Associations of urinary polycyclic aromatic hydrocarbon (PAH) metabolites and their mixture with thyroid hormone concentration during pregnancy in the LIFECODES cohort: A repeated measures study.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are endocrine disruptors resulting from incomplete combustion. Pregnancy represents a particularly vulnerable period to such exposures, given the significant influence of hormone physiology on fetal growth and pregnancy outcomes. Maternal thyroid hormones play crucial roles in fetal development and pregnancy outcomes. However, limited studies have examined gestational PAH exposure and maternal thyroid hormones during pregnancy. METHODS: Our study included 439 women enrolled in the LIFECODES birth cohort in Boston, aiming to explore the relationship between urinary PAH metabolites and thyroid hormones throughout pregnancy. Urine samples for PAH metabolite analysis and plasma samples for thyroid hormone were measured up to four visits throughout gestation. Single pollutant analyses employed linear mixed effect models to investigate individual associations between each PAH metabolite and thyroid hormone concentration. Sensitivity analyses were conducted to assess potential susceptibility windows and fetal-sex-specific effects of PAH exposure. Mixture analyses utilized quantile g-computation to evaluate the collective impact of eight PAH metabolites on thyroid hormone concentrations. Additionally, Bayesian kernel machine regression (BKMR) was employed to explore potential non-linear associations and interactions between PAH metabolites. Subject-specific random intercepts were incorporated to address intra-individual correlation of serial measurements over time in both single pollutant and mixture analyses. RESULTS: Our findings revealed positive trends in associations between PAH metabolites and thyroid hormones, both individually and collectively as a mixture. Sensitivity analyses indicated that these associations were influenced by the study visit and fetal sex. Mixture analyses suggested non-linear relationships and interactions between different PAH exposures. CONCLUSIONS: This comprehensive investigation underscores the critical importance of understanding the impact of PAH exposures on thyroid hormone physiology during pregnancy. The findings highlight the intricate interplay between environmental pollutants and human pregnancy physiology, emphasizing the need for targeted interventions and public health policies to mitigate adverse outcomes associated with prenatal PAH exposure.

Prenatal per- and polyfluoroalkyl substances (PFAS) and maternal oxidative stress: Evidence from the LIFECODES study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals linked to adverse pregnancy outcomes. Although their underlying biological mechanisms are not fully understood, evidence suggests PFAS may disrupt endocrine functions and contribute to oxidative stress (OS) and inflammation. OBJECTIVE: We examined associations between early pregnancy PFAS exposure and OS biomarkers, exploring potential effect modifications by fetal sex and maternal race. METHODS: We used data from 469 LIFECODES participants with measured plasma PFAS (median 10 weeks gestation) and repeated measures (median 10, 18, 26, and 35 weeks gestation) of urinary OS biomarkers [8-iso-prostaglandin-F2α (8-isoprostane) and 8-hydroxydeoxyguanosine (8-OHdG)]. Protein damage biomarkers (chlorotyrosine, dityrosine, and nitrotyrosine) were additionally measured in plasma from a subset (N = 167) during the third visit. Associations between each PFAS and OS biomarkers were examined using linear mixed-effects models and multivariable linear regressions, adjusting for potential confounders, including maternal age, race, education level, pre-pregnancy BMI, insurance status, and parity. Effect modifications were evaluated by including an interaction term between each PFAS and fetal sex or maternal race in the models. RESULTS: We observed significant positive associations between PFOS and 8-isoprostane, with a 9.68% increase in 8-isoprostane levels (95% CI: 0.10%, 20.18%) per interquartile range increase in PFOS. In contrast, PFUA was negatively associated [9.32% (95% CI: -17.68%, -0.11%)], while there were suggestive positive associations for MPAH and PFOA with 8-isoprostane. The associations of several PFAS with 8-OHdG varied by fetal sex, showing generally positive trends in women who delivered females, but negative or null in those who delivered males. No significant effect modification by maternal race was observed. CONCLUSIONS: This study provides evidence linking PFAS exposure to OS during pregnancy, with potential sex-specific effects of certain PFAS on 8-OHdG. Further research should explore additional OS/inflammatory biomarkers and assess the modifying effects of dietary and behavioral patterns across diverse populations.

Prenatal per- and polyfluoroalkyl substances (PFAS) exposure in relation to preterm birth subtypes and size-for-gestational age in the LIFECODES cohort 2006-2008.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals widely used in consumer and industrial products. Numerous studies have linked prenatal PFAS exposures to increased risks of adverse pregnancy outcomes such as preterm birth (PTB) and small-for-gestational age (SGA).However, limited evidence is available for the effects of PFAS on PTB subtypes and large-for-gestational age (LGA). OBJECTIVE: To examine the associations of PFAS with PTB [overall, placental (pPTB), spontaneous (sPTB)], BW Z-score, and size-for-gestational age (SGA, LGA). METHODS: Our nested case-control study included 128 preterm cases and 373 term controls from the LIFECODES cohort between 2006 and 2008 (n = 501). Plasma concentrations of nine PFAS were measured in early pregnancy samples. Logistic regression was used to assess individual PFAS-birth outcome associations, while Bayesian Kernel Machine Regression (BKMR) was used to evaluate the joint effects of all PFAS. Effect modification by fetal sex was examined, and stratified analyses were conducted to obtain fetal sex-specific estimates. RESULTS: Compared to term births, the odds of pPTB were higher from an interquartile range increase in perfluorodecanoic acid (PFDA) (OR = 1.60, 95% CI: 1.00-2.56), perfluorononanoic acid (PFNA) (OR = 1.67, 95% CI: 1.06-2.61), and perfluoroundecanoic acid (PFUA) (OR = 1.77, 95% CI: 1.00-3.12), with stronger associations observed in women who delivered males. BKMR analysis identified PFNA as the most important PFAS responsible for pPTB (conditional PIP = 0.78), with increasing ORs at higher percentiles of PFAS mixture. For LGA, positive associations were observed with PFDA and perfluorooctanoic acid in females only, and with PFUA in males only. BKMR analysis showed increasing, but null effects of PFAS mixture on LGA. CONCLUSIONS: The effect of prenatal exposure to single and multiple PFAS on PTB and LGA depended on fetal sex. Future studies should strongly consider examining PTB subtypes and sex-specific effects of PFAS on pregnancy outcomes.

Meta-analysis of animal studies applied to short-term inhalation exposure levels of hazardous chemicals.

For short-term chemical inhalation exposures to hazardous chemicals, the incidence of a health effect in biological testing usually conforms to a general linear model with a probit link function dependent on inhalant concentration C and the duration of exposure t. The National Academy's Acute Exposure Guideline Levels (AEGLs) Committee relies on these models when establishing AEGLs. Threshold concentrations at AEGL durations are established by the toxic load equation Cn x t = constant, which toxic load exponent n (TLE or n-value) directly follows from the bivariate probit model. When multiple probit datasets are available, the AEGL Committee routinely pools studies' incidence data. Such meta-analytical models are valid only when the pooled data are homogeneous, with similar sensitivities and equivalent responses to exposure concentrations and durations. In the present study, the homogeneity of datasets meta-analyzed by the AEGL Committee was examined, finding that 70% of datasets pooled by the AEGL Committee are heterogeneous. In these instances, data pooling leads to a statistically invalid model and TLE estimate, potentially resulting in under- or over-estimated inhalation guidance levels. When data pooling is inappropriate, other meta-analysis options include categorical regression, fixed-effect and random-effects models, or even designation of a key study based on scientific judgement. In the present work, options of TLE meta-analysis are summarized in a decision tree contingent on statistical testing.