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Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development – a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011–2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median n all  = 98, n developmental  = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.

Background Epigenetic processes are fast emerging as a promising molecular system in the search for both biomarkers and mechanisms underlying human health and disease risk, including psychopathology. Methods In this review, we discuss the application of epigenetics (specifically DNA methylation) to research in child and adolescent mental health, with a focus on the use of developmentally sensitive datasets, such as prospective, population‐based cohorts. We look back at lessons learned to date, highlight current developments in the field and areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers. Results To move the field forward, we advocate for the need of large‐scale, harmonized, collaborative efforts that explicitly account for the time‐varying nature of epigenetic and mental health data across development. Conclusion We conclude with a perspective on what the future may hold in terms of translational applications as more robust signals emerge from epigenetic research on child and adolescent mental health. In this paper, we discuss the application of epigenetics to research in child and adolescent mental health. We look back at lessons learned, highlight current developments in the field and point to areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers, before concluding with a view on potential translational applications that could emerge as the field matures.

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity ( N effective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D ( r g = 0.39, P = 2e-34) and weakly correlated with depression ( r g = 0.13, P = 3e-6). Depression was weakly correlated with T2D ( r g = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank ( N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74–2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

Recent research suggests biological age, based on epigenetic or neuroimaging measures, may predict health traits in adulthood more accurately than chronological age. However, it is unclear if these findings apply earlier in life. We aimed to characterise the performance and interdependence between measures of biological age in young people, leveraging a longitudinal subsample from the population-based ALSPAC cohort ( n  = 386). We derived four epigenetic age measures from blood samples in young people (17–19 years) and a measure of brain age derived from structural neuroimaging data (18–24 years). We examined associations between measures of biological age, and relationships with five measures of physical, cognitive and mental health (8–18 years). We found little evidence for an association between brain age and epigenetic age measures, after accounting for age, sex, cell type, array and study (beta range: -0.59 to 0.59, all p  > 0.05). Increased smoking DNAm was associated with advanced epigenetic age (PACE and Zhang clock), and increased BMI sds with advanced EpiAge Horvath(diff) (all p  < 0.05), but not brain age. Depressive symptoms and cognitive ability were unrelated to all measures of biological age. Our findings highlight the variability of epigenetic- and brain-based age measures in young people, emphasizing the importance of tracking ageing in younger populations.

Cognitive skills are a strong predictor of a wide range of later life outcomes. Genetic and epigenetic associations across the genome explain some of the variation in general cognitive abilities in the general population and it is plausible that epigenetic associations might arise from prenatal environmental exposures and/or genetic variation early in life. We investigated the association between cord blood DNA methylation at birth and cognitive skills assessed in children from eight pregnancy cohorts within the Pregnancy And Childhood Epigenetics (PACE) Consortium across overall (total N = 2196), verbal (total N = 2206) and non-verbal cognitive scores (total N = 3300). The associations at single CpG sites were weak for all of the cognitive domains investigated. One region near DUSP22 on chromosome 6 was associated with non-verbal cognition in a model adjusted for maternal IQ. We conclude that there is little evidence to support the idea that variation in cord blood DNA methylation at single CpG sites is associated with cognitive skills and further studies are needed to confirm the association at DUSP22.

Epigenetic age acceleration (EAA), defined as the difference between chronological age and epigenetically predicted age, was calculated from multiple gestational epigenetic clocks (Bohlin, EPIC overlap, and Knight) using DNA methylation levels from cord blood in three large population-based birth cohorts: the Generation R Study (The Netherlands), the Avon Longitudinal Study of Parents and Children (United Kingdom), and the Norwegian Mother, Father and Child Cohort Study (Norway). We hypothesized that a lower EAA associates prospectively with increased ADHD symptoms. We tested our hypotheses in these three cohorts and meta-analyzed the results ( n  = 3383). We replicated previous research on the association between gestational age (GA) and ADHD. Both clinically measured gestational age as well as epigenetic age measures at birth were negatively associated with ADHD symptoms at ages 5–7 years (clinical GA: β  = −0.04, p  < 0.001, Bohlin: β  = −0.05, p  = 0.01; EPIC overlap: β  = −0.05, p  = 0.01; Knight: β  = −0.01, p  = 0.26). Raw EAA (difference between clinical and epigenetically estimated gestational age) was positively associated with ADHD in our main model, whereas residual EAA (raw EAA corrected for clinical gestational age) was not associated with ADHD symptoms across cohorts. Overall, findings support a link between lower gestational age (either measured clinically or using epigenetic-derived estimates) and ADHD symptoms. Epigenetic age acceleration does not, however, add unique information about ADHD risk independent of clinically estimated gestational age at birth.

