Human Study to Develop a Signature of Occupational Diesel Exhaust Exposure

1. Purpose: Over 100,000 employees in Alberta are inadvertently exposed to diesel exhaust at work because of wide use of diesel engines in vehicles and machines used in road construction, trucking, forestry, oil extraction and mineral mining. Although ambient air monitoring of DE exposure exists in some occupational settings, ambient air monitoring depends heavily on surrogate models and may yield a distorted picture of past exhaust exposure. Thus, a clear exposure limit based on bio-monitoring is needed to adequately protect the workers.
2. Objective: Our research aims to establish the relationship between exposure concentration and biological effect as an aid to determination of reference ranges for acceptable exposure.
3. Hypotheses and Aims: Hypothesis 1: Diesel exhaust (DE) inhalation elicits a characteristic protein output, in a dose-dependent manner. Aim 1. Demonstrate, using a proteomic analysis of serum and urine, a signature that acutely increases in response to a range of occupationally relevant DE concentrations. Hypothesis 2: DE inhalation increases concentrations of metabolites of polyaromatic hydrocarbons (PAH) in urine, in a dose-dependent manner. Aim 2. Ascertain the range of PAH metabolites accumulation in urine following acute exposure to a range of occupationally relevant DE concentrations. Hypothesis 3: DE inhalation alters the airway responsiveness to a contractile stimulus, in a dose-dependent manner, and that alteration is associated with changes in a combined proteomic/PAH-metabolomic signature. Aim 3: Determine the dose-response slope to methacholine, in response to a range of occupationally relevant DE concentrations, and correlate changes in this slope to changes in proteins and metabolites. Additionally, we aim to establish the relationship between a range of controlled DE exposure concentrations and sleep quality and breathing in sleep through the sub-study component.
4. Justification: Our work will inform decision makers and stakeholders in creating evidence-based policies to limit occupational diesel exhaust exposure based on relevant biology.
5. Research Method: This is an order-randomized, double-blinded, crossover human exposure study. This project aims to determine markers of DE exposure that can be used in an occupational setting. Therefore, we will use a range of occupational exposure levels to appropriately contextualize our results. For this, 20 healthy participants will be exposed to a control condition and 3 different levels of DE concentration, each for a period of 4 hours, in a randomized order. Each exposure will be separated by a washout period of two weeks. The levels will be DE titrated to 20, 50 and 150 ug/m3 PM2.5, and the control exposure will be filtered air (FA). Participants will undergo a methacholine challenge and will provide urine and blood samples before and after exposures to analyze lung function and biological responses. If participants consent to participation in the sleep sub-study, they will be provided with additional questionnaires throughout their visits pertaining to their sleep quality. The participants will be provided with an Alice NightOne sleep monitor and instructions on how to operate the equipment. The sleep monitor will be hooked up by the participant at home when they are about to sleep, following an exposure, and will monitor their sleep patterns for that night.
6. Statistical Analysis:

First, the changes in clinical parameters (methacholine PC20 and dose response slope) and serum blood protein abundance between pre- and post-exposure will be determined. These 'delta' values will be statistically compared across exposures using linear mixed effects models using R program, as outlined in our previous publications from similarly-designed protocols from our group. Values of p<0.05 will be considered significant throughout, with adjustments for multiple comparisons. Although the 2-week washout period is intended to minimize the likelihood of carryover effects, we will formally assess for this by including a term for order of exposures in the models.

Analyses for the sleep component will be performed at the Hospital of Ottawa and will be completed through a linear or logistic mixed effects model, as applicable using the R program. Similar methods to data collected from the main study. Data interpretation will be completed through a software algorithm on the local server.