Abstract
BACKGROUND: The exposome is a novel research paradigm offering promise for understanding the complexity of human exposures, including endocrine-disrupting chemicals (EDCs) and pregnancy outcomes. The physiologically active state of pregnancy requires understanding temporal changes in EDCs to better inform the application of the exposome research paradigm and serve as the impetus for study. METHODS: We randomly selected 50 healthy pregnant women with uncomplicated pregnancies from a pregnancy cohort who had available serum/urine samples in each trimester for measuring 144 persistent and 48 nonpersistent EDCs. We used unsupervised machine-learning techniques capable of handling hierarchical clustering of exposures to identify EDC patterns across pregnancy, and linear mixed-effects modeling with false-discovery rate correction to identify those that change over pregnancy trimesters. We estimated the percent variation in chemical concentrations accounted for by time (pregnancy trimester) using Akaike Information Criterion-based R methods. RESULTS: Four chemical clusters comprising 80 compounds, of which six consistently increased, 63 consistently decreased, and 11 reflected inconsistent patterns over pregnancy. Overall, concentrations tended to decrease over pregnancy for persistent EDCs; a reverse pattern was seen for many nonpersistent chemicals. Explained variance was highest for five persistent chemicals: polybrominated diphenyl ethers #191 (51%) and #126 (47%), hexachlorobenzene (46%), p,p'-dichloro-diphenyl-dichloroethylene (46%), and o,p'-dichloro-diphenyl-dichloroethane (36%). CONCLUSIONS: Concentrations of many EDCs are not stable across pregnancy and reflect varying patterns depending on their persistency underscoring the importance of timed biospecimen collection. Analytic techniques are available for assessing temporal patterns of EDCs during pregnancy apart from physiologic changes.