Is epidemiology ready for epigenetics?

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Low reliability of DNA methylation across Illumina Infinium platforms in cord blood: implications for replication studies and meta-analyses of prenatal exposures

Background

There is an increasing interest in the role of epigenetics in epidemiology, but the emerging research field faces several critical biological and technical challenges. In particular, recent studies have shown poor correlation of measured DNA methylation (DNAm) levels within and across Illumina Infinium platforms in various tissues. In this study, we have investigated concordance between 450 k and EPIC Infinium platforms in cord blood. We could not replicate our previous findings on the association of prenatal paracetamol exposure with cord blood DNAm, which prompted an investigation of cross-platform DNAm differences.

Results

This study is based on two DNAm data sets from cord blood samples selected from the Norwegian Mother, Father and Child Cohort Study (MoBa). DNAm of one data set was measured using the 450 k platform and the other data set was measured using the EPIC platform. Initial analyses of the EPIC data could not replicate any of our previous significant findings in the 450 k data on associations between prenatal paracetamol exposure and cord blood DNAm. A subset of the samples (n = 17) was included in both data sets, which enabled analyses of technical sources potentially contributing to the negative replication. Analyses of these 17 samples with repeated measurements revealed high per-sample correlations (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\stackrel{\mathrm{-}}{\text{R}}\hspace{0.17em}\approx$$\end{document}R-≈ 0.99), but low per-CpG correlations (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\stackrel{\mathrm{-}}{\text{R}}$$\end{document}R- ≈ 0.24) between the platforms. 1.7% of the CpGs exhibited a mean DNAm difference across platforms > 0.1. Furthermore, only 26.7% of the CpGs exhibited a moderate or better cross-platform reliability (intra-class correlation coefficient ≥ 0.5).

Conclusion

The observations of low cross-platform probe correlation and reliability corroborate previous reports in other tissues. Our study cannot determine the origin of the differences between platforms. Nevertheless, it emulates the setting in studies using data from multiple Infinium platforms, often analysed several years apart. Therefore, the findings may have important implications for future epigenome-wide association studies (EWASs), in replication, meta-analyses and longitudinal studies. Cognisance and transparency of the challenges related to cross-platform studies may enhance the interpretation, replicability and validity of EWAS results both in cord blood and other tissues, ultimately improving the clinical relevance of epigenetic epidemiology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01299-3.

An evaluation of the National Institutes of Health grants portfolio: identifying opportunities and challenges for multi-omics research that leverage metabolomics data

BACKGROUND

Through the systematic large-scale profiling of metabolites, metabolomics provides a tool for biomarker discovery and improving disease monitoring, diagnosis, prognosis, and treatment response, as well as for delineating disease mechanisms and etiology. As a downstream product of the genome and epigenome, transcriptome, and proteome activity, the metabolome can be considered as being the most proximal correlate to the phenotype. Integration of metabolomics data with other -omics data in multi-omics analyses has the potential to advance understanding of human disease development and treatment.

AIM OF REVIEW

To understand the current funding and potential research opportunities for when metabolomics is used in human multi-omics studies, we cross-sectionally evaluated National Institutes of Health (NIH)-funded grants to examine the use of metabolomics data when collected with at least one other -omics data type. First, we aimed to determine what types of multi-omics studies included metabolomics data collection. Then, we looked at those multi-omics studies to examine how often grants employed an integrative analysis approach using metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We observed that the majority of NIH-funded multi-omics studies that include metabolomics data performed integration, but to a limited extent, with integration primarily incorporating only one other -omics data type. Some opportunities to improve data integration may include increasing confidence in metabolite identification, as well as addressing variability between -omics approach requirements and -omics data incompatibility.

Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study

BACKGROUND

It is unclear if smoking-related DNA methylation represents a causal pathway between smoking and risk of lung cancer. We sought to identify novel smoking-related DNA methylation sites in blood, with repeated measurements, and to appraise the putative role of DNA methylation in the pathway between smoking and lung cancer development.

METHODS

We derived a nested case-control study from the Trøndelag Health Study (HUNT), including 140 incident patients who developed lung cancer during 2009-13 and 140 controls. We profiled 850 K DNA methylation sites (Illumina Infinium EPIC array) in DNA extracted from blood that was collected in HUNT2 (1995-97) and HUNT3 (2006-08) for the same individuals. Epigenome-wide association studies (EWAS) were performed for a detailed smoking phenotype and for lung cancer. Two-step Mendelian randomization (MR) analyses were performed to assess the potential causal effect of smoking on DNA methylation as well as of DNA methylation (13 sites as putative mediators) on risk of lung cancer.

RESULTS

The EWAS for smoking in HUNT2 identified associations at 76 DNA methylation sites (P < 5 × 10-8), including 16 novel sites. Smoking was associated with DNA hypomethylation in a dose-response relationship among 83% of the 76 sites, which was confirmed by analyses using repeated measurements from blood that was collected at 11 years apart for the same individuals. Two-step MR analyses showed evidence for a causal effect of smoking on DNA methylation but no evidence for a causal link between DNA methylation and the risk of lung cancer.

CONCLUSIONS

DNA methylation modifications in blood did not seem to represent a causal pathway linking smoking and the lung cancer risk.

Going 'trans-E-3-ve': Educational principles for a new generation of medical students

Educating medical students represents a thrilling yet challenging task. In an era of research breakthroughs but also global health setbacks, there is a risk that scientists and educators focus on highly specialized areas of knowledge, neglecting interrelated systemic issues. Here, we argue that the education of medical students should be embraced using a different strategy remodeled through what we call a 'tranS-E-3-ve' lens. In this new approach, there is no room for scientific reductionism. Instead, health disciplines should be seen from a translational, trans-disciplinary and trans-territorial scope, and should be sensitive to problems and pathways that link global phenomena to health. While current health issues cannot be approached without an equity lens, there are three interconnected dimensions of health that should pervade the content, goals, and design of academic curricula in medical schools: (1) exposome, or the understanding of the environmental contributors to health and disease; (2) identification of the mechanisms involved in the interactions between the elements that constitute complex systems; and (3) 'inner space', or the study of how cells communicate within the human body.

