an existing software (PRSice v1.25) for generating PRS for major depressive disorder using a community cohort (N = 264). We found PRSoS to perform faster than PRSice v1.25 when PRS were generated for a large number of SNPs (~ 17 million SNPs; t = 42.865, p = 5.43E-04). We also show that the use of imputed posterior probabilities and the inclusion of strand-ambiguous SNPs increase the proportion of variance explained by a PRS for major depressive disorder (from 4.3% to 4.8%).

CONCLUSIONS

PRSoS provides the user with the ability to generate PRS using an inclusive and efficient approach that considers a larger number of SNPs than conventional approaches. We show that a PRS for major depressive disorder that includes strand-ambiguous SNPs, calculated using PRSoS, accounts for the largest proportion of variance in symptoms of depression in a community cohort, demonstrating the utility of this approach. The availability of this software will help users develop more informative PRS for a variety of complex phenotypes.

Reproduction predicts shorter telomeres and epigenetic age acceleration among young adult women

Evolutionary theory predicts that reproduction entails costs that detract from somatic maintenance, accelerating biological aging. Despite support from studies in human and non-human animals, mechanisms linking 'costs of reproduction' (CoR) to aging are poorly understood. Human pregnancy is characterized by major alterations in metabolic regulation, oxidative stress, and immune cell proliferation. We hypothesized that these adaptations could accelerate blood-derived cellular aging. To test this hypothesis, we examined gravidity in relation to telomere length (TL, n = 821) and DNA-methylation age (DNAmAge, n = 397) in a cohort of young (20-22 year-old) Filipino women. Age-corrected TL and accelerated DNAmAge both predict age-related morbidity and mortality, and provide markers of mitotic and non-mitotic cellular aging, respectively. Consistent with theoretical predictions, TL decreased (p = 0.031) and DNAmAge increased (p = 0.007) with gravidity, a relationship that was not contingent upon resource availability. Neither biomarker was associated with subsequent fertility (both p > 0.3), broadly consistent with a causal effect of gravidity on cellular aging. Our findings provide evidence that reproduction in women carries costs in the form of accelerated aging through two independent cellular pathways.

Perinatally acquired HIV infection accelerates epigenetic aging in South African adolescents

OBJECTIVE

Recent studies demonstrate that infection with the HIV-1 is associated with accelerated aging effects in adults according to a highly accurate epigenetic biomarker of aging known as epigenetic clock. However, it is not yet known whether epigenetic age acceleration occurs as early as adolescence in perinatally HIV-infected (PHIV+) youth.

DESIGN

Observational study of PHIV and HIV-uninfected adolescents enrolled in the Cape Town Adolescent Antiretroviral Cohort Study.

METHODS

The Illumina EPIC array was used to generate blood DNA methylation data from 204 PHIV and 44 age-matched, uninfected (HIV-) adolescents aged 9-12 years old. The epigenetic clock software and method was used to estimate two measures of epigenetic age acceleration. Each participant completed a comprehensive neuropsychological test battery upon enrollment to Cape Town Adolescent Antiretroviral Cohort.

RESULTS

HIV is associated with biologically older blood in PHIV+ adolescents according to both measures of epigenetic age acceleration. One of the measures, extrinsic epigenetic age acceleration, is negatively correlated with measures of cognitive functioning (executive functioning, working memory, processing speed).

CONCLUSION

Overall, our results indicate that epigenetic age acceleration in blood can be observed in PHIV+ adolescents and that these epigenetic changes accompany poorer cognitive functioning.

Altered DNA methylation is associated with aberrant gene expression in parenchymal but not airway fibroblasts isolated from individuals with COPD

Background

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease of the lungs that is currently the fourth leading cause of death worldwide. Genetic factors account for only a small amount of COPD risk, but epigenetic mechanisms, including DNA methylation, have the potential to mediate the interactions between an individual's genetics and environmental exposure. DNA methylation is highly cell type-specific, and individual cell type studies of DNA methylation in COPD are sparse. Fibroblasts are present within the airway and parenchyma of the lung and contribute to the aberrant deposition of extracellular matrix in COPD. No assessment or comparison of genome-wide DNA methylation profiles in the airway and parenchymal fibroblasts from individuals with and without COPD has been undertaken. These data provide valuable insight into the molecular mechanisms contributing to COPD and the differing pathologies of small airways disease and emphysema in COPD.

Methods

Genome-wide DNA methylation was evaluated at over 485,000 CpG sites using the Illumina Infinium HumanMethylation450 BeadChip array in the airway (non-COPD n = 8, COPD n = 7) and parenchymal fibroblasts (non-COPD n = 17, COPD n = 29) isolated from individuals with and without COPD. Targeted gene expression was assessed by qPCR in matched RNA samples.

Results

Differentially methylated DNA regions were identified between cells isolated from individuals with and without COPD in both airway and parenchymal fibroblasts. Only in parenchymal fibroblasts was differential DNA methylation associated with differential gene expression. A second analysis of differential DNA methylation variability identified 359 individual differentially variable CpG sites in parenchymal fibroblasts. No differentially variable CpG sites were identified in the airway fibroblasts. Five differentially variable-methylated CpG sites, associated with three genes, were subsequently assessed for gene expression differences. Two genes (OAT and GRIK2) displayed significantly increased gene expression in cells isolated from individuals with COPD.

