Search

Background and Hypothesis Children exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association. Study Design Data were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994–1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences. Study Results Higher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses. Conclusions Cognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Background and ObjectivesDNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults.MethodsWe tested 3 “generations” of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia.ResultsIn ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08–0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = −0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = −0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07–1.49]).DiscussionThird-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

INTRODUCTION: We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging. METHODS: We analyzed Framingham Offspring Cohort data (≥60y). We measured healthy diet using the Dietary Guideline for Americans (DGA, 3 visits 1991-2008), pace of aging using the DunedinPACE epigenetic clock (2005-2008), and incident dementia and mortality using records (compiled 2005-2018). RESULTS: Of n=1,525 included participants (mean age 69.7, 54% female), n=129 developed dementia and n=432 died over follow-up. Greater DGA adherence was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. Slower DunedinPACE accounted for 15% of the DGA association with dementia and 39% of the DGA association with mortality. DISCUSSION: Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention.

Stressful life events have been linked to declining health, and inflammation has been proposed as a physiological mechanism that might explain this association. Using 828 participants from the Dunedin Longitudinal Study, we tested whether people who experienced more stressful life events during adulthood would show elevated systemic inflammation when followed up in midlife, at age 45. We studied three inflammatory biomarkers: C-reactive protein (CRP), interleukin-6 (IL-6), and a newer biomarker, soluble urokinase plasminogen activator receptor (suPAR), which is thought to index systemic chronic inflammation. Stressful life events were not associated with CRP or IL-6. However, people who experienced more stressful life events from age 38 to 44 had elevated suPAR at age 45, and had significantly greater increases in suPAR from baseline to follow-up across the same period. When examining stressful life events across the lifespan, both adverse childhood experiences (ACEs) and adult stressful life events were independently associated with suPAR at age 45. ACEs moderated the association of adult stressful life events and suPAR at age 45—children with more ACEs showed higher suPAR levels after experiencing stressful life events as adults. The results suggest systemic chronic inflammation is one physiological mechanism that could link stressful life events and health, and support the use of suPAR as a useful biomarker for such research.

OBJECTIVE: To understand whether genetic risk for attention-deficit/hyperactivity disorder (ADHD) is associated with the course of the disorder across childhood and into young adulthood.METHOD: Participants were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a population-based birth cohort of 2,232 twins. ADHD was assessed at ages 5, 7, 10, and 12 with mother- and teacher-reports and at age 18 with self-report. Polygenic risk scores (PRSs) were created using a genome-wide association study of ADHD case status. Associations with PRS were examined at multiple points in childhood and longitudinally from early childhood to adolescence. We investigated ADHD PRS and course to young adulthood, as reflected by ADHD remission, persistence, and late onset.RESULTS: Participants with higher ADHD PRSs had increased risk for meeting ADHD diagnostic criteria (odds ratios ranging from 1.17 at age 10 to 1.54 at age 12) and for elevated symptoms at ages 5, 7, 10, and 12. Higher PRS was longitudinally associated with more hyperactivity/impulsivity (incidence rate ratio = 1.18) and inattention (incidence rate ratio = 1.14) from age 5 to age 12. In young adulthood, participants with persistent ADHD exhibited the highest PRS (mean PRS = 0.37), followed by participants with remission (mean PRS = 0.21); both groups had higher PRS than controls (mean PRS = -0.03), but did not significantly differ from one another. Participants with late-onset ADHD did not show elevated PRS for ADHD, depression, alcohol dependence, or marijuana use disorder.CONCLUSION: Genetic risk scores derived from case-control genome-wide association studies may have relevance not only for incidence of mental health disorders, but also for understanding the longitudinal course of mental health disorders.

