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Parental age is a known risk factor for autism spectrum disorder (ASD), however, studies to identify the biologic changes underpinning this association are limited. In recent years, "epigenetic clock" algorithms have been developed to estimate biologic age and to evaluate how the epigenetic aging impacts health and disease. In this study, we examined the relationship between parental epigenetic aging and their child's prospective risk of ASD and autism related quantitative traits in the Early Autism Risk Longitudinal Investigation study. Estimates of epigenetic age were computed using three robust clock algorithms and DNA methylation measures from the Infinium HumanMethylation450k platform for maternal blood and paternal blood specimens collected during pregnancy. Epigenetic age acceleration was defined as the residual of regressing chronological age on epigenetic age while accounting for cell type proportions. Multinomial logistic regression and linear regression models were completed adjusting for potential confounders for both maternal epigenetic age acceleration (n = 163) and paternal epigenetic age acceleration (n = 80). We found accelerated epigenetic aging in mothers estimated by Hannum's clock was significantly associated with lower cognitive ability and function in offspring at 12 months, as measured by Mullen Scales of Early Learning scores (β = -1.66, 95% CI: -3.28, -0.04 for a one-unit increase). We also observed a marginal association between accelerated maternal epigenetic aging by Horvath's clock and increased odds of ASD in offspring at 36 months of age (aOR = 1.12, 95% CI: 0.99, 1.26). By contrast, fathers accelerated aging was marginally associated with decreased ASD risk in their offspring (aOR = 0.83, 95% CI: 0.68, 1.01). Our findings suggest epigenetic aging could play a role in parental age risks on child brain development.

Introduction: Measures of pulmonary function are associated with cardiovascular disease risk; however, the underlying mechanism remains unclear. Hypothesis: We hypothesize that protein biomarkers are associated with pulmonary function decline, as well as the risk of subsequent incident coronary heart disease (CHD), heart failure (HF), and mortality. Methods: We included participants from the Atherosclerosis Risk in Communities (ARIC) study with plasma proteome measured by SOMAscan and spirometric measures (forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC)) at both visits 2 (1990-1992) and 5 (2011-2013). Cross-sectional associations of protein levels with FEV1 and FVC at both visits were assessed using multivariable linear regression. The decline of FEV1 was evaluated among proteins related to cross-sectional FEV1 and FVC measures. The FEV1-decline-related proteins were further probed into the effects on incident CHD, HF, and mortality, using Cox proportional hazard models post-visit 2. Results: Out of 4,677 proteins, 364 were cross-sectionally associated with both FEV1 and FVC at visit 2 (n=11,354, age 57, 23% blacks, and 56% women) and 5 (n=3,517, age 75, 17% blacks, and 58% women) at FDR Figure ). Gamma-aminobutyric acid receptor-associated protein showed the greatest effect with FEV1 decline, and its per SD increase was associated with 20% higher risk of HF and mortality. Compared to HF and mortality, FEV1 decline-related proteins were less associated with incident CHD. Conclusions: Twenty-seven proteins related to pulmonary function decline were heavily associated with the risk of HF and mortality, suggesting shared etiology between those conditions.

Given inconsistent evidence on preconception or prenatal tobacco use and offspring autism spectrum disorder (ASD), this study assessed associations of maternal smoking with ASD and ASD-related traits. Among 72 cohorts in the Environmental Influences on Child Health Outcomes consortium, 11 had ASD diagnosis and prenatal tobaccosmoking (n = 8648). and 7 had Social Responsiveness Scale (SRS) scores of ASD traits (n = 2399). Cohorts had diagnoses alone (6), traits alone (2), or both (5). Diagnoses drew from parent/caregiver report, review of records, or standardized instruments. Regression models estimated smoking-related odds ratios (ORs) for diagnoses and standardized mean differences for SRS scores. Cohort-specific ORs were meta-analyzed. Overall, maternal smoking was unassociated with child ASD (adjusted OR, 1.08; 95% confidence interval [CI], 0.72-1.61). However, heterogeneity across studies was strong: preterm cohorts showed reduced ASD risk for exposed children. After excluding preterm cohorts (biased by restrictions on causal intermediate and exposure opportunity) and small cohorts (very few ASD cases in either smoking category), the adjusted OR for ASD from maternal smoking was 1.44 (95% CI, 1.02-2.03). Children of smoking (versus non-smoking) mothers had more ASD traits (SRS T-score + 2.37 points, 95% CI, 0.73-4.01 points), with results homogeneous across cohorts. Maternal preconception/prenatal smoking was consistently associated with quantitative ASD traits and modestly associated with ASD diagnosis among sufficiently powered United States cohorts of non-preterm children. Limitations resulting from self-reported smoking and unmeasured confounders preclude definitive conclusions. Nevertheless, counseling on potential and known risks to the child from maternal smoking is warranted for pregnant women and pregnancy planners. LAY SUMMARY: Evidence on the association between maternal prenatal smoking and the child's risk for autism spectrum disorder has been conflicting, with some studies reporting harmful effects, and others finding reduced risks. Our analysis of children in the ECHO consortium found that maternal prenatal tobacco smoking is consistently associated with an increase in autism-related symptoms in the general population and modestly associated with elevated risk for a diagnosis of autism spectrum disorder when looking at a combined analysis from multiple studies that each included both pre- and full-term births. However, this study is not proof of a causal connection. Future studies to clarify the role of smoking in autism-like behaviors or autism diagnoses should collect more reliable data on smoking and measure other exposures or lifestyle factors that might have confounded our results.

