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Background: This study investigated the association of prenatal and early childhood exposure to air pollution with epigenetic age acceleration (EAA) at six years of age using the Environment and Development of Children Cohort (EDC Cohort) Materials & methods: Air pollution, including particulate matter [< 2.5 µm (PM2.5) and < 10 µm (PM10) in an aerodynamic diameter], nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and sulfur dioxide (SO2) were estimated based on the residential address for two periods: 1) during the whole pregnancy, and 2) for one year before the follow-up in children at six years of age. The methylation levels in whole blood at six years of age were measured, and the methylation clocks, including Horvath’s clock, Horvath’s skin and blood clock, PedBE, and Wu’s clock, were estimated. Multivariate linear regression models were constructed to analyze the association between EAA and air pollutants. Results: A total of 76 children in EDC cohort were enrolled in this study. During the whole pregnancy, interquartile range (IQR) increases in exposure to PM2.5 (4.56 μg/m3) and CO (0.156 ppm) were associated with 0.406 years and 0.799 years of EAA (Horvath’s clock), respectively. An IQR increase in PM2.5 (4.76 μg/m3) for one year before the child was six years of age was associated with 0.509 years of EAA (Horvath’s clock) and 0.289 years of EAA (Wu’s clock). PM10 (4.30 μg/m3) and O3 (0.003 ppm) exposure in the period were also associated with EAA in Horvath’s clock (0.280 years) and EAA in Horvath’s skin and blood clock (0.163 years), respectively. Conclusion: We found that prenatal and childhood exposure to ambient air pollutants is associated with EAA among children. The results suggest that air pollution could induce excess biological aging even in prenatal and early life.

Background: Bisphenol A (BPA) is known as an obesogenic endocrine disruptor. Bisphenol S (BPS) and F (BPF) are substitutes that have recently replaced BPA. Objectives: To investigate the relationships of urinary bisphenols (BPA, BPS and BPF) with adiposity measurements (obesity, BMI z-score, and fat mass), serum adipokine levels (adiponectin and leptin), and adiponectin/leptin ratio (A/L ratio) in 6- and 8-year-old children. Methods: A total of 561 children who participated in the Environment and Development of Children cohort (482 and 516 children visited at age 6 and 8, respectively) at Seoul National University Children’s Hospital during 2015–2019 were included. Urinary BPA levels were log-transformed. BPS levels were categorized into three groups (non-detected, lower-half, and higher-half of detected), and BPF levels were classified into two groups (non-detected and detected). Results: The urinary BPS higher-half group had a higher BMI z-score (β = 0.160, P = 0.044), higher fat mass (β = 0.104, P < 0.001), lower adiponectin concentration (β =- 0.069, P < 0.001), higher leptin concentration (β = 0.360, P < 0.001), and lower A/L ratio (β =- 0.428, P < 0.001) compared with the non-detected group. The urinary BPF-detected group had a higher fat mass (β = 0.074, P < 0.001), lower adiponectin concentration (β =- 0.069, P < 0.001), higher leptin concentration (β = 0.360, P < 0.001), and lower A/L ratio (β =- 0.428, P < 0.001) compared with the non-detected group. The BPA levels showed no consistent associations with outcomes, except for isolated associations of BPA at age 6 with a higher BMI z-score at age 6 (P = 0.016) and leptin at age 8 (P = 0.021). Conclusions: Increased exposure to BPS and BPF is associated with higher fat mass and leptin concentration, lower serum adiponectin, and lower A/L ratio in children. These findings suggest potential adverse effects of BPA substitutes on adiposity and adipokines. No consistent association of BPA exposure with outcomes could be partly explained by the decreasing BPA levels over time.