Intergenerational transmission: Theoretical and methodological issues and an introduction to four Dutch cohorts

Behaviors, traits and characteristics are transmitted from parents to offspring because of complex genetic and non-genetic processes. We review genetic and non-genetic mechanisms of intergenerational transmission of psychopathology and parenting and focus on recent methodological advances in disentangling genetic and non-genetic factors. In light of this review, we propose that future studies on intergenerational transmission should aim to disentangle genetic and non-genetic transmission, take a long-term longitudinal perspective, and focus on paternal and maternal intergenerational transmission. We present four large longitudinal cohort studies within the Consortium on Individual Development, which together address many of these methodological challenges. These four cohort studies aim to examine the extent to which genetic and non-genetic transmission from the parental generation shapes parenting behavior and psychopathology in the next generation, as well as the extent to which self-regulation and social competence mediate this transmission. Conjointly, these four cohorts provide a comprehensive approach to the study of intergenerational transmission.

Leveraging epigenetics to examine differences in developmental trajectories of social attention: A proof-of-principle study of DNA methylation in infants with older siblings with autism

Preliminary evidence suggests that changes in DNA methylation, a widely studied epigenetic mechanism, contribute to the etiology of Autism Spectrum Disorder (ASD). However, data is primarily derived from post-mortem brain samples or peripheral tissue from adults. Deep-phenotyped longitudinal infant cohorts are essential to understand how epigenetic modifications relate to early developmental trajectories and emergence of ASD symptoms. We present a proof-of-principle study designed to evaluate the potential of prospective epigenetic studies of infant siblings of children with ASD. Illumina genome-wide 450 K DNA methylation data from buccal swabs was generated for 63 male infants at multiple time-points from 8 months to 2 years of age (total N = 107 samples). 11 of those infants received a diagnosis of ASD at 3 years. We conducted a series of analyses to characterize DNA methylation signatures associated with categorical outcome and neurocognitive measures from parent-report questionnaire, eye-tracking and electro-encephalography. Effects observed across the entire genome (epigenome-wide association analyses) suggest that collecting DNA methylation samples within infant-sibling designs allows for the detection of meaningful signals with smaller sample sizes than previously estimated. Mapping networks of co-methylated probes associated with neural correlates of social attention implicated enrichment of pathways involved in brain development. Longitudinal modelling found covariation between phenotypic traits and DNA methylation levels in the proximity of genes previously associated with cognitive development, although larger samples and more complete datasets are needed to obtain generalizable results. In conclusion, assessment of DNA methylation profiles at multiple time-points in infant-sibling designs is a promising avenue to comprehend developmental origins and mechanisms of ASD.

Epigenetic variations due to nutritional status in early-life and its later impact on aging and disease

Epigenetics refers to changes in gene function, not resulting from the primary DNA sequence, influenced by the environment. It provides a link between the molecular regulation of the genome and the environmental signals exposed during the life of individuals (including lifestyle, social behavior, development, and nutrition). Notably, early development (intrauterine or postnatal) is highly influenced by the adverse socioeconomic status that leads to malnutrition or obesity; these conditions induce changes over the fetal epigenetic programming and can be transferred by transgenerational inheritance, inducing alterations of the transcription of genes related to several metabolic and neurological processes. Moreover, obesity during pregnancy, and excessive gestational weight gain are associated with an increased risk of fatal pregnancy complications, and adverse cardio-metabolic, respiratory and cognitive-related outcomes of the future child. However, most of our knowledge in this field comes from experimental animal models, that partially resemble the nutritional effects of humans. In this context, nutritional effects implicated in historical famines represent valuable information about the transgenerational effects of undernutrition and stress. In the present review, we attempt to describe the most outstanding results from the most studied famines about the impact of malnutrition on the epigenome.

Associations between body size, nutrition and socioeconomic position in early life and the epigenome: A systematic review

Background

Body size, nutrition and socioeconomic position (SEP) in early life have been associated with a wide range of long-term health effects. Epigenetics is one possible mechanism through which these early life exposures can impact later life health. We conducted a systematic review examining the observational evidence for the impact of body size, nutrition and SEP in early life on the epigenome in humans.

Methods

This systematic review is registered with the PROSPERO database (registration number: CRD42016050193). Three datasets were simultaneously searched using Ovid and the resulting studies were evaluated by at least two independent reviewers. Studies measuring epigenetic markers either at the same time as, or after, the early life exposure and have a measure of body size, nutrition or SEP in early life (up to 12 years), written in English and from a community-dwelling participants were included.

Results

We identified 90 eligible studies. Seventeen of these papers examined more than one early life exposure of interest. Fifty six papers examined body size, 37 nutrition and 17 SEP. All of the included papers examined DNA methylation (DNAm) as the epigenetic marker. Overall there was no strong evidence for a consistent association between these early life variables in DNAm which may be due to the heterogeneous study designs, data collection methods and statistical analyses.

Conclusions

Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation. We provide recommendations for future studies.

