Project Summary (2025-2030)

The burden of perinatal morbidity and mortality related to preterm birth (PTB) is astounding. Studies show that environmental exposures contribute to an increased susceptibility to PTB. Identification of the causative etiology of PTB is essential to improving global maternal and child health. During the prior funding period researchers have worked to investigate the mechanistic role underpinning the increased risk of PTB with exposures to polycyclic aromatic hydrocarbons (PAHs) during pregnancy. Researchers have reported that proximity to Superfund sites in Harris County is associated with increased levels of placental PAHs and increased preterm delivery. In this proposal researchers continue to delve into the placental alterations which occur by virtue of PAH exposure and lead to preterm delivery. The central hypothesis is that exposure to PAHs and other environmental chemicals at Superfund sites will alter the placental epigenome and disrupt functional gene expression. In order to investigate this, researchers have proposed three specific aims which leverage the research support cores as well as the Center’s data management and analysis core.

In Aim 1, the research team will utilize cutting edge methodologies to fully characterize epigenetic and transcriptomic changes in placenta cells with PAH treatment. The team will utilize RNA-seq, bisulfite-seq, RPPA and ATAC-seq to fully profile these molecular changes in trophoblasts. With input from the DMAC team, researchers will integrate these datasets using machine learning approaches in order to predict which epigenetic changes are associated with changes in specific gene expression networks that could lead to preterm delivery.

In Aim 2, the researchers propose a prospective study design where they will recruit subjects at delivery and collect placenta, maternal urine, maternal serum, cord serum and colostrum (i.e., breastmilk). With support from the Research Support Core, researchers will measure levels of 16 PAHs in these samples. They will utilize geostatistical modeling to integrate exposure data, residential address information and maternal and neonatal outcomes data to reveal associations between proximity to Superfund sites, exposures and maternal and neonatal outcomes. The researchers will investigate epigenetic changes in the placenta using RPPA. Of note, the subjects recruited as part of this project will be followed for six months to determine neonatal outcomes as part of the Role of cytochrome P450 (CYP)1A/1B1 enzymes in the potentiation of neonatal lung injury in newborn mice exposed prenatally to PAHs, and increased risk of premature infants to chronic lung disease (Project 3). In Project 3, longitudinal breastmilk samples will be collected and PAHs measured to determine exposures in neonatal life.

In the third and final aim, the research team will utilize unbiased LC-MS/MS and GC-MS/MS approaches in order to investigate which environmental contaminants from Superfund sites are associated with preterm delivery and which metabolic pathways in placenta are disrupted with these exposures. Exposure data will also be modeled using geostatistical methodologies in order to determine how exposures associate with proximity to Superfund sites.