OBJECTIVE:To estimate associations of more than minimal prenatal nicotine, alcohol, cannabis, and opioid exposures with gestational age, birth weight, and birth weight for gestational age. METHODS:Data were drawn from the HEALthy Brain and Child Development (HBCD) Study, a multisite, longitudinal study in the United States. Predefined recruitment thresholds for each substance were assessed using maternal self-report, maternal toxicology results, and newborn substance exposure-related diagnoses. Birth outcomes included gestational age at delivery (weeks), birth weight (grams), and birth weight for gestational age (centiles). Mean differences and risk ratios for the associations between substance exposure and birth outcomes were estimated using multilevel mixed-effect linear regression or multilevel mixed-effect Poisson regression. RESULTS:Among 660 mother-infant dyads, 17% (n = 115) of participants met recruitment thresholds for prenatal cannabis, 15% for nicotine (n = 102), 13% for alcohol (n = 86), and 5% for opioids (n = 32). In adjusted models, prenatal cannabis and opioid exposures were each associated with lower birth weight (cannabis: -272.2 [95% CI -444.6 to -99.8] g; opioids: -295.4 [95% CI -574.9 to -15.9] g) and birth weight centiles (cannabis: -8.2 [95% CI -15.3 to -1.1] centiles; opioids: -14.4 [95% CI -25.5, -3.4] centiles), although the results were sensitive to model specifications. Prenatal nicotine and alcohol estimates were in similar directions but not statistically significant. No significant associations between exposures and gestational age at delivery were detected. CONCLUSIONS:In this initial HBCD Study data release, more than minimal exposure to cannabis and opioids was associated with smaller birth size, adding evidence to an inconsistent literature. Future studies from HBCD can more deeply interrogate timing and dose of each substance and expand to childhood outcomes.

Background Prenatal exposure to pesticides and psychosocial factors often co-occurs, particularly in low- and middle-income settings, yet their joint effects on epigenetic age acceleration (EAA) in early life remain unknown. We investigated the joint associations of prenatal pesticides metabolites and psychosocial factors on EAA in the first five years of life in the South African Drakenstein Child Health Study. Methods In 643 mothers, we measured 11 urinary pesticide metabolites and seven psychosocial factors during the second trimester of pregnancy. Child DNA methylation was measured in whole blood at ages 1, 3, and 5 years. EAA was estimated using the Horvath, Skin & Blood Horvath (skinHorvath), and Wu epigenetic clocks. Longitudinal associations were estimated using generalized estimating equations, adjusted for confounders. Joint mixture associations were evaluated using weighted quantile sum regression (WQS) and quantile g-computation (QGCOMP). Results The joint prenatal exposure mixture was positively associated with Wu (β per one quintile increase in the mixture [95% CI]: 0.41 years [0.15, 0.80]), skinHorvath (0.11 years [0.06, 0.16]), and Horvath EAA (0.31 years [0.20, 0.46]) over time using WQS. Psychosocial factors, particularly food insecurity, physical interpersonal violence, and stress biomarkers, contributed most to the total mixture effect for all clocks. Pyrethroid metabolites PBA and TDCCA were top pesticide contributors to Wu EAA. Pathway enrichment analyses of clock-specific CpGs revealed distinct biological architectures, with the Wu clock enriched for neurodevelopmental and immune pathways, and metabolic pathways for the Horvath clock. Discussion Joint prenatal exposure to pesticides and psychosocial factors was associated with increased EAA across early childhood, with psychosocial factors contributing the most to the total effect. These findings highlight the importance of assessing chemical and non-chemical stressors jointly and clock-specific biological interpretation in epigenetic aging research.

The Developmental Origins of Health and Disease (DOHaD) hypothesis proposes that the perinatal environment shapes susceptibility to complex traits across life [1]. The placenta, a transient organ mediating maternal-fetal exchange, plays a central role in this process and has emerged as a key molecular archive in utero [2-4]. Placental DNA methylation (DNAm) is a unique mediator between prenatal exposures, fetal genetics and later-life outcomes [5-9]. DNAm quantitative trait loci (mQTL) have helped disentangling causal mechanisms underlying GWAS loci for complex diseases [10-15]. Despite growing evidence that placental genomic regulation has broad and profound effects on the developmental programming of early- and later-life health outcomes [17], existing placental studies remain limited in scale and largely focused on growth- and neuro-related traits [12-16]. Here, we construct a high-resolution placental mQTL resource and systematically investigate how placental DNAm relates to early- and later-life traits, and to shared vulnerability and complex interactions among them.