Psychosocial adversity and socioeconomic position during childhood and epigenetic age: analysis of two prospective cohort studies

Psychosocial adversity in childhood (e.g. abuse) and low socioeconomic position (SEP) can have significant lasting effects on social and health outcomes. DNA methylation-based biomarkers are highly correlated with chronological age; departures of methylation-predicted age from chronological age can be used to define a measure of age acceleration, which may represent a potential biological mechanism linking environmental exposures to later health outcomes. Using data from two cohorts of women Avon Longitudinal Study of Parents and Children, (ALSPAC), N = 989 and MRC National Survey of Health and Development, NSHD, N = 773), we assessed associations of SEP, psychosocial adversity in childhood (parental physical or mental illness or death, parental separation, parental absence, sub-optimal maternal bonding, sexual, emotional and physical abuse and neglect) and a cumulative score of these psychosocial adversity measures, with DNA methylation age acceleration in adulthood (measured in peripheral blood at mean chronological ages 29 and 47 in ALSPAC and buccal cells at age 53 in NSHD). Sexual abuse was strongly associated with age acceleration in ALSPAC (sexual abuse data were not available in NSHD), e.g. at the 47-year time point sexual abuse associated with a 3.41 years higher DNA methylation age (95% CI 1.53 to 5.29) after adjusting for childhood and adulthood SEP. No associations were observed between low SEP, any other psychosocial adversity measure or the cumulative psychosocial adversity score and age acceleration. DNA methylation age acceleration is associated with sexual abuse, suggesting a potential mechanism linking sexual abuse with adverse outcomes. Replication studies with larger sample sizes are warranted.

Estimating and testing direct genetic effects in directed acyclic graphs using estimating equations

In genetic association studies, it is important to distinguish direct and indirect genetic effects in order to build truly functional models. For this purpose, we consider a directed acyclic graph setting with genetic variants, primary and intermediate phenotypes, and confounding factors. In order to make valid statistical inference on direct genetic effects on the primary phenotype, it is necessary to consider all potential effects in the graph, and we propose to use the estimating equations method with robust Huber-White sandwich standard errors. We evaluate the proposed causal inference based on estimating equations (CIEE) method and compare it with traditional multiple regression methods, the structural equation modeling method, and sequential G-estimation methods through a simulation study for the analysis of (completely observed) quantitative traits and time-to-event traits subject to censoring as primary phenotypes. The results show that CIEE provides valid estimators and inference by successfully removing the effect of intermediate phenotypes from the primary phenotype and is robust against measured and unmeasured confounding of the indirect effect through observed factors. All other methods except the sequential G-estimation method for quantitative traits fail in some scenarios where their test statistics yield inflated type I errors. In the analysis of the Genetic Analysis Workshop 19 dataset, we estimate and test genetic effects on blood pressure accounting for intermediate gene expression phenotypes. The results show that CIEE can identify genetic variants that would be missed by traditional regression analyses. CIEE is computationally fast, widely applicable to different fields, and available as an R package.

Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy

Methods have been developed for Mendelian randomization that can obtain consistent causal estimates while relaxing the instrumental variable assumptions. These include multivariable Mendelian randomization, in which a genetic variant may be associated with multiple risk factors so long as any association with the outcome is via the measured risk factors (measured pleiotropy), and the MR‐Egger (Mendelian randomization‐Egger) method, in which a genetic variant may be directly associated with the outcome not via the risk factor of interest, so long as the direct effects of the variants on the outcome are uncorrelated with their associations with the risk factor (unmeasured pleiotropy). In this paper, we extend the MR‐Egger method to a multivariable setting to correct for both measured and unmeasured pleiotropy. We show, through theoretical arguments and a simulation study, that the multivariable MR‐Egger method has advantages over its univariable counterpart in terms of plausibility of the assumption needed for consistent causal estimation and power to detect a causal effect when this assumption is satisfied. The methods are compared in an applied analysis to investigate the causal effect of high‐density lipoprotein cholesterol on coronary heart disease risk. The multivariable MR‐Egger method will be useful to analyse high‐dimensional data in situations where the risk factors are highly related and it is difficult to find genetic variants specifically associated with the risk factor of interest (multivariable by design), and as a sensitivity analysis when the genetic variants are known to have pleiotropic effects on measured risk factors.

Multigenerational cohorts in patients with asthma and allergy

Recent observations that disease risk can be transmitted across generations without the need for direct exposure of the child to the index environmental insult has sparked interest in transgenerational inheritance. Epigenetics describes processes that modify gene expression without a change in the nucleotide sequence. Epigenetic processes can be induced in response to environmental exposures, can influence disease risk, and might explain these multigenerational effects. In experimental models a number of epigenetic mechanisms have been identified that could mediate vertical transmission of epigenetic inheritance. However, relevance of these findings to human disease is not yet clear. An alternative model is one in which transgenerational inheritance of disease risk requires the presence of exposure-related diseases in the mother during pregnancy (termed induced epigenetic transmission model). A number of cross-sectional studies have investigated multigenerational effects in allergy and asthma. However, given the early-life origins of asthma and allergy, birth cohort studies are ideal to investigate the effect of genetic predisposition, epigenetics, and environmental exposures, avoiding pitfalls, such as recall bias and confounding by ongoing exposures, disease, and treatment. The well-characterized 3 generations of the Isle of Wight cohort include 2 consecutive birth cohorts, providing longitudinal data that can be studied for epigenetic transfer of information, such as the effect of grand parental smoking or exposure to other toxic compounds. Further large multigenerational birth cohorts are needed to establish the clinical relevance of this phenomenon and differentiate between vertical and induced transmission models, which might influence future preventive strategies.

Particulate Air Pollution and Fasting Blood Glucose in Nondiabetic Individuals: Associations and Epigenetic Mediation in the Normative Aging Study, 2000-2011

BACKGROUND

Among nondiabetic individuals, higher fasting blood glucose (FBG) independently predicts diabetes risk, cardiovascular disease, and dementia. Ambient PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) is an emerging determinant of glucose dysregulation. PM2.5 effects and mechanisms are understudied among nondiabetic individuals.

OBJECTIVES

Our goals were to investigate whether PM2.5 is associated with an increase in FBG and to explore potential mediating roles of epigenetic gene regulation.