Reports on the association between the prevalence of atopic diseases and neurodevelopmental disabilities (NDs) have been inconsistent in the literature. We investigated whether autism spectrum disorder (ASD), attention deficit-hyperactivity disorders (ADHD), and other NDs are more prevalent in children with asthma, atopic dermatitis (AD) and allergic rhinitis (AR) compared to those without specific atopic conditions. A total of 2580 children enrolled at birth were followed prospectively, of which 119 have ASD, 423 have ADHD, 765 have other NDs, and 1273 have no NDs. Atopic diseases and NDs were defined based on physician diagnoses in electronic medical records. Logistic regressions adjusting for maternal and child characteristics estimated the associations between NDs (i.e., ASD, ADHD, and other NDs) and asthma, AD and AR, respectively. Children with asthma, AD or AR had a greater likelihood of having ADHD or other NDs compared with children without specific atopic conditions. The association between ASD and asthma diminished after adjusting for maternal and child factors. Either mothers or children having atopic conditions and both mothers and children with atopic conditions were associated with a higher prevalence of ADHD in children, compared with neither mothers nor children having atopic conditions. Children diagnosed with multiple atopic diseases were more likely to have NDs compared with those without or with only one type of atopic disease. In conclusion, in this U.S. urban birth cohort, children with atopic diseases had a higher co-morbidity of NDs. The findings have implications for etiologic research that searches for common early life antecedents of NDs and atopic conditions. Findings from this study also should raise awareness among health care providers and parents about the possible co-occurrence of both NDs and atopic conditions, which calls for coordinated efforts to screen, prevent and manage NDs and atopic conditions.

This review article provides a framework for the use of deoxyribonucleic acid (DNA) methylation (DNAm) biomarkers to study the biological embedding of socioeconomic position (SEP) and summarizes the latest developments in the area. It presents the emerging literature showing associations between individual- and neighborhood-level SEP exposures and DNAm across the life course. In contrast to questionnaire-based methods of assessing SEP, we suggest that DNAm biomarkers may offer an accessible metric to study questions about SEP and health outcomes, acting as a personal dosimeter of exposure. However, further work remains in standardizing SEP measures across studies and evaluating consistency across domains, tissue types, and time periods. Meta-analyses of epigenetic associations with SEP are offered as one approach to confirm the replication of DNAm loci across studies. The development of DNAm biomarkers of SEP would provide a method for examining its impact on health outcomes in a more robust way, increasing the rigor of epidemiological studies.

Background: 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 opioid, cannabis, and polysubstance use. We also evaluated whether DNA methylation patterns have predictive utility. Methods: We examined 932 mother-child pairs in the Boston Birth Cohort between 1998-2020 with cord blood DNA methylation and maternal substance use data. For each substance, we performed adjusted linear regression analysis at 865,859 CpG sites to identify related methylation changes. We generated 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. Results: We identified methylation changes at 72, 21, and 1 novel CpG associated with prenatal exposure to opioids, cannabis, and polysubstance use respectively, at epigenome-wide significance (PConclusion: We identified novel DNA methylation differences in cord blood associated with prenatal exposure and showed that methylation scores are highly predictive of substance exposures. These CpGs provide biologic insights for reducing the impact of substance exposure. These findings may serve as a biomarker of prenatal substance exposure for future studies and potential clinical utility.