Language development is a critical part of human development that unfolds across time. We aimed to examine how prenatal phthalate exposure affects early childhood language development, utilizing a robust longitudinal analysis methodology. Participants were drawn from the Early Autism Risk Longitudinal Investigation (EARLI) (n = 251) and the Markers of Autism Risk in Babies - Learning Early Signs (MARBLES) (n = 393) cohorts that recruited pregnant mothers who previously had a child with autism (ASD). Expressive and receptive language development was measured using the Mullen Scales of Early Learning (MSEL) at ages 6,12, 24, and 36 months. Fourteen phthalate metabolites were assessed in first morning urine in each trimester of pregnancy. We used latent class growth analysis (LCGA) to determine language trajectories and measure their associations with prenatal phthalqaates. We found three trajectories for both expressive and receptive languages. Most of the phthalates measured were not significantly associated with language development, though metabolites of di(2-ethylhexyl) phthalate decreased the risk of belonging to an abnormal receptive language trajectory. These observations, along with general trends observed within molecular weight classes, were largely consistent with prior literature.

Blood DNA methylation patterns are highly predictive of prenatal exposure to smoking, and differential methylation has been associated with maternal alcohol use. We extended this to determine whether DNA methylation patterns in cord blood are associated with prenatal exposure to opioids, cannabis, and polysubstance use. We also evaluated whether DNA methylation patterns have predictive utility. We examined 932 mother-child pairs in the Boston Birth Cohort between 1998 and 2020 with cord blood DNA methylation data. For each substance self-reported within 72 hr after birth, we performed an adjusted linear regression analysis at 865,859 CpG sites to identify related methylation differences. We generated polyepigenetic scores using summary statistics for each exposure and assessed predictive ability using cross-validation and receiver operating characteristic curves. Specificity of methylation associations was evaluated by assessing overlap across exposure summary statistics and using logistic regression for methylation scores, adjusted for concurrent use. We identified methylation changes at 72, 21, and 1 CpG suggestively associated with prenatal exposure to opioids, cannabis, and polysubstance use, respectively (p < 1e-6), in cord blood, reported for the first time for these exposures. We identified two loci associated at epigenome-wide significance with opioids and one with polysubstance use (p < 1e-8). Methylation scores were highly predictive and exposure-specific, with area under the curve accuracy of 91% for opioids, 90% for cannabis, and 93%-98% depending on polysubstance number. These CpGs provide biologic insights for reducing the impact of substance exposure, and these findings may serve as a biomarker of prenatal substance exposure for future studies and potential clinical utility.

Quantitative measures of autism spectrum disorder (ASD)-related traits can provide insight into trait presentation across the population. Previous studies have identified epigenomic variation associated with ASD diagnosis, but few have evaluated quantitative traits. We sought to identify DNA methylation patterns in child blood associated with Social Responsiveness Scale score, Second Edition (SRS). We conducted an epigenome-wide association study of SRS in child blood at approximately age 5 in the Study to Explore Early Development, a case-control study of ASD in the United States. We measured DNA methylation using the Illumina 450K array with 857 samples in our analysis after quality control. We performed regression of the M-value to identify single sites or differentially methylated regions (DMRs) associated with SRS scores, adjusting for sources of biological and technical variation. We examined methylation quantitative trait loci and conducted gene-ontology-term pathway analyses for regions of interest. We identified a region about 3.5 kb upstream of ZFP57 on chromosome 6 as differentially methylated (family-wise error rate [fwer] < 0.1) by continuous SRS T-score in the full sample (N = 857; fwer = 0.074) and among ASD cases only (N = 390; fwer = 0.021). ZFP57 encodes a transcription factor involved in imprinting regulation and maintenance, and this DMR has been previously associated with ASD in brain and buccal samples. Blood DNA methylation near ZFP57 was associated (fwer < 0.1) with SRS in the full population sample and appears to be largely driven by trait heterogeneity within the autism case group. Our results indicate DNA methylation associations with ASD quantitative traits are observable in a population and provide insights into specific biologic changes related to autism trait heterogeneity.

