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Psychological stress during pregnancy is known to have a range of long-lasting negative consequences on the development and health of offspring. Here, we tested whether a measure of prenatal early-life stress was associated with a biomarker of physiological development at birth, namely epigenetic gestational age, using foetal cord-blood DNA-methylation data. Longitudinal cohorts from the Netherlands (Generation R Study [Generation R], n = 1,396), the UK (British Avon Longitudinal Study of Parents and Children [ALSPAC], n = 642), and Norway (Mother, Father and Child Cohort Study [MoBa], n1 = 1,212 and n2 = 678) provided data on prenatal maternal stress and genome-wide DNA methylation from cord blood and were meta-analysed (pooled n = 3,928). Measures of epigenetic age acceleration were calculated using three different gestational epigenetic clocks: "Bohlin", "EPIC overlap" and "Knight". Prenatal stress exposure, examined as an overall cumulative score, was not significantly associated with epigenetically-estimated gestational age acceleration or deceleration in any of the clocks, based on the results of the pooled meta-analysis or those of the individual cohorts. No significant associations were identified with specific domains of prenatal stress exposure, including negative life events, contextual (socio-economic) stressors, parental risks (e.g., maternal psychopathology) and interpersonal risks (e.g., family conflict). Further, no significant associations were identified when analyses were stratified by sex. Overall, we find little support that prenatal psychosocial stress is associated with variation in epigenetic age at birth within the general paediatric population.
ABSTRACT
Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.
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BACKGROUND: Infections during pregnancy have been robustly associated with adverse mental and physical health outcomes in offspring, yet the underlying molecular pathways remain largely unknown. Here, we examined whether exposure to common infections in utero associates with DNA methylation (DNAm) patterns at birth and whether this in turn relates to offspring health outcomes in the general population. METHODS: Using data from 2,367 children from the Dutch population-based Generation R Study, we first performed an epigenome-wide association study to identify differentially methylated sites and regions at birth associated with prenatal infection exposure. We also examined the influence of infection timing by using self-reported cumulative infection scores for each trimester. Second, we sought to develop an aggregate methylation profile score (MPS) based on cord blood DNAm as an epigenetic proxy of prenatal infection exposure and tested whether this MPS prospectively associates with offspring health outcomes, including psychiatric symptoms, BMI, and asthma at ages 13-16 years. Third, we investigated whether prenatal infection exposure associates with offspring epigenetic age acceleration - a marker of biological aging. Across all analysis steps, we tested whether our findings replicate in 864 participants from an independent population-based cohort (ALSPAC, UK). RESULTS: We observed no differentially methylated sites or regions in cord blood in relation to prenatal infection exposure, after multiple testing correction. 33 DNAm sites showed suggestive associations (p < 5e10 - 5; of which one was also nominally associated in ALSPAC), indicating potential links to genes associated with immune, neurodevelopmental, and cardiovascular pathways. While the MPS of prenatal infections associated with maternal reports of infections in the internal hold out sample in the Generation R Study (R2incremental = 0.049), it did not replicate in ALSPAC (R2incremental = 0.001), and it did not prospectively associate with offspring health outcomes in either cohort. Moreover, we observed no association between prenatal exposure to infections and epigenetic age acceleration across cohorts and clocks. CONCLUSION: In contrast to prior studies, which reported DNAm differences in offspring exposed to severe infections in utero, we do not find evidence for associations between self-reported clinically evident common infections during pregnancy and DNAm or epigenetic aging in cord blood within the general pediatric population. Future studies are needed to establish whether associations exist but are too subtle to be statistically meaningful with present sample sizes, whether they replicate in a cohort with a more similar infection score as our discovery cohort, whether they occur in different tissues than cord blood, and whether other biological pathways may be more relevant for mediating the effect of prenatal common infection exposure on downstream offspring health outcomes.
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Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.
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Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.
Subject(s)
DNA Methylation , Environmental Exposure , Humans , Female , Pregnancy , Infant, Newborn , Cohort Studies , Male , Fetal Blood/chemistry , Child , Birth CohortABSTRACT
DNA methylation (DNAm) at specific sites can be used to calculate 'epigenetic clocks', which in adulthood are used as indicators of age(ing). However, little is known about how these clock sites 'behave' during development and what factors influence their variability in early life. This knowledge could be used to optimize healthy aging well before the onset of age-related conditions. Here, we leveraged results from two longitudinal population-based cohorts (N=5,019 samples from 2,348 individuals) to characterize trajectories of adult clock sites from birth to early adulthood. We find that clock sites (i) diverge widely in their developmental trajectories, often showing non-linear change over time; (ii) are substantially more likely than non-clock sites to vary between individuals already from birth, differences that are predictive of DNAm variation at later ages; and (iii) show enrichment for genetic and prenatal environmental exposures, supporting an early-origins perspective to epigenetic aging.
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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: ß = -0.04, p < 0.001, Bohlin: ß = -0.05, p = 0.01; EPIC overlap: ß = -0.05, p = 0.01; Knight: ß = -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.
