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Childhood adversity is a potent determinant of health across development and is associated with altered DNA methylation signatures, which might be more common in children exposed during sensitive periods in development. However, it remains unclear whether adversity has persistent epigenetic associations across childhood and adolescence. We aimed to examine the relationship between time-varying adversity (defined through sensitive period, accumulation of risk, and recency life course hypotheses) and genome-wide DNA methylation, measured three times from birth to adolescence, using data from a prospective, longitudinal cohort study.

Early-life nutritional exposures may contribute to offspring epigenetic modifications. However, few studies have evaluated parental dietary quality effects on offspring DNA methylation (DNAm).

ABSTRACTDNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilizing precious or limited DNA sources. We used a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip. We found that data are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; and that low DNA input is associated with a reduction in power to detect EWAS associations, requiring larger sample sizes. We conclude that DNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.

The idea that information can be transmitted to subsequent generation(s) by epigenetic means has been studied for decades but remains controversial in humans. Epidemiological studies have established that grandparental exposures are associated with health outcomes in their grandchildren, often with sex-specific effects; however, the mechanism of transmission is still unclear. We conducted Epigenome Wide Association Studies (EWAS) to test whether grandmaternal smoking during pregnancy is associated with altered DNA methylation (DNAm) in peripheral blood from their adolescent grandchildren. We used data from a birth cohort, with discovery and replication datasets of up to 1225 and 708 individuals (respectively, for the maternal line), aged 15–17 years, and tested replication in the same individuals at birth and 7 years. We show for the first time that DNAm at a small number of loci in cord blood is associated with grandmaternal smoking in humans. In adolescents we see suggestive associations in regions of the genome which we hypothesised a priori could be involved in transgenerational transmission - we observe sex-specific associations at two sites on the X chromosome and one in an imprinting control region. All are within transcription factor binding sites (TFBSs), and we observe enrichment for TFBS among the CpG sites with the strongest associations; however, there is limited evidence that the associations we see replicate between timepoints. The implication of this work is that effects of smoking during pregnancy may induce DNAm changes in later generations and that these changes are often sex-specific, in line with epidemiological associations.

ABSTRACTBiomedical research has grown increasingly cooperative through the sharing of consortia-level epigenetic data. Since consortia preprocess data prior to distribution, new processing pipelines can lead to different versions of the same dataset. Similarly, analytic frameworks evolve to incorporate cutting-edge methods and best practices. However, it remains unknown how different data and analytic versions alter the results of epigenome-wide analyses, which could influence the replicability of epigenetic associations. Thus, we assessed the impact of these changes using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We analysed DNA methylation from two data versions, processed using separate preprocessing and analytic pipelines, examining associations between seven childhood adversities or prenatal smoking exposure and DNA methylation at age 7. We performed two sets of analyses: (1) epigenome-wide association studies (EWAS); (2) Structured Life Course Modelling Approach (SLCMA), a two-stage method that models time-dependent effects. SLCMA results were also compared across two analytic versions. Data version changes impacted both EWAS and SLCMA analyses, yielding different associations at conventional p-value thresholds. However, the magnitude and direction of associations was generally consistent between data versions, regardless of p-values. Differences were especially apparent in analyses of childhood adversity, while smoking associations were more consistent using significance thresholds. SLCMA analytic versions similarly altered top associations, but time-dependent effects remained concordant. Alterations to data and analytic versions influenced the results of epigenome-wide analyses. Our findings highlight that magnitude and direction are better measures for replication and stability than p-value thresholds.