Purpose:The objectives of this study were to investigate associations between co-occurring developmental, psychiatric, behavioral, and medical symptoms and conditions and autism spectrum disorder (ASD) traits, as well as predictors of changes in autistic traits from early childhood to adolescence. Methods:Participants from the Study to Explore Early Development (SEED) were identified as having autism spectrum disorder (ASD) (n=707), another developmental disorder (DD) (n=995), or as a population comparison group (POP) (n=898). Caregivers completed the Social Responsiveness Scale-2nd edition (SRS-2) to measure autistic traits and were asked about co-occurring symptoms and conditions when their child was 2-5 years old and 12-16 years old. Children completed the Mullen Scales of Early Learning (MSEL) when they were 2-5 years old. Results:Regression models revealed that in early childhood and adolescence, multiple co-occurring symptoms and conditions were significantly associated with higher SRS-2 scores (e.g., motor, sensory, and sleep problems for children with ASD and DD). Within the ASD and DD groups, but not the POP group, lower MSEL scores at childhood were associated with greater increases in SRS-2 scores between early childhood and adolescence. Conclusions:Findings suggest that motor, sensory, and sleep problems may be important intervention targets for ASD and DD youth with elevated SRS-2 scores and that interventions that target cognitive functioning in childhood may be important to modify trajectories of autistic traits from childhood to adolescence.

Background:Prenatal air pollutants have been associated with adverse birth outcomes, and DNA methylation (DNAm) changes in placenta may contribute to these associations. DNAm-based epigenetic gestational age (GA) estimators are emerging biomarkers for aging/biological age that can reflect early-life exposures and predict long-term health outcomes. We leveraged 103 mother-offspring pairs from the Early Autism Risk Longitudinal Investigation cohort to assess associations between prenatal air pollution and placental epigenetic GA at birth. Methods:Prenatal air pollution concentrations (NO2, O3, PM2.5, and PM10) were estimated from weekly data from monitoring stations near maternal residence and calculated for preconception and pregnancy periods. DNAm from fetal-side placenta samples was measured on Illumina HumanMethylation450 BeadChip. Epigenetic GA was computed using Lee's robust placenta clock algorithm. GA acceleration/deceleration was the residual of predicted epigenetic GA on chronologic GA, adjusted (intrinsic) or unadjusted (extrinsic) for cell type proportions. We used linear regressions to examine associations between average air pollution levels in each period and GA acceleration/deceleration, and weekly distributed lag models to examine critical exposure windows. Results:Higher pregnancy average O3 and PM10 exposures were associated with decelerated intrinsic (β = -0.65 and -0.79) and extrinsic GA (β = -0.69 and -0.74) at birth (per 10-unit increment). Trimester-specific analyses revealed higher O3 and PM10 exposures in trimesters 2 to 3 associated with decelerated GA at birth. Weekly distributed lag models suggested pregnancy weeks 21 to 31 and 21 to 29 were critical windows of O3 and PM10 exposures, respectively. Conclusions:Prenatal air pollution exposures, especially during mid- to late-pregnancy, were associated with lower biological maturity at birth.