METHODS

In 551 nondiabetic participants in the Normative Aging Study, we measured FBG, and DNA methylation of four inflammatory genes (IFN-γ, IL-6, ICAM-1, and TLR-2), up to four times between 2000 and 2011 (median = 2). We estimated short- and medium-term (1-, 7-, and 28-day preceding each clinical visit) ambient PM2.5 at each participant's address using a validated hybrid land-use regression satellite-based model. We fitted covariate-adjusted regression models accounting for repeated measures.

RESULTS

Mean FBG was 99.8 mg/dL (SD = 10.7), 18% of the participants had impaired fasting glucose (IFG; i.e., 100-125 mg/dL FBG) at first visit. Interquartile increases in 1-, 7-, and 28-day PM2.5 were associated with 0.57 mg/dL (95% CI: 0.02, 1.11, p = 0.04), 1.02 mg/dL (95% CI: 0.41, 1.63, p = 0.001), and 0.89 mg/dL (95% CI: 0.32, 1.47, p = 0.003) higher FBG, respectively. The same PM2.5 metrics were associated with 13% (95% CI: -3%, 33%, p = 0.12), 27% (95% CI: 6%, 52%, p = 0.01) and 32% (95% CI: 10%, 58%, p = 0.003) higher odds of IFG, respectively. PM2.5 was negatively correlated with ICAM-1 methylation (p = 0.01), but not with other genes. Mediation analysis estimated that ICAM-1 methylation mediated 9% of the association of 28-day PM2.5 with FBG.

CONCLUSIONS

Among nondiabetics, short- and medium-term PM2.5 were associated with higher FBG. Mediation analysis indicated that part of this association was mediated by ICAM-1 promoter methylation. Citation: Peng C, Bind MA, Colicino E, Kloog I, Byun HM, Cantone L, Trevisi L, Zhong J, Brennan K, Dereix AE, Vokonas PS, Coull BA, Schwartz JD, Baccarelli AA. 2016. Particulate air pollution and fasting blood glucose in nondiabetic individuals: associations and epigenetic mediation in the Normative Aging Study, 2000-2011. Environ Health Perspect 124:1715-1721; http://dx.doi.org/10.1289/EHP183.

Epigenome-wide Association Studies and the Interpretation of Disease -Omics

Epigenome-wide association studies represent one means of applying genome-wide assays to identify molecular events that could be associated with human phenotypes. The epigenome is especially intriguing as a target for study, as epigenetic regulatory processes are, by definition, heritable from parent to daughter cells and are found to have transcriptional regulatory properties. As such, the epigenome is an attractive candidate for mediating long-term responses to cellular stimuli, such as environmental effects modifying disease risk. Such epigenomic studies represent a broader category of disease -omics, which suffer from multiple problems in design and execution that severely limit their interpretability. Here we define many of the problems with current epigenomic studies and propose solutions that can be applied to allow this and other disease -omics studies to achieve their potential for generating valuable insights.

Epigenetic Inheritance and Its Role in Evolutionary Biology: Re-Evaluation and New Perspectives

Epigenetics increasingly occupies a pivotal position in our understanding of inheritance, natural selection and, perhaps, even evolution. A survey of the PubMed database, however, reveals that the great majority (>93%) of epigenetic papers have an intra-, rather than an inter-generational focus, primarily on mechanisms and disease. Approximately ~1% of epigenetic papers even mention the nexus of epigenetics, natural selection and evolution. Yet, when environments are dynamic (e.g., climate change effects), there may be an “epigenetic advantage” to phenotypic switching by epigenetic inheritance, rather than by gene mutation. An epigenetically-inherited trait can arise simultaneously in many individuals, as opposed to a single individual with a gene mutation. Moreover, a transient epigenetically-modified phenotype can be quickly “sunsetted”, with individuals reverting to the original phenotype. Thus, epigenetic phenotype switching is dynamic and temporary and can help bridge periods of environmental stress. Epigenetic inheritance likely contributes to evolution both directly and indirectly. While there is as yet incomplete evidence of direct permanent incorporation of a complex epigenetic phenotype into the genome, doubtlessly, the presence of epigenetic markers and the phenotypes they create (which may sort quite separately from the genotype within a population) will influence natural selection and, so, drive the collective genotype of a population.

Genome-Wide Epigenetic Studies in Human Disease: A Primer on -Omic Technologies

Epigenetic information encoded in covalent modifications of DNA and histone proteins regulates fundamental biological processes through the action of chromatin regulators, transcription factors, and noncoding RNA species. Epigenetic plasticity enables an organism to respond to developmental and environmental signals without genetic changes. However, aberrant epigenetic control plays a key role in pathogenesis of disease. Normal epigenetic states could be disrupted by detrimental mutations and expression alteration of chromatin regulators or by environmental factors. In this primer, we briefly review the epigenetic basis of human disease and discuss how recent discoveries in this field could be translated into clinical diagnosis, prevention, and treatment. We introduce platforms for mapping genome-wide chromatin accessibility, nucleosome occupancy, DNA-binding proteins, and DNA methylation, primarily focusing on the integration of DNA methylation and chromatin immunoprecipitation-sequencing technologies into disease association studies. We highlight practical considerations in applying high-throughput epigenetic assays and formulating analytical strategies. Finally, we summarize current challenges in sample acquisition, experimental procedures, data analysis, and interpretation and make recommendations on further refinement in these areas. Incorporating epigenomic testing into the clinical research arsenal will greatly facilitate our understanding of the epigenetic basis of disease and help identify novel therapeutic targets.

