Authors
Michael Yoon, Min Hyung Ryu, Christopher F Rider, Ryan Huff, Amrit Singh, Christopher Carlsten
Published in
Environmental research. Pages 125625. Sep 10, 2026. Epub Sep 10, 2026.
Abstract
Traffic-related air pollution (TRAP) exposure is associated with adverse health effects, including chronic inflammation and the exacerbation of respiratory diseases. Although the effects of TRAP exposure begin locally in the lungs, they can spread systemically throughout the body via the blood. To understand blood-lung dynamics upon TRAP exposure, we interrogated blood and airway gene expression and performed a concordant analysis. Specifically, we investigated the transcriptomic response of the blood and airway epithelium to inhaled diesel exhaust (DE), an experimental model of TRAP, across thirty-two research participants from a mixed population. In this double-blinded, crossover, controlled human exposure study, participants were exposed to DE and filtered air for two hours on two separate occasions. Paired-end RNA-sequencing was conducted on blood and bronchial brushing samples. Differential gene expression analysis revealed significant genes in airways (FDR < 10%), including upregulation of GPX2 and NQO1, genes essential to antioxidant defense. Differentially expressed genes (DEGs) were mapped to hallmark pathways and cell types using the Human Molecular Signatures Database (MSigDB). In the blood and airway epithelium, pathways with altered activity included interferon alpha (IFN-α) response, interferon gamma (IFN-γ) response, inflammatory response, and reactive oxygen species (ROS). Concordant analysis highlighted correlated expression patterns between blood and airways, providing exploratory evidence of a potential blood-lung relationship in response to DE exposure, which was not detectable through independent analysis. Combining local and systemic data may enrich our understanding of the downstream biological pathways affected by DE exposure, allowing for new avenues to monitor lung responses through blood analysis.
PMID:
42722095
Bibliographic data and abstract were imported from PubMed on 11 Sep 2026.
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