Background: Socioeconomic position (SEP), which reflects one's position in society and access to resources, is strongly tied to neurodevelopment and is associated with epigenetic changes. AIM: This study examined whether DNA methylation signatures of prenatal SEP, measured in birth samples, are associated with child neurodevelopmental outcomes at 36 months of age. METHODS: Prenatal SEP DNA methylation scores were derived using 97 placenta and 127 cord blood biospecimens in the Early Autism Risk Longitudinal Investigation cohort. Participants completed the Mullen Scales of Early Learning (MSEL) and Vineland Adaptive Behavior Scales (VABS) at 36 months of age. Generalized regression analyses, adjusting for maternal age and race, were performed to test the association between SEP methylation score, for each birth biospecimen type, and MSEL and VABS scores. RESULTS: Significant associations were observed between placenta SEP methylation score and MSEL Expressive Language outcomes (beta = -2.7, p = 0.046, 95 % CI [- 5.43, -0.05]) and Receptive Language outcomes (beta = -2.5, p = 0.037, 95 % CI [-4.82, -0.16]). In cord blood, methylation-SEP scores were significantly associated with Receptive Language outcomes (beta = -2.0, p = 0.037, 95 % CI [-3.85, -0.12]). No significant associations were observed with VABS scores. CONCLUSION: Our results confirm associations between prenatal SEP and early childhood language development using a novel empiric DNA methylation measure of exposure

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The HBCD Study aims to reflect the sociodemographic diversity of pregnant individuals in the U.S. The study will also oversample individuals who use substances during pregnancy and enroll similar individuals who do not use to allow for generalizable inferences of the impact of prenatal substance use on trajectories of child development. Without probability sampling or a randomization-based design, the study requires innovation during enrollment, close monitoring of group differences, and rigorous evaluation of external and internal validity across the enrollment period. In this article, we discuss the HBCD Study recruitment and enrollment data collection processes and potential analytic strategies to account for sources of heterogeneity and potential bias. First, we introduce the adaptive design and enrollment monitoring indices to assess and enhance external and internal validity. Second, we describe the visit schedule for in-person and remote data collection where dyads are randomly assigned to visit windows based on a jittered design to optimize longitudinal trajectory estimation. Lastly, we provide an overview of analytic procedures planned for estimating trajectories.

BACKGROUND Emerging evidence reveals a complex relationship between cardiovascular disease (CVD) and cancer, which share common risk factors and biological pathways. OBJECTIVES The aim of this study was to evaluate common epigenetic signatures for CVD and cancer incidence in 3 ethnically diverse cohorts: Native Americans from the SHS (Strong Heart Study), European Americans from the FHS (Framingham Heart Study), and European Americans and African Americans from the ARIC (Atherosclerosis Risk In Communities) study. METHODS A 2-stage strategy was used that included first conducting untargeted epigenome-wide association studies for each cohort and then running targeted models in the union set of identified differentially methylated positions (DMPs). We also explored potential molecular pathways by conducting a bioinformatics analysis. RESULTS Common DMPs were identified across all populations. In a subsequent meta-analysis, 3 and 1 of those DMPs were statistically significant for CVD only and both cancer and CVD, respectively. No meta-analyzed DMPs were statistically significant for cancer only. The enrichment analysis pointed to interconnected biological pathways involved in cancer and CVD. In the DrugBank database, elements related to 1-carbon metabolism and cancer and CVD medications were identified as potential drugs for target gene products. In an additional analysis restricted to the 950 SHS participants who developed incident CVD, the C index for incident cancer increased from 0.618 (95% CI: 0.570-0.672) to 0.971 (95% CI: 0.963-0.978) when adjusting the models for the combined cancer and CVD DMPs identified in the other cohorts. CONCLUSIONS These results point to molecular pathways and potential treatments for precision prevention of CVD and cancer. Screening based on common epigenetic signatures of incident CVD and cancer may help identify patients with newly diagnosed CVD at increased cancer risk. (JACC CardioOncol. 2024;6:731-742) (c) 2024 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Objective:Many children with autism spectrum disorder (ASD) and other developmental disabilities (DD) transitioned to telehealth services due to the COVID-19 pandemic. Our objectives were to describe reductions in allied and behavioral healthcare services and receipt of caregiver training to deliver services at home because of COVID-19 for children with ASD and other DD, and factors associated with worse response to remote delivery of services for children with ASD.Method:Prior to the pandemic, children 2 to 5 years of age were enrolled in a multi-site case-control study and completed a developmental assessment. Caregivers completed questionnaires on child behavior problems and ASD symptoms. Children were classified as having ASD vs another DD based on standardized diagnostic measures. Subsequently, caregivers completed a survey during January to June 2021 to assess how COVID-19 affected children and families.Results:Caregivers reported that most children with ASD and other DD had a decrease in service hours (50.0%-76.9% by service type) during the COVID-19 pandemic. Children with ASD were significantly more likely to experience reduced speech/language therapy than children with other DD. Receipt of caregiver training to deliver services at home ranged from 38.1% to 57.4% by service type. Among children with ASD, pre-pandemic problems with internalizing behaviors and social communication/interaction were associated with worse response to behavioral telehealth but no other common therapies.Conclusion:Our study demonstrates the caregiver-reported impacts of COVID-19 on remote delivery of allied and behavioral healthcare services for children with ASD and other DD. Considerations for caregiver support and remote delivery of services are provided.