Knowledge of a person’s risk for Alzheimer’s disease and related dementias (ADRDs) is required to triage candidates for preventive interventions, surveillance, and treatment trials. ADRD risk indexes exist for this purpose, but each includes only a subset of known risk factors. Information missing from published indexes could improve risk prediction. In the Dunedin Study of a population-representative New Zealand-based birth cohort followed to midlife (N = 938, 49.5% female), we compared associations of four leading risk indexes with midlife antecedents of ADRD against a novel benchmark index comprised of nearly all known ADRD risk factors, the Dunedin ADRD Risk Benchmark (DunedinARB). Existing indexes included the Cardiovascular Risk Factors, Aging, and Dementia index (CAIDE), LIfestyle for BRAin health index (LIBRA), Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), and risks selected by the Lancet Commission on Dementia. The Dunedin benchmark was comprised of 48 separate indicators of risk organized into 10 conceptually distinct risk domains. Midlife antecedents of ADRD treated as outcome measures included age-45 measures of brain structural integrity [magnetic resonance imaging-assessed: (i) machine-learning-algorithm-estimated brain age, (ii) log-transformed volume of white matter hyperintensities, and (iii) mean grey matter volume of the hippocampus] and measures of brain functional integrity [(i) objective cognitive function assessed via the Wechsler Adult Intelligence Scale-IV, (ii) subjective problems in everyday cognitive function, and (iii) objective cognitive decline measured as residualized change in cognitive scores from childhood to midlife on matched Weschler Intelligence scales]. All indexes were quantitatively distributed and proved informative about midlife antecedents of ADRD, including algorithm-estimated brain age (β's from 0.16 to 0.22), white matter hyperintensities volume (β's from 0.16 to 0.19), hippocampal volume (β's from −0.08 to −0.11), tested cognitive deficits (β's from −0.36 to −0.49), everyday cognitive problems (β's from 0.14 to 0.38), and longitudinal cognitive decline (β's from −0.18 to −0.26). Existing indexes compared favourably to the comprehensive benchmark in their association with the brain structural integrity measures but were outperformed in their association with the functional integrity measures, particularly subjective cognitive problems and tested cognitive decline. Results indicated that existing indexes could be improved with targeted additions, particularly of measures assessing socioeconomic status, physical and sensory function, epigenetic aging, and subjective overall health. Existing premorbid ADRD risk indexes perform well in identifying linear gradients of risk among members of the general population at midlife, even when they include only a small subset of potential risk factors. They could be improved, however, with targeted additions to more holistically capture the different facets of risk for this multiply determined, age-related disease.

Some humans age faster than others. Variation in biological aging can be measured in midlife, but the implications of this variation are poorly understood. We tested associations between midlife biological aging and indicators of future frailty risk in the Dunedin cohort of 1,037 infants born the same year and followed to age 45. Participants’ ‘Pace of Aging’ was quantified by tracking declining function in 19 biomarkers indexing the cardiovascular, metabolic, renal, immune, dental and pulmonary systems across ages 26, 32, 38 and 45 years. At age 45 in 2019, participants with faster Pace of Aging had more cognitive difficulties, signs of advanced brain aging, diminished sensory–motor functions, older appearances and more pessimistic perceptions of aging. People who are aging more rapidly than same-age peers in midlife may prematurely need supports to sustain independence that are usually reserved for older adults. Chronological age does not adequately identify need for such supports. A cohort study tracking 20-year age-related declines in multiple organ systems finds that, already by midlife, those aging fastest showed cognitive declines, signs of brain aging, diminished sensory–motor function and negative views about aging.

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used Genomic Structural Equation Modeling and prior genome-wide association studies (GWAS) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability.We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Non-cognitive genetics were enriched in the same brain tissues and cell types as cognitive performance but showed different associations with gray-matter brain volumes. Non-cognitive genetics were further distinguished by associations with personality traits, less risky behavior,and increased risk for certain psychiatric disorders.For socioeconomic success and longevity, non-cognitive and cognitive-performance genetics demonstrated similar-magnitude associations. By conducting a GWAS of a phenotype that was not directly measured, we offer a first view of genetic architecture of non-cognitive skills influencing educational success.

Accumulating evidence suggests that individuals exposed to victimization at key developmental stages may have different epigenetic fingerprints compared to those exposed to no/minimal stressful events, however results are inconclusive. This study aimed to strengthen causal inference regarding the impact of adolescent victimization on the epigenome by controlling for genetic variation, age, gender, and shared environmental exposures. We conducted longitudinal epigenome-wide association analyses (EWAS) on DNA methylation (DNAm) profiles of 118 monozygotic (MZ) twin pairs from the Environmental Risk study with and without severe adolescent victimization generated using buccal DNA collected at ages 5, 10 and 18, and the Illumina EPIC array. Additionally, we performed cross-sectional EWAS on age-18 blood and buccal DNA from the same individuals to elucidate tissue-specific signatures of severe adolescent victimization. Our analyses identified 20 suggestive differentially methylated positions (DMPs) (P

Background The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine–guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We utilised both nested cross-validation and two independent test sets for the comparisons. Results We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. This approach achieved a correlation between estimated and actual TL of 0.295 (83.4% CI [0.201, 0.384]) on the EXTEND test data set. Contrastingly, the baseline model of elastic net regression with no prior feature reduction stage performed less well in general—suggesting a prior feature-selection stage may have important utility. A previously developed TL estimator, DNAmTL, achieved a correlation of 0.216 (83.4% CI [0.118, 0.310]) on the EXTEND data. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. Conclusions The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.

