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BACKGROUND: Maternal anxiety, depression, and stress during and after pregnancy are negatively associated with child cognitive development. However, the contribution of positive maternal experiences, such as social support, to child cognitive development has received less attention. Furthermore, how maternal experience of social support during specific developmental periods impacts child cognitive development is largely unknown. METHODS: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 5784) and the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study (PREDO; n = 420), we investigated the associations between maternal perceived social support during and after pregnancy and child's general cognitive ability at 8 years of age, assessed with the Wechsler Intelligence Scale for Children (WISC). Bayesian relevant life course modeling was used to investigate timing effects of maternal social support on child cognitive ability. RESULTS: In both cohorts, higher maternal perceived social support during pregnancy was associated with higher performance on the WISC, independent of sociodemographic factors and concurrent maternal symptoms of depression and anxiety. In ALSPAC, pregnancy emerged as a sensitive period for the effects of perceived social support on child cognitive ability, with a stronger effect of social support during pregnancy than after pregnancy on child cognitive ability. CONCLUSIONS: Our findings, supported from two prospective longitudinal cohorts, suggest a distinct role of maternal perceived social support during pregnancy for cognitive development in children. Our study suggests that interventions aimed at increasing maternal social support during pregnancy may be an important strategy for promoting maternal and child well-being.
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Background: Autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and schizophrenia (SCZ) are highly heritable and linked to disruptions in foetal (neuro)development. While epigenetic processes are considered an important underlying pathway between genetic susceptibility and neurodevelopmental conditions, it is unclear (i) whether genetic susceptibility to these conditions is associated with epigenetic patterns, specifically DNA methylation (DNAm), already at birth; (ii) to what extent DNAm patterns are unique or shared across conditions, and (iii) whether these neonatal DNAm patterns can be leveraged to enhance genetic prediction of (neuro)developmental outcomes. Methods: We conducted epigenome-wide meta-analyses of genetic susceptibility to ASD, ADHD, and schizophrenia, quantified using polygenic scores (PGSs) on cord blood DNAm, using four population-based cohorts (n pooled=5,802), all North European. Heterogeneity statistics were used to estimate overlap in DNAm patterns between PGSs. Subsequently, DNAm-based measures of PGSs were built in a target sample, and used as predictors to test incremental variance explained over PGS in 130 (neuro)developmental outcomes spanning birth to 14 years. Outcomes: In probe-level analyses, SCZ-PGS associated with neonatal DNAm at 246 loci (p<9×10-8), predominantly in the major histocompatibility complex. Functional characterization of these DNAm loci confirmed strong genetic effects, significant blood-brain concordance and enrichment for immune-related pathways. 8 loci were identified for ASD-PGS (mapping to FDFT1 and MFHAS1), and none for ADHD-PGS. Regional analyses indicated a large number of differentially methylated regions for all PGSs (SCZ-PGS: 157, ASD-PGS: 130, ADHD-PGS: 166). DNAm signals showed little overlap between PGSs. We found suggestive evidence that incorporating DNAm-based measures of genetic susceptibility at birth increases explained variance for several child cognitive and motor outcomes over and above PGS. Interpretation: Genetic susceptibility for neurodevelopmental conditions, particularly schizophrenia, is detectable in cord blood DNAm at birth in a population-based sample, with largely distinct DNAm patterns between PGSs. These findings support an early-origins perspective on schizophrenia. Funding: HorizonEurope; European Research Council.
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BACKGROUND: Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age were based on DNA methylation data from the Illumina HumanMethylation 27 K or 450 K array, which have subsequently been replaced by the Illumina MethylationEPIC 850 K array (EPIC). Our aims here were to build an epigenetic gestational age clock specific for the EPIC array and to evaluate its precision and accuracy using the embryo transfer date of newborns from the largest EPIC-derived dataset to date on assisted reproductive technologies (ART). METHODS: We built an epigenetic gestational age clock using Lasso regression trained on 755 randomly selected non-ART newborns from the Norwegian Study of Assisted Reproductive Technologies (START)-a substudy of the Norwegian Mother, Father, and Child Cohort Study (MoBa). For the ART-conceived newborns, the START dataset had detailed information on the embryo transfer date and the specific ART procedure used for conception. The predicted gestational age was compared to clinically estimated gestational age in 200 non-ART and 838 ART newborns using MM-type robust regression. The performance of the clock was compared to previously published gestational age clocks in an independent replication sample of 148 newborns from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restrictions (PREDO) study-a prospective pregnancy cohort of Finnish women. RESULTS: Our new epigenetic gestational age clock showed higher precision and accuracy in predicting gestational age than previous gestational age clocks (R2 = 0.724, median absolute deviation (MAD) = 3.14 days). Restricting the analysis to CpGs shared between 450 K and EPIC did not reduce the precision of the clock. Furthermore, validating the clock on ART newborns with known embryo transfer date confirmed that DNA methylation is an accurate predictor of gestational age (R2 = 0.767, MAD = 3.7 days). CONCLUSIONS: We present the first EPIC-based predictor of gestational age and demonstrate its robustness and precision in ART and non-ART newborns. As more datasets are being generated on the EPIC platform, this clock will be valuable in studies using gestational age to assess neonatal development.
Assuntos
Metilação de DNA/genética , Epigênese Genética/genética , Epigenômica/métodos , Idade Gestacional , Técnicas de Reprodução Assistida , Estudos de Coortes , Conjuntos de Dados como Assunto , Feminino , Finlândia , Humanos , Recém-Nascido , Masculino , Noruega , Estudos Prospectivos , Reprodutibilidade dos TestesRESUMO
BACKGROUND: Maternal depression and anxiety during pregnancy may enhance fetal exposure to glucocorticoids (GCs) and harm neurodevelopment. We tested whether a novel cross-tissue polyepigenetic biomarker indicative of in utero exposure to GC is associated with mental and behavioral disorders and their severity in children, possibly mediating the associations between maternal prenatal depressive and anxiety symptoms and these child outcomes. METHODS: Children (n = 814) from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study were followed-up from birth to age 7.1-10.7 years. A weighted polyepigenetic GC exposure score was calculated based on the methylation profile of 24 CpGs from umbilical cord blood. Child diagnosis of mental and behavioral disorder (n = 99) and its severity, defined as the number of days the child had received treatment (all 99 had received outpatient treatment and 8 had been additionally in inpatient treatment) for mental or behavioral disorder as the primary diagnosis, came from the Care Register for Health Care. Mothers (n = 408) reported on child total behavior problems at child's age of 2.3-5.8 years and their own depressive and anxiety symptoms during pregnancy (n = 583). RESULTS: The fetal polyepigenetic GC exposure score at birth was not associated with child hazard of mental and behavioral disorder (HR = 0.82, 95% CI 0.54; 1.24, p = 0.35) or total behavior problems (unstandardized beta = -0.10, 95% CI -0.31; 0.10, p = 0.33). However, for one standard deviation decrease in the polyepigenetic score, the child had spent 2.94 (95%CI 1.59; 5.45, p < 0.001) more days in inpatient or outpatient treatment with any mental and behavioral disorder as the primary diagnosis. Criteria for mediation tests were not met. CONCLUSIONS: These findings suggest that fetal polyepigenetic GC exposure score at birth was not associated with any mental or behavioral disorder diagnosis or mother-rated total behavior problems, but it may contribute to identifying children at birth who are at risk for more severe mental or behavioral disorders.