ABSTRACTThe preconception period represents an important window for foetal and epigenetic programming. Some micronutrients (B vitamins, choline, betaine, methionine) implicated in one-carbon metabolism (OCM) are essential for major epigenetic processes that take place in early pregnancy. However, few studies have evaluated the implication of the micronutrients in placental DNA methylation. We investigated whether intake of OCM nutrients in the year before pregnancy was associated with placental DNA methylation in the EDEN mother–child cohort. Maternal dietary intake was assessed with a food-frequency questionnaire. Three dietary patterns, ‘varied and balanced diet,’ ‘vegetarian tendency,’ and ‘bread and starchy food,’ were used to characterize maternal OCM dietary intake. The Illumina Infinium HumanMethylation450 BeadChip was used to measure placental DNA methylation of 573 women included in the analyses. We evaluated the association of dietary patterns with global DNA methylation. Then, we conducted an agnostic epigenome-wide association study (EWAS) and investigated differentially methylated regions (DMRs) associated with each dietary pattern. We found no significant association between the three dietary patterns and global DNA methylation or individual CpG sites. DMR analyses highlighted associations between the ‘varied and balanced’ or ‘vegetarian tendency’ pattern and DMRs located at genes previously implicated in functions essential for embryonic development, such as neurodevelopment. The ‘bread and starchy food’ pattern was associated with regions related to genes whose functions involve various metabolic and cell synthesis-related processes. In mainly well-nourished French women without major deficiencies, OCM intake before pregnancy was not associated with major variation in DNA methylation.

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

The adverse effects on the child of maternal smoking in pregnancy is well-recognized, but little research has been carried out on the possible non-genetic effects of ancestral smoking prior to the pregnancy including parental initiation of cigarette smoking in their own childhoods or a grandmother smoking during pregnancy. Here, we summarize the studies that have been published mainly using data from the Avon Longitudinal Study of Parents and Children. We demonstrate evidence that ancestral smoking prior to or during pregnancy can often be beneficial for offspring health and both ancestor- and sex-specific. More specifically, we report evidence of (i) adverse effects of the father starting to smoke pre-puberty on his son’s development; (ii) beneficial effects on the grandson if his maternal grandmother had smoked in pregnancy; and (iii) mainly adverse effects on the granddaughter when the paternal grandmother had smoked in pregnancy. The ancestor- and sex-specificity of these results are consistent with earlier studies reporting associations of health and mortality with ancestral food supply in their parents’ and grandparents’ pre-pubertal childhoods.Review of published ALSPAC studies demonstrate ancestral smoking prior to pregnancy can be beneficial or detrimental for offspring health and development and often both ancestor- and sex-specific.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15–17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype–phenotype map than previously anticipated.

Low prosocial behavior in childhood has been consistently linked to later psychopathology, with evidence supporting the influence of both genetic and environmental factors on its development. Although neonatal DNA methylation (DNAm) has been found to prospectively associate with a range of psychological traits in childhood, its potential role in prosocial development has yet to be investigated. This study investigated prospective associations between cord blood DNAm at birth and low prosocial behavior within and across four longitudinal birth cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium. We examined (a) developmental trajectories of “chronic‐low” versus “typical” prosocial behavior across childhood in a case–control design (N= 2,095), and (b) continuous “low prosocial” scores at comparable cross‐cohort time‐points (N= 2,121). Meta‐analyses were performed to examine differentially methylated positions and regions. At the cohort‐specific level, three CpGs were found to associate with chronic low prosocial behavior; however, none of these associations was replicated in another cohort. Meta‐analysis revealed no epigenome‐wide significant CpGs or regions. Overall, we found no evidence for associations between DNAm patterns at birth and low prosocial behavior across childhood. Findings highlight the importance of employing multi‐cohort approaches to replicate epigenetic associations and reduce the risk of false positive discoveries.

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N= 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10−7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r= 0.74, p= 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3–82%) of the aggression–methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

