New insights and updated guidelines for epigenome-wide association studies

Probing prenatal bisphenol exposures and tissue-specific DNA methylation responses in cord blood, cord tissue, and placenta

The early-gestational fetal epigenome establishes the landscape for fetal development and is susceptible to disruption via environmental stressors including chemical exposures. Research has explored how cell- and tissue-type-specific epigenomic signatures contribute to human disease, but how the epigenome in each tissue comparatively responds to environmental exposures is largely unknown. This pilot study compared DNA methylation in four previously identified genes across matched cord blood (CB), cord tissue (CT), and placental (PL) samples from 28 mother-infant pairs in tthe Michigan Mother Infant Pairs study; evaluated association between prenatal exposure to bisphenols (BPA, BPF, and BPS) and DNA methylation (DNAm) by tissue type; compared epigenome-wide DNAm of CB and PL; and explored associations between prenatal bisphenol exposures and epigenome-wide DNAm in PL. Bisphenol concentrations were quantified in first-trimester maternal urine. DNAm was assessed at four genes via pyrosequencing in three tissues; epigenome-wide DNAm analysis via Infinium MethylationEPIC array was completed on CB and PL. Candidate gene analysis revealed tissue-specific differences across all genes. In adjusted linear regression, BPA and BPF were associated with DNAm across candidate genes in PL but not CB and CT. Epigenome-wide comparison of matched CB and PL DNAm revealed tissue-specific differences at most CpG sites and modest associations between maternal first-trimester bisphenol exposures and PL but not CB DNAm. These data endorse inclusion of a variety of tissues in prenatal exposure studies. Overlapping and divergent responses in CB, CT, and PL demonstrate their utility in combination to capture a fuller picture of the epigenetic effect of developmental exposures.

EpiVisR: exploratory data analysis and visualization in epigenome-wide association analyses

Background

With the widespread availability of microarray technology for epigenetic research, methods for calling differentially methylated probes or differentially methylated regions have become effective tools to analyze this type of data. Furthermore, visualization is usually employed for quality check of results and for further insights. Expert knowledge is required to leverage capabilities of these methods. To overcome this limitation and make visualization in epigenetic research available to the public, we designed EpiVisR.

Results

The EpiVisR tool allows to select and visualize combinations of traits (i.e., concentrations of chemical compounds) and differentially methylated probes/regions. It supports various modes of enriched presentation to get the most knowledge out of existing data: (1) enriched Manhattan plot and enriched volcano plot for selection of probes, (2) trait-methylation plot for visualization of selected trait values against methylation values, (3) methylation profile plot for visualization of a selected range of probes against selected trait values as well as, (4) correlation profile plot for selection and visualization of further probes that are correlated to the selected probe. EpiVisR additionally allows exporting selected data to external tools for tasks such as network analysis.

Conclusion

The key advantage of EpiVisR is the annotation of data in the enriched plots (and tied tables) as well as linking to external data sources for further integrated data analysis. Using the EpiVisR approach will allow users to integrate data from traits with epigenetic analyses that are connected by belonging to the same individuals. Merging data from various data sources among the same cohort and visualizing them will enable users to gain more insights from existing data.

Data Analysis of DNA Methylation Epigenome-Wide Association Studies (EWAS): A Guide to the Principles of Best Practice

Array-based EWAS have become an increasingly popular technique to identify population epigenetic effects, particularly in humans. With the arrival of nonhuman species arrays, such as the mouse, this is likely to become an even more widely used technology. This chapter provides the less experienced researcher a guide to the analysis of data from the most widely used platform, the Illumina Infinium Methylation assay. This includes an overview of quality filtering, data normalization, analysis options, and techniques to improve the interpretation of results.