Macular drusen are associated with age-related maculopathy but are not an ocular manifestation or biomarker of systemic ageing.Macular drusen are the first sign of age-related maculopathy, an eye disease for which age is the strongest risk factor. The aim of this cohort study was to investigate whether macular drusen in midlife - a sign of the earliest stages of age-related macular degeneration (AMD) - are associated with accelerated biological ageing more generally.Members of the long-running Dunedin Multidisciplinary Health and Development Study (hereafter the Dunedin Study, n = 1037) underwent retinal photography at their most recent assessment at the age of 45 years. Images were graded for the presence of AMD using a simplified scale from the Age-Related Eye Disease Study (AREDS). Accelerated ageing was assessed by (i) a measure of Pace of Ageing defined from a combination of clinical and serum biomarkers obtained at ages 26, 32, 38, and 45 years and (ii) Facial Ageing, defined from photographs obtained at age 38 and 45 years.Of the 938 participants who participated at the age 45 assessments, 834 had gradable retinal photographs, and of these 165 (19.8%) had macular drusen. There was no significant difference in Pace of Ageing (In this representative general population sample, macular drusen in midlife were not associated with accelerated ageing. Future studies tracking longitudinal changes in drusen number and severity at older ages may reveal whether drusen are a biomarker of accelerated ageing.

The mechanisms underlying how monozygotic (or identical) twins arise are yet to be determined. Here, the authors investigate this in an epigenome-wide association study, showing that monozygotic twinning has a characteristic DNA methylation signature in adult somatic tissues. Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin., Netherlands Organization for Scientific Research (NWO); Biobanking and Biomolecular Research Infrastructure (BBMRI–NL); NWO Large Scale infrastructures; X-Omics

Background:Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).Methods:We used data from the Dunedin Study 1972–1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.Results:DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.Conclusions:DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.Funding:This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

Soluble urokinase-type plasminogen activator receptor (suPAR) is a chronic inflammation marker associated with the development of a range of diseases, including cancer and cardiovascular disease. The genetics of suPAR remain unexplored but may shed light on the biology of the marker and its connection to outcomes. We report a heritability estimate of 60% for the variation in suPAR and performed a genome-wide association meta-analysis on suPAR levels measured in Iceland (N = 35,559) and in Denmark (N = 12,177). We identified 13 independently genome-wide significant sequence variants associated with suPAR across 11 distinct loci. Associated variants were found in and around genes encoding uPAR (PLAUR), its ligand uPA (PLAU), the kidney-disease-associated gene PLA2R1 as well as genes with relations to glycosylation, glycoprotein biosynthesis, and the immune response. These findings provide new insight into the causes of variation in suPAR plasma levels, which may clarify suPAR’s potential role in associated diseases, as well as the underlying mechanisms that give suPAR its prognostic value as a unique marker of chronic inflammation., Dowsett and colleagues used a genome-wide association approach to investigate the genetic influence on soluble urokinase-type plasminogen activator receptor presence in the plasma of humans. Their findings indicate a 60% heritability factor in British twins, and using a wide sample of Northern European genome samples they identify eleven genetic loci associated with an increase or decrease of this chronic inflammation marker.

This study tested implications of new genetic discoveries for understanding the association between parental investment and children's educational attainment. A novel design matched genetic data from 860 British mothers and their children with home-visit measures of parenting: the E-Risk Study. Three findings emerged. First, both mothers' and children's education-associated genetics, summarized in a genome-wide polygenic score, predicted parenting -- a gene-environment correlation. Second, accounting for genetic influences slightly reduced associations between parenting and children's attainment -- indicating some genetic confounding. Third, mothers' genetics influenced children's attainment over and above genetic mother-to-child transmission, via cognitively-stimulating parenting -- an environmentally-mediated effect. Findings imply that, when interpreting parents' effects on children, environmentalists must consider genetic transmission, but geneticists must also consider environmental transmission.