ABSTRACTBullying among children is ubiquitous and associated with pervasive mental health problems. However, little is known about the biological pathways that change after exposure to bullying. Epigenome-wide changes in DNA methylation in peripheral blood were studied from pre- to post measurement of bullying exposure, in a longitudinal study of the population-based Generation R Study and Avon Longitudinal Study of Parents and Children (combined n = 1,352). Linear mixed-model results were meta-analysed to estimate how DNA methylation changed as a function of exposure to bullying. Sensitivity analyses including co-occurring child characteristics and risks were performed, as well as a Gene Ontology analysis. A candidate follow-up was employed for CpG (cytosine-phosphate-guanine) sites annotated to 5-HTTand NR3C1. One site, cg17312179, showed small changes in DNA methylation associated to bullying exposure (b = −2.67e-03, SE = 4.97e-04, p = 7.17e-08). This site is annotated to RAB14, an oncogene related to Golgi apparatus functioning, and its methylation levels decreased for exposed but increased for non-exposed. This result was consistent across sensitivity analyses. Enriched Gene Ontology pathways for differentially methylated sites included cardiac function and neurodevelopmental processes. Top CpG sites tended to have overall low levels of DNA methylation, decreasing in exposed, increasing in non-exposed individuals. There were no gene-wide corrected findings for 5-HTTand NR3C1. This is the first study to identify changes in DNA methylation associated with bullying exposure at the epigenome-wide significance level. Consistent with other population-based studies, we do not find evidence for strong associations between bullying exposure and DNA methylation.

Major depressive disorder (MDD) has an enormous impact on global disease burden, affecting millions of people worldwide and ranking as a leading cause of disability for almost three decades. Past molecular studies of MDD employed bulk homogenates of postmortem brain tissue, which obscures gene expression changes within individual cell types. Here we used single-nucleus transcriptomics to examine ~80,000 nuclei from the dorsolateral prefrontal cortex of male individuals with MDD (n= 17) and of healthy controls (n= 17). We identified 26 cellular clusters, and over 60% of these showed differential gene expression between groups. We found that the greatest dysregulation occurred in deep layer excitatory neurons and immature oligodendrocyte precursor cells (OPCs), and these contributed almost half (47%) of all changes in gene expression. These results highlight the importance of dissecting cell-type-specific contributions to the disease and offer opportunities to identify new avenues of research and novel targets for treatment.

Background: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. Results: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1and DOCK7(total cholesterol levels), and ICOSLG(inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACDand SENP7which can modulate DNA methylation at distal sites). Conclusions: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk.

Genomic and biosocial research data about individuals is rapidly proliferating, bringing the potential for novel opportunities for data integration and use. The scale, pace and novelty of these applications raise a number of urgent sociotechnical, ethical and legal questions, including optimal methods of data storage, management and access. Although the open science movement advocates unfettered access to research data, many of the UK’s longitudinal cohort studies operate systems of manageddata access, in which access is governed by legal and ethical agreements between stewards of research datasets and researchers wishing to make use of them. Amongst other things, these agreements aim to respect the reasonable expectations of the research participants who provided data and samples, as expressed in the consent process. Arguably, responsible data management and governance of data and sample use are foundational to the consent process in longitudinal studies and are an important source of trustworthiness in the eyes of those who contribute data to genomic and biosocial research. This paper presents an ethnographic case study exploring the foundational principles of a governance infrastructure for Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC), which are operationalised through a committee known as the METADAC Access Committee. METADAC governs access to phenotype, genotype and ‘omic’ data and samples from five UK longitudinal studies. Using the example of METADAC, we argue that three key structural features are foundational for practising responsible data sharing: independence and transparency; interdisciplinarity; and participant-centric decision-making. We observe that the international research community is proactively working towards optimising the use of research data, integrating/linking these data with routine data generated by health and social care services and other administrative data services to improve the analysis, interpretation and utility of these data. The governance of these new complex data assemblages will require a range of expertise from across a number of domains and disciplines, including that of study participants. Human-mediated decision-making bodies will be central to ensuring achievable, reasoned and responsible decisions about the use of these data; the METADAC model described in this paper provides an example of how this could be realised.