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OBJECTIVE: Early-life stress (ELS) is an established risk factor for a host of adult mental and physical health problems, including both depression and obesity. Recent studies additionally showed that ELS was associated with an increased risk of comorbidity between mental and physical health problems, already in adolescence. Healthy lifestyle factors, including physical activity, sleep and diet have also been robustly linked to both emotional and physical wellbeing. However, it is yet unclear whether these lifestyle factors may moderate the association between ELS and psycho-physical comorbidity. METHODS: We investigated whether (a) participation in physical activity, (b) sleep duration, and (c) adherence to a Mediterranean diet, moderated the relationship between cumulative ELS exposure over the first 10 years of life and psycho-physical comorbidity at the age of 13.5 years. Analyses were conducted in 2022-2023, using data from two large adolescent samples based in the UK (ALSPAC; n = 8428) and The Netherlands (Generation R; n = 4268). RESULTS: Exposure to ELS was significantly associated with a higher risk of developing comorbidity, however this association was not modified by any of the three lifestyle factors investigated. Only physical activity was significantly associated with a reduced risk of comorbidity in one cohort (ORALSPAC [95%CI] = 0.73 [0.59;0.89]). CONCLUSIONS: In conclusion, while we found some evidence that more frequent physical activity may be associated with a reduction in psycho-physical comorbidity, we did not find evidence in support of the hypothesised moderation effects. However, more research is warranted to examine how these associations may evolve over time.
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Early-life stress (ELS) has been robustly associated with a range of poor mental and physical health outcomes. Recent studies implicate the gut microbiome in stress-related mental, cardio-metabolic and immune health problems, but research on humans is scarce and thus far often based on small, selected samples, often using retrospective reports of ELS. We examined associations between ELS and the human gut microbiome in a large, population-based study of children. ELS was measured prospectively from birth to 10 years of age in 2,004 children from the Generation R Study. We studied overall ELS, as well as unique effects of five different ELS domains, including life events, contextual risk, parental risk, interpersonal risk, and direct victimization. Stool microbiome was assessed using 16S rRNA sequencing at age 10 years and data were analyzed at multiple levels (i.e. α- and ß-diversity indices, individual genera and predicted functional pathways). In addition, we explored potential mediators of ELS-microbiome associations, including diet at age 8 and body mass index at 10 years. While no associations were observed between overall ELS (composite score of five domains) and the microbiome after multiple testing correction, contextual risk - a specific ELS domain related to socio-economic stress, including risk factors such as financial difficulties and low maternal education - was significantly associated with microbiome variability. This ELS domain was associated with lower α-diversity, with ß-diversity, and with predicted functional pathways involved, amongst others, in tryptophan biosynthesis. These associations were in part mediated by overall diet quality, a pro-inflammatory diet, fiber intake, and body mass index (BMI). These results suggest that stress related to socio-economic adversity - but not overall early life stress - is associated with a less diverse microbiome in the general population, and that this association may in part be explained by poorer diet and higher BMI. Future research is needed to test causality and to establish whether modifiable factors such as diet could be used to mitigate the negative effects of socio-economic adversity on the microbiome and related health consequences.
Subject(s)
Adverse Childhood Experiences , Gastrointestinal Microbiome , Child , Humans , Gastrointestinal Microbiome/genetics , Retrospective Studies , RNA, Ribosomal, 16S/genetics , FecesABSTRACT
BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.
Subject(s)
Diabetes, Gestational , Hypertension, Pregnancy-Induced , Pre-Eclampsia , Female , Humans , Infant, Newborn , Pregnancy , Body Mass Index , Cesarean Section , Hypertension, Pregnancy-Induced/epidemiology , Pre-Eclampsia/epidemiology , Mendelian Randomization AnalysisABSTRACT
BACKGROUND: Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. METHODS: We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger's Z-test and further validated in a pediatric cohort without diabetes (aged 9-12 years old, n = 3866). RESULTS: We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta - 0.08 SD, 95% CI [- 0.10-0.07], p = 6.50 × 10-32) and beta-cell dysfunction (Beta - 0.10 SD, 95% CI [- 0.12, - 0.08], p = 1.46 × 10-47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06-0.10, p = 8.0 × 10-33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02-1.62, p = 0.03). CONCLUSIONS: We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin Resistance , Humans , Child , Diabetes Mellitus, Type 2/genetics , Genetic Risk Score , Insulin Resistance/genetics , Cluster Analysis , Obesity/geneticsABSTRACT
BACKGROUND: Higher early-life animal protein intake is associated with a higher childhood obesity risk compared to plant protein intake. Differential DNA methylation may represent an underlying mechanism. METHODS: We analysed associations of infant animal and plant protein intakes with DNA methylation in early (2-6 years, N = 579) and late (7Ì-12 years, N = 604) childhood in two studies. Study-specific robust linear regression models adjusted for relevant confounders were run, and then meta-analysed using a fixed-effects model. We also performed sex-stratified meta-analyses. Follow-up analyses included pathway analysis and eQTM look-up. RESULTS: Infant animal protein intake was not associated with DNA methylation in early childhood, but was associated with late-childhood DNA methylation at cg21300373 (P = 4.27 × 10¯8, MARCHF1) and cg10633363 (P = 1.09 × 10¯7, HOXB9) after FDR correction. Infant plant protein intake was associated with early-childhood DNA methylation at cg25973293 (P = 2.26 × 10-7, C1orf159) and cg15407373 (P = 2.13 × 10-7, MBP) after FDR correction. There was no overlap between the findings from the animal and plant protein analyses. We did not find enriched functional pathways at either time point using CpGs associated with animal and plant protein. These CpGs were not previously associated with childhood gene expression. Sex-stratified meta-analyses showed sex-specific DNA methylation associations for both animal and plant protein intake. CONCLUSION: Infant animal protein intake was associated with DNA methylation at two CpGs in late childhood. Infant plant protein intake was associated with DNA methylation in early childhood at two CpGs. A potential mediating role of DNA methylation at these CpGs between infant protein intake and health outcomes requires further investigation.