The Role of DNA Methylation in Cardiovascular Risk and Disease: Methodological Aspects, Study Design, and Data Analysis for Epidemiological Studies

Epidemiological studies have demonstrated that genetic, environmental, behavioral, and clinical factors contribute to cardiovascular disease development. How these risk factors interact at the cellular level to cause cardiovascular disease is not well known. Epigenetic epidemiology enables researchers to explore critical links between genomic coding, modifiable exposures, and manifestation of disease phenotype. One epigenetic link, DNA methylation, is potentially an important mechanism underlying these associations. In the past decade, there has been a significant increase in the number of epidemiological studies investigating cardiovascular risk factors and outcomes in relation to DNA methylation, but many gaps remain in our understanding of the underlying cause and biological implications. In this review, we provide a brief overview of the biology and mechanisms of DNA methylation and its role in cardiovascular disease. In addition, we summarize the current evidence base in epigenetic epidemiology studies relevant to cardiovascular health and disease and discuss the limitations, challenges, and future directions of the field. Finally, we provide guidelines for well-designed epigenetic epidemiology studies, with particular focus on methodological aspects, study design, and analytical challenges.

Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex

DNA methylation (DNAm) is important in brain development and is potentially important in schizophrenia. We characterized DNAm in prefrontal cortex from 335 non-psychiatric controls across the lifespan and 191 patients with schizophrenia and identified widespread changes in the transition from prenatal to postnatal life. These DNAm changes manifest in the transcriptome, correlate strongly with a shifting cellular landscape and overlap regions of genetic risk for schizophrenia. A quarter of published genome-wide association studies (GWAS)-suggestive loci (4,208 of 15,930, P < 10(-100)) manifest as significant methylation quantitative trait loci (meQTLs), including 59.6% of GWAS-positive schizophrenia loci. We identified 2,104 CpGs that differ between schizophrenia patients and controls that were enriched for genes related to development and neurodifferentiation. The schizophrenia-associated CpGs strongly correlate with changes related to the prenatal-postnatal transition and show slight enrichment for GWAS risk loci while not corresponding to CpGs differentiating adolescence from later adult life. These data implicate an epigenetic component to the developmental origins of this disorder.

From stem cells to the law courts: DNA methylation, the forensic epigenome and the possibility of a biosocial archive

The growth in epigenetics continues to attract considerable cross-disciplinary interest, apparently representing an opportunity to move beyond genomics towards the goal of understanding phenotypic variability from molecular through organismal to the societal level. The epigenome may also harbour useful information about life-time exposures (measured or unmeasured) irrespective of their influence on health or disease, creating the potential for a person-specific biosocial archive . Furthermore such data may prove of use in providing identifying information, providing the possibility of a future forensic epigenome . The mechanisms involved in ensuring that environmentally induced epigenetic changes perpetuate across the life course remain unclear. Here we propose a potential role of adult stem cells in maintaining epigenetic states provides a useful basis for formulating such epidemiologically-relevant concepts.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

BACKGROUND

Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation.

METHODS

We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid.

RESULTS

These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates.

CONCLUSIONS

These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes.

Approaches for drawing causal inferences from epidemiological birth cohorts: a review

Large-scale population-based birth cohorts, which recruit women during pregnancy or at birth and follow up their offspring through infancy and into childhood and adolescence, provide the opportunity to monitor and model early life exposures in relation to developmental characteristics and later life outcomes. However, due to confounding and other limitations, identification of causal risk factors has proved challenging and published findings are often not reproducible. A suite of methods has been developed in recent years to minimise problems afflicting observational epidemiology, to strengthen causal inference and to provide greater insights into modifiable intra-uterine and early life risk factors. The aim of this review is to describe these causal inference methods and to suggest how they may be applied in the context of birth cohorts and extended along with the development of birth cohort consortia and expansion of "omic" technologies.

Scrutinizing the epigenetics revolution

Epigenetics is one of the most rapidly expanding fields in the life sciences. Its rise is frequently framed as a revolutionary turn that heralds a new epoch both for gene-based epistemology and for the wider discourse on life that pervades knowledge-intensive societies of the molecular age. The fundamentals of this revolution remain however to be scrutinized, and indeed the very contours of what counts as 'epigenetic' are often blurred. This is reflected also in the mounting discourse on the societal implications of epigenetics, in which vast expectations coexist with significant uncertainty about what aspects of this science are most relevant for politics or policy alike. This is therefore a suitable time to reflect on the directions that social theory could most productively take in the scrutiny of this revolution. Here we take this opportunity in both its scholarly and normative dimension, that is, proposing a roadmap for social theorizing on epigenetics that does not shy away from, and indeed hopefully guides, the framing of its most socially relevant outputs. To this end, we start with an epistemological reappraisal of epigenetic discourse that valorizes the blurring of meanings as a critical asset for the field and privileged analytical entry point. We then propose three paths of investigation. The first looks at the structuring elements of controversies and visions around epigenetics. The second probes the mutual constitution between the epigenetic reordering of living phenomena and the normative settlements that orient individual and collective responsibilities. The third highlights the material import of epigenetics and the molecularization of culture that it mediates. We suggest that these complementary strands provide both an epistemically and socially self-reflective framework to advance the study of epigenetics as a molecular juncture between nature and nurture and thus as the new critical frontier in the social studies of the life sciences.

Behavior genetics: past, present, future

The disciplines of developmental psychopathology and behavior genetics are concerned with many of the same questions about the etiology and course of normal and abnormal behavior and about the factors that promote typical development despite the presence of risk. The goal of this paper is to summarize how research in behavior genetics has shed light on questions that are central to developmental psychopathology. We briefly review the origins of behavior genetics, summarize the findings that have been gleaned from several decades of quantitative and molecular genetics research, and describe future directions for research that will delineate gene function as well as pathways from genes to brain to behavior. The importance of environmental contributions, at both genetic and epigenetic levels, will be discussed. We conclude that behavior genetics has made significant contributions to developmental psychopathology by documenting the interplay among risk and protective factors at multiple levels of the organism, by clarifying the causal status of risk exposures, and by identifying factors that account for change and stability in psychopathology. As the tools to identify gene function become increasingly sophisticated, and as behavioral geneticists become increasingly interdisciplinary in their scope, the field is poised to make ever greater contributions to our understanding of typical and atypical development.

