Environmental Exposures, Mental Health Outcomes, and Connection to the Metabolome: An Exposomics Framework

Abstract

Anxiety and depression are the most prevalent of all psychiatric disorders both domestically and globally, fueling an urgency to identify and intervene on possible individual- and population-level risk factors. With the advent of the concept of the exposome in the field of environmental epidemiology, there is a universal call to examine how multiple exposures work independently and jointly to impact physical and mental health outcomes. This dissertation aims to illustrate the application of an exposomics framework to study associations between multiple environmental exposures and mental health outcomes and identify exogenous and endogenous mechanisms responsible. The first chapter of this dissertation assessed the association between a single exposure, annual average temperature, and depression in the Nurses’ Health Study II (NHSII). Higher long-term residential temperature was associated with an increased risk of developing depression. This was the first study to directly assess the association between long-term residential temperature and depression in the United States. The second chapter of this dissertation looked to examine associations between multiple environmental exposures (one-, three-, and 12-month averages of fine particulate matter (PM2.5) exposure, nitrogen dioxide (NO2) exposure, and temperature; residential greenness; neighborhood walkability; and neighborhood socioeconomic status) and anxiety symptoms as characterized by the Generalized Anxiety Disorder Assessment (GAD-7) in NHSII. When assessing single exposures, higher summer residential greenness was protective for symptoms of anxiety, while short- and long-term average NO2, neighborhood walkability, and long-term average temperature were adversely associated. When assessing exposures jointly, these associations were generally attenuated barring summer residential greenness and nSES, for which protective associations increased in magnitude. Finally, the third chapter of this dissertation aimed to assess metabolomic signatures associated with short- and long-term exposure to PM2.5, coarse particulate matter (PM2.5-10), and NO2 in pooled participants from across the Nurses’ Health Study (NHS), NHSII, and the Health Professionals Follow-Up Study (HPFS). Four pathways were identified as being perturbed by the air pollutants assessed in the study: glycerophospholipid metabolism, steroid hormone biosynthesis, arginine biosynthesis, and glycine, serine, and threonine metabolism. This is the largest study of metabolomic signatures of air pollution conducted to date. Results validated findings of smaller studies and identified possible mechanisms through which air pollution could adversely affect mental health outcomes. This dissertation aimed to address gaps at two levels: one was to dive into the complex associations between environmental exposures and mental health outcomes and to assess the biological plausibility of some of these exposures. The other was to demonstrate the use of an exposomics framework that highlighted the importance of studying both single- and joint-associations and utilized a metabolomics approach to connect the internal and external environments that are encompassed in the exposome. The first two studies identified population-level risk factors for mental health outcomes that can and should serve as intervention points as the threat of climate change intensifies. The final study bolstered the body of literature elucidating the biological basis for the adverse health effects of air pollution and identified specific pathways that should be further studied.