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| ID | Type | Description | Link |
|---|---|---|---|
| LG3-193738 | Other Grant/Funding Number | Canadian Institutes of Health Research (CIHR) | |
| RFA 24-2 | Other Grant/Funding Number | Health Effects Institute |
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Wildfire smoke (WFS) is the leading climate-related risk in Canada and the main source of harmful air pollution. While short-term breathing problems caused by smoke are well known, there is limited knowledge on how repeated exposure contributes to long-term lung disease. This study is a controlled human exposure to varying concentrations of WFS in a safe setting. By comparing the effects of different concentrations, this research will improve understanding of health impacts, identify who may be most vulnerable to exposures, and explore biological changes that could lead to chronic illness.
PURPOSE: To use responses to controlled human exposures to woodsmoke, as a model of wildfire smoke (WFS), to quantify risk of, and add biological plausibility to, the supposition that WFS-related particulate matter with a diameter of 2.5 micrometers or less (PM2.5) contributes to the development of neurological and chronic lung diseases.
Study Exposure Arms:
Arm A: 3 consecutive days with 2h woodsmoke exposures at 35 µg/m3 of PM2.5 Arm B: 3 consecutive days with 2h woodsmoke exposures at 105 µg/m3 of PM2.5 Arm C: 2 consecutive days of Filtered Air (FA), followed by 1 day with a 2h woodsmoke exposure at 315 µg/m3 of PM2.5
HYPOTHESIS, JUSTIFICATIONS, AND OBJECTIVES Aim 1A: Enhance plausibility for, and quantify risk of, WFS contributions to chronic lung disease.
Hypothesis 1A: The investigators will determine mechanisms that plausibly link WFS exposure to the development of chronic disease, by connecting WFS exposures to lung function decline, asthma, chronic obstructive pulmonary disease (COPD), or lung cancer.
To assess the plausibility of linking WFS exposure to Chronic Lung Diseases such as asthma, COPD, and lung cancer.
To evaluate the biological impacts of WFS on the airways.
Aim 1B: Use a controlled human exposure study to identify, across different intensities of WFS exposure:
1.1 Neurocognitive changes relevant to the development of chronic neurological diseases 1.2 Temporal patterns of onset and resolution in relevant circulating neuro-inflammatory markers 1.3 Sex, age, and genetics as effect-modifying susceptibility factors for the above phenomena
Hypothesis 1B: The investigators will demonstrate disturbances in the brain default mode network (DMN), and intensity-dependent increases in circulating neuro-inflammatory markers, particularly in older individuals and those with genotypes conferring deficient anti-oxidant metabolism or those conferring risk of dementia.
RESEARCH DESIGN A randomized, double-blinded, crossover-controlled human exposure study.
STATISTICAL ANALYSIS Data will be analysed in R using generalized and linear mixed-effects models. Models will run with exposure as a fixed effect and participant ID as a random effect.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Arm A) Three repeated exposures to a low air pollution concentration | Experimental | Three consecutive days with a 2-hour woodsmoke exposure at 35 µg/m3 of PM2.5 each day. |
|
| Arm B) Three repeated exposures to a moderate air pollution concentration | Experimental | Three consecutive days with a 2-hour woodsmoke exposure at 105 µg/m3 of PM2.5 each day. |
|
| Arm C) Single exposure to a higher air pollution concentration | Experimental | Two consecutive days of 2-hour filtered air exposures, followed by 1 day with a 2-hour woodsmoke exposure at 315 µg/m3 of PM2.5. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Woodsmoke (Lodgepole Pine) exposure | Other | Woodsmoke will be freshly generated using a furnace tube burning dried, ground lodgepole pine (Pinus contorta) to achieve the nominal PM2.5 (particulate matter with an aerodynamic diameter of less than or equal to 2.5 micrometres) concentrations specified for each study arm. |
| Measure | Description | Time Frame |
|---|---|---|
| Effects of PM2.5 exposures and concentration on exhaled nitric oxide. | Measurement of fractional exhaled nitric oxide (FeNO). | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on Cambridge Neuropsychological Test Automated Battery (CANTAB) | Computational testing using CANTAB to determine e.g. 5-choice reaction time and percent correct all delays. | Comparison of the different arms over the span of 4 months. |
| Measure | Description | Time Frame |
|---|---|---|
| Effects of PM2.5 exposures and concentration on sputum cell numbers. | Differentially count sputum cells. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on brain functional connectivity. |
| Measure | Description | Time Frame |
|---|---|---|
| Effects of PM2.5 exposures and concentration on breath volatile organic compounds. | Collection and analysis of breath volatiles using ReCIVA technology. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on airway microbial taxon abundance. |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| PJ (Parteek) Johal, BCS | Contact | 604-875-5132 | p.johal@ubc.ca | |
| Agnes Yuen, BSc | Contact | 604-875-4111 | 66455 | agnes.yuen@ubc.ca |
| Name | Affiliation | Role |
|---|---|---|
| Chris Carlsten, MD, MPH | University of British Columbia | Principal Investigator |
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Participants will act as their own controls, as they will complete all three study arms:
Arm A) Three consecutive days with a 2-hour woodsmoke exposure at 35 µg/m3 of PM2.5 each day.
