Title | Modeling PAH Mixture Interactions in a Human In Vitro Organotypic Respiratory Model. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Colvin, VC, Bramer, LM, Rivera, BN, Pennington, JM, Waters, KM, Tilton, SC |
Journal | Int J Mol Sci |
Volume | 25 |
Issue | 8 |
Date Published | 2024 Apr 13 |
ISSN | 1422-0067 |
Keywords | Air Pollutants, Biomarkers, Bronchi, Cells, Cultured, DNA Damage, Epithelial Cells, Humans, Models, Biological, Oxidative Stress, Polycyclic Aromatic Hydrocarbons |
Abstract | One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air-liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples. |
DOI | 10.3390/ijms25084326 |
Alternate Journal | Int J Mol Sci |
PubMed ID | 38673911 |
PubMed Central ID | PMC11050152 |
Grant List | P42 ES016465 / ES / NIEHS NIH HHS / United States P30 ES030287 / ES / NIEHS NIH HHS / United States T32 ES07060 / ES / NIEHS NIH HHS / United States |