Sterol metabolism includes the developmentally critical sex steroid hormones, bile acids, neurosteroids, andcholesterol metabolites of lipid membranes. Certain persistent organic pollutants, including polybrominateddiphenyl ethers (PBDEs), as well as high volume production chemicals, including phenols such as triclosan(TCS), are thought to interfere with steroid metabolism and action. Meconium, the first bowel movements of anewborn, begins accumulation in approximately the 12th week of gestation, and contains high sterol content.Thus, meconium provides a window into the prenatal metabolic environment during neurodevelopmentallyrelevant periods. This proposal will quantify differences in sterol metabolites from meconium in childrenenrolled in a prospective cohort of early events in neurodevelopment by levels of maternal exposure to PBDEsand major phenols. To deal with the complexity of exposure quantification, we will use a novel variation onpartial least squares (PLS) methods, incorporating assumptions of sparsity, non-negativity and biologicallyplausible structure. These additional modeling constraints will facilitate identification of the most likelybiomarkers of exposure response within the already acquired dataset of sterol metabolites. To extend therelevance of the putatively identified sterols, the structures of the biomarkers will be partially or fully elucidatedand targeted methods will be developed for future validation as potential biomarkers of exposure. We wiLLConduct this research in three specific aims as follows; Aim 1: Identify unknown chromatographic features withdifferential abundance by maternal exposure to PBDEs and phenols. Aim 2: Elucidate structuralcharacteristics of sterols identified as interesting in Aim 1. Aim 3: Examine the relationship of PBDE and phenolsubtypes with sterols characterized in aim 2 using a Bayesian mixture model. This innovative work willgenerate testable hypotheses for future research in the field of prenatal neurodevelopment.
Interagency Autism Coordinating Committee (IACC)
Autism Research Database (AFD)
