Abstract Neurodegenerative disorders, including Alzheimer?s disease (AD), other dementias, and Parkinson?s disease (PD), are major health concerns for older adults associated with debilitating cognitive and/or motor symptoms which progressively worsen, leading to significant morbidity and mortality. Increasing evidence links metabolic dysfunction, including Type-2 diabetes mellitus (T2DM), and neurodegenerative disorders. Risk factors and pathways connecting metabolic dysfunction and neurodegeneration are largely unexplored. However, environmental exposures to some toxicants, like pesticides and air pollution, have been independently associated with both neurodegenerative disorders and metabolic dysfunction, and have been related to common mechanisms of pathogenesis, including oxidative stress, insulin dysregulation, and inflammation. With three, large, independent epidemiologic studies, we propose to investigate how specific chemicals (pesticides, NOx, etc.), explicitly identified as endocrine disruptors through literature reviews, including toxicology and experimental reports, influence functional outcomes (i.e. biomarkers, methylation profiles); providing translational findings confirming results of experimentally identified toxicants via functional intermediate outcomes in human populations. We propose to follow the functional results with analyses that assess whether these exposures are also associated with neurodegenerative outcomes (PD/dementia) or whether they influence the progression of symptoms or survival, taking into consideration metabolic dysfunction in study participants. Finally, we will investigate novel gene-environment interactions, examining whether functional variation in metabolism related genes interacts with these exposures to increase risk of PD or dementia, and how metabolic dysfunction further influences this risk. This training will include collaborating with experts to acquire skills in temporal spatial air pollution modeling, methylation analyses, and new analytic techniques (marginal structural models and structural nested mean models for intermediate/mediator analysis); the applicant also will gain experience with new aging-related outcomes (dementia and T2DM) i.e. broaden beyond Parkinson?s related work having access to data from two PD studies and a longitudinal study of aging in Mexican Americans (SALSA).