Background This study aims to clarify relationships of maternal psychiatric conditions and selective serotonin reuptake inhibitor (SSRI) use during preconception and pregnancy with risk of neurodevelopmental disorders in offspring. Methods We used data from the Study to Explore Early Development, a multisite case-control study conducted in the United States among children born between 2003 and 2011. Final study group classifications of autism spectrum disorder (ASD) (n = 1367), developmental delays or disorders (DDs) (n = 1750), and general population controls (n = 1671) were determined by an in-person standardized developmental assessment. Maternal psychiatric conditions and SSRI use during pregnancy were ascertained from both self-report and medical records. We used logistic regression to evaluate associations of ASD and DDs (vs. population controls) with maternal psychiatric conditions and SSRI treatment in pregnancy. To reduce confounding by indication, we also examined SSRI associations in analyses restricted to mothers with psychiatric conditions during pregnancy. Results Psychiatric conditions and SSRI use during pregnancy were significantly more common among mothers of children with either ASD or DDs than among population controls. Odds of ASD were similarly elevated among mothers with psychiatric conditions who did not use SSRIs during pregnancy (adjusted odds ratio 1.81, 95% confidence interval 1.44–2.27) as in mothers who did use SSRIs (adjusted odds ratio 2.05, 95% confidence interval 1.50–2.80). Among mothers with psychiatric conditions, SSRI use was not significantly associated with ASD in offspring (adjusted odds ratio 1.14, 95% confidence interval 0.80–1.62). Primary findings for DDs exhibited similar relationships to those observed with ASD. Conclusions Maternal psychiatric conditions but not use of SSRIs during pregnancy were associated with increased risk of neurodevelopmental disorders in offspring.

The number of children diagnosed with autism spectrum disorder (ASD) has increased substantially over the past two decades with current research unable to fully account for this dramatic increase in prevalence. One explanation proposes that both intrinsic (e.g., genetic) and extrinsic (e.g., environmental) risk factors may be involved in the etiology of ASD. The goal of this review paper is to explore modifiable pathways for intervention in children at risk for ASD, specifically examining how early social experience may be correlated with epigenetic change in genes associated with autism. We present an innovative model which proposes that polygenic risk and social experience (via epigenetic mechanisms) may both contribute to the observed ASD phenotype. Previous research on genetic, environmental, and epigenetic mechanisms implicated in the etiology of ASD will be reviewed, with an emphasis on the oxytocin receptor gene, which is epigenetically altered by early social experience, plays a crucial role in mammalian social and cognitive development, and is associated with both genetic and epigenetic risk for ASD. Identifying intrinsic (e.g., genetic) and extrinsic (e.g., social experience) risk markers for ASD, a combination of which has not previously been examined, would transform our understanding of this condition, facilitate earlier identification of ASD risk, and guide early intervention efforts. This may have a far-reaching impact on individuals with ASD, their families, and society.

Polysubstance use among pregnant women has increased because of the opioid epidemic and the increasing legalization of cannabis along with persistent tobacco and alcohol consumption. Previous research on prenatal substance use and the child's risk of attention-deficit/hyperactivity disorder (ADHD) has mostly focused on single-substance exposures; simultaneous examination of multiple substance use and assessment of their synergistic health consequences is needed.To assess the consequences of the use of specific substances during pregnancy, investigate whether the interaction of multiple prenatal substance exposures is associated with increases in the risk of childhood ADHD, and estimate the aggregate burden of polysubstance exposure during gestation.This cohort study analyzed data from the Boston Birth Cohort from 1998 to 2019. The sample of the present study comprised a multiethnic urban cohort of mother-child pairs who were predominantly low income. A total of 3138 children who were enrolled shortly after birth at Boston Medical Center were included and followed up from age 6 months to 21 years.Substance use during pregnancy was identified based on self-reported tobacco smoking, alcohol consumption, and use of cannabis, cocaine, or opioids in any trimester of pregnancy. Diagnostic codes for neonatal opioid withdrawal syndrome or neonatal abstinence syndrome from the International Classification of Diseases, Ninth Revision, and the International Classification of Diseases, Tenth Revision, were also used to identify opioid exposure during gestation.ADHD diagnosis in the child's electronic medical record.Among 3138 children (1583 boys [50.4%]; median age, 12 years [IQR, 9-14 years]; median follow-up, 10 years [IQR, 7-12 years]) in the final analytic sample, 486 (15.5%) had an ADHD diagnosis and 2652 (84.5%) were neurotypical. The median postnatal follow-up duration was 12 years (IQR, 9-14 years). Among mothers, 46 women (1.5%) self-identified as Asian (non-Pacific Islander), 701 (22.3%) as Hispanic, 1838 (58.6%) as non-Hispanic Black, 227 (7.2%) as non-Hispanic White, and 326 (10.4%) as other races and/or ethnicities (including American Indian or Indigenous, Cape Verdean, Pacific Islander, multiracial, other, or unknown). A total of 759 women (24.2%) reported the use of at least 1 substance during pregnancy, with tobacco being the most frequently reported (580 women [18.5%]). Cox proportional hazards models revealed that opioid exposure (60 children) had the highest adjusted hazard ratio (HR) for ADHD (2.19; 95% CI, 1.10-4.37). After including main statistical effects of all individual substances in an elastic net regression model, the HR of opioids was reduced to 1.60, and evidence of a statistical interaction between opioids and both cannabis and alcohol was found, producing 1.42 and 1.15 times higher risk of ADHD, respectively. The interaction between opioids and smoking was also associated with a higher risk of ADHD (HR, 1.17).The findings of this study suggest that it is important to consider prenatal concurrent exposure to multiple substances and their possible interactions when counseling women regarding substance use during pregnancy, the future risk of ADHD for their children, and strategies for cessation and treatment programs.

