PROJECT SUMMARY/ABSTRACT Many epidemiological investigations have associated exposure to traffic-derived air pollution from motor vehicles, air toxins from industry, and other environmental toxins with measures of poor birth outcomes consisting of preeclampsia (PE), preterm birth (PTB) and intra-uterine growth restriction (IUGR). These conditions, which collectively constitute ischemic placental disease, correlate strongly with infant morbidity and a host of adult diseases, ranging from coronary artery disease to cancer. Although it is widely believed that the pathophysiological mechanisms leading to complications of ischemic placental disease and placental insufficiency have similar biological origins, starting as early as defective placental implantation, to date there are no predictive studies that prospectively examine placental function. Thus, non-invasive assessment and prediction of normalcy versus aberrancy of placental function are lacking. Therefore, the overarching objective of this proposal is to develop and evaluate a suite of exosomal micro-transcriptomic and transcriptomic signatures (predictor) for predicting placental insufficiency. Moreover, we seek to use these novel signatures to assess the impact of environmental pollution exposure on placental aberrancy/insufficiency and related outcomes (PE, PTB and IUGR) (primary outcome). Our central hypothesis is that chronic exposure to environmental pollution, independent of socio-economic status (SES), increases the risk of placental insufficiency due to early gestational development of adverse placental function, and that these outcomes can be predicted non-invasively by developing maternal blood derived placental-enriched exosomal micro-transcriptomic and transcriptomic signatures. To test this hypothesis, our specific aims are to: AIM 1: Develop non-invasively in maternal blood, placenta-derived exosomal micro- transcriptomic and transcriptomic signatures that predict in-vivo placental function through all three trimesters. AIM 2: Use the micro-transcriptomic and transcriptomic data from Aim 1 to predict environmental pollution data collected during the course of this study. We will construct models to predict the environmental pollution state based on these signatures, so that they may be used as proxy of the pollution when this data is not available. AIM 3: Perform Epigenome Wide Association Studies using DNA methylation from placental tissues of the same cohort. We will use our Reduced Representation Bisulfite Sequencing to identify loci whose methylation is associated with placental insufficiency and environmental exposures. These studies will help identify genes confirmed by transcriptomic analysis that may be useful in future development of therapeutic interventions for women at high risk of placental insufficiency due to air pollution exposures. Identification of molecular signatures that predict the presence of environmental pollution and adverse pregnancy outcomes may beco...