Meta-analysis of epigenome-wide association studies of carotid intima-media thickness

Common carotid intima-media thickness (cIMT) is an index of subclinical atherosclerosis that is associated with ischemic stroke and coronary artery disease (CAD). We undertook a cross-sectional epigenome-wide association study (EWAS) of measures of cIMT in 6400 individuals. Mendelian randomization analysis was applied to investigate the potential causal role of DNA methylation in the link between atherosclerotic cardiovascular risk factors and cIMT or clinical cardiovascular disease. The CpG site cg05575921 was associated with cIMT (beta = -0.0264, p value = 3.5 × 10^-8) in the discovery panel and was replicated in replication panel (beta = -0.07, p value = 0.005). This CpG is located at chr5:81649347 in the intron 3 of the aryl hydrocarbon receptor repressor gene (AHRR). Our results indicate that DNA methylation at cg05575921 might be in the pathway between smoking, cIMT and stroke. Moreover, in a region-based analysis, 34 differentially methylated regions (DMRs) were identified of which a DMR upstream of ALOX12 showed the strongest association with cIMT (p value = 1.4 × 10^-13). In conclusion, our study suggests that DNA methylation may play a role in the link between cardiovascular risk factors, cIMT and clinical cardiovascular disease.

Anatomy of DNA methylation signatures: Emerging insights and applications

DNA methylation (DNAm) signatures are unique patterns of DNAm alterations defined for rare disorders caused by pathogenic variants in epigenetic regulatory genes. The potential of DNAm signatures (also known as "episignatures") is just beginning to emerge as there are >300 known epigenetic regulatory genes, ∼100 of which are linked to neurodevelopmental disorders. To date, approximately 50 signatures have been identified, which have proven unexpectedly successful as predictive tools for classifying variants of uncertain significance as pathogenic or benign. The molecular basis of these signatures is poorly understood. Furthermore, their relationships to primary disease pathophysiology have yet to be adequately investigated, despite clear demonstrations of potential connections. There are currently no published guidelines for signature development. As signatures are highly dependent on the samples and methods used to derive them, we propose a framework for consideration in signature development including sample size, statistical parameters, cell type of origin, and the value of detailed clinical and molecular information. We illustrate the relationship between signature output/efficacy and sample size by generating and testing 837 DNAm signatures of Kleefstra syndrome using downsampling analysis. Our findings highlight that no single DNAm signature encompasses all DNAm alterations present in a rare disorder, and that a substandard study design can generate a DNAm signature that misclassifies variants. Finally, we discuss the importance of further investigating DNAm signatures to inform disease pathophysiology and broaden their scope as a functional assay.

Precision medicine: Concept and tools

Precision medicine is the new age medicine and refers to tailoring treatments to a subpopulation who have a common susceptibility to a particular disease or similar response to a particular drug. Although the concept existed even during the times of Sir William Osler, it was given a shot in the arm with the Precision Medicine Initiative launched by Barack Obama in 2015. The main tools of precision medicine are Big data, artificial intelligence, the various omics, pharmaco-omics, environmental and social factors and the integration of these with preventive and population medicine. Big data can be acquired from electronic health records of patients and includes various biomarkers (clinical and omics based), laboratory and radiological investigations and these can be analysed through machine learning by various complex flowcharts setting up an algorithm for the management of specific subpopulations. So, there is a move away from the traditional "one size fits all" treatment to precision-based medicine. Research in "omics" has increased in leaps and bounds and advancements have included the fields of genomics, epigenomics, proteomics, transcriptomics, metabolomics and microbiomics. Pharmaco-omics has also come to the forefront with development of new drugs and suiting a particular drug to a particular subpopulation, thus avoiding their prescription to non-responders, preventing unwanted adverse effects and proving economical in the long run. Environmental, social and behavioural factors are as important or in fact more important than genetic factors in most complex diseases and managing these factors form an important part of precision medicine. Finally integrating precision with preventive and public health makes "precision medicine" a complete final product which will change the way medicine will be practised in future.

Controlled human exposures to diesel exhaust: a human epigenome-wide experiment of target bronchial epithelial cells