Genetic association studies of child health outcomes often employ family-based study designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide marker data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multiethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

Prior work proposed a shortened version of the Social Responsiveness Scale (SRS), a commonly used quantitative measure of social communication traits. We used data from 3,031 participants (including 190 ASD cases) from the Environmental Influences on Child Health Outcomes (ECHO) Program to compare distributional properties and criterion validity of 16-item “short” to 65-item “full” SRS scores. Results demonstrated highly overlapping distributions of short and full scores. Both scores separated case from non-case individuals by approximately two standard deviations. ASD prediction was nearly identical for short and full scores (area under the curve values of 0.87, 0.86 respectively). Findings support comparability of shortened and full scores, suggesting opportunities to increase efficiency. Future work should confirm additional psychometric properties of short scores.

Gestational exposure to air pollution increases the risk of autism spectrum disorder and cognitive impairments with unresolved molecular mechanisms. This study exposed C57BL/6J mice throughout gestation to urban-derived nanosized particulate matter (nPM). Young adult male and female offspring were studied for behavioral and metabolic changes using forced swim test, fat gain, glucose tolerance, and hippocampal transcriptome. Gestational nPM exposure caused increased depressive behaviors, decreased neurogenesis in the dentate gyrus, and increased glucose tolerance in adult male offspring. Both sexes gained fat and body weight. Gestational nPM exposure induced 29 differentially expressed genes (DEGs) in adult hippocampus related to cytokine production, IL17a signaling, and dopamine degradation in both sexes. Stratification by sex showed twofold more DEGs in males than females (69 vs 37), as well as male-specific enrichment of DEGs mediating serotonin signaling, endocytosis, Gαi, and cAMP signaling. Gene co-expression analysis (WCGNA) identified a module of 43 genes with divergent responses to nPM between the sexes. Chronic changes in 14 DEGs (e.g., microRNA9-1) were associated with depressive behaviors, adiposity and glucose intolerance. These genes enriched neuroimmune pathways such as HMGB1 and TLR4. Based on cerebral cortex transcriptome data of neonates, we traced the initial nPM responses of HMGB1 pathway. In vitro, mixed glia responded to 24 h nPM with lower HMGB1 protein and increased proinflammatory cytokines. This response was ameliorated by TLR4 knockdown. In sum, we identified transcriptional changes that could be associated with air pollution-mediated behavioral and phenotypic changes. These identified genes merit further mechanistic studies for therapeutic intervention development.