Conclusions

Differential and variable DNA methylation was associated with COPD status in the parenchymal fibroblasts but not airway fibroblasts. Aberrant DNA methylation was associated with altered gene expression imparting biological function to DNA methylation changes. Changes in DNA methylation are therefore implicated in the molecular mechanisms underlying COPD pathogenesis and may represent novel therapeutic targets.

Agreement in DNA methylation levels from the Illumina 450K array across batches, tissues, and time

Epigenome-wide association studies (EWAS) have focused primarily on DNA methylation as a chemically stable and functional epigenetic modification. However, the stability and accuracy of the measurement of methylation in different tissues and extraction types is still being actively studied, and the longitudinal stability of DNA methylation in commonly studied peripheral tissues is of great interest. Here, we used data from two studies, three tissue types, and multiple time points to assess the stability of DNA methylation measured with the Illumina Infinium HumanMethylation450 BeadChip array. Redundancy analysis enabled visual assessment of agreement of replicate samples overall and showed good agreement after removing effects of tissue type, age, and sex. At the probe level, analysis of variance contrasts separating technical and biological replicates clearly showed better agreement between technical replicates versus longitudinal samples, and suggested increased stability for buccal cells versus blood or blood spots. Intraclass correlations (ICCs) demonstrated that inter-individual variability is of similar magnitude to within-sample variability at many probes; however, as inter-individual variability increased, so did ICC. Furthermore, we were able to demonstrate decreasing agreement in methylation levels with time, despite a maximal sampling interval of only 576 days. Finally, at 6 popular candidate genes, there was a large range of stability across probes. Our findings highlight important sources of technical and biological variation in DNA methylation across different tissues over time. These data will help to inform longitudinal sampling strategies of future EWAS.

DNA methylation as a predictor of fetal alcohol spectrum disorder

Background

Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD.

Methods

Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759).

Results

We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity.

Conclusion

These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.

Choice of surrogate tissue influences neonatal EWAS findings

BACKGROUND

Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth.

METHODS

In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues.

RESULTS

Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude.

CONCLUSIONS

The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS.

TRIAL REGISTRATION

This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .

DNA methylation signatures in peripheral blood mononuclear cells from a lifestyle intervention for women at midlife: a pilot randomized controlled trial

Physical activity confers many health benefits, but the underlying mechanisms require further exploration. In this pilot randomized controlled trial we tested the association between longitudinal measures of DNA methylation and changes in objective measures, including physical activity, weight loss, and C-reactive protein levels in community-dwelling women aged 55 to 70 years. We assessed DNA methylation from 20 healthy postmenopausal women, who did not have a mobility disability and allocated them to a group-based intervention, Everyday Activity Supports You, or a control group (monthly group-based health-related education sessions). The original randomized controlled trial was 6 months in duration and consisted of nine 2-h sessions that focused on reducing sedentary behaviour for the intervention group, or six 1-h sessions that focused on other topics for the control group. We collected peripheral blood mononuclear cells, both at baseline and 6 months later. Samples were processed using the Illumina 450k Methylation array to quantify DNA methylation at >485 000 CpG sites in the genome. There were no significant associations between DNA methylation and physical activity, but we did observe alterations at epigenetic modifications that correlated with change in percent body weight over a 6-month period at 12 genomic loci, 2 of which were located near the previously reported weight-associated genes RUNX3 and NAMPT. We also generated a potential epigenetic predictor of weight loss using baseline DNA methylation at 5 CpG sites. These exploratory findings suggest a potential biological link between body weight changes and epigenetic processes.

RECQ-like helicases Sgs1 and BLM regulate R-loop-associated genome instability

Sgs1, the orthologue of human Bloom's syndrome helicase BLM, is a yeast DNA helicase functioning in DNA replication and repair. We show that SGS1 loss increases R-loop accumulation and sensitizes cells to transcription-replication collisions. Yeast lacking SGS1 accumulate R-loops and γ-H2A at sites of Sgs1 binding, replication pausing regions, and long genes. The mutation signature of sgs1Δ reveals copy number changes flanked by repetitive regions with high R-loop-forming potential. Analysis of BLM in Bloom's syndrome fibroblasts or by depletion of BLM from human cancer cells confirms a role for Sgs1/BLM in suppressing R-loop-associated genome instability across species. In support of a potential direct effect, BLM is found physically proximal to DNA:RNA hybrids in human cells, and can efficiently unwind R-loops in vitro. Together, our data describe a conserved role for Sgs1/BLM in R-loop suppression and support an increasingly broad view of DNA repair and replication fork stabilizing proteins as modulators of R-loop-mediated genome instability.