Gestational diabetes is associated with risk for metabolic disease later in life. Using a cross-species approach in rat and humans, we examined the hypothesis that gestational diabetes during pregnancy triggers changes in the methylome of the offspring that might be mediating these risks. We show in a gestation diabetes rat model, the Cohen diabetic rat, that gestational diabetes triggers wide alterations in DNA methylation in the placenta in both candidate diabetes genes and genome-wide promoters, thus providing evidence for a causal relationship between diabetes during pregnancy and DNA methylation alterations. There is a significant overlap between differentially methylated genes in the placenta and the liver of the rat offspring. Several genes differentially methylated in rat placenta exposed to maternal diabetes are also differentially methylated in the human placenta of offspring exposed to gestational diabetes in utero. DNA methylation changes inversely correlate with changes in expression. The changes in DNA methylation affect known functional gene pathways involved in endocrine function, metabolism, and insulin responses. These data provide support to the hypothesis that early-life exposures and their effects on metabolic disease are mediated by DNA methylation changes. This has important diagnostic and therapeutic implications.

Breast carcinoma (BC) has been extensively profiled by high-throughput technologies for over a decade, and broadly speaking, these studies can be grouped into those that seek to identify patient subtypes (studies of heterogeneity) or those that seek to identify gene signatures with prognostic or predictive capacity. The sheer number of reported signatures has led to speculation that everything is prognostic in BC. Here, we show that this ubiquity is an apparition caused by a poor understanding of the interrelatedness between subtype and the molecular determinants of prognosis. Our approach constructively shows how to avoid confounding due to a patient’s subtype, clinicopathological profile, or treatment profile. The approach identifies patients who are predicted to have good outcome at time of diagnosis by all available clinical and molecular markers but who experience a distant metastasis within 5 years. These inherently difficult patients (∼7% of BC) are prioritized for investigations of intratumoral heterogeneity.

DNA methylation patterns are characterized by highly conserved developmental programs, but allow for divergent gene expression resulting from stochastic epigenetic drift or divergent environments. Genome-wide methylation studies in monozygotic (MZ) twins are providing insight into the extent of epigenetic variation that occurs, irrespective of genotype. However, little is known about the variability of DNA methylation patterns in adolescence, a period involving significant and rapid physical, emotional, social, and neurodevelopmental change. Here, we assessed genome-wide DNA methylation using the 450 K Illumina BeadChip in a sample of 37 MZ twin pairs followed longitudinally since birth to investigate: 1) the extent of variation in DNA methylation in identical genetic backgrounds in adolescence and; 2) whether these variations are randomly distributed or enriched in particular functional pathways. We also assessed stability of DNA methylation over 3–6 months to distinguish stable trait-like and variable state-like genes. A pathway analysis found high within-pair variability in genes associated with development, cellular mechanisms, tissue and cell morphology, and various disorders. Test-retest analyses performed in a sub-sample of 8 twin pairs demonstrated enrichment in gene pathways involved in organismal development, cellular growth and proliferation, cell signaling, and particular disorders. The variability found in functional gene pathways may plausibly underlie phenotypic differences in this adolescent MZ twin sample. Furthermore, we assessed stability of methylation over 3–6 months and found that some genes were stable while others were unstable, suggesting that the methylome remains dynamic in adolescence and that dynamic sites tend to be organized in certain gene pathways.

Previous studies indicate that a subgroup of suicide completers has low cortical brain expression levels of TrkB-T1, a TrkBgene transcript that is highly expressed in astrocytes. Epigenetic modifications, including methylation changes in the TrkBpromoter, partially explain TrkB-T1 low expression levels in brain tissue from suicide completers. The aim of this study was to investigate whether methylation changes in other regions of the TrkBgene could also contribute to the significant downregulation of the TrkB-T1 transcript observed in the brain of suicide completers. Methylation levels were assessed on BA8/9 from suicide completers expressing low TrkB-T1 transcript levels and controls, using custom-made Agilent arrays tiling the whole TrkBgene. After statistical correction for multiple testing, five probes located in the TrkB-T1 3′UTR region were found hypermethylated in the frontal cortex of suicide completers. These results were validated for four CpGs spanning a 150 bp sequence by cloning and Sanger sequencing bisulfite treated DNA. We found a significant correlation between the methylation level at these four CpGs and TrkB-T1 expression in BA8/9. Site-specific hypermethylation on this 3′UTR sequence induced decreased luciferase activity in reporter gene cell assays. Site-specific differential methylation in the TrkB-T1 3′UTR region associates with functional changes in TrkB-T1 expression and may play a significant role in the important decrease of cortical TrkB-T1 expression observed among suicide completers.