Young people's life chances can be predicted by characteristics of their neighbourhood1. Children growing up in disadvantaged neighbourhoods exhibit worse physical and mental health and suffer poorer educational and economic outcomes than children growing up in advantaged neighbourhoods. Increasing recognition that aspects of social inequalities tend, in fact, to be geographical inequalities2-5 is stimulating research and focusing policy interest on the role of place in shaping health, behaviour and social outcomes. Where neighbourhood effects are causal, neighbourhood-level interventions can be effective. Where neighbourhood effects reflect selection of families with different characteristics into different neighbourhoods, interventions should instead target families or individuals directly. To test how selection may affect different neighbourhood-linked problems, we linked neighbourhood data with genetic, health and social outcome data for >7,000 European-descent UK and US young people in the E-Risk and Add Health studies. We tested selection/concentration of genetic risks for obesity, schizophrenia, teen pregnancy and poor educational outcomes in high-risk neighbourhoods, including genetic analysis of neighbourhood mobility. Findings argue against genetic selection/concentration as an explanation for neighbourhood gradients in obesity and mental health problems. By contrast, modest genetic selection/concentration was evident for teen pregnancy and poor educational outcomes, suggesting that neighbourhood effects for these outcomes should be interpreted with care.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies—some of which are novel—from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the “additive SNP factor.” Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

BackgroundA recent genome-wide association study identified molecular-genetic associations with age-at-first-birth. However, the meaning of these genetic discoveries is unclear. Drawing on evidence linking early pregnancy with disinhibitory behavior, we tested the hypothesis that genetic discoveries for age-at-first-birth predict disinhibition.MethodsWe included participants with genotype data from the two-decade-long Environmental Risk (E-Risk) Study (N = 1,999) and the four-decade-long Dunedin Study (N = 918). We calculated a genome-wide polygenic score for age-at-first-birth and tested whether it was associated with a range of disinhibitory outcomes across the life course, including low childhood self-control; risk for externalizing psychopathology; officially recorded criminal offending; substance dependence; informant reports of disinhibitory problems; and number of lifetime sexual partners. We further tested whether associations were attributable to accelerated pubertal maturation.ResultsIn both cohorts, the age-at-first-birth polygenic score predicted low childhood self-control, externalizing psychopathology, officially recorded criminal offending, substance dependence, and number of sexual partners. Associations were modest, but robust across replication. Childhood disinhibition partly mediated associations between the polygenic score and reproductive behaviors. In contrast, associations were not attributable to accelerated pubertal timing.ConclusionsGenomic discoveries for age-at-first-birth are about more than reproductive biology: They provide insight into the disinhibitory traits and behaviors that accompany early parenthood. Age-at-first-birth is a useful proxy phenotype for researchers interested in disinhibition. Further, interventions that improve self-regulation abilities may benefit young parents and their children.

Importance: DNA methylation has been proposed as an epigenetic mechanism by which the childhood neighborhood environment may influence the genome to compromise adult health.Objective: To de...

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs. 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.

BackgroundAssociations of socioenvironmental features like urbanicity and neighborhood deprivation with psychosis are well-established. An enduring question, however, is whether these associations are causal. Genetic confounding could occur due to downward mobility of individuals at high genetic risk for psychiatric problems into disadvantaged environments.MethodsWe examined correlations of five indices of genetic risk [polygenic risk scores (PRS) for schizophrenia and depression, maternal psychotic symptoms, family psychiatric history, and zygosity-based latent genetic risk] with multiple area-, neighborhood-, and family-level risks during upbringing. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins born in 1994–1995 and followed to age 18 (93% retention). Socioenvironmental risks included urbanicity, air pollution, neighborhood deprivation, neighborhood crime, neighborhood disorder, social cohesion, residential mobility, family poverty, and a cumulative environmental risk scale. At age 18, participants were privately interviewed about psychotic experiences.ResultsHigher genetic risk on all indices was associated with riskier environments during upbringing. For example, participants with higher schizophrenia PRS (OR = 1.19, 95% CI = 1.06–1.33), depression PRS (OR = 1.20, 95% CI = 1.08–1.34), family history (OR = 1.25, 95% CI = 1.11–1.40), and latent genetic risk (OR = 1.21, 95% CI = 1.07–1.38) had accumulated more socioenvironmental risks for schizophrenia by age 18. However, associations between socioenvironmental risks and psychotic experiences mostly remained significant after covariate adjustment for genetic risk.ConclusionGenetic risk is correlated with socioenvironmental risk for schizophrenia during upbringing, but the associations between socioenvironmental risk and adolescent psychotic experiences appear, at present, to exist above and beyond this gene-environment correlation.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (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 mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both blood DNAm levels and complex diseases but in most cases these associations do not reflect causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than has previously been hypothesised.

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 2,425 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 peripherl 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.

