Faculty Bibliography

BACKGROUND:Evidence suggests prenatal phthalate exposure adversely affects children's behavior. However, epidemiological studies on alternative plasticizers remain scarce. This study investigated associations of gestational exposure to phthalates and alternative plasticizers with internalizing and externalizing behaviors in children aged 1.5-5 years. METHODS:The study included 2617 mother-child dyads from 13 Environmental influences on Child Health Outcomes (ECHO) cohorts. Maternal urine samples, primarily collected mid- to late-pregnancy, were analyzed for 27 phthalate metabolites and 6 alternative plasticizer metabolites. Based on detection frequency, metabolite concentrations were modeled either continuously or categorically (Group 1: non-detectable, 2: lower detectable, 3: higher detectable). Covariate-adjusted associations between individual metabolite concentrations and internalizing and externalizing T-scores on the Child Behavior Checklist for Ages 1½-5 were estimated using linear mixed-effects models. Effect modification by child sex was also examined. RESULTS:for MHxP Group 3 = 1.23, 95% CI: 0.35, 2.12). We observed no robust associations between phthalate metabolites and internalizing T-scores, nor between cyclohexane-1,2-dicarboxylic acid mono carboxyisooctyl ester (DINCH) metabolites and any behavioral outcomes. Child sex modified associations between several metabolites and externalizing T-scores, although the direction of effect varied by metabolite. CONCLUSION/CONCLUSIONS:This large-scale study suggests that prenatal exposure to several phthalates, but not to the alternative plasticizer DINCH, may be associated with a small-to-modest increase in externalizing behaviors in young children.

INTRODUCTION/BACKGROUND:Secondhand exposure to e-cigarettes represents a potential population health risk given e-cigarette's prevalence and their unknown health effects, particularly among vulnerable populations such as pregnant people. OBJECTIVES/OBJECTIVE:To explore metabolomic differences between pregnant people exposed vs. not exposed to secondhand e-cigarette aeresols, to identify possible biomarkers of exposure and metabolic pathways perturbed by e-cigarettes. METHODS:Exposed participants (n = 19) from the NYU Children's Health and Environment Study were matched to unexposed participants (n = 57) at a 1:3 ratio on age, hospital of recruitment, and race/ethnicity. Early-pregnancy urine samples were analyzed via an untargeted metabolomics platform using reverse-phase liquid chromatography mass-spectrometry. Feature-exposure associations were estimated using conditional logistic regression to adjust for matching factors. A sensitivity analysis was conducted adjusting for secondhand tobacco exposure. RESULTS:Among features enriched in the exposed group were flavonoids and flavor-related compounds including homoeriodictyol and naringenin-7-O-beta-D-glucuronide, 3-acetomidocoumarin, and guaiacol pentosylglucoside; synthetic drugs such as the endocannabinoid AM1172 and the stimulant alpha-PVP; and metabolites associated with lipid metabolism, including 2,4-undecadiene-8,10-diynoic acid isobutylamide, palmitamide, glycerol trihexanoate, and tetradecyl phosphonate. Among features negatively associated with exposure were xanthines. CONCLUSION/CONCLUSIONS:This study is the first untargeted metabolomics study investigating metabolomic markers of e-cigarette exposure, including secondhand exposure, in a pregnant cohort. Despite this study's small size and exploratory nature, the results of this work suggest that flavoring components could be biomarkers for e-cigarette exposure, and that co-exposure to e-cigarettes and other drugs may be prevalent.

BACKGROUND/UNASSIGNED:Organophosphate ester flame retardants and plasticizers (OPEs) have myriad uses in industry and consumer products. Increasing human exposure to OPEs has raised concerns about their potential effects on child neurodevelopment during pregnancy. OBJECTIVE/UNASSIGNED:We investigated whether OPE urinary concentrations during pregnancy were associated with child autism-related outcomes. METHODS/UNASSIGNED:We included 4159 mother-child pairs from 15 cohorts in the NIH Environmental influences on Child Health Outcomes (ECHO) Consortium, with children born from 2006-2020 (median age [interquartile range]: 6 [4,10] years). Nine OPE biomarkers were measured in urine samples collected mid- to late pregnancy. Dilution-adjusted biomarkers were modeled continuously, categorically (high [> median], moderate [≤ median], non-detect), or as detect/non-detect depending on their detection frequency. We assessed child autism-related traits via a) parent report on the Social Responsiveness Scale (SRS) and b) clinical autism diagnosis. We examined associations of OPEs with child outcomes, including modification by child sex, using generalized estimating equations to account for clustering by ECHO cohort. RESULTS/UNASSIGNED:Compared with non-detectable concentrations, high exposure to bis(butoxyethyl) phosphate (BBOEP) was associated with higher autistic trait scores (adj-β 0.97, 95% confidence interval [CI]: 0.42, 1.52) and greater odds of autism diagnosis (adjusted odds ratio [adj-OR]: 1.27, 95% CI: 1.07, 1.50). Bis(1-chloro-2-propyl) phosphate (BCPP) showed associations with autistic trait scores (BCPP adj-β for high exposure vs. non-detect: 0.34, 95% CI: -0.46, 1.13; BCPP adj-β for moderate exposure vs. non-detect: 0.72, 95% CI: 0.24, 1.20). High exposure to bis(2-chloroethyl) phosphate (BCETP) was associated with lower odds of autism diagnosis (adj-OR: 0.76, 95% CI: 0.60, 0.95). Other OPEs showed no associations in adjusted models. Associations between BBOEP and higher autistic trait scores were stronger in males than females. DISCUSSION/UNASSIGNED:Prenatal exposure to OPEs, specifically BCPP and BBOEP, may be associated with higher risk of autism diagnosis and related traits in childhood. https://doi.org/10.1289/EHP16177.

