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Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring
Lauren E Koval1,2, Celeste K Carberry1,2, Yong Ho Kim3,4
1Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina27599, United States.
Environmental Science & Technology
|November 18, 2022
Summary
Wildfire smoke health risks vary by fuel and burn type. Transcriptomic analysis grouped similar smoke exposures, aiding risk assessment for public health protection.
Area of Science:
- Environmental Health
- Toxicology
- Biomedical Science
Background:
- Wildfire prevalence is increasing globally, leading to greater disease risk from smoke exposure.
- Assessing health risks is challenging due to diverse wildfire emissions from varied fuels and combustion conditions.
- Understanding smoke exposure impacts is crucial for public health protection.
Purpose of the Study:
- To test if biomass smoke exposures from different fuels and burn conditions cluster based on similar transcriptional responses.
- To inform which wildfire-relevant exposures can be grouped for health risk evaluations.
- To compare transcriptomic-based groupings with smoke chemistry and pulmonary toxicity markers.
Main Methods:
- Mice were exposed to biomass smoke condensates from eucalyptus, peat, pine, pine needles, and red oak under flaming or smoldering conditions.
- Lung transcriptomic signatures were analyzed to compute similarity scores and group exposures.
- Pulmonary toxicity markers and smoke chemistry were evaluated for comparison.
Main Results:
- Exposures from flaming peat, flaming eucalyptus, and smoldering eucalyptus showed the most significant transcriptomic responses.
- Flaming peat smoke grouped with lipopolysaccharide, a known pro-inflammatory agent.
- Transcriptomic and toxicity-based groupings differed from those based on smoke chemistry.
- Smoldering red oak and peat smoke induced the lowest transcriptomic responses.
Conclusions:
- Transcriptomic profiles effectively group biomass smoke exposures, providing a basis for health risk assessment.
- Grouping wildfire-relevant exposures aids in developing targeted public health strategies.
- Transcriptomic analysis offers higher resolution for evaluating health impacts compared to smoke chemistry alone.