This cohort study traces the biological responses and associated phenotypes of an upbringing in a socially and economically disadvantaged environment., Key Points Question Is childhood neighborhood disadvantage associated with differential DNA methylation? Findings In this cohort study of 1619 children in Great Britain, exposure to neighborhood socioeconomic disadvantage during childhood was associated with differential DNA methylation at age 18 years in genes involved in inflammation, exposure to tobacco smoke, and metabolism of toxic air pollutants. Meaning The study found that children who were raised in socioeconomically disadvantaged neighborhoods appeared to enter young adulthood epigenetically distinct from their more advantaged peers., Importance DNA methylation has been proposed as an epigenetic mechanism by which the childhood neighborhood environment may have implications for the genome that compromise adult health. Objective To ascertain whether childhood neighborhood socioeconomic disadvantage is associated with differences in DNA methylation by age 18 years. Design, Setting, and Participants This longitudinal cohort study analyzed data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative birth cohort of children born between 1994 and 1995 in England and Wales and followed up from age 5 to 18 years. Data analysis was performed from March 15, 2019, to June 30, 2019. Exposures High-resolution neighborhood data (indexing deprivation, dilapidation, disconnection, and dangerousness) collected across childhood. Main Outcomes and Measures DNA methylation in whole blood was drawn at age 18 years. Associations between neighborhood socioeconomic disadvantage and methylation were tested using 3 prespecified approaches: (1) testing probes annotated to candidate genes involved in biological responses to growing up in socioeconomically disadvantaged neighborhoods and investigated in previous epigenetic research (stress reactivity–related and inflammation-related genes), (2) polyepigenetic scores indexing differential methylation in phenotypes associated with growing up in disadvantaged neighborhoods (obesity, inflammation, and smoking), and (3) a theory-free epigenome-wide association study. Results A total of 1619 participants (806 female individuals [50%]) had complete neighborhood and DNA methylation data. Children raised in socioeconomically disadvantaged neighborhoods exhibited differential DNA methylation in genes involved in inflammation (β = 0.12; 95% CI, 0.06-0.19; P

Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972–1973. Rates of change in each biomarker over ages 26–38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person’s pace of biological aging., eLife digest People’s bodies age at different rates. Age-related biological changes that increase the risk of disease and disability progress rapidly in some people. In others, these processes occur at a slower pace, allowing those individuals to live longer, healthier lives. This observation has led scientists to try to develop therapies that slow aging. The hope is that such treatments could prevent or delay diseases like heart disease or dementia, for which older age is the leading risk factor. Studies in animals have identified treatments that extend the creatures’ lives and slow age-related disease. But testing these treatments in humans is challenging. Our lives are much longer than the worms, flies or mice used in the experiments. Scientists would have to follow human study participants for decades to detect delays in disease onset or an extension of their lives. An alternative approach is to try to develop a test that measures the pace of aging, or essentially “a speedometer for aging”. This would allow scientists to more quickly determine if treatments slow the aging process. Now, Belsky et al. show a blood test designed to measure the pace of aging predicts which people are at increased risk of poor health, chronic disease and an earlier death. First, data about chemical changes to an individual’s DNA, called DNA methylation, were analyzed from white blood cell samples collected from 954 people in a long-term health study known as “The Dunedin Study”. Using the data, Belsky et al. then developed an algorithm – named “DunedinPoAm” – that identified people with an accelerated or slowed pace of aging based on a single blood test. Next, they used the algorithm on samples from participants in three other long-term studies. This verified that those people the algorithm identified as aging faster had a greater risk of poor health, developing chronic diseases or dying earlier. Similarly, those identified as aging more slowly performed better on tests of balance, strength, walking speed and mental ability, and they also looked younger to trained raters. Additionally, Belsky et al. used the test on participants in a randomized trial testing whether restricting calories had potential to extend healthy lifespan. The results suggested that the calorie restriction could counter the effects of an accelerated pace of aging. The test developed by Belsky et al. may provide an alternate way of measuring whether age-slowing treatments work. This would allow faster testing of treatments that can extend the healthy lifespan of humans. The test may also help identify individuals with accelerated aging. This might help public health officials test whether policies or programs can help people lead longer, healthier lives.