Background: Bisphenol A (BPA) has been linked to attention-deficit/hyperactivity disorder (ADHD) symptoms, but the neurotoxic effects of bisphenol substitutes such as bisphenol F (BPF) and S (BPS) have not been well investigated. We investigated the associations between BPA, BPF, and BPS with ADHD symptoms at multiple time points in children. Methods: The levels of BPA (at ages 4, 6, and 8), BPF (at ages 6 and 8), and BPS (at ages 6 and 8) were measured in 619 children. Because of the low detection frequency of BPF and BPS levels, participants were divided into categories (97%), whereas BPF and BPS were less frequently detected (age 6: 17.5% for BPF and 42.0% for BPS; age 8: 51.6% for BPF and 73.3% for BPS). Doubling in BPA levels was associated with increased ARS scores by 4.7% (95% confidence intervals [CI]: 0.5, 9.2) at age 6. The association was greater with BPA levels higher than 3.0 μg/g creatinine (24.2% [95% CI: 15.5, 33.6] increase). The BPF ≥ LOD group had 10.8% (95% CI: 1.2, 21.4) higher ARS scores than the BPF

Background: Pyrethroid insecticides are commonly used in residential settings, and their use has increased rapidly. Although research has been scarce, they have been reported to be associated with impaired neurodevelopment. Moreover, susceptible exposure windows and the long-term effects of pyrethroids have not been investigated. We examined the association between pyrethroid exposure and attention-deficit/hyperactivity disorder (ADHD) symptoms over time, with exposure windows spanning from the prenatal period to school-age. Methods: Using 524 mother–child pairs, we measured urinary concentrations of 3-phenoxybenzoic acid (3-PBA), a major pyrethroid metabolite, and asked parents to fill-out the ADHD Rating Scale IV (ARS). We used Poisson regression to identify the susceptible periods of pyrethroid exposure, by correlating various 3-PBA exposure windows (prenatal, ages 2, 4, 6 and 8) with ADHD symptoms at ages 6 and 8. Results: Doubling of prenatal and age 2 3-PBA concentrations was associated with increased ADHD symptoms at age 6 (2.7% change, 95% confidence interval [CI]: 0.3, 5.2; 5.2% change [95% CI: 0.5, 10.2], respectively). The 3-PBA concentrations at age 4 and age 6 were linked with ADHD symptoms at age 8 (2.7% change [95% CI: 0.3, 5.3]; 3.3% change [95% CI: 0.2, 6.4], respectively). There were no clear sex-specific patterns in association. Discussion: Both prenatal and early-childhood exposure to 3-PBA were found to be associated with ADHD symptoms. Exposure during pregnancy, and at ages 2 to 6 were found to be susceptible periods for pyrethroid neurotoxicity at ages 6 and 8.

Background: Phthalates are synthetic chemicals with endocrine-disrupting properties. They are reportedly associated with various neurotoxic outcomes. Studies on exposure to phthalates and children’s autistic traits have shown inconsistent results with respect to sex and susceptible time periods. We investigated the association of phthalate exposure during the prenatal period and childhood with autistic traits over time using a birth cohort in South Korea. Methods: Five phthalate metabolites were measured during mid-term pregnancy and children's follow-up at ages of 4, 6, and 8 years among a total of 547 mother–child pairs. The social communication questionnaire (SCQ) was used to assess autistic traits of children at each time point. The relationship between phthalate metabolites and SCQ scores were analyzed by exposure windows and sex. Results: A 2.7 fold increase in di-(2-ethylhexyl) phthalate metabolite levels, mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) during pregnancy was associated with increased SCQ scores at 4 years by 8.5% (95% confidence intervals [CI]: 1.9%, 15.5%) and 7.4% (95% CI: 0.3%, 15.0%), respectively, but not at the age of 6 or 8 years. Moreover, MEHHP levels at ages of 4 and 8 years were associated with increased SCQ scores at 8 years by 9.9% (95% CI: 1.8%, 18.6%) and 9.6% (95% CI: 1.3%, 18.6%), respectively. Boys showed stronger associations between phthalate exposure and SCQ scores than girls. Conclusion: The study suggested different susceptible time windows of phthalate exposure: exposure during pregnancy is associated with autistic traits in young children, whereas exposure during early childhood years leads to autistic traits in school-aged children, particularly boys.

