Exposures to phthalates, parabens, and other phenols are often correlated due to their ubiquitous use in personal care products and plastics. Examining these compounds as a complex mixture may clarify inconsistent relationships between individual chemicals and childhood adiposity. Using data from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) study, a longitudinal cohort of children in Salinas Valley, California (n = 309), we examined biomarkers of 11 phthalate metabolites and 9 phenols, including several parabens and bisphenol A, measured in maternal urine at two time points during pregnancy. We measured child height and weight at age five to calculate the body mass index (BMI) z-scores and overweight/obesity status. The association between prenatal urinary concentrations of biomarkers with the childhood BMI z-score and overweight/obesity status was analyzed using single-pollutant models and two mixture methods: Bayesian hierarchical modeling (BMH) and Bayesian kernel machine regression (BKMR). Urinary concentrations of monoethyl phthalate, monocarboxy-isononly phthalate (metabolites of diethyl phthalate and di-isodecyl phthalate, respectively), and propylparaben were consistently associated with an increased BMI z-score and overweight/obesity status across all modeling approaches. Higher prenatal exposures to the cumulative biomarker mixture also trended with greater childhood adiposity. These results, robust across two methods that control for co-pollutant confounding, suggest that prenatal exposure to certain phthalates and parabens may increase the risk for obesity in early childhood.

Associations between maternal immune dysregulation (including autoimmunity and skewed cytokine/chemokine profiles) and offspring neurodevelopmental disorders such as autism have been reported. In maternal autoantibody-related autism, specific maternally derived autoantibodies can access the fetal compartment to target eight proteins critical for neurodevelopment. We examined the relationship between maternal autoantibodies to the eight maternal autoantibody-related autism proteins and cytokine/chemokine profiles in the second trimester of pregnancy in mothers of children later diagnosed with autism and their neonates’ cytokine/chemokine profiles. Using banked maternal serum samples from 15 to 19 weeks of gestation from the Early Markers for Autism Study and corresponding banked newborn bloodspots, we identified three maternal/offspring groups based on maternal autoantibody status: (1) mothers with autoantibodies to one or more of the eight maternal autoantibody-related autismassociated proteins but not a maternal autoantibody-related autism-specific pattern, (2) mothers with a known maternal autoantibody-related autism pattern, and (3) mothers without autoantibodies to any of the eight maternal autoantibody-related autism proteins. Using a multiplex platform, we measured maternal second trimester and neonatal cytokine/chemokine levels. This combined analysis aimed to determine potential associations between maternal autoantibodies and the maternal and neonatal cytokine/chemokine profiles, each of which has been shown to have implications on offspring neurodevelopment independently.