BACKGROUND/UNASSIGNED:The relationship between prenatal exposure to low-level air pollution and child autism spectrum disorder (ASD) is unclear. OBJECTIVE/UNASSIGNED:To examine associations of prenatal air pollution exposure with autism. METHODS/UNASSIGNED:quantiles) using quantile regression and with ASD diagnosis using logistic regression. Models were run within census divisions, and coefficients were pooled in a meta-analysis. RESULTS/UNASSIGNED:also was associated with ASD. DISCUSSION/UNASSIGNED:Associations with ASD outcomes were present even at low levels of air pollutants. https://doi.org/10.1289/EHP16675.

BACKGROUND/UNASSIGNED:Maternal sustained smoking during pregnancy is associated with thousands of differentially methylated CpGs in newborns, but impacts of other prenatal tobacco smoking exposures remain unclear. OBJECTIVE/UNASSIGNED:To identify differential DNA methylation in newborns from maternal sustained smoking and less studied prenatal smoking exposures (i.e., maternal exposure to secondhand smoke [SHS] exposure during pregnancy, maternal quitting before pregnancy, paternal smoking around conception, paternal quitting before pregnancy). METHODS/UNASSIGNED:We conducted a large meta-analysis of prenatal tobacco smoking exposures and epigenome-wide newborn blood DNA methylation through the Pregnancy And Childhood Epigenetics Consortium (PACE). Across 19 cohorts, 11,175 parent-newborn pairs contributed information on at least one prenatal smoking exposure, mostly from questionnaires. Maternal blood or urine cotinine measurements, available in a few studies, provided objective data on maternal SHS and smoking during pregnancy. Primary analyses used Illumina450K methylation data; secondary analyses in 5 cohorts examined CpGs unique to the EPIC array. RESULTS/UNASSIGNED:) was associated with paternal former smoking. Forty-one novel genes were identified using maternal cotinine measurements compared to questionnaire. In EPIC unique analyses (n=3,415), differential methylation was observed with maternal sustained smoking (211 CpGs), maternal SHS (5 CpGs), and paternal former smoking (4 CpGs). Smoking-associated CpGs in blood were strongly enriched for functional elements across multiple tissues. CONCLUSIONS/UNASSIGNED:Maternal sustained smoking has the largest impact on newborn DNA methylation, suggesting a strong influence of the intrauterine environment. We observed minimal impacts for less studied exposures including SHS, maternal former smoking and paternal smoking. https://doi.org/10.1289/EHP16303.

Polycystic ovarian syndrome (PCOS) is a common female endocrinologic condition that affects both the metabolic and reproductive systems and is the most frequent cause of anovulatory infertility. It is also associated with a range of psychiatric outcomes in individuals, including bulimia nervosa, schizophrenia, bipolar disorder, depression, anxiety, and personality disorders. At the same time, evidence suggests that hyperandrogenism, the characteristic trait of PCOS, may impair fetal neurodevelopment. Epidemiological studies have linked maternal PCOS with a variety of behavioral and psychiatric conditions in offspring including autism spectrum disorder and attention deficit hyperactivity disorder. In this review, we explore evidence for potential underlying biological mechanisms that might explain these observed associations, discuss the complex interplay between genetics and various environmental factors across generations, and highlight avenues for future research.

Humans are widely exposed to synthetic chemicals, especially via food. The types of chemical contaminants in food (including food contact chemicals) are diverse, and many of these are known to be hazardous, with mounting evidence that some contribute to noncommunicable diseases. The increasing consumption of ultra-processed foods, which contain synthetic chemicals, also contributes to adverse health. If the chemical contamination of foods were better characterized, then this issue would likely receive more attention as an important opportunity for disease prevention. In this Review, we discuss types and sources of synthetic food contaminants, focusing on food contact chemicals and their presence in ultra-processed foods. We outline future research needs and highlight possible responses at different food system levels. A sustainable transition of the food system must address the health impacts of synthetic chemicals in food; we discuss existing solutions that do justice to the complexity of the issue while avoiding regrettable substitutions and rebound effects.

