A Data-Driven Computational Framework for Assessing the Risk of Placental Exposure to Environmental Chemicals.

A computational framework based on placental gene networks was proposed in this work to improve the accuracy of the placental exposure risk assessment of environmental compounds. The framework quantitatively characterizes the ability of compounds to cross the placental barrier by systematically considering the interaction and pathway-level information on multiple placental transporters. As a result, probability scores were generated for 307 compounds crossing the placental barrier based on this framework. These scores were then used to categorize the compounds into different levels of transplacental transport range, creating a gradient partition. These probability scores not only facilitated a more intuitive understanding of a compound's ability to cross the placental barrier but also provided valuable information for predicting potential placental disruptors. Compounds with probability scores greater than 90% were considered to have significant transplacental transport potential, whereas those with probability scores less than 80% were classified as unlikely to cross the placental barrier. Furthermore, external validation set results showed that the probability score could accurately predict the compounds known to cross the placental barrier. In conclusion, the computational framework proposed in this study enhances the intuitive understanding of the ability of compounds to cross the placental barrier and opens up new avenues for assessing the placental exposure risk of compounds.

Assessment of Fetal Exposure and Elimination of Perfluoroalkyl and Polyfluoroalkyl Substances: New Evidence from Paired Serum, Placenta, and Meconium Samples.

Multiple pieces of evidence have shown that prenatal exposure to perfluoroalkyl and polyfluoroalkyl substances (PFASs) is closely related to adverse birth outcomes for infants. However, difficult access to human samples limits our understanding of PFASs transport and metabolism across the human placental barrier, as well as the accurate assessment of fetal PFASs exposure. Herein, we assess fetal exposure to 28 PFASs based on paired serum, placenta, and meconium samples. Overall, 21 PFASs were identified first to be exposed to the fetus prenatally and to be metabolized and excreted by the fetus. In meconium samples, 25 PFASs were detected, with perfluorooctane sulfonate and perfluorohexane sulfonic acid being the dominant congeners, suggesting the metabolism and excretion of PFASs through meconium. Perfluoroalkyl sulfonic acids might be more easily eliminated through the meconium than perfluorinated carboxylic acids. Importantly, based on molecular docking, MRP1, OATP2B1, ASCT1, and P-gp were identified as crucial transporters in the dynamic placental transfer of PFASs between the mother and the fetus. ATSC5p and PubchemFP679 were recognized as critical structural features that affect the metabolism and secretion of PFASs through meconium. With increasing carbon chain length, both the transplacental transfer efficiency and meconium excretion efficiency of PFASs showed a structure-dependent manner. This study reports, for the first time, that meconium, which is a noninvasive and stable biological matrix, can be strong evidence of prenatal PFASs exposure.