Parental obesity and risk of autism spectrum disorder

OBJECTIVES

The objective of the study was to investigate the associations among maternal prepregnancy BMI, paternal BMI, and the risk of autism spectrum disorders (ASDs) in children.

METHODS

The study sample of 92 909 children was derived from the population-based, prospective Norwegian Mother and Child Cohort Study. The age range was 4.0 through 13.1 (mean 7.4) years. Relative risks of ASDs were estimated by odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression models.

RESULTS

At the end of follow-up on December 31, 2012, 419 children in the study sample had been diagnosed with ASDs: 162 with autistic disorder, 103 with Asperger disorder, and 154 with pervasive developmental disorder not otherwise specified. Maternal obesity (BMI ≥30) was only weakly associated with ASD risk, whereas paternal obesity was associated with an increased risk of autistic disorder and Asperger disorder. The risk of autistic disorder was 0.27% (25 of 9267) in children of obese fathers and 0.14% (59 of 41 603) in children of fathers with normal weight (BMI <25), generating an adjusted OR of 1.73 (95% CI: 1.07-2.82). For Asperger disorder, analyses were limited to children aged ≥7 years (n = 50 116). The risk was 0.38% (18 of 4761) in children of obese fathers and 0.18% (42 of 22 736) in children of normal-weight fathers, and the adjusted OR was 2.01 (95% CI: 1.13-3.57). No associations were found for pervasive developmental disorder not otherwise specified.

CONCLUSIONS

Paternal obesity is an independent risk factor for ASDs in children. The associations should be investigated further in genetic and epigenetic studies.

Lifecourse health development: past, present and future

During the latter half of the twentieth century, an explosion of research elucidated a growing number of causes of disease and contributors to health. Biopsychosocial models that accounted for the wide range of factors influencing health began to replace outmoded and overly simplified biomedical models of disease causation. More recently, models of lifecourse health development (LCHD) have synthesized research from biological, behavioral and social science disciplines, defined health development as a dynamic process that begins before conception and continues throughout the lifespan, and paved the way for the creation of novel strategies aimed at optimization of individual and population health trajectories. As rapid advances in epigenetics and biological systems research continue to inform and refine LCHD models, our healthcare delivery system has struggled to keep pace, and the gulf between knowledge and practice has widened. This paper attempts to chart the evolution of the LCHD framework, and illustrate its potential to transform how the MCH system addresses social, psychological, biological, and genetic influences on health, eliminates health disparities, reduces chronic illness, and contains healthcare costs. The LCHD approach can serve to highlight the foundational importance of MCH, moving it from the margins of national debate to the forefront of healthcare reform efforts. The paper concludes with suggestions for innovations that could accelerate the translation of health development principles into MCH practice.

Lifecourse health development: past, present and future

During the latter half of the twentieth century, an explosion of research elucidated a growing number of causes of disease and contributors to health. Biopsychosocial models that accounted for the wide range of factors influencing health began to replace outmoded and overly simplified biomedical models of disease causation. More recently, models of lifecourse health development (LCHD) have synthesized research from biological, behavioral and social science disciplines, defined health development as a dynamic process that begins before conception and continues throughout the lifespan, and paved the way for the creation of novel strategies aimed at optimization of individual and population health trajectories. As rapid advances in epigenetics and biological systems research continue to inform and refine LCHD models, our healthcare delivery system has struggled to keep pace, and the gulf between knowledge and practice has widened. This paper attempts to chart the evolution of the LCHD framework, and illustrate its potential to transform how the MCH system addresses social, psychological, biological, and genetic influences on health, eliminates health disparities, reduces chronic illness, and contains healthcare costs. The LCHD approach can serve to highlight the foundational importance of MCH, moving it from the margins of national debate to the forefront of healthcare reform efforts. The paper concludes with suggestions for innovations that could accelerate the translation of health development principles into MCH practice.

Epigenetic research in cancer epidemiology: trends, opportunities, and challenges

Epigenetics is emerging as an important field in cancer epidemiology that promises to provide insights into gene regulation and facilitate cancer control throughout the cancer care continuum. Increasingly, investigators are incorporating epigenetic analysis into the studies of etiology and outcomes. To understand current progress and trends in the inclusion of epigenetics in cancer epidemiology, we evaluated the published literature and the National Cancer Institute (NCI)-supported research grant awards in this field to identify trends in epigenetics research. We present a summary of the epidemiologic studies in NCI's grant portfolio (from January 2005 through December 2012) and in the scientific literature published during the same period, irrespective of support from the NCI. Blood cells and tumor tissue were the most commonly used biospecimens in these studies, although buccal cells, cervical cells, sputum, and stool samples were also used. DNA methylation profiling was the focus of the majority of studies, but several studies also measured microRNA profiles. We illustrate here the current status of epidemiologic studies that are evaluating epigenetic changes in large populations. The incorporation of epigenomic assessments in cancer epidemiology studies has and is likely to continue to provide important insights into the field of cancer research.

DNA methylation pattern in overweight women under an energy-restricted diet supplemented with fish oil

Dietary factors modulate gene expression and are able to alter epigenetic signatures in peripheral blood mononuclear cells (PBMC). However, there are limited studies about the effects of omega-3 polyunsaturated fatty acids (n-3 PUFA) on the epigenetic mechanisms that regulate gene expression. This research investigates the effects of n-3-rich fish oil supplementation on DNA methylation profile of several genes whose expression has been reported to be downregulated by n-3 PUFA in PBMC: CD36, FFAR3, CD14, PDK4, and FADS1. Young overweight women were supplemented with fish oil or control in a randomized 8-week intervention trial following a balanced diet with 30% energy restriction. Fatty acid receptor CD36 decreased DNA methylation at CpG +477 due to energy restriction. Hypocaloric diet-induced weight loss also reduced the methylation percentages of CpG sites located in CD14, PDK4, and FADS1. The methylation patterns of these genes were only slightly affected by the fish oil supplementation, being the most relevant to the attenuation of the weight loss-induced decrease in CD36 methylation after adjusting by baseline body weight. These results suggest that the n-3 PUFA-induced changes in the expression of these genes in PBMC are not mediated by DNA methylation, although other epigenetic mechanisms cannot be discarded.

