Genetic mechanisms underlying maladaptive respiratory responses to air pollution - Project Summary Long-term exposure to ambient air pollutant ozone (O3) is associated with decreased lung function and the development and/or progression of asthma and chronic obstructive pulmonary disease (COPD). The underlying mechanisms remain obscure, however. We seek to identify new mechanisms by which O3 exposure causes these common, chronic diseases by focusing on a paradoxical yet highly reproducible finding in human controlled O3 exposure studies: while a single O3 exposure causes airway inflammation, injury, and decreased lung function, responses decrease–rather than increase–after repeated O3 exposures, a process referred to as adaptation. Intriguingly, not all individuals adapt, leading to our overarching hypothesis that failure to adapt (FtA) may render individuals susceptible to the development of asthma or COPD after long-term O3 exposure. Using a new mouse model of O3 adaptation involving four consecutive O3 exposures (“4X O3”), we ruled out previous hypotheses for mechanisms of adaptation, most prominently upregulation of antioxidants. Instead, our new data point to alveolar macrophages (AMs) as key determinants of adaptation. We found that 4X O3 exposures lead to an altered transcriptome in AMs, rendering them hypo-responsive. Further, using genetically diverse mice from the Collaborative Cross (CC) mouse genetics reference population, we identified mouse strains that adapt (A) or fail to adapt (FtA) after 4X O3 exposure, mimicking the diversity of responses observed in human studies. Comparing the genomes, epigenomes, and transcriptomes of AMs from these phenotypically divergent strains will enable us to identify novel genes and pathways (i.e., new mechanisms) that influence adaptation to O3. In Aim 1, we will test the hypothesis that genetically-encoded differences O3-induced gene expression in AMs underlie differences in adaptation. We will profile the transcriptomes and epigenomes of AMs in phenotypically divergent CC strains, revealing genes and pathways associated with adaptation. Through subsequent bioinformatic analyses, we will identify putative regulators of differential response, and then experimentally validate their roles in vivo using a lentivirus-based gene targeting approach. In Aim 2, we will identify genetic loci that that drive adaptation through the classical genetic approach of quantitative trait locus (QTL) mapping. We will identify candidate genes at QTL by integrating omic data generated in Aim 1, then functionally test these genes in vivo. Finally, in Aim 3, we will explicitly test the hypotheses that failure to adapt is a predictor of susceptibility to long-term, O3-induced chronic lung disease and that AMs are a critical to this process. We will compare the incidence and severity of chronic lung disease phenotypes caused by 5-week O3 exposure between CC-A vs. CC-FtA strains, and test whether modifying AM gene expression using a long-lived lentivirus approach modifies outcomes after 5-week O3 exposure. Completion of our aims will lead to the identification of genes and pathways that underlie adaptation and improve our understanding of susceptibility to air pollution-induced lung disease.
