Short- and long-term exposures to traffic pollution have been linked to numerous adverse health endpoints. While various approaches have been proposed to model traffic exposures and corresponding health response, few have systematically examined how well these approaches reflect actual and biologically-relevant exposures along a complete emissions-to-dose pathway. The overarching goal of this dissertation is to develop and evaluate external and internal methods for assessing exposures to traffic related air pollution (TRAP). To achieve this goal, two large prospective panel-studies were conducted. In the first study, the Dorm Room Inhalation to Vehicle Emissions (DRIVE) study, I examined spatiotemporal variability trends and assessed the potential for bias and errors when using a roadside monitor as a primary traffic pollution exposure surrogate, in lieu of more spatially-refined, proximal exposure indicators (Aim1). Using data from the DRIVE study, I also examined the feasibility of using high-resolution metabolomics (HRM) as means of assessing internal exposures, through the identification of traffic pollution-related metabolites (Aim 2). Finally, in the second study, the Atlanta Commuters Exposure (ACE-2) study, I applied high-resolution environmental metabolomics to examine and develop metabolic signals that are most predictive of TRAP exposure or the corresponding effects, and to investigate the potential effect modification of asthma on modifying the metabolic responses to TRAP exposures (Aim 3).
For Aim 1, I measured several single TRAP indicators with high spatial and temporal resolution at six indoor and outdoor sites ranging from 0.01 to 2.3 km away from a major highway artery. I examined spatiotemporal variability trends of these TRAP indicators and estimated errors when using a roadside monitor as a primary traffic pollution exposure surrogate for use in epidemiologic studies. For Aim 2, 54 students living in dormitories either near (20 m) or far (1.4 km) from the highway conducted personal sampling and contributed bio samples (plasma and saliva) during the DRIVE study. Untargeted HRM were used to identify potential metabolic pathways associated with traffic-related air pollutants in the panel. For Aim 3, we conducted extensive exposure assessment on 27 air pollutants during each commute session and conducted high-resolution metabolomics profiling on blood samples from the commuters prior to and after the commute in ACE-2 study. I further evaluated metabolite and metabolic pathway alternations using an untargeted metabolome-wide association study (MWAS) framework with pathway analyses and chemical annotation.
In Aim 1, Pollutant levels measured during DRIVE showed a low impact of this highway hotspot source. Patterns of correlation among the sites also varied by pollutant and time of day. Pronounced attenuation of observed changes in health effects were found when using measured pollutant from the near-road monitor as a surrogate for true exposure, and the magnitude varied substantially over the course of the day. In Aim 2, I identified and verified biological perturbations associated with primary traffic pollutant, including arginine, histidine, γ-linolenic acid, and hypoxanthine. Observed response was consistent with endogenous metabolic signaling related to oxidative stress, inflammation, and nucleic acid damage and repair. In Aim 3, I observed significant and robust metabolic perturbations associated with TRAP exposure among commuters in ACE-2 study. I confirmed the chemical identity of 45 unique metabolites enriched in these metabolic pathways, including inflammatory amino acids such as arginine, histidine, and methionine. Many of these molecules were not only associated with multiple TRAPs, but also responded differentially among asthmatic and healthy participants.
Collectively, the aims and analyses for this dissertation centered on a highly chemically-speciated set of external and internal measurements of traffic pollution, in a range of near road microenvironments. Caution should be taken when using near-road monitoring network observations, alone, to investigate health effects of traffic pollutants. Using the high-resolution environmental metabolomics platform, we observed significant and robust metabolic perturbations associated with TRAP exposure in two independent panels. I identified xenobiotic-mediated oxidative stress and acute inflammatory response related pathways and metabolites. These results motivate future studies geared towards development of metabolic markers for reflecting TRAP exposures, their corresponding effects, and the asthma etiology.
Table of Contents
CHAPTER 1 TABLES AND FIGURES........28
CHAPTER 1 SUPPLEMENTAL MATERIALS........36
CHAPTER 2 TABLES AND FIGURES........73
CHAPTER 2 SUPPLEMENTAL MATERIALS........79
CHAPTER 3 TABLES AND FIGURES........118
CHAPTER 3 SUPPLEMENTAL MATERIALS........130
About this Dissertation
|Committee Chair / Thesis Advisor|
|File download under embargo until 17 August 2020||2018-06-18||File download under embargo until 17 August 2020|