Background: Humans are exposed to a mixture of metals during their lifetime; however, evidence of neurotoxicity of such mixtures in critical time windows is still insufficient. We aimed to elucidate the associations of four metals mixture across multiple time points with children’s intelligence quotient (IQ) in a prospective cohort study. Methods: Prenatal exposure and exposure at age 4 and 6 years to four types of blood metals, namely lead, mercury, cadmium, and manganese were quantified in 502 pregnant women and their children who participated in the Environment and Development Cohort study. Children’ s IQ scores were assessed using the Wechsler Intelligence Scale at age 6. Bayesian kernel machine regression (BKMR), quantile g-computation models, and elastic net (ENET) models were used to assess the associations of their blood metals mixture with IQ scores. Results: Multivariate linear regression models indicated that postnatal blood manganese exposure at the age of 4 years was significantly negatively associated with children’s IQ [β = − 5.99, 95% confidence interval (CI): −11.37 to − 0.61]. In the multi-chemical BKMR and quantile g-computation model, statistically significant inverse associations were found between the mixture of prenatal and postnatal metals and children’s IQ score (Difference in children’ IQ per quartile increase: −2.83; 95% CI: −5.28, −0.38). Interestingly, we found that manganese levels at both age of 4 and 6 years were contributing factors to children’s IQ in the mixture models, namely, BKMR, quantile g-computation, and ENET models. Conclusions: Multi-pollutant mixtures of prenatal and postnatal exposures to four metals affected child IQ at 6 years of age. We found a relationship between manganese exposure at both age 4, and 6 years and children’s IQ. Additional studies are warranted to confirm these associations and to control the exposure to different metals during pregnancy and preschool childhood.

Background: The Mothers and Children's Environmental Health study (MOCEH) is a multi-centric prospective birth cohort study investigating effects of various environmental pollutants like heavy metals, endocrine disruptors, air pollutants, nutrition and lifestyle on birth outcomes, growth and development, health and disease of children. In this study, we report all the outcomes from the MOCEH study describing the different environmental pollutants affecting children’s health and disease. Methods: In MOCEH study, 1,751 pregnant women in their first trimester were recruited at 3 centers from 2006 to 2010 in South Korea. The children were followed from birth up to 6 years. Information on health outcomes of children including birth parameters, demographic characteristics, medical and child-rearing history, and nutritional status, were repeatedly obtained through the follow-ups by questionnaires administration, clinical evaluation, and biological specimen collection and measurements. Prenatal and postnatal measurement in biospecimen, i.e., lead, mercury, cadmium, manganese, 1-hydroxypyrene, 2-naphthol, malonadialdehyde, hippuric acid, bisphenol A and phthalate metabolites, and measurement in air samples, i.e., particulate matter, nitrogen dioxide, and total volatile organic compounds were performed. Results: The results show the adverse effect of prenatal exposure to heavy metals like mercury, lead and cadmium on children’s physical, cognitive and neurobehavioral development. Exposure to endocrine disruptors, air pollution, second hand smoke, and mother’s lifestyle during pregnancy affects children’s growth and development. We also identified specific window periods of exposure of pollutants significantly related to children’s health outcomes. Conclusion: The collective results from MOCEH study provide strong scientific evidence that exposures to prenatal and postnatal environmental pollutants have a negative effect on growth and development of children, which will be useful in implementing effective national policy to improve children’s environmental health. Keywords: Birth cohort, Children Environmental health, Environmental pollutants

Objectives: Epigenetic mechanisms have been suggested to play a role in the link between in utero exposure to bisphenol A (BPA) and pediatric obesity; however, there is little evidence regarding this mechanism in humans. We obtained data on obesity-associated CpG sites from a previous epigenome-wide association study, and then examined whether methylation at those CpG sites was influenced by prenatal BPA exposure. We then evaluated the relationship between CpG methylation status and body mass index (BMI) in a prospective children’s cohort at ages 2, 4, 6, and 8 years. Methods: Methylation profiles of 59 children were longitudinally analyzed at ages 2 and 6 years using the Infinium Human Methylation BeadChip. A total of 594 CpG sites known to be BMI or obesity-associated sites were tested for an association with prenatal BPA levels, categorized into low and high exposure groups based on the 80th percentile of maternal BPA levels (2.68 μg/g creatinine), followed by an analysis of the association between DNA methylation and BMI from ages 2–8. Results: There was a significant increase in the methylation levels of cg19196862 (IGF2R) in the high BPA group at age 2 years (p = 0.00030, false discovery rate corrected p

