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Human Study to Develop a Signature of Occupational Diesel Exhaust Exposure

A Controlled Dose-Response Human Study to Develop a Signature of Occupational Diesel Exhaust Exposure

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03234790
Acronym
DICE
Enrollment
20
Registered
2017-07-31
Start date
2017-09-27
Completion date
2021-07-16
Last updated
2021-11-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Experimental

Keywords

Diesel Exhaust, Air Pollution, Airway Responsiveness, Proteomics, Urine PAH Metabolites

Brief summary

Strong scientific understanding of how emissions from diesel engines impact the lungs could improve policies and regulations protecting workers exposed to diesel exhaust. Accordingly, we are recruiting healthy volunteers who are non-smokers to participate in our study. Volunteers sit in a room for four hours and breathe either clean filtered air or air that contains pollution at various concentrations similar to occupational settings such as bus and ferry terminals where diesel engines are used. A respirologist assesses the volunteer's lung health and clinical samples are taken. We are equipped with advanced molecular biology tools to measure different molecules and compare samples from our volunteer subjects following exposure to clean air or diesel exhaust. Our research aim is to find a simple, clinically relevant strategy that can be used to measure the impact of diesel exhaust on workers' lung health. This knowledge will empower regulators, companies, and ultimately workers to better manage their health risks. Our research aims to provide specific data to help regulators to make informed decisions about the risks of diesel exhaust exposure.

Detailed description

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.

Interventions

Exposure to Filtered air

Diesel exposure to different concentrations at different times: 20, 50 and 150ug/m3

Sponsors

Government of Alberta
CollaboratorOTHER_GOV
Ottawa Hospital Research Institute
CollaboratorOTHER
University of British Columbia
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
SCREENING
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)

Eligibility

Sex/Gender
ALL
Age
19 Years to 49 Years
Healthy volunteers
Yes

Inclusion criteria

1. 19-49 years 2. Non-smokers 3. No physician diagnosed asthma

Exclusion criteria

1. Pregnant/breastfeeding 2. Using inhaled corticosteroids 3. Co-existing medical conditions (as assessed by the primary investigator) 4. Taking part in another study that involves taking medications. 5. Abnormal lung function based on screening spirometry 6. Cardiac diagnosis or arrhythmia is discovered during the screening process

Design outcomes

Primary

MeasureTime frameDescription
Serum proteome in response to DE exposure4 hours & 24 hoursSerum from each experimental condition will be analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) to observe any changes between the baseline and listed time points

Secondary

MeasureTime frameDescription
Urine proteins in response to DE exposure4 hours & 24 hoursUrine from each experimental condition will be analyzed by liquid mass chromatography to observe any changes between the baseline and listed time points.
Polycyclic Aromatic Hydrocarbons (PAH) metabolites in response to DE exposure4 hours & 24 hoursPAH metabolites in urine samples will be analyzed by HPLC to observe any changes between the baseline and listed time points.
Sleep qualitybaseline versus 24 hours post-exposureSleep quality will be assessed by level 3 overnight monitor and questionnaires

Countries

Canada

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 11, 2026