Diesel exhaust (DE) is a major contributor to ambient air pollution around the world. It is a known human carcinogen that targets the respiratory system and increases risk for many diseases, but there is limited research on the effects of DE exposure on the epigenome of human bronchial epithelial cells. Understanding the epigenetic impact of this environmental pollutant can elucidate biological mechanisms involved in the pathogenesis of harmful DE-related health effects. To estimate the causal effect of short-term DE exposure on the bronchial epithelial epigenome, we conducted a controlled single-blinded randomized crossover human experiment of exposure to DE and used bronchoscopy and Illumina 450K arrays for data collection and analysis, respectively. Of the 13 participants, 11 (85%) were male and 2 (15%) were female, and 12 (92%) were White and one (8%) was Hispanic; the mean age was 26 years (SD = 3.8 years). Eighty CpGs were differentially methylated, achieving the minimum possible exact P-value of P = 2.44 × 10-4 (i.e. 2/213). In regional analyses, we found two differentially methylated regions (DMRs) annotated to the chromosome 5 open reading frame 63 genes (C5orf63; 7-CpGs) and unc-45 myosin chaperone A gene (UNC45A; 5-CpGs). Both DMRs showed increased DNA methylation after DE exposure. The average causal effects for the DMRs ranged from 1.5% to 6.0% increases in DNA methylation at individual CpGs. In conclusion, we found that short-term DE alters DNA methylation of genes in target bronchial epithelial cells, demonstrating epigenetic level effects of exposure that could be implicated in pulmonary pathologies.

Social epigenomics: are we at an impasse?

Aim: Social scientists have placed particularly high expectations on the study of epigenomics to explain how exposure to adverse social factors like poverty, child maltreatment and racism - particularly early in childhood - might contribute to complex diseases. However, progress has stalled, reflecting many of the same challenges faced in genomics, including overhype, lack of diversity in samples, limited replication and difficulty interpreting significance of findings. Materials & methods: This review focuses on the future of social epigenomics by discussing progress made, ongoing methodological and analytical challenges and suggestions for improvement. Results & conclusion: Recommendations include more diverse sample types, cross-cultural, longitudinal and multi-generational studies. True integration of social and epigenomic data will require increased access to both data types in publicly available databases, enhanced data integration frameworks, and more collaborative efforts between social scientists and geneticists.

Critical evaluation of the DNA-methylation markers ABCG1 and SREBF1 for Type 2 diabetes stratification

Aim: Validation of epigenome-wide association studies is sparse. Therefore, we evaluated the methylation markers cg06500161 (ABCG1) and cg11024682 (SREBF1) as classifiers for diabetes stratification. Patients & methods: DNA methylation was measured in blood (n = 167), liver (n = 99) and visceral adipose tissue (n = 99) of nondiabetic or Type 2 diabetic subjects by bisulfite pyrosequencing. Results: DNA methylation at cg11024682 in blood and liver correlated with BMI. Methylation at cg06500161 was influenced by the adjacent SNP rs9982016. Insulin-resistant and sensitive subjects could be stratified by DNA methylation status in blood or visceral adipose tissue. Conclusion: DNA methylation at both loci in blood presents a promising approach for risk group stratification and could be valuable for personalized Type 2 diabetes risk prediction in the future.

Epigenetics and ADHD: Toward an Integrative Approach of the Disorder Pathogenesis

OBJECTIVE

Epigenetic hypothesis is one of the research pathways used to explain the complex etiology of neurodevelopmental disorders. This review highlights the findings of recent studies in the field of epigenetics in ADHD.

METHODS

An electronic literature search using Medline.

RESULTS

In the Gene × Environment interaction model, several clinical, genetic and molecular arguments support the epigenetic hypothesis in ADHD etiology. Environmental ADHD risk factors including toxic, nutritional factors and stressful life events lead to changes in DNA methylation and in histone modification levels. One critical CpG site located in the promoter of the DRD4 gene exhibited a specific pattern in ADHD children. A methylome wide exploration of DNA showed decreased methylation in vasoactive intestinal peptide receptor 2 gene, which was not replicated by further research.

CONCLUSION

Current data require consolidation and could lead to the identification of biomarkers and the introduction of new modalities of treatment.

Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation

Background

The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages.

Results

BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood.

Conclusions

Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0245-6) contains supplementary material, which is available to authorized users.

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 .