Abstract Background Common genetic variation has been shown to account for a large proportion of ASD heritability. Polygenic scores generated for autism spectrum disorder (ASD-PGS) using the most recent discovery data, however, explain less variance than expected, despite reporting significant associations with ASD and other ASD-related traits. Here, we investigate the extent to which information loss on the target study genome-wide microarray weakens the predictive power of the ASD-PGS. Methods We studied genotype data from three cohorts of individuals with high familial liability for ASD: The Early Autism Risk Longitudinal Investigation (EARLI), Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), and the Infant Brain Imaging Study (IBIS), and one population-based sample, Study to Explore Early Development Phase I (SEED I). Individuals were genotyped on different microarrays ranging from 1 to 5 million sites. Coverage of the top 88 genome-wide suggestive variants implicated in the discovery was evaluated in all four studies before quality control (QC), after QC, and after imputation. We then created a novel method to assess coverage on the resulting ASD-PGS by correlating a PGS informed by a comprehensive list of variants to a PGS informed with only the available variants. Results Prior to imputations, None of the four cohorts directly or indirectly covered all 88 variants among the measured genotype data. After imputation, the two cohorts genotyped on 5-million arrays reached full coverage. Analysis of our novel metric showed generally high genome-wide coverage across all four studies, but a greater number of SNPs informing the ASD-PGS did not result in improved coverage according to our metric. Limitations. The studies we analyzed contained modest sample sizes. Our analyses included microarrays with more than 1-million sites, so smaller arrays such as Global Diversity and the PsychArray were not included. Our PGS metric for ASD is only generalizable to samples of European ancestries, though the coverage metric can be computed for traits that have sufficiently large-sized discovery findings in other ancestries. Conclusions We show that commonly used genotyping microarrays have incomplete coverage for common ASD variants, and imputation cannot always recover lost information. Our novel metric provides an intuitive approach to reporting information loss in PGS and an alternative to reporting the total number of SNPs included in the PGS. While applied only to ASD here, this metric can easily be used with other traits.

Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5-10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR < 0.05). Eight of these CpGs were located near/in the MTNR1B gene, coding for a melatonin receptor. Regional analysis identified them together as a differentially methylated region consisting of 9 CpGs in/near MTNR1B, at which higher DNAm was associated with greater maternal age (PFDR = 6.92 × 10-8) in newborns. In childhood blood samples, these differences in blood DNAm of MTNR1B CpGs were nominally significant (p < 0.05) and retained the same positive direction, suggesting persistence of associations. Maternal age was also positively associated with higher DNA methylation at three CpGs in RTEL1-TNFRSF6B at birth (PFDR < 0.05) and nominally in childhood (p < 0.0001). Of the remaining 10 CpGs also persistent in childhood, methylation at cg26709300 in YPEL3/BOLA2B in external data was associated with expression of ITGAL, an immune regulator. While further study is needed to establish causality, particularly due to the small effect sizes observed, our results potentially support offspring DNAm as a mechanism underlying associations of maternal age with child health.