The etiologic pathways leading to neuropsychiatric diseases remain poorly defined. As genomic technologies have advanced over the past several decades, considerable progress has been made linking neuropsychiatric disorders to genetic underpinnings. Interest and consideration of nongenetic risk factors (e.g., lead exposure and schizophrenia) have, in contrast, lagged behind heritable frameworks of explanation. Thus, the association of neuropsychiatric illness to environmental chemical exposure, and their potential interactions with genetic susceptibility, are largely unexplored. In this review, we describe emerging approaches for considering the impact of chemical risk factors acting alone and in concert with genetic risk, and point to the potential role of epigenetics in mediating exposure effects on transcription of genes implicated in mental disorders. We highlight recent examples of research in nongenetic risk factors in psychiatric disorders that point to potential shared biological mechanisms—synaptic dysfunction, immune alterations, and gut–brain interactions. We outline new tools and resources that can be harnessed for the study of environmental factors in psychiatric disorders. These tools, combined with emerging experimental evidence, suggest that there is a need to broadly incorporate environmental exposures in psychiatric research, with the ultimate goal of identifying modifiable risk factors and informing new treatment strategies for neuropsychiatric disease.

Genetic association studies of child health outcomes often employ family-based designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multi-ethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

PURPOSE OF REVIEW: This review demonstrates the growing body of evidence connecting DNA methylation to prior exposure. It highlights the potential to use DNA methylation patterns as a feasible, stable, and accurate biomarker of past exposure, opening new opportunities for environmental and gene-environment interaction studies among existing banked samples. RECENT FINDINGS: We present the evidence for association between past exposure, including prenatal exposures, and DNA methylation measured at a later time in the life course. We demonstrate the potential utility of DNA methylation-based biomarkers of past exposure using results from multiple studies of smoking as an example. Multiple studies show the ability to accurately predict prenatal smoking exposure based on DNA methylation measured at birth, in childhood, and even adulthood. Separate sets of DNA methylation loci have been used to predict past personal smoking exposure (postnatal) as well. Further, it appears that these two types of exposures, prenatal and previous personal exposure, can be isolated from each other. There is also a suggestion that quantitative methylation scores may be useful for estimating dose. We highlight the remaining needs for rigor in methylation biomarker development including analytic challenges as well as the need for development across multiple developmental windows, multiple tissue types, and multiple ancestries. SUMMARY: If fully developed, DNA methylation-based biomarkers can dramatically shift our ability to carry out environmental and genetic-environmental epidemiology using existing biobanks, opening up unprecedented opportunities for environmental health.

ImportanceRisk to airflow limitation and Chronic Obstructive Pulmonary Disease (COPD) is influenced by combinations of cigarette smoking and genetic susceptibility, yet it remains unclear whether gene-by-smoking interactions contribute to quantitative measures of lung function.ObjectiveDetermine whether smoking modifies the effect of a polygenic risk score’s (PRS’s) association with reduced lung function.DesignUnited Kingdom (UK) Biobank prospective cohort study.SettingPopulation cohort.ParticipantsUK citizens of European ancestry aged 40-69 years, with genetic and spirometry data passing quality control metrics.ExposuresPRS, self-reported pack-years of smoking, ever-versus never-smoking status, and current-versus former-/never-smoking status.Main Outcomes and MeasuresForced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC). We tested for interactions with models including the main effects of PRS, different smoking variables, and their cross-product term(s). We also compared the effects of pack-years of smoking on FEV1/FVC for those in the highest versus lowest decile of predicted genetic risk for low lung function.ResultsWe included 319,730 individuals (24,915 with moderate-to-severe COPD). The PRS and pack-years were significantly associated with lower FEV1/FVC, as was the interaction term (β [interaction] = −0.0028 [95% CI: −0.0029, −0.0026]; all p < 0.0001). A stepwise increment in estimated effect sizes for these interaction terms was observed per 10 pack-years of smoking exposure (all p < 0.0001). There was evidence of significant interaction between PRS with ever/never smoking status (β [interaction] = −0.0064 [95% CI: −0.0068, −0.0060]) and current/not-current smoking (β [interaction] = −0.0091 [95% CI: −0.0097, −0.0084]). For any given level of pack-years of smoking exposure, FEV1/FVC was significantly lower for individuals in the tenth compared to the first decile of genetic risk (p < 0.0001). For every 20 pack-years of smoking, those in the top compared to the bottom decile of genetic risk showed nearly a twofold reduction in FEV1/FVC.Conclusions and RelevanceCOPD is characterized by diminished lung function, and our analyses suggest there is substantial interaction between genome-wide PRS and smoking exposures. While smoking has negative effects on lung function across all genetic risk categories, effects of smoking are highest in those with higher predicted genetic risk.Key PointsQuestionDoes cigarette smoking modify the magnitude of genetic effects on forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC)?FindingsFEV1/FVC is influenced by PRS-by-smoking interactions. Smoking was detrimental across all categories of predicted genetic risk, though it was worse for those with highest predicted genetic risks. For every reported 20 pack-years of reported smoking, individuals in the top compared to the bottom decile of genetic risk showed nearly twice the reduction in FEV1/FVC.MeaningElucidating mechanisms for the interaction between smoking and genetic risk could yield greater insight into the pathogenesis of chronic obstructive pulmonary disease (COPD).