UNLABELLED:Exposures to phthalates and synthetic phenols are common among expectant mothers in the US. Previous studies on the neurotoxicity of these compounds have primarily assessed the effects of individual compounds on child behavior, but have not assessed potential combined effects of these substances. We assessed associations between prenatal exposure to a mixture of phthalates and phenols with behavioral problems among preschool-age children participating in the Environmental influences on Child Health Outcome (ECHO) Program. The study sample included 878 mother-child pairs from three cohorts with data on urinary concentrations of 10 phenols and 11 phthalate metabolites during pregnancy, along with caregiver reported Child Behavioral Checklist Ages 1½ to 5 (CBCL) data. Using covariate-adjusted weighted quantile sum (WQS) regression, we estimated associations between the phenol - phthalate mixture and CBCL behavioral scales T-scores. We fitted additional models stratified by sex due to previous reports of sex-specific associations. No statistically significant associations were observed in the overall sample when both male and female children were combined. However, in males, a quintile increase in the WQS index was associated with a 0.04 (95% CI: 0.00; 0.08) higher T-score of externalizing problems. The major contributors to this mixture effect were butylparaben (with a weight of 21%), benzophenone-3 (15%) and MCNP (11%). Conversely, in females, significant negative associations were observed between the WQS index with the total behavioral problems scale (beta = −0.05, 95% CI: −0.09; −0.01), externalizing problems (beta = −0.06, 95% CI = −0.10; −0.02) and internalizing problems (beta = −0.04, 95% CI: −0.08; −0.00). CONCLUSION::Our findings suggest that exposure to synthetic phenols and phthalate metabolite mixtures during pregnancy may impact childhood externalizing behavior with distinct associations in males and females. These findings contribute to the existing evidence on the combined effects of these compounds during development, emphasizing the need for further research on the combined effects of these mixtures.

IMPORTANCE/UNASSIGNED:Identifying atypical body mass index (BMI) trajectories in children and understanding associated, modifiable early-life factors may help prevent childhood obesity. OBJECTIVE/UNASSIGNED:To characterize multiphase BMI trajectories in children and identify associated modifiable early-life factors. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study included longitudinal data obtained from January 1997 to June 2024, from the Environmental influences on Child Health Outcomes (ECHO) cohort, which included children aged 1 to 9 years with 4 or more weight and height assessments. Analyses were conducted from January to June 2024. EXPOSURES/UNASSIGNED:Prenatal exposure to substances and stress (smoking, alcohol, depression, anxiety), maternal characteristics (prepregnancy BMI, gestational weight gain), child characteristics (preterm birth, birth weight, breastfeeding), and demographic covariates. MAIN OUTCOMES AND MEASURES/UNASSIGNED:BMI (calculated as weight in kilograms divided by length in meters squared for children aged 1 and 2 years and as weight in kilograms divided by height in meters squared for children older than 2 years) obtained using medical records, staff measurements, caregiver reports, or remote study measures. The analysis was conducted using a multiphase latent growth mixture model. RESULTS/UNASSIGNED:This study included 9483 children (4925 boys [51.9%]). Two distinct 2-phase BMI patterns were identified: typical and atypical. The typical group (n = 8477 [89.4%]) showed linear decreases in BMI (b2, -0.23 [95% CI, -0.24 to -0.22]), with the lowest BMI at age 6 years (95% CI, 5.94-6.11), followed by linear increases from 6 to 9 years (slope difference [b4 - b2], 0.81 [95% CI, 0.76-0.86]; mean BMI at 9 years: 17.33). The atypical group (n = 1006 [10.6%]) showed a stable BMI from ages 1 to 3.5 years (b6, 0.06 [95% CI, -0.04 to 0.15]), followed by rapid linear increases from ages 3.5 to 9 years (slope difference [b8 - b6], 1.44 [95% CI, 1.34-1.55]). At age 9 years, this group reached a mean BMI (26.2) that exceeded the 99th percentile. Prenatal smoking, high prepregnancy BMI, high gestational weight gain, and high birth weight were key risk factors for the atypical trajectory. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cohort study of children in the ECHO cohort, analyses identified children on the path to obesity as early as age 3.5 years. Modifiable factors could be targeted for early prevention and intervention programs aimed at reducing childhood obesity.

Environmental exposures often exhibit temporal variability, prompting extensive research to understand their dynamic impacts on human health. There has been a growing interest in studying time-dependent exposure mixtures beyond a single exposure. However, current analytic methods typically assess each exposure individually or assume an additive relationship. This paper aims to fill the gap in method development for evaluating the joint effects of multiple time-dependent exposures on a scalar outcome. We introduce a dynamic single-index scalar-on-function model to characterize the exposure mixture's time-varying effect through a non-parametric bivariate exposure-time-outcome surface function. Utilizing B-spline tensor product bases to approximate the surface function, we propose a profiling algorithm for model estimation and establish large-sample properties for the resulting single-index estimators. In addition, we introduce a non-parametric hypothesis testing procedure to determine whether the surface function varies over time at each fixed mixture level and a model averaging solution to circumvent the issue of knot selection for spline approximations. The performance of our proposed methods is examined through extensive simulations and further illustrated using real-world applications.