Key Points Question Do mental disorder life histories shift among different successive disorders? Findings In this cohort study of 1037 participants in the Dunedin Study birth cohort, with assessments from ages 11 to 45 years, mental disorder life histories shifted among different successive internalizing, externalizing, and thought disorders. Mental disorder life histories are better described by age of onset, duration, and diversity of disorder than by any particular diagnosis. Meaning The finding that most mental disorder life histories involve different successive disorders helps to account for genetic and neuroimaging findings pointing to transdiagnostic causes and cautions against overreliance on diagnosis-specific research and clinical protocols., This cohort study describes mental disorder life histories across 4 decades among participants in the Dunedin Study., Importance Mental health professionals typically encounter patients at 1 point in patients’ lives. This cross-sectional window understandably fosters focus on the current presenting diagnosis. Research programs, treatment protocols, specialist clinics, and specialist journals are oriented to presenting diagnoses, on the assumption that diagnosis informs about causes and prognosis. This study tests an alternative hypothesis: people with mental disorders experience many different kinds of disorders across diagnostic families, when followed for 4 decades. Objective To describe mental disorder life histories across the first half of the life course. Design, Setting, and Participants This cohort study involved participants born in New Zealand from 1972 to 1973 who were enrolled in the population-representative Dunedin Study. Participants were observed from birth to age 45 years (until April 2019). Data were analyzed from May 2019 to January 2020. Main Outcomes and Measures Diagnosed impairing disorders were assessed 9 times from ages 11 to 45 years. Brain function was assessed through neurocognitive examinations conducted at age 3 years, neuropsychological testing during childhood and adulthood, and midlife neuroimaging-based brain age. Results Of 1037 original participants (535 male [51.6%]), 1013 had mental health data available. The proportions of participants meeting the criteria for a mental disorder were as follows: 35% (346 of 975) at ages 11 to 15 years, 50% (473 of 941) at age 18 years, 51% (489 of 961) at age 21 years, 48% (472 of 977) at age 26 years, 46% (444 of 969) at age 32 years, 45% (429 of 955) at age 38 years, and 44% (407 of 927) at age 45 years. The onset of the disorder occurred by adolescence for 59% of participants (600 of 1013), eventually affecting 86% of the cohort (869 of 1013) by midlife. By age 45 years, 85% of participants (737 of 869) with a disorder had accumulated comorbid diagnoses. Participants with adolescent-onset disorders subsequently presented with disorders at more past-year assessments (r = 0.71; 95% CI, 0.68 to 0.74; P

SUMMARY DNA methylation plays an important role in both normal human development and risk of disease. The most utilized method of assessing DNA methylation uses BeadChips, generating an epigenome-wide “snapshot” of >450,000 observations (probe measurements) per assay. However, the reliability of each of these measurements is not equal, and little consideration is paid to consequences for research. We correlated repeat measurements of the same DNA samples using the Illumina HumanMethylation450K and the Infinium MethylationEPIC BeadChips in 350 blood DNA samples. Probes that were reliably measured were more heritable and showed consistent associations with environmental exposures, gene expression, and greater cross-tissue concordance. Unreliable probes were less replicable and generated an unknown volume of false negatives. This serves as a lesson for working with DNA methylation data, but the lessons are equally applicable to working with other data: as we advance toward generating increasingly greater volumes of data, failure to document reliability risks harming reproducibility., In Brief DNA methylation is an important mechanism of gene regulation. The most popular method to measure methylation is to use BeadChips that contain probes to index hundreds of thousands of methylation sites at once. However, these probes are not equally reliable. In blood DNA, unreliable probes were less heritable and less likely to index gene expression, and associations were less replicable. This has serious downstream consequences for reproducible science and should serve as a caution for all data scientists regardless of discipline., Graphical Abstract

Background To understand and measure the association between chronic inflammation, aging, and age-related diseases, broadly applicable standard biomarkers of systemic chronic inflammation are needed. We tested whether elevated blood levels of the emerging chronic inflammation marker soluble urokinase plasminogen activator receptor (suPAR) were associated with accelerated aging, lower functional capacity, and cognitive decline. Methods We used data from the Dunedin Study, a population-representative 1972–1973 New Zealand birth cohort (n = 1037) that has observed participants to age 45 years. Plasma suPAR levels were analyzed at ages 38 and 45 years. We performed regression analyses adjusted for sex, smoking, C-reactive protein, and current health conditions. Results Of 997 still-living participants, 875 (88%) had plasma suPAR measured at age 45. Elevated suPAR was associated with accelerated pace of biological aging across multiple organ systems, older facial appearance, and with structural signs of older brain age. Moreover, participants with higher suPAR levels had greater decline in physical function and cognitive function from childhood to adulthood compared to those with lower suPAR levels. Finally, improvements in health habits between ages 38 and 45 (smoking cessation or increased physical activity) were associated with less steep increases in suPAR levels over those years. Conclusions Our findings provide initial support for the utility of suPAR in studying the role of chronic inflammation in accelerated aging and functional decline.