Arm B) Three consecutive days with a 2-hour woodsmoke exposure at 105 µg/m3 of PM2.5 each day.
Arm C) Two consecutive days of 2-hour filtered air exposures, followed by 1 day with a 2-hour woodsmoke exposure at 315 µg/m3 of PM2.5.
The study arms will be separated by 4-week washout periods.
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Blinding of exposures will be performed by the air pollution exposure laboratory (APEL) engineer. Participant coordination and testing will be conducted by a researcher without knowledge of which study arm a given participant is undergoing. The study investigator will be blinded to which study arm participants are undergoing. All assays will be performed by personnel who do not know the exposure conditions of individual samples.
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| Filtered air exposure | Other | Exposures to HEPA filtered air, as a control. |
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Resting-state functional MRI (rs-fMRI) will assess functional connectivity within the default mode network (DMN) using a seed-based approach. Preprocessing will follow established neuroimaging methods. Functional connectivity will be determined as temporal correlations between blood-oxygen-level-dependent (BOLD) signal time series from a posterior cingulate cortex seed and DMN regions, using group-level statistical models.
| Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on oxidative stress. | Assessment of oxidative stress using H2DCFDA. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on lung inflammatory markers. | An inflammation matrix will be generated, including data from RNA and protein inflammatory markers (e.g. interleukins (IL)-1ß, 4, 5, 6, 8, 9, 13, 17, 25 and 33, IFN., CSF1, TSLP, CC16/SCGB1A1 and c-reactive protein). | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on lung imaging. | The lungs will be imaged with hyperpolarized 129Xe gas to measure ventilation defect percent, membrane-to-gas ratio and red blood cell-to-gas ratio. These measures will be standardized and averaged to generate a single composite lung function imaging score per participant. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on circulating brain-derived biomarkers of neuroinflammation. | Analysis of circulating brain-derived biomarkers of neuroinflammation using the NULISAseq CNS Diesease Panel 120. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on neutrophil extracellular traps (NETs). | Analysis of counts of neutrophil extracellular traps (NETs). | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on host defence proteins. | Host defense peptides matrix, from e.g. alpha defensin-1, S100A7 and cystatin-SA. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on DNA methylation. | Measurement of DNA methylation after exposures and determination of epigenetic age. | Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on glia-derived extracellular vesicles. | Glia-derived extracellular vesicles will be measured in circulating blood using nanoflow cytometry-based direct labelling. | Comparison of the different arms over the span of 4 months. |
The airway microbiome will be characterized using sequencing. Differential abundance analysis will quantify changes in the relative abundance of individual airway microbial taxa across exposure conditions. |
| Comparison of the different arms over the span of 4 months. |
| Effects of PM2.5 exposures and concentration on symptoms. | Symptoms and Perception questionnaires (e.g. https://particleandfibretoxicology.biomedcentral.com/articles/10.1186/s12989-022-00506-6#Sec15) will be completed. | Comparison of the different arms over the span of 4 months. |
| ID | Term |
|---|---|
| D001249 | Asthma |
| D029424 | Pulmonary Disease, Chronic Obstructive |
| D008175 | Lung Neoplasms |
| ID | Term |
|---|---|
| D001982 | Bronchial Diseases |
| D012140 | Respiratory Tract Diseases |
| D008173 | Lung Diseases, Obstructive |
| D008171 | Lung Diseases |
| D012130 | Respiratory Hypersensitivity |
| D006969 | Hypersensitivity, Immediate |
| D006967 | Hypersensitivity |
| D007154 | Immune System Diseases |
| D002908 | Chronic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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