The Intersection of Aging Biology and the Pathobiology of Lung Diseases: A Joint NHLBI/NIA Workshop

Death from chronic lung disease is increasing and chronic obstructive pulmonary disease has become the third leading cause of death in the United States in the past decade. Both chronic and acute lung diseases disproportionately affect elderly individuals, making it likely that these diseases will become more frequent and severe as the worldwide population ages. Chronic lung diseases are associated with substantial morbidity, frequently resulting in exercise limiting dyspnea, immobilization, and isolation. Therefore, effective strategies to prevent or treat lung disease are likely to increase healthspan as well as life span. This review summarizes the findings of a joint workshop sponsored by the NIA and NHLBI that brought together investigators focused on aging and lung biology. These investigators encouraged the use of genetic systems and aged animals in the study of lung disease and the development of integrative systems-based platforms that can dynamically incorporate data sets that describe the genomics, transcriptomics, epigenomics, metabolomics, and proteomics of the aging lung in health and disease. Further research was recommended to integrate benchmark biological hallmarks of aging in the lung with the pathobiology of acute and chronic lung diseases with divergent pathologies for which advanced age is the most important risk factor.

Accelerated DNA methylation age in adolescent girls: associations with elevated diurnal cortisol and reduced hippocampal volume

Numerous studies have linked exposure to stress to adverse health outcomes through the effects of cortisol, a product of the stress response system, on cellular aging processes. Accelerated DNA methylation age is a promising epigenetic marker associated with stress and disease risk that may constitute a link from stress response to changes in neural structures. Specifically, elevated glucocorticoid signaling likely contributes to accelerating DNA methylation age, which may signify a maladaptive stress-related cascade that leads to hippocampal atrophy. We examined the relations among diurnal cortisol levels, DNA methylation age and hippocampal volume in a longitudinal study of 46 adolescent girls. We computed area under the curve from two daily cortisol collection periods, and calculated DNA methylation age using previously established methods based on a set of CpG sites associated with chronological age. We computed a residual score by partialling out chronological age; higher discrepancies reflect relatively accelerated DNA methylation age. We assessed hippocampal volume via T1-weighted images and automated volumetric segmentation. We found that greater diurnal cortisol production was associated with accelerated DNA methylation age, which in turn was associated with reduced left hippocampal volume. Finally, accelerated DNA methylation age significantly mediated the association between diurnal cortisol and left hippocampal volume. Thus, accelerated DNA methylation age may be an epigenetic marker linking hypothalamic-pituitary-adrenal axis dysregulation with neural structure. If these findings are replicated, the current study provides a method for advancing our understanding of mechanisms by which glucocorticoid signaling is associated with cellular aging and brain development.

DNA methylation signatures of chronic alcohol dependence in purified CD3+ T-cells of patients undergoing alcohol treatment

Several studies have shown an association of alcohol dependence with DNA methylation (DNAm), suggesting that environmentally-induced changes on epigenomic variation may play an important role in alcohol dependence. In the present study, we analysed genome-wide DNAm profiles of purified CD3⁺ T-cells from pre- and post-treatment alcohol dependent patients, as well as closely matched healthy controls. We identified 59 differentially methylated CpG sites comparing patients prior to treatment with healthy controls and were able to confirm 8 of those sites in additional analyses for differentially methylated regions. Comparing patients before and after a 3-week alcohol treatment program we revealed another unique set of 48 differentially methylated CpG sites. Additionally, we found that the mean global DNAm was significantly lower in patients prior to treatment compared to controls, but reverted back to levels similar to controls after treatment. We validated top-ranked hits derived from the epigenome-wide analysis by pyrosequencing and further replicated two of them in an independent cohort and confirmed differential DNAm of HECW2 and SRPK3 in whole blood. This study is the first to show widespread DNAm variation in a disease-relevant blood cell type and implicates HECW2 and SRPK3 DNAm as promising blood-based candidates to follow up in future studies.

Maternal blood contamination of collected cord blood can be identified using DNA methylation at three CpGs

Background

Cord blood is a commonly used tissue in environmental, genetic, and epigenetic population studies due to its ready availability and potential to inform on a sensitive period of human development. However, the introduction of maternal blood during labor or cross-contamination during sample collection may complicate downstream analyses. After discovering maternal contamination of cord blood in a cohort study of 150 neonates using Illumina 450K DNA methylation (DNAm) data, we used a combination of linear regression and random forest machine learning to create a DNAm-based screening method. We identified a panel of DNAm sites that could discriminate between contaminated and non-contaminated samples, then designed pyrosequencing assays to pre-screen DNA prior to being assayed on an array.

Results

Maternal contamination of cord blood was initially identified by unusual X chromosome DNA methylation patterns in 17 males. We utilized our DNAm panel to detect contaminated male samples and a proportional amount of female samples in the same cohort. We validated our DNAm screening method on an additional 189 sample cohort using both pyrosequencing and DNAm arrays, as well as 9 publically available cord blood 450K data sets. The rate of contamination varied from 0 to 10% within these studies, likely related to collection specific methods.

Conclusions

Maternal blood can contaminate cord blood during sample collection at appreciable levels across multiple studies. We have identified a panel of markers that can be used to identify this contamination, either post hoc after DNAm arrays have been completed, or in advance using a targeted technique like pyrosequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0370-2) contains supplementary material, which is available to authorized users.