Combined Exposure to Folate and Lead during Pregnancy and Autistic-Like Behaviors among Canadian Children from the MIREC Pregnancy and Birth Cohort.

BACKGROUND: Folic acid (FA) supplementation may attenuate the associations between gestational exposure to certain chemicals and autism or autistic-like behaviors, but to our knowledge, this has not been assessed for lead. OBJECTIVES: We examined whether the relationship between gestational blood-lead levels (BLLs) and autistic-like behaviors was modified by gestational plasma total folate concentrations, FA supplementation, and maternal methylenetetrahydrofolate reductase (MTHFR) 677C>T genotype. METHODS: We used data from the Maternal-Infant Research on Environmental Chemicals study (2008-2011), a Canadian pregnancy and birth cohort study. Childhood autistic-like behaviors were documented in 601 children 3-4 y of age with the Social Responsiveness Scale-2 (SRS-2), where higher scores denote more autistic-like behaviors. We measured BLLs and plasma total folate concentrations during the first and third trimesters of pregnancy. We also estimated gestational FA supplementation via surveys and genotyped the maternal MTHFR 677C>T single nucleotide polymorphism (SNP). We estimated the confounder-adjusted associations between log2-transformed BLLs and SRS-2 scores by two indicators of folate exposure and maternal MTHFR 677C>T genotype using linear regression. RESULTS: Third-trimester BLLs were associated with increased SRS-2 scores [ßadj=3.3; 95% confidence interval (CI): 1.1, 5.5] among participants with low (<10th percentile), third-trimester, plasma total folate concentrations, but BLL-SRS-2 associations were null (ßadj=-0.3; 95% CI: -1.2, 0.5) among those in the middle category (≥10th and <80th percentiles) (p-interaction <0.001). FA supplementation also attenuated these associations. Both folate indicators modified first-trimester BLL-SRS-2 associations, but to a lesser extent. Third-trimester BLL-SRS-2 associations were slightly stronger among participants who were homozygous for the T (minor) allele of the MTHFR 677C>T SNP (ßadj=0.9; 95% CI: -1.2, 3.1) than those without the T allele (ßadj=-0.3; 95% CI: -1.3, 0.7), but the difference was not statistically significant (p-interaction=0.28). DISCUSSION: Folate may modify the associations between gestational lead exposure and childhood autistic-like behaviors, suggesting that it mitigates the neurotoxic effects of prenatal lead exposure. https://doi.org/10.1289/EHP14479.

Gestational exposure to organochlorine compounds and metals and infant birth weight: effect modification by maternal hardships.

BACKGROUND: Gestational exposure to toxic environmental chemicals and maternal social hardships are individually associated with impaired fetal growth, but it is unclear whether the effects of environmental chemical exposure on infant birth weight are modified by maternal hardships. METHODS: We used data from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a pan-Canadian cohort of 1982 pregnant females enrolled between 2008 and 2011. We quantified eleven environmental chemical concentrations from two chemical classes - six organochlorine compounds (OCs) and five metals - that were detected in ≥ 70% of blood samples collected during the first trimester. We examined fetal growth using birth weight adjusted for gestational age and assessed nine maternal hardships by questionnaire. Each maternal hardship variable was dichotomized to indicate whether the females experienced the hardship. In our analysis, we used elastic net to select the environmental chemicals, maternal hardships, and 2-way interactions between maternal hardships and environmental chemicals that were most predictive of birth weight. Next, we obtained effect estimates using multiple linear regression, and plotted the relationships by hardship status for visual interpretation. RESULTS: Elastic net selected trans-nonachlor, lead, low educational status, racially minoritized background, and low supplemental folic acid intake. All were inversely associated with birth weight. Elastic net also selected interaction terms. Among those with increasing environmental chemical exposures and reported hardships, we observed stronger negative associations and a few positive associations. For example, every two-fold increase in lead concentrations was more strongly associated with reduced infant birth weight among participants with low educational status (ß = -100 g (g); 95% confidence interval (CI): -215, 16), than those with higher educational status (ß = -34 g; 95% CI: -63, -3). In contrast, every two-fold increase in mercury concentrations was associated with slightly higher birth weight among participants with low educational status (ß = 23 g; 95% CI: -25, 71) compared to those with higher educational status (ß = -9 g; 95% CI: -24, 6). CONCLUSIONS: Our findings suggest that maternal hardships can modify the associations of gestational exposure to some OCs and metals with infant birth weight.

Effects of gestational exposures to chemical mixtures on birth weight using Bayesian factor analysis in the Health Outcome and Measures of Environment (HOME) Study.