A bipartite graph is biplanar if the vertices can be placed on two parallel lines (layers) in the plane such that there are no edge crossings when edges are drawn as line segments between the layers. In this paper we study the 2-Layer Planarization problem: Can k edges be deleted from a given graph G so that the remaining graph is biplanar? This problem is NP-complete, and remains so if the permutation of the vertices in one layer is fixed (the 1-Layer Planarization problem). We prove that these problems are fixed-parameter tractable by giving linear-time algorithms for their solution (for fixed k). In particular, we solve the 2-Layer Planarization problem in O(k · 6k+ |G|) time and the 1-Layer Planarization problem in O(3k· |G|) time. We also show that there are polynomial-time constant-approximation algorithms for both problems.A bipartite graph is biplanar if the vertices can be placed on two parallel lines (layers) in the plane such that there are no edge crossings when edges are drawn as line segments between the layers. In this paper we study the 2-Layer Planarization problem: Can k edges be deleted from a given graph G so that the remaining graph is biplanar? This problem is NP-complete, and remains so if the permutation of the vertices in one layer is fixed (the 1-Layer Planarization problem). We prove that these problems are fixed-parameter tractable by giving linear-time algorithms for their solution (for fixed k). In particular, we solve the 2-Layer Planarization problem in O(k · 6k+ |G|) time and the 1-Layer Planarization problem in O(3k· |G|) time. We also show that there are polynomial-time constant-approximation algorithms for both problems.

There is increasing policy emphasis on adverse childhood experiences (ACEs). We aimed to assess the relative contributions of these experiences and socioeconomic factors to educational attainment and health.

Data from epidemiological and animal studies suggests that the paternal epigenetic contribution in sperm may serve as a route to altered offspring phenotypes. However to date there is little to no evidence of direct effects of diets on the sperm epigenome or consequences for the offspring. Epigenetics refers to heritable changes in gene expression that are regulated by DNA methylation and the covalent modification of histones. Given that dietary folate can alter the supply of methyl donors, we hypothesized that male germ cells may be sensitive to dietary folate and that this may manifest as altered epigenetic programming and have downstream consequences for spermatogenesis and reproductive outcomes. The objective of this study was to determine the impact of exposure to a low folate diet, beginning during embryonic development through to adulthood on spermatogenesis, the sperm epigenome, fertility, and offspring. Inbred C57/BL6 mice were fed either a folate-sufficient (FS, 2 mg of folate/kg of diet), or a folate-deficient diet (FD, 0.3 mg of folate/kg of diet). Adult FS (n=54) and FD (n=49) males remained on the diets for either 2 or 4-4.5 months and were assessed for fertility parameters and overall health. In adults, spermatogenesis and sperm counts were not altered by diet nor were body, testis and epididymis weights. Epigenetic programming was disturbed in the sperm of folate depleted mice. Histone H3 methylation was significantly reduced in sperm from FD versus FS mice. Notably histone H3 methylation has been shown to mark genes for embryonic development. Genome wide DNA methylation (MeDIP-chip) analysis revealed alterations at more than 50 gene promoter regions. Bisulfite sequencing confirmed that 6 of these regions including genes implicated in developmental processes had significant decreases in DNA methylation at specific CpG locations in the sperm of FD males (n=5 for both groups). FD (n=29) and FS (n=27) males were then mated to females on control diets and pregnancy outcomes at embryonic day 18.5 were analyzed. Embryonic loss was 2 fold greater in the litters sired by FD vs FS mice and developmental abnormalities were observed in 27% of the litters sired by FD mice vs 3% for those sired by FS mice. This is the first study to show that diet can alter the sperm epigenome and suggests that an altered sperm epigenome leads to negative pregnancy outcomes. This research was supported by NSERC, and the Réseau Québécois en Reproduction (RQR-FQRNT).