Background: Prenatal exposure to metals is hypothesized to be associated with child autism. We aim to investigate the joint and individual effects of prenatal exposure to urine metals including lead (Pb), mercury (Hg), manganese (Mn), and selenium (Se) on child Social Responsiveness Scale (SRS) scores. Methods: We used data from 2 cohorts enriched for likelihood of autism spectrum disorder (ASD): Early Autism Risk Longitudinal Investigation (EARLI) and the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) studies. Metal concentrations were measured in urine collected during pregnancy. We used Bayesian Kernel Machine Regression and linear regression models to investigate both joint and independent associations of metals with SRS Z-scores in each cohort. We adjusted for maternal age at delivery, interpregnancy interval, maternal education, child race/ethnicity, child sex, and/or study site. Results: The final analytic sample consisted of 251 mother-child pairs. When Pb, Hg, Se, and Mn were at their 75th percentiles, there was a 0.03 increase (95% credible interval [CI]: −0.11, 0.17) in EARLI and 0.07 decrease (95% CI: −0.29, 0.15) in MARBLES in childhood SRS Z-scores, compared to when all 4 metals were at their 50th percentiles. In both cohorts, increasing concentrations of Pb were associated with increasing values of SRS Z-scores, fixing the other metals to their 50th percentiles. However, all the 95% credible intervals contained the null. Conclusions: There were no clear monotonic associations between the overall prenatal metal mixture in pregnancy and childhood SRS Z-scores at 36 months. There were also no clear associations between individual metals within this mixture and childhood SRS Z-scores at 36 months. The overall effects of the metal mixture and the individual effects of each metal within this mixture on offspring SRS Z-scores might be heterogeneous across child sex and cohort. Further studies with larger sample sizes are warranted.

Food and nutrition-related factors have the potential to impact development of autism spectrum disorder (ASD) and quality of life for people with ASD, but gaps in evidence exist. On 10 November 2022, Tufts University ' s Friedman School of Nutrition Science and Policy and Food and Nutrition Innovation Institute hosted a 1-d meeting to explore the evidence and evidence gaps regarding the relationships of food and nutrition with ASD. This meeting report summarizes the presentations and deliberations from the meeting. Topics addressed included prenatal and child dietary intake, the microbiome, obesity, food-related environmental exposures, mechanisms and biological processes linking these factors and ASD, food-related social factors, and data sources for future research. Presentations highlighted evidence for protective associations with prenatal folic acid supplementation and ASD development, increases in risk of ASD with maternal gestational obesity, and the potential for exposure to environmental contaminants in foods and food packaging to in fl uence ASD development. The importance of the maternal and child microbiome in ASD development or ASD-related behaviors in the child was reviewed, as was the role of discrimination in leading to disparities in environmental exposures and psychosocial factors that may in fl uence ASD. The role of child diet and high prevalence of food selectivity in children with ASD and its association with adverse outcomes were also discussed. Priority evidence gaps identi fi ed by participants include further clarifying ASD development, including biomarkers and key mechanisms; interactions among psychosocial, social, and biological determinants; interventions addressing diet, supplementation, and the microbiome to prevent and improve quality of life for people with ASD; and mechanisms of action of diet-related factors associated with ASD. Participants developed research proposals to address the priority evidence gaps. The workshop fi ndings serve as a foundation for future prioritization of scienti fi c research to address evidence gaps related to food, nutrition, and ASD.

Thyroid hormones are essential for neurodevelopment. Few studies have considered associations with quantitatively measured autism spectrum disorder (ASD)-related traits, which may help elucidate associations for a broader population. Participants were drawn from two prospective pregnancy cohorts: the Early Autism Risk Longitudinal Investigation (EARLI), enrolling pregnant women who already had a child with ASD, and the Health Outcomes and Measures of the Environment (HOME) Study, following pregnant women from the greater Cincinnati, OH area. Gestational thyroid-stimulating hormone (TSH) and free thyroxine (FT4) were measured in mid-pregnancy 16 (±3) weeks gestation serum samples. ASD-related traits were measured using the Social Responsiveness Scale (SRS) at ages 3-8 years. The association was examined using quantile regression, adjusting for maternal and sociodemographic factors. 278 participants (132 from EARLI, 146 from HOME) were included. TSH distributions were similar across cohorts, while FT4 levels were higher in EARLI compared to HOME. In pooled analyses, particularly for those in the highest SRS quantile (95th percentile), higher FT4 levels were associated with increasing SRS scores (β = 5.21, 95% CI = 0.93, 9.48), and higher TSH levels were associated with decreasing SRS scores (β = -6.94, 95% CI = -11.04, -2.83). The association between TSH and SRS remained significant in HOME for the 95% percentile of SRS scores (β = -6.48, 95% CI = -12.16, -0.80), but not EARLI. Results for FT4 were attenuated when examined in the individual cohorts. Our results add to evidence that gestational thyroid hormones may be associated with ASD-related outcomes by suggesting that relationships may differ across the distribution of ASD-related traits and by familial likelihood of ASD.