Studying the effects of gestational exposures to chemical mixtures on infant birth weight is inconclusive due to several challenges. One of the challenges is which statistical methods to rely on. Bayesian factor analysis (BFA), which has not been utilized for chemical mixtures, has advantages in variance reduction and model interpretation. METHODS: We analyzed data from a cohort of 384 pregnant women and their newborns using urinary biomarkers of phthalates, phenols, and organophosphate pesticides (OPs) and serum biomarkers of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), perfluoroalkyl substances (PFAS), and organochlorine pesticides (OCPs). We examined the association between exposure to chemical mixtures and birth weight using BFA and compared with multiple linear regression (MLR) and Bayesian kernel regression models (BKMR). RESULTS: For BFA, a 10-fold increase in the concentrations of PCB and PFAS mixtures was associated with an 81 g (95% confidence intervals [CI] = -132 to -31 g) and 57 g (95% CI = -105 to -10 g) reduction in birth weight, respectively. BKMR results confirmed the direction of effect. However, the 95% credible intervals all contained the null. For single-pollutant MLR, a 10-fold increases in the concentrations of multiple chemicals were associated with reduced birth weight, yet the 95% CI all contained the null. Variance inflation from MLR was apparent for models that adjusted for copollutants, resulting in less precise confidence intervals. CONCLUSION: We demonstrated the merits of BFA on mixture analysis in terms of precision and interpretation compared with MLR and BKMR. We also identified the association between exposure to PCBs and PFAS and lower birth weight.

Prenatal exposure to endocrine disrupting chemical mixtures and infant birth weight: A Bayesian analysis using kernel machine regression.

BACKGROUND: Pregnant women are regularly exposed to a multitude of endocrine disrupting chemicals (EDCs). EDC exposures, both individually and as mixtures, may affect fetal growth. The relationship of EDC mixtures with infant birth weight, however, remains poorly understood. We examined the relations between prenatal exposure to EDC mixtures and infant birth weight. METHODS: We used data from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a pan-Canadian cohort of 1857 pregnant women enrolled between 2008 and 2011. We quantified twenty-one chemical concentrations from five EDC classes, including organochlorine compounds (OCs), metals, perfluoroalkyl substances (PFAS), phenols and phthalate metabolites that were detected in >70% of urine or blood samples collected during the first trimester. In our primary analysis, we used Bayesian kernel machine regression (BKMR) models to assess variable importance, explore EDC mixture effects, and identify any interactions among EDCs. Our secondary analysis used traditional linear regression to compare the results with those of BKMR and to quantify the changes in mean birth weight in relation to prenatal EDC exposures. RESULTS: We found evidence that mixtures of OCs and metals were associated with monotonic decreases in mean birth weight across the whole range of exposure. trans-Nonachlor from the OC mixture and lead (Pb) from the metal mixture had the greatest impact on birth weight. Our linear regression analysis corroborated the BKMR results and found that a 2-fold increase in trans-nonachlor and Pb concentrations reduced mean birth weight by -38 g (95% confidence interval (CI): -67, -10) and -39 g (95% CI: -69, -9), respectively. A sex-specific association for OC mixture was observed among female infants. PFAS, phenols and phthalates were not associated with birth weight. No interactions were observed among the EDCs. CONCLUSIONS: Using BKMR, we observed that both OC and metal mixtures were associated with decreased birth weight in the MIREC Study. trans-Nonachlor from the OC mixture and Pb from the metal mixture contributed most to the adverse effects.

Associations of prenatal urinary phthalate exposure with preterm birth: the Maternal-Infant Research on Environmental Chemicals (MIREC) Study.

OBJECTIVES: To examine the relation between prenatal urinary phthalate metabolite concentrations and preterm birth (PTB). METHODS: The data were drawn from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a pan-Canadian cohort of 1857 pregnant women enrolled between 2008 and 2011. We quantified urinary concentrations of 7 phthalate metabolites that were detected in > 70% of urine samples collected during the first trimester. Gestational age was obtained from either the last menstrual period or early ultrasound. We used Cox proportional hazard models to examine the associations of urinary phthalate metabolite concentrations, plus the molar sum of di-2-ethylhexyl phthalate metabolites (∑DEHP), with time to delivery before 37 weeks of gestation. We also examined PTB by clinical presentation. PTBs presented with either spontaneous labour or premature rupture of the membrane were considered spontaneous PTB (sPTB). Additionally, we used multiple linear regression to model changes in mean gestational age in relation to phthalate exposure. RESULTS: We found no evidence of an association between first trimester phthalate metabolite concentrations and PTB among the MIREC study participants. For example, each 2-fold increase in any of the 7 phthalate concentrations or ∑DEHP was associated with hazard ratios (HRs) for PTB ranging from 0.95 to 1.07 with 95% confidence intervals including the null. An assessment of non-linear trends showed some evidence of non-monotonic dose-response relationships between phthalates and PTB. Furthermore, male infants exposed to MCPP showed higher sPTB risk compared with female infants. CONCLUSION: Phthalate exposure during early pregnancy is not clearly associated with the risk of PTB among this Canadian population.