Background: Limited studies have investigated the association between prenatal and early childhood phthalate exposures and thyroid function among children. Objectives: To investigate the association between early life phthalate exposure and thyroid function among school-age children, considering both prenatal and early childhood exposures, using longitudinal data from an established prospective cohort. Methods: We measured urinary phthalate metabolite levels during pregnancy and at 2, 4, and 6 years of age and conducted thyroid function tests at 6 years of age. We assessed the associations between phthalate metabolite levels and thyroid function using linear regression and Bayesian kernel machine regression (BKMR) models (n = 492). Results: In linear regression models, a doubling of urinary mono-n-butyl phthalate (MnBP) levels, measured during pregnancy and at 4 years of age, was associated with lower thyroid-stimulating hormone (TSH) levels at 6 years of age (−5.0%, 95% confidence interval [CI]: −8.8%, −1.0% and −5.7%, 95% CI: −9.7%, −1.5%, respectively). A similar association was found between mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) levels at 4 years of age and TSH levels at 6 years of age (−5.5%, 95% CI: −9.7%, −1.1%). Urinary mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) (2.3%, 95% CI: 0.1%, 4.5%) and MEOHP levels at 2 years of age (2.2%, 95% CI: 0.1%, 4.4%) and mono-2-ethyl-5-carboxypentyl phthalate (1.4%, 95% CI: 0.1%, 2.7%) and mono-benzyl phthalate levels at 6 years of age (1.1%, 95% CI: 0.4%, 1.9%) were associated with higher triiodothyronine (T3) levels at 6 years of age. Urinary MnBP during pregnancy, MEHHP, MEOHP, and MnBP at 4 years of age were also associated with lower free thyroxine (fT4) × TSH. In BKMR models, urinary MnBP levels during pregnancy were associated with lower TSH levels and fT4 × TSH (both posterior inclusion probabilities: 0.99). Conclusions: Our findings suggest that early life phthalate exposure influences subsequent thyroid function. However, the results should be interpreted cautiously, because a single spot urine sample was used to quantify the phthalate exposures at each time point.

Objective: Sleep problems is the most common side effect of methylphenidate (MPH) treatment in ADHD youth and carry potential to negatively impact long-term self-regulatory functioning. This study aimed to examine whether applying machine learning approaches to pre-treatment demographic, clinical questionnaire, environmental, neuropsychological, genetic, and neuroimaging features can predict sleep side effects following MPH administration. Method: The present study included 83 ADHD subjects as a training dataset. The participants were enrolled in an 8-week, open-label trial of MPH. The Barkley Stimulant Side Effects Rating Scale was used to determine the presence/absence of sleep problems at the 2nd week of treatment. Prediction of sleep side effects were performed with step-wise addition of variables measured at baseline: demographics (age, gender, IQ, height/weight) and clinical variables (ADHD Rating Scale-IV (ADHD-RS) and Disruptive Behavior Disorder rating scale) at stage 1, neuropsychological test (continuous performance test (CPT), Stroop color word test) and genetic/environmental variables (dopamine and norepinephrine receptor gene (DAT1, DRD4, ADRA2A, and SLC6A2) polymorphisms, blood lead, and urine cotinine level) at stage 2, and structural connectivities of frontostriatal circuits at stage 3. Three different machine learning algorithms ((Logistic Ridge Regression (LR), support vector machine (SVM), J48) were used for data analysis. Robustness of classifier model was validated in the independent dataset of 36 ADHD subjects. Results: Classification accuracy of LR was 95.5% (area under receiver operating characteristic curve (AUC) 0.99), followed by SVM (91.0%, AUC 0.85) and J48 (90.0%, AUC 0.87) at stage 3 for predicting sleep problems. The inattention symptoms of ADHD-RS, CPT response time variability, the DAT1, ADRA2A DraI, and SLC6A2 A-3081T polymorphisms, and the structural connectivities between frontal and striatal brain regions were identified as the most differentiating subset of features. Validation analysis achieved accuracy of 86.1% (AUC 0.92) at stage 3 with J48. Conclusions: Our results provide preliminary support to the combination of multimodal classifier, in particular, neuroimaging features, as an informative method that can assist in predicting MPH side effects in ADHD.