Prenatal phthalate exposure and altered patterns of DNA methylation in cord blood

Epigenetic changes such as DNA methylation may be a molecular mechanism through which environmental exposures affect health. Phthalates are known endocrine disruptors with ubiquitous exposures in the general population including pregnant women, and they have been linked with a number of adverse health outcomes. We examined the association between in utero phthalate exposure and altered patterns of cord blood DNA methylation in 336 Mexican-American newborns. Concentrations of 11 phthalate metabolites were analyzed in maternal urine samples collected at 13 and 26 weeks gestation as a measure of fetal exposure. DNA methylation was assessed using the Infinium HumanMethylation 450K BeadChip adjusting for cord blood cell composition. To identify differentially methylated regions (DMRs) that may be more informative than individual CpG sites, we used two different approaches, DMRcate and comb-p. Regional assessment by both methods identified 27 distinct DMRs, the majority of which were in relation to multiple phthalate metabolites. Most of the significant DMRs (67%) were observed for later pregnancy (26 weeks gestation). Further, 51% of the significant DMRs were associated with the di-(2-ethylhexyl) phthalate metabolites. Five individual CpG sites were associated with phthalate metabolite concentrations after multiple comparisons adjustment (FDR), all showing hypermethylation. Genes with DMRs were involved in inflammatory response (IRAK4 and ESM1), cancer (BRCA1 and LASP1), endocrine function (CNPY1), and male fertility (IFT140, TESC, and PRDM8). These results on differential DNA methylation in newborns with prenatal phthalate exposure provide new insights and targets to explore mechanism of adverse effects of phthalates on human health. Environ. Mol. Mutagen. 58:398-410, 2017. © 2017 Wiley Periodicals, Inc.

Future of environmental research in the age of epigenomics and exposomics

Environmental research and public health in the 21st century face serious challenges such as increased air pollution and global warming, widespread use of potentially harmful chemicals including pesticides, plasticizers, and other endocrine disruptors, and radical changes in nutrition and lifestyle typical of modern societies. In particular, exposure to environmental and occupational toxicants may contribute to the occurrence of adverse birth outcomes, neurodevelopmental deficits, and increased risk of cancer and other multifactorial diseases such as diabetes and asthma. Rapidly evolving methodologies of exposure assessment and the conceptual framework of the Exposome, first introduced in 2005, are new frontiers of environmental research. Metabolomics and adductomics provide remarkable opportunities for a better understanding of exposure and prediction of potential adverse health outcomes. Metabolomics, the study of metabolism at whole-body level, involves assessment of the total repertoire of small molecules present in a biological sample, shedding light on interactions between gene expression, protein expression, and the environment. Advances in genomics, transcriptomics, and epigenomics are generating multidimensional structures of biomarkers of effect and susceptibility, increasingly important for the understanding of molecular mechanisms and the emergence of personalized medicine. Epigenetic mechanisms, particularly DNA methylation and miRNA expression, attract increasing attention as potential links between the genetic and environmental determinants of health and disease. Unlike genetics, epigenetic mechanisms could be reversible and an understanding of their role may lead to better protection of susceptible populations and improved public health.

CpG Methylation across the adipogenic PPARγ gene and its relationship with birthweight and child BMI at 9 years

Background

To examine methylation of the peroxisome proliferator-activated receptor γ (PPARγ) gene and its relationship with child weight status, at birth and 9 years.

Methods

We measured PPARγ methylation across 23 CpG sites using the Infinium Illumina 450 k array for children from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) cohort at birth (N = 373) and 9 years (N = 245).

Results

Methylation level correlation patterns across the 23 PPARγ CpG sites were conserved between birth and 9-year ages. We found high inter-CpG correlations between sites 1–3 (methylation block 1) and also between sites 18–23 (methylation block 2) for both time points, although these patterns were less pronounced at 9 years. Additionally, sites 1–3 (north shore) had the highest intra-CpG correlations over time (r = 0.24, 0.42, and 0.3; P = 0.002, P < 0.001, P < 0.001, respectively). PPARγ methylation levels tended to increase with age, and the largest differences were observed for north shore sites (7.4%). Adjusting for sex, both site 1 and site 20 (gene body) methylation at birth was significantly and inversely associated with birth weight (β = −0.13, P = 0.033; β = −0.09, P = 0.025, respectively). Similarly, we found that site 1 and site 20 methylation at 9 years was significantly and inversely associated with 9-year BMI z-score (β = −0.41, P = 0.015; β = −0.23, P = 0.045, respectively).

Conclusion

Our results indicate that PPARγ methylation is highly organized and conserved over time, and highlight the potential functional importance of north shore sites, adding to a better understanding of regional human methylome patterns. Overall, our results suggest that PPARγ methylation may be associated with child body size.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-016-0365-4) contains supplementary material, which is available to authorized users.