Childhood psychiatric symptoms are often diffuse but can coalesce into discrete mental illnesses during late adolescence. We leveraged polygenic scores (PGSs) to parse genomic risk for childhood symptoms and to uncover related neurodevelopmental mechanisms with transcriptomic and neuroimaging data. In independent samples (Adolescent Brain Cognitive Development, Generation R) a narrow cross-disorder neurodevelopmental PGS, reflecting risk for attention deficit hyperactivity disorder, autism, depression and Tourette syndrome, predicted psychiatric symptoms through early adolescence with greater sensitivity than broad cross-disorder PGSs reflecting shared risk across eight psychiatric disorders, the disorder-specific PGS individually or two other narrow cross-disorder (Compulsive, Mood-Psychotic) scores. Neurodevelopmental PGS-associated genes were preferentially expressed in the cerebellum, where their expression peaked prenatally. Further, lower gray matter volumes in cerebellum and functionally coupled cortical regions associated with psychiatric symptoms in mid-childhood. These findings demonstrate that the genetic underpinnings of pediatric psychiatric symptoms differ from those of adult illness, and implicate fetal cerebellar developmental processes that endure through childhood. The authors associate a novel genomic risk score with a broad set of psychiatric symptoms in children. They trace the impact of associated genes on cerebellar developmental processes that originate in fetal life and endure through early adolescence.

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder influenced by both genetic and environmental factors, typically identified in the school-age years but hypothesized to have developmental origins beginning in utero. To improve current strategies for prediction, prevention and treatment, a central challenge is to delineate how, at a molecular level, genetic and environmental influences jointly shape ADHD risk, phenotypic presentation, and developmental course. Epigenetic processes that regulate gene expression, such as DNA methylation, have emerged as a promising molecular system in the search for both biomarkers and mechanisms to address this challenge. In this Current Opinion , we discuss the relevance of epigenetics (specifically DNA methylation) for ADHD research and clinical practice, starting with the current state of knowledge, what challenges we have yet to overcome, and what the future may hold in terms of methylation-based applications for personalized medicine in ADHD. We conclude that the field of epigenetics and ADHD is promising but is still in its infancy, and the potential for transformative translational applications remains a distant goal. Nevertheless, rapid methodological advances, together with the rise of collaborative science and increased availability of high-quality, longitudinal data make this a thriving research area that in future may contribute to the development of new tools for improved prediction, management, and treatment of ADHD.

In Wertz et al. (2019), parents' polygenic scores of educational attainment (PGS‐EA) predicted parental sensitive responses to the child's needs for support, as observed in a dyadic task (i.e., observed sensitivity). We aimed to replicate and expand these findings by combining longitudinal data, child genotype data and several polygenic scores in the Generation R Study. Mother–child dyads participated in two developmental periods, toddlerhood (14 months old; n = 648) and early childhood (3–4 years old, n = 613). Higher maternal PGS‐EA scores predicted higher observed sensitivity in toddlerhood (b = 0.12, 95% CI 0.03, 0.20) and early childhood (b = 0.16, 95% CI 0.08, 0.24). Child PGS‐EA was significantly associated with maternal sensitivity in early childhood (b = 0.11, 95% CI 0.02, 0.21), and the effect of maternal PGS‐EA was no longer significant when correcting for child PGS‐EA. A latent factor of PGSs based on educational attainment, intelligence (IQ) and income showed similar results. These polygenic scores might be associated with maternal cognitive and behavioral skills that help shape parenting. Maternal PGSs predicted observed sensitivity over and above the maternal phenotypes, showing an additional role for PGSs in parenting research. In conclusion, we replicated the central finding of Wertz et al. (2019) that parental PGS‐EA partially explains parental sensitivity. Our findings may be consistent with evocative gene–environment correlation (rGE), emphasizing the dynamic nature of parenting behavior across time, although further research using family trios is needed to adequately test this hypothesis. We replicated the Dunedin study on the relation between the polygenic score for educational attainment and observed sensitivity but also showed that the children's genotypic make‐up has to be taken into account. Our results point to the role of evocative gene–environment correlation in the dynamic interactions between parents and children.

Background Comorbidity between depression and cardiometabolic diseases is an emerging health concern, with childhood maltreatment as a major risk factor. These conditions are also linked to unhealthy lifestyle behaviours such as physical inactivity, smoking, and alcohol intake. However, the precise degree to which lifestyle behaviours moderate the risk between childhood maltreatment and comorbid depression and cardiometabolic disease is entirely unknown. Methods We analysed clinical and self-reported data from four longitudinal studies (N pooled  = 181,423; mean follow-up period of 5–18 years) to investigate the moderating effects of physical activity, smoking, and alcohol intake, on the association between retrospectively reported childhood maltreatment and i) depression, ii) cardiometabolic disease and iii) their comorbidity in older adults (mean age range of 47–66 years). Estimates of these moderation effects were derived using multinomial logistic regressions and then meta-analysed. Results No meaningful moderation effects were detected for any of the lifestyle behaviours on the association between childhood maltreatment and each health outcome. Physical activity was linked to lower odds of depression (OR [95% CI] = 0.94 [0.92; 0.96]), while smoking was a risk factor for all three outcomes (OR [95% CI] = 1.16 [1.04; 1.31] or larger). Alcohol intake was associated with slightly lower odds of comorbidity (OR [95% CI] = 0.69 [0.66; 0.73]), although this association was not stable across all sensitivity analyses. Conclusions Lifestyle behaviours did not moderate the risk association between childhood maltreatment and depression, cardiometabolic disease, and their comorbidity in older adults. However, we confirmed that childhood maltreatment was associated with these conditions. Further research should address the limitations of this study to elucidate the most optimal targets for intervention.