Abstract Background Autism spectrum disorder (ASD) is a prevalent and heterogeneous neurodevelopmental disorder. Risk is attributed to genetic and prenatal environmental factors, though the environmental agents are incompletely characterized. Methods In Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies Learning Early Signs (MARBLES), two pregnancy cohorts of siblings of children with ASD, urinary metals concentrations during two pregnancy time periods (< 28 weeks and ≥ 28 weeks of gestation) were measured using inductively coupled plasma mass spectrometry. At age three, clinicians assessed ASD with DSM-5 criteria. In an exposure-wide association framework, using multivariable log binomial regression, we examined each metal for association with ASD status, adjusting for gestational age at urine sampling, child sex, age at pregnancy, race/ethnicity and education. We meta-analyzed across the two cohorts. Results In EARLI (n = 170) 17% of children were diagnosed with ASD, and 44% were classified as having non-neurotypical development (Non-TD). In MARBLES (n = 231), 21% were diagnosed with ASD, and 14% classified as Non-TD. During the first and second trimester period (< 28 weeks), having cadmium concentration over the level of detection was associated with 1.69 (1.08, 2.64) times higher risk of ASD, and 1.29 (0.95, 1.75)times higher risk of Non-TD. A doubling of first and second trimester cesium concentration was marginally associated with 1.89 (0.94, 3.80) times higher risk of ASD, and a doubling of third trimester cesium with 1.69 (0.97, 2.95) times higher risk of ASD. Conclusion Exposure in utero to elevated levels of cadmium and cesium, as measured in urine collected during pregnancy, was associated with increased risk of developing ASD.

Parents of autistic children report barriers to engaging in physical activity, which may be exacerbated during subsequent pregnancies. We aimed to describe physical activity of parents caring for an autistic child, before and during a subsequent pregnancy, and to explore whether physical activity was associated with the autistic child's Social Responsiveness Scale score, a measure of autism-related traits. We used data from the Early Autism Risk Longitudinal Investigation, in which families with an autistic child were followed through a subsequent pregnancy. Mothers (n = 245) self-reported physical activity in the 3 months before conception and during pregnancy; fathers (n = 130) reported on the 6 months prior to enrollment. Approximately 40% of nonpregnant mothers and fathers and 9.3% of pregnant mothers met Physical Activity Guidelines for Americans recommendations. Most (83.5%) pregnant mothers reported no vigorous activity; after adjustment for covariates, this was more common among mothers of children with Social Responsiveness Scale T-scores >75 compared with mothers of children with lower T-scores (adjusted odds ratio (95% confidence interval) = 2.94 (1.11, 7.78)). Among parents caring for an autistic child before and during a subsequent pregnancy, physical activity was lower than recommended. Family-based interventions may be necessary to help support physical activity levels. Lay Abstract Parents of autistic children may have limited time and resources to participate in physical activity, a key aspect of health. Previous studies have been small and included mostly mothers, rather than fathers. No studies have examined physical activity in these parents during another pregnancy, when physical activity is especially important for maternal and fetal health. We aimed to fill this gap by examining physical activity levels among mothers and fathers caring for an autistic child before and during a subsequent pregnancy. We used data from a study which followed pregnant individuals who already had a child with autism. We asked mothers and fathers to report their levels of moderate and vigorous physical activity. We found that mothers and fathers of autistic children reported lower physical activity levels than the national average and were unlikely to meet Physical Activity Guidelines for Americans. Pregnant mothers were the least likely to participate in physical activity, particularly if their autistic child scored highly on a measure of autistic traits. Given that parental physical activity has benefits for parents and children, family-based interventions may be needed to help support parents' physical activity levels.