Fetal sex-specific differences in placental morphology and physiology have been associated with sexually dimorphic health outcomes. However, the molecular mechanisms underlying these sex differences are not well understood. We performed whole genome bisulfite sequencing in 133 placenta samples and discovered a significant difference in DNA methylation (DNAm) at the ZNF300 gene locus between male and female offspring and replicated this result in 6 independent datasets. Additionally, the sex-specific pattern appears to be placenta-specific, is robust to a wide range of gestational ages and adverse health outcomes and is present in sorted placenta villous cytotrophoblast cells. Integration of DNAm, genetic, and placental morphology data from the same individuals revealed ZNF300 methylation is also associated with placenta area, perimeter, and max diameter, genetic variants on chromosomes 5 and X, and may mediate the effects of genetic variation on placental area.

Background A family history of specific disorders (e.g., autism, depression, epilepsy) has been linked to risk for autism spectrum disorder (ASD). This study examines whether family history data could be used for ASD risk prediction. Methods We followed all Danish live births, from 1980 to 2012, of Denmark-born parents for an ASD diagnosis through April 10, 2017 (N = 1,697,231 births; 26,840 ASD cases). Linking each birth to three-generation family members, we identified 438 morbidity indicators, comprising 73 disorders reported prospectively for each family member. We tested various models using a machine learning approach. From the best-performing model, we calculated a family history risk score and estimated odds ratios and 95% confidence intervals for the risk of ASD. Results The best-performing model comprised 41 indicators: eight mental conditions (e.g., ASD, attention-deficit/hyperactivity disorder, neurotic/stress disorders) and nine nonmental conditions (e.g., obesity, hypertension, asthma) across six family member types; model performance was similar in training and test subsamples. The highest risk score group had 17.0% ASD prevalence and a 15.3-fold (95% confidence interval, 14.0–17.1) increased ASD risk compared with the lowest score group, which had 0.6% ASD prevalence. In contrast, individuals with a full sibling with ASD had 9.5% ASD prevalence and a 6.1-fold (95% confidence interval, 5.9–6.4) higher risk than individuals without an affected sibling. Conclusions Family history of multiple mental and nonmental conditions can identify more individuals at highest risk for ASD than only considering the immediate family history of ASD. A comprehensive family history may be critical for a clinically relevant ASD risk prediction framework in the future.

BackgroundMetals exposures have important health effects in pregnancy. The maternal epigenome may be responsive to these exposures. We tested whether metals are associated with concurrent differential maternal whole blood DNA methylation.MethodsIn the Early Autism Risk Longitudinal Investigation (EARLI) cohort, we measured first or second trimester maternal blood metals concentrations (cadmium, lead, mercury, manganese, and selenium) in 215 participants using inductively coupled plasma mass spectrometry. DNA methylation in maternal whole blood was measured in the same specimens on the Illumina 450K array (201 participants). A subset sample of 97 women had both measures available for analysis, all of whom did not report smoking during pregnancy. Linear regression was used to test for site-specific associations between individual metals and DNA methylation, adjusting for cell type composition and confounding variables. Discovery gene ontology analysis was conducted on the top 1,000 sites associated with each metal to elucidate downstream pathways.ResultsIn multiple linear regression, we observed hypermethylation at 11 DNA methylation sites associated with lead (FDR q-value CYP24A1, ASCL2, FAT1, SNX31, NKX6-2, LRC4C, BMP7, HOXC11, PCDH7, ZSCAN18, and VIPR2. Lead associated sites were enriched (FDR q-value ARID2. Manganese associated sites were enriched for cellular metabolism pathways (FDR q-value0.86).DiscussionSingle DNA methylation sites associated with lead and manganese may be potential biomarkers of exposure or implicate downstream gene pathways. Future studies should replicate our findings to characterize potential toxicological mechanisms of trace metals through the maternal epigenome.