Educational attainment (EA) is influenced by cognitive abilities and by other characteristics and traits. However little is known about the genetic architecture of these “non-cognitive” contributions to EA. Here, we use Genomic Structural Equation Modelling and results of prior genome-wide association studies (GWASs) of EA (N = 1,131,881) and cognitive test performance (N = 257,841) to estimate SNP associations with variation in EA that is independent of cognitive ability. We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in EA. Phenotypic and biological annotation revealed that (1) both cognitive and non-cognitive contributions to EA were genetically correlated with socioeconomic success and longevity; and (2) non-cognitive contributions to EA were related to personality, decision making, risk-behavior, and increased risk for psychiatric disorders; (3) non-cognitive and cognitive contributions to EA were enriched in the same tissues and cell types, but (4) showed different associations with gray-matter neuroimaging phenotypes.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies—some not previously published—from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the “additive SNP factor.” Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

Large-scale epigenome-wide association meta-analyses have identified multiple ‘signatures’’ of smoking. Drawing on these findings, we describe the construction of a polyepigenetic DNA methylation score that indexes smoking behavior and that can be utilized for multiple purposes in population health research. To validate the score, we use data from two birth cohort studies: The Dunedin Longitudinal Study, followed to age-38 years, and the Environmental Risk Study, followed to age-18 years. Longitudinal data show that changes in DNA methylation accumulate with increased exposure to tobacco smoking and attenuate with quitting. Data from twins discordant for smoking behavior show that smoking influences DNA methylation independently of genetic and environmental risk factors. Physiological data show that changes in DNA methylation track smoking-related changes in lung function and gum health over time. Moreover, DNA methylation changes predict corresponding changes in gene expression in pathways related to inflammation, immune response, and cellular trafficking. Finally, we present prospective data about the link between adverse childhood experiences (ACEs) and epigenetic modifications; these findings document the importance of controlling for smoking-related DNA methylation changes when studying biological embedding of stress in life-course research. We introduce the polyepigenetic DNA methylation score as a tool both for discovery and theory-guided research in epigenetic epidemiology.

Contains fulltext : 209008.pdf (Publisher’s version ) (Open Access) BACKGROUND: Previous studies have reported associations between attention-deficit/hyperactivity disorder symptoms and DNA methylation in children. We report the first epigenome-wide association study meta-analysis of adult attention-deficit/hyperactivity disorder symptoms, based on peripheral blood DNA methylation (Infinium HumanMethylation450K array) in three population-based adult cohorts. METHODS: An epigenome-wide association study was performed in the Netherlands Twin Register (N = 2258, mean age 37 years), Dunedin Multidisciplinary Health and Development Study (N = 800, age 38 years), and Environmental Risk Longitudinal Twin Study (N = 1631, age 18 years), and results were combined through meta-analysis (total sample size N = 4689). Region-based analyses accounting for the correlation between nearby methylation sites were also performed. RESULTS: One epigenome-wide significant differentially methylated position was detected in the Dunedin study, but meta-analysis did not detect differentially methylated positions that were robustly associated across cohorts. In region-based analyses, six significant differentially methylation regions (DMRs) were identified in the Netherlands Twin Register, 19 in the Dunedin study, and none in the Environmental Risk Longitudinal Twin Study. Of these DMRs, 92% were associated with methylation quantitative trait loci, and 68% showed moderate to large blood-brain correlations for DNA methylation levels. DMRs included six nonoverlapping DMRs (three in the Netherlands Twin Register, three in the Dunedin study) in the major histocompatibility complex, which were associated with expression of genes in the major histocompatibility complex, including C4A and C4B, previously implicated in schizophrenia. CONCLUSIONS: Our findings point at new candidate loci involved in immune and neuronal functions that await further replication. Our work also illustrates the need for further research to examine to what extent epigenetic associations with psychiatric traits depend on characteristics such as age, comorbidities, exposures, and genetic background.

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study ( N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children’s polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

