Scientific evidence in both humans and animal models suggests that prenatal, early life and potentially transgenerational environmental exposures can result in childhood health deficits and life-long consequences in subsequent generations. In particular, exposures to elevated ambient air pollution, regional and near- roadway pollutants, and heavy metals have been associated with respiratory and/or metabolic health outcomes in childhood. Much less is known about the effects of prenatal exposures on these outcomes, and virtually nothing is known about whether exposures during previous generations can affect respiratory and metabolic outcomes - illustrating critical gaps in scientific knowledge. Studies are just beginning to disentangle the effects of mixtures across the life course using novel biomarkers of exposure, biological mediators and innovative statistical methods. We will address these critical gaps in a new proposal entitled ?Life course Approach to Developmental Repercussions of Environmental Agents on MEtabolic and Respiratory health (LA DREAMERs).?The major goal of this proposal is to take a transgenerational life course approach to studying the contribution of the environment to the developmental origins of childhood and emerging adult respiratory and metabolic health. LA DREAMERs will combine 8931 subjects from two population- based longitudinal cohorts of children that cover the prenatal to early adulthood periods of exposure- the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) and Children's Health Study (CHS) cohorts. The proposed study addresses the following key questions in the field: 1) Do prenatal and early childhood environmental exposures alter childhood and emergent adult respiratory and metabolic health? If so, are there critical periods of exposure across the lifecourse? 2) What is the role of altered immune functions in the underlying biological mechanisms? 3) Will more precise exposure assessment for ambient air pollutants through application of a national spatiotemporal model or development of biomarkers in neonatal dried blood spots and cord blood allow critical components of the mixture to be identified? 4) Do prenatal environmental exposures induce transgenerational epigenetic alterations that help explain increased risk of disease? 5) Can innovative statistical approaches untangle the effects of exposure mixtures on multiple health outcomes? We will address these important questions by focusing on the health effects of ambient and near-roadway air pollution, metals (As, Pb, Cd, Hg), and novel albumin adducts (e.g. reactive electrophiles such as oxidized polyaromatic hydrocarbons and quinones) in a series of three distinct research projects focused on respiratory health (ECHO Focus area #1), metabolic health (ECHO Focus area #2) and statistical methods. By combining MADRES and CHS, we are uniquely positioned to answer environmental health questions pertaining to respiratory and metabolic health using a transgenerational life course approach, spanning from pregnancy through 22 years of age and across generations.
Little is known about the effects of prenatal environmental exposures on respiratory and metabolic health outcomes, and virtually nothing is known about whether exposures during previous generations can affect these outcomes. We propose to address these critical gaps in knowledge by taking a transgenerational lifecourse approach to studying the health effects of ambient and near roadway air pollution, heavy metals, and novel human serum albumin adducts on childhood and emerging adult respiratory and metabolic health. By combining 8931 subjects from two complementary population-based longitudinal cohorts of children, we will address key questions of multiple exposures, timing of exposures, and underlying biological pathways in the context of developmental origins of disease.
| Alderete, T L; Song, A Y; Bastain, T et al. (2018) Prenatal traffic-related air pollution exposures, cord blood adipokines and infant weight. Pediatr Obes 13:348-356 |
| Li, Lianfa; Lurmann, Fred; Habre, Rima et al. (2017) Constrained Mixed-Effect Models with Ensemble Learning for Prediction of Nitrogen Oxides Concentrations at High Spatiotemporal Resolution. Environ Sci Technol 51:9920-9929 |