Background Pica, the repeated ingestion of nonfood items, can result in gastrointestinal (GI) outcomes. Children with autism spectrum disorder (ASD) and other developmental disabilities (DDs) are disproportionately affected by both pica and GI symptoms. Study of the inter-relationship between pica, GI symptoms, and ASD/DD is limited. Objective/Hypothesis We assessed associations between pica and GI symptoms in preschool-aged children with and without ASD and other (non-ASD) DDs in the Study to Explore Early Development. Methods Our sample included children with ASD (n = 1244), other DDs (n = 1593), and population (POP) controls (n = 1487). Data to define final case-control status, pica, and GI symptoms were from standardized developmental assessments/questionnaires. Prevalence ratios, adjusted for sociodemographic factors (aPRs), and 95% confidence intervals were derived from modified Poisson regression. Results Within each group (ASD, DD, POP) and for the total sample, pica was associated with vomiting (aPR for total sample 2.6 [1.7, 4.0]), diarrhea (1.8 [1.4, 2.2]), and loose stools (1.8 [1.4, 2.2]). In the DD group, pica was associated with constipation (1.4 [1.03, 1.9]) and pain on stooling (1.8 [1.2, 2.6]). In analyses of the subgroup without pica, increases in GI symptoms were still evident in the ASD and DD groups compared to POP group. Conclusion These findings highlight an important adverse effect of pica, GI symptoms, in children with and without ASD and DDs; nonetheless, pica does not fully explain the increased risk for GI symptoms among children with ASD and DDs. These findings inform the specialized healthcare needs of children with ASD and other DDs.

The epigenetic effects of individual environmental toxicants in tobacco remain largely unexplored. Cadmium (Cd) has been associated with smoking-related health effects, and its concentration in tobacco smoke is higher in comparison with other metals. We studied the association of Cd and smoking exposures with human blood DNA methylation (DNAm) profiles. We also evaluated the implication of findings to relevant methylation pathways and the potential contribution of Cd exposure from smoking to explain the association between smoking and site-specific DNAm. We conducted an epigenome-wide association study of urine Cd and self-reported smoking (current and former vs. never, and cumulative smoking dose) with blood DNAm in 790,026 CpGs (methylation sites) measured with the Illumina Infinium Human MethylationEPIC (Illumina Inc.) platform in 2,325 adults 45-74 years of age who participated in the Strong Heart Study in 1989-1991. In a mediation analysis, we estimated the amount of change in DNAm associated with smoking that can be independently attributed to increases in urine Cd concentrations from smoking. We also conducted enrichment analyses and in silico protein-protein interaction networks to explore the biological relevance of the findings. At a false discovery rate (FDR)-corrected level of 0.05, we found 6 differentially methylated positions (DMPs) for Cd; 288 and 17, respectively, for current and former smoking status; and 77 for cigarette pack-years. Enrichment analyses of these DMPs displayed enrichment of 58 and 6 Gene Ontology and Kyoto Encyclopedia of Genes and Genomes gene sets, respectively, including biological pathways for cancer and cardiovascular disease. In in silico protein-to-protein networks, we observed key proteins in DNAm pathways directly and indirectly connected to Cd- and smoking-DMPs. Among DMPs that were significant for both Cd and current smoking (annotated to PRSS23, AHRR, F2RL3, RARA, and 2q37.1), we found statistically significant contributions of Cd to smoking-related DNAm. Beyond replicating well-known smoking epigenetic signatures, we found novel DMPs related to smoking. Moreover, increases in smoking-related Cd exposure were associated with differential DNAm. Our integrative analysis supports a biological link for Cd and smoking-associated health effects, including the possibility that Cd is partly responsible for smoking toxicity through epigenetic changes. https://doi.org/10.1289/EHP6345. This work was supported by grants by the National Heart, Lung, and Blood Institute (NHLBI) (under contract numbers 75N92019D00027, 75N92019D00028, 75N92019D00029, & 75N92019D00030) and previous grants (R01HL090863, R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and cooperative agreements U01HL41642, U01HL41652, U01HL41654, U01HL65520, and U01HL65521), by the National Institute of Health Sciences (R01ES021367, R01ES025216, P42ES010349, P30ES009089), by the Spanish Funds for Research In Health Sciences, Carlos III Health Institute, co-funded by European Regional Development Fund (CP12/03080 and PI15/00071), by Chilean CONICYT/FONDECYT-POSTDOCTORADO Nº3180486 (A.L.R.-C) and a fellowship from “La Caixa” Foundation (ID 100010434). The fellowship code is “LCF/BQ/DR19/11740016.” Sí