Importance: Childhood stress exposure is associated with inflammation as measured by C-reactive protein (CRP) and interleukin 6 (IL-6). However, findings are inconsistent and effect sizes are small. The addition of soluble urokinase plasminogen activator receptor (suPAR), a new biomarker of chronic inflammation, may improve measurement of stress-related inflammatory burden. Objectives: To assess whether exposure to adverse experiences, stress, and violence is associated with an increase in suPAR levels in young people and to test the hypothesis that measuring suPAR in addition to CRP or IL-6 levels improves the assessment of the inflammatory burden associated with early-life stress. Design, Setting, and Participants: This cohort study included 1391 participants from a 1994 to 1995 birth cohort of twins from the nationally representative Environmental Risk Longitudinal Twin Study in the United Kingdom. Participants were followed up until 18 years of age (93% retention). Plasma samples were analyzed in July 2018, and statistical analysis was performed from October 1, 2018, to May 31, 2019. Exposures: Adverse childhood experiences and childhood and adolescent experience of stress and violence exposure. Main Outcomes and Measures: Plasma CRP, IL-6, and suPAR levels at 18 years of age. Results: Among 1391 young people (mean [SD] age, 18.4 [0.36] years; 733 [52.7%] female), those who had been exposed to stressful experiences had elevated suPAR levels by 18 years of age after controlling for sex, body mass index, and smoking: 0.03-ng/mL (95% CI, 0.01-0.05 ng/mL) increase in suPAR per each additional adverse childhood experience, 0.09-ng/mL (95% CI, 0.01-0.17 ng/mL) increase in suPAR per each additional severe childhood experience of stress or violence, and 0.04-ng/mL (95% CI, -0.02 to 0.10 ng/mL) increase in suPAR per each additional severe adolescent experience of stress or violence. Individuals exposed to multiple types of violence in both childhood and adolescence had 0.26-ng/mL (95% CI, 0.07-0.45 ng/mL) higher suPAR levels compared with children who did not experience stress or violence. These stress-exposed young people were significantly more likely to have elevated suPAR levels at 18 years of age even if they did not have elevated CRP or IL-6 levels. Measuring suPAR in addition to CRP or IL-6 increased the association between stress exposure and inflammatory burden. For example, after adjusting for CRP and IL-6 levels, each additional adverse childhood experience was associated with a 0.05-mL (95% CI, 0.03-0.07 ng/mL) increase in suPAR, each additional severe childhood experience of stress or violence was associated with a 0.14-ng/mL (95% CI, 0.06-0.22 ng/mL) increase in suPAR, and each additional severe adolescent experience of stress or violence was associated with a 0.10-ng/mL (95% CI, 0.04-0.16 ng/mL) increase in suPAR. Conclusions and Relevance: The results suggest that adult inflammation is associated with childhood exposure to stress. Adding information about suPAR to traditional biomarkers of inflammation may improve the measurement of inflammatory burden associated with exposure to stress and violence..

People’s life chances can be predicted by their neighborhoods. This observation is driving efforts to improve lives by changing neighborhoods. Some neighborhood effects may be causal, supporting neighborhood-level interventions. Other neighborhood effects may reflect selection of families with different characteristics into different neighborhoods, supporting interventions that target families/individuals directly. To test how selection affects different neighborhood-linked problems, we linked neighborhood data with genetic, health, and social-outcome data for >7,000 European-descent UK and US young people in the E-Risk and Add Health Studies. We tested selection/concentration of genetic risks for obesity, schizophrenia, teen-pregnancy, and poor educational outcomes in high-risk neighborhoods, including genetic analysis of neighborhood mobility. Findings argue against genetic selection/concentration as an explanation for neighborhood gradients in obesity and mental-health problems, suggesting neighborhoods may be causal. In contrast, modest genetic selection/concentration was evident for teen-pregnancy and poor educational outcomes, suggesting neighborhood effects for these outcomes should be interpreted with care.

OBJECTIVE: DNA methylation has been proposed as an epigenetic mechanism by which early-life experiences become "embedded" in the genome and alter transcriptional processes to compromise health. The authors sought to investigate whether early-life victimization stress is associated with genome-wide DNA methylation.METHOD: The authors tested the hypothesis that victimization is associated with DNA methylation in the Environmental Risk (E-Risk) Longitudinal Study, a nationally representative 1994-1995 birth cohort of 2,232 twins born in England and Wales and assessed at ages 5, 7, 10, 12, and 18 years. Multiple forms of victimization were ascertained in childhood and adolescence (including physical, sexual, and emotional abuse; neglect; exposure to intimate-partner violence; bullying; cyber-victimization; and crime).RESULTS: Epigenome-wide analyses of polyvictimization across childhood and adolescence revealed few significant associations with DNA methylation in peripheral blood at age 18, but these analyses were confounded by tobacco smoking and/or did not survive co-twin control tests. Secondary analyses of specific forms of victimization revealed sparse associations with DNA methylation that did not replicate across different operationalizations of the same putative victimization experience. Hypothesis-driven analyses of six candidate genes in the stress response (NR3C1, FKBP5, BDNF, AVP, CRHR1, SLC6A4) did not reveal predicted associations with DNA methylation in probes annotated to these genes.CONCLUSIONS: Findings from this epidemiological analysis of the epigenetic effects of early-life stress do not support the hypothesis of robust changes in DNA methylation in victimized young people. We need to come to terms with the possibility that epigenetic epidemiology is not yet well matched to experimental, nonhuman models in uncovering the biological embedding of stress.