DNA methylation: conducting the orchestra from exposure to phenotype?

DNA methylation, through 5-methyl- and 5-hydroxymethylcytosine (5mC and 5hmC), is considered to be one of the principal interfaces between the genome and our environment, and it helps explain phenotypic variations in human populations. Initial reports of large differences in methylation level in genomic regulatory regions, coupled with clear gene expression data in both imprinted genes and malignant diseases, provided easily dissected molecular mechanisms for switching genes on or off. However, a more subtle process is becoming evident, where small (<10 %) changes to intermediate methylation levels are associated with complex disease phenotypes. This has resulted in two clear methylation paradigms. The latter “subtle change” paradigm is rapidly becoming the epigenetic hallmark of complex disease phenotypes, although we are currently hampered by a lack of data addressing the true biological significance and meaning of these small differences.

Our initial expectation of rapidly identifying mechanisms linking environmental exposure to a disease phenotype led to numerous observational/association studies being performed. Although this expectation remains unmet, there is now a growing body of literature on specific genes, suggesting wide ranging transcriptional and translational consequences of such subtle methylation changes. Data from the glucocorticoid receptor (NR3C1) has shown that a complex interplay between DNA methylation, extensive 5′UTR splicing, and microvariability gives rise to the overall level and relative distribution of total and N-terminal protein isoforms generated. Additionally, the presence of multiple AUG translation initiation codons throughout the complete, processed mRNA enables translation variability, hereby enhancing the translational isoforms and the resulting protein isoform diversity, providing a clear link between small changes in DNA methylation and significant changes in protein isoforms and cellular locations. Methylation changes in the NR3C1 CpG island alters the NR3C1 transcription and eventually protein isoforms in the tissues, resulting in subtle but visible physiological variability.

This review addresses the current pathophysiological and clinical associations of such characteristically small DNA methylation changes, the ever-growing roles of DNA methylation and the evidence available, particularly from the glucocorticoid receptor of the cascade of events initiated by such subtle methylation changes, as well as addressing the underlying question as to what represents a genuine biologically significant difference in methylation.

How to make DNA methylome wide association studies more powerful

Genome-wide association studies had a troublesome adolescence, while researchers increased statistical power, in part by increasing subject numbers. Interrogating the interaction of genetic and environmental influences raised new challenges of statistical power, which were not easily bested by the addition of subjects. Screening the DNA methylome offers an attractive alternative as methylation can be thought of as a proxy for the combined influences of genetics and environment. There are statistical challenges unique to DNA methylome data and also multiple features, which can be exploited to increase power. We anticipate the development of DNA methylome association study designs and new analytical methods, together with integration of data from other molecular species and other studies, which will boost statistical power and tackle causality. In this way, the molecular trajectories that underlie disease development will be uncovered.

The multifaceted interplay between lipids and epigenetics

PURPOSE OF REVIEW

The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships.

RECENT FINDINGS

Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids.

SUMMARY

It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.

Estimation of blood cellular heterogeneity in newborns and children for epigenome-wide association studies

Confounding by cellular heterogeneity has become a major concern for epigenome-wide association studies (EWAS) in peripheral blood samples from population and clinical studies. Adjusting for white blood cell percentage estimates produced by the minfi implementation of the Houseman algorithm (minfi) during statistical analysis is now an established method to account for this bias in adults. However, minfi has not been benchmarked against white blood cell counts in children that may differ substantially from the reference dataset used in its estimation. We compared estimates of white blood cell type percentages produced by two methods, minfi and differential cell count (DCC), in a birth cohort at two time points (birth and 12 years of age). We found that both minfi and DCC had similar trends as children aged, and neither count method differed by sex among newborns (P > 0.10). However, minfi estimates did not correlate well with DCC in samples from newborns (ρ = -0.05 for granulocytes; ρ = -0.03 for lymphocytes). In older children, correlation improved substantially (ρ = 0.77 for granulocytes; ρ = 0.75 for lymphocytes), likely due to increasing similarity with minfi's adult reference data as children aged. Our findings suggest that the minfi method may provide suitable estimates of white blood cell composition for samples from adults and older children, but may not currently be appropriate for EWAS involving newborns or young children.