Influence of DNMT genotype on global and site specific DNA methylation patterns in neonates and pregnant women

This study examines the relationship between common genetic variation within DNA methyltransferase genes and inter-individual variation in DNA methylation. Eleven polymorphisms spanning DNMT1 and DNMT3B were genotyped. Global and gene specific (IGF2, IGFBP3, ZNT5) DNA methylation was quantified by LUMA and bisulfite Pyrosequencing assays, respectively, in neonatal cord blood and in maternal peripheral blood. Associations between maternal genotype and maternal methylation (n (≈) 333), neonatal genotype and neonatal methylation (n (≈) 454), and maternal genotype and neonatal methylation (n (≈) 137) were assessed. The findings of this study provide some support to the hypothesis that genetic variation in DNA methylating enzymes influence DNA methylation at global and gene-specific levels; however observations were not robust to correction for multiple testing. More comprehensive analysis of the influence of genetic variation on global and site specific DNA methylation is warranted.

Differences between blood donors and a population sample: implications for case-control studies

BACKGROUND

Selecting appropriate controls for studies of genetic variation in case series is important. The two major candidates involve the use of blood donors or a random sample of the population.

METHODS

We compare and contrast the two different populations of controls for studies of genetic variation using data from parents enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC). In addition we compute different biases using a series of hypothetical assumptions.

RESULTS

The study subjects who had been blood donors differed markedly from the general population in social, health-related, anthropometric, and personality-related variables. Using theoretical examples, we show that blood donors are a poor control group for non-genetic studies of diseases related to environmentally, behaviourally, or socially patterned exposures. However, we show that if blood donors are used as controls in genetic studies, these factors are unlikely to make a major difference in detecting true associations with relatively rare disorders (cumulative incidence through life of <10%). Nevertheless, for more common disorders, the reduction in accuracy resulting from the inclusion in any control population of individuals who have or will develop the disease in question can create a greater bias than can socially patterned factors.

CONCLUSIONS

Information about the medical history of a control and the parents of the control (as a proxy for whether the control will develop the disease) is more important with regard to the choice of controls than whether the controls are a random population sample or blood donors.

Epigenetic mechanisms and models in the origins of asthma

PURPOSE OF REVIEW

Epigenetic mechanisms have the ability to alter the phenotype without changing the genetic code. The science of epigenetics has grown considerably in recent years, and future epigenetically based treatments or prevention strategies are likely. Epigenetic associations with asthma have received growing interest because genetic and environmental factors have been unable to independently explain the cause of asthma.

RECENT FINDINGS

Recent findings suggest that both the environment and underlying genetic sequence variation influence DNA methylation, which in turn seems to modify the risk conferred by genetic variants for various asthma phenotypes. In particular, DNA methylation may act as an archive of a variety of early developmental exposures, which then can modify the risk related to genetic variants.

SUMMARY

Current asthma treatments may control the symptoms of asthma but do not modify its natural history. Epigenetic mechanisms and novel explanatory models provide burgeoning approaches to significantly increase our understanding of the initiation and progression of asthma. Due to the inheritance of epigenetics, we anticipate a rapid emergence of critical information that will provide novel treatment strategies for asthma in the current generation and ultimately the prevention of asthma in future generations.

Epigenetics in sports

The heritability of specific phenotypical traits relevant for physical performance has been extensively investigated and discussed by experts from various research fields. By deciphering the complete human DNA sequence, the human genome project has provided impressive insights into the genomic landscape. The hope that this information would reveal the origin of phenotypical traits relevant for physical performance or disease risks has proven overly optimistic, and it is still premature to refer to a 'post-genomic' era of biological science. Linking genomic regions with functions, phenotypical traits and variation in disease risk is now a major experimental bottleneck. The recent deluge of genome-wide association studies (GWAS) generates extensive lists of sequence variants and genes potentially linked to phenotypical traits, but functional insight is at best sparse. The focus of this review is on the complex mechanisms that modulate gene expression. A large fraction of these mechanisms is integrated into the field of epigenetics, mainly DNA methylation and histone modifications, which lead to persistent effects on the availability of DNA for transcription. With the exceptions of genomic imprinting and very rare cases of epigenetic inheritance, epigenetic modifications are not inherited transgenerationally. Along with their susceptibility to external influences, epigenetic patterns are highly specific to the individual and may represent pivotal control centers predisposing towards higher or lower physical performance capacities. In that context, we specifically review how epigenetics combined with classical genetics could broaden our knowledge of genotype-phenotype interactions. We discuss some of the shortcomings of GWAS and explain how epigenetic influences can mask the outcome of quantitative genetic studies. We consider epigenetic influences, such as genomic imprinting and epigenetic inheritance, as well as the life-long variability of epigenetic modification patterns and their potential impact on phenotype with special emphasis on traits related to physical performance. We suggest that epigenetic effects may also play a considerable role in the determination of athletic potential and these effects will need to be studied using more sophisticated quantitative genetic models. In the future, epigenetic status and its potential influence on athletic performance will have to be considered, explored and validated using well controlled model systems before we can begin to extrapolate new findings to complex and heterogeneous human populations. A combination of the fields of genomics, epigenomics and transcriptomics along with improved bioinformatics tools and precise phenotyping, as well as a precise classification of the test populations is required for future research to better understand the inter-relations of exercise physiology, performance traits and also susceptibility towards diseases. Only this combined input can provide the overall outlook necessary to decode the molecular foundation of physical performance.

From promises to practical strategies in epigenetic epidemiology

The epigenome has been heralded as a key 'missing piece' of the aetiological puzzle for complex phenotypes across the biomedical sciences. The standard research approaches developed for genetic epidemiology, however, are not necessarily appropriate for epigenetic studies of common disease. Here, we discuss the optimal execution of population-based studies of epigenetic variation, which will contribute to the emerging field of 'epigenetic epidemiology' and emphasize the importance of establishing a causal role in pathology for disease-associated epigenetic changes. We propose that improved understanding of the molecular mechanisms underlying human health and disease are best achieved through carrying out studies of epigenetics in populations as a part of an integrated functional genomics strategy.

Social Epigenetics and Equality of Opportunity

Recent epidemiological reports of associations between socioeconomic status and epigenetic markers that predict vulnerability to diseases are bringing to light substantial biological effects of social inequalities. Here, we start the discussion of the moral consequences of these findings. We firstly highlight their explanatory importance in the context of the research program on the Developmental Origins of Health and Disease (DOHaD) and the social determinants of health. In the second section, we review some theories of the moral status of health inequalities. Rather than a complete outline of the debate, we single out those theories that rest on the principle of equality of opportunity and analyze the consequences of DOHaD and epigenetics for these particular conceptions of justice. We argue that DOHaD and epigenetics reshape the conceptual distinction between natural and acquired traits on which these theories rely and might provide important policy tools to tackle unjust distributions of health.

Effects of early-life environment and epigenetics on cardiovascular disease risk in children: highlighting the role of twin studies

Cardiovascular disease (CVD) is the leading cause of death worldwide and originates in early life. The exact mechanisms of this early-life origin are unclear, but a likely mediator at the molecular level is epigenetic dysregulation of gene expression. Epigenetic factors have thus been posited as the likely drivers of early-life programming of adult-onset diseases. This review summarizes recent advances in epidemiology and epigenetic research of CVD risk in children, with a particular focus on twin studies. Classic twin studies enable partitioning of phenotypic variance within a population into additive genetic, shared, and nonshared environmental variances, and are invaluable in research in this area. Longitudinal cohort twin studies, in particular, may provide important insights into the role of epigenetics in the pathogenesis of CVD. We describe candidate gene and epigenome-wide association studies (EWASs) and transgenerational epigenetic inheritance of CVD, and discuss the potential for evidence-based interventions. Identifying epigenetic changes associated with CVD-risk biomarkers in children will provide new opportunities to unravel the underlying biological mechanism of the origins of CVD and enable identification of those at risk for early-life interventions to alter the risk trajectory and potentially reduce CVD incidence later in life.

Who and what is a "population"? Historical debates, current controversies, and implications for understanding "population health" and rectifying health inequities

CONTEXT

The idea of "population" is core to the population sciences but is rarely defined except in statistical terms. Yet who and what defines and makes a population has everything to do with whether population means are meaningful or meaningless, with profound implications for work on population health and health inequities.

METHODS

In this article, I review the current conventional definitions of, and historical debates over, the meaning(s) of "population," trace back the contemporary emphasis on populations as statistical rather than substantive entities to Adolphe Quetelet's powerful astronomical metaphor, conceived in the 1830s, of l'homme moyen (the average man), and argue for an alternative definition of populations as relational beings. As informed by the ecosocial theory of disease distribution, I then analyze several case examples to explore the utility of critical population-informed thinking for research, knowledge, and policy involving population health and health inequities.

FINDINGS

Four propositions emerge: (1) the meaningfulness of means depends on how meaningfully the populations are defined in relation to the inherent intrinsic and extrinsic dynamic generative relationships by which they are constituted; (2) structured chance drives population distributions of health and entails conceptualizing health and disease, including biomarkers, as embodied phenotype and health inequities as historically contingent; (3) persons included in population health research are study participants, and the casual equation of this term with "study population" should be avoided; and (4) the conventional cleavage of "internal validity" and "generalizability" is misleading, since a meaningful choice of study participants must be in relation to the range of exposures experienced (or not) in the real-world societies, that is, meaningful populations, of which they are a part.

CONCLUSIONS

To improve conceptual clarity, causal inference, and action to promote health equity, population sciences need to expand and deepen their theorizing about who and what makes populations and their means.

Epigenetics of host-pathogen interactions: the road ahead and the road behind

A growing body of evidence points towards epigenetic mechanisms being responsible for a wide range of biological phenomena, from the plasticity of plant growth and development to the nutritional control of caste determination in honeybees and the etiology of human disease (e.g., cancer). With the (partial) elucidation of the molecular basis of epigenetic variation and the heritability of certain of these changes, the field of evolutionary epigenetics is flourishing. Despite this, the role of epigenetics in shaping host-pathogen interactions has received comparatively little attention. Yet there is plenty of evidence supporting the implication of epigenetic mechanisms in the modulation of the biological interaction between hosts and pathogens. The phenotypic plasticity of many key parasite life-history traits appears to be under epigenetic control. Moreover, pathogen-induced effects in host phenotype may have transgenerational consequences, and the bases of these changes and their heritability probably have an epigenetic component. The significance of epigenetic modifications may, however, go beyond providing a mechanistic basis for host and pathogen plasticity. Epigenetic epidemiology has recently emerged as a promising area for future research on infectious diseases. In addition, the incorporation of epigenetic inheritance and epigenetic plasticity mechanisms to evolutionary models and empirical studies of host-pathogen interactions will provide new insights into the evolution and coevolution of these associations. Here, we review the evidence available for the role epigenetics on host-pathogen interactions, and the utility and versatility of the epigenetic technologies available that can be cross-applied to host-pathogen studies. We conclude with recommendations and directions for future research on the burgeoning field of epigenetics as applied to host-pathogen interactions.