Understanding the Genetic Contributions to Variation in Ozone Exposure Response

PROJECT SUMMARY Ozone is a common ambient air pollutant that presents a significant public health hazard as a trigger for lung function decrements, airway inflammation, and exacerbations of asthma and COPD symptoms. Controlled human exposure studies have found that the severity of these responses varies widely across individuals while

the severity of a given individual’s reaction is reproducible across multiple independent exposures, indicating a potential genetic contribution to one’s risk for a severe response. Results from animal models also indicate that response to ozone is a complex trait. The genetic variants that underly this variation are currently unknown and

this data gap needs to be addressed to identify high-risk individuals. Mapping expression quantitative trait loci (eQTL), which are statistical associations between variants and gene expression, is one approach used by human geneticists to study the genetic basis of complex traits. However, most eQTL mapping studies have used

unperturbed/unexposed samples which may miss eQTL that only manifest after exposure or have an altered magnitude of effect with exposure, termed “response eQTL.” These response eQTL are thus gene-by- environment interactions. Studying these interactions in humans is often difficult, making in vitro models an

attractive approach. Primary human bronchial epithelial cells (HBECs) isolated from the airway are a highly relevant in vitro model. HBECs can be readily cultured into a well-differentiated pseudo-stratified epithelium similar to that found in vivo and are cultured at an air-liquid interface, enabling in vitro exposures which mimic in

vivo exposures. Additionally, using primary cells from different donors provides the genetic variation necessary for mapping eQTL. The goal of my project is to use this in vitro model to identify ozone response eQTL, genome- wide, and identify overlapping signals with asthma and COPD GWAS loci. I hypothesize that mapping ozone

response eQTL in a physiologically relevant cell culture model will identify variants associated with response variability. Further, I hypothesize that some of these response eQTL will colocalize with GWAS signals for asthma and COPD, which have both been shown to be affected by air pollution exposure. In Aim 1, I will characterize

the transcriptomic response to ozone in HBECs from 202 donors with diversity in age, sex, genetic ancestry, and smoking history. In Aim 2, I will map baseline and ozone response eQTL, using the difference in gene expression between filtered air and ozone exposed culture pairs from each donor to map response eQTL. In Aim 3 I will

perform colocalization between ozone response eQTL and GWAS for asthma and COPD, followed by Mendelian

randomization analysis to evaluate a signal’s effect on disease via gene expression. In total, I will identify genetic drivers of increased risk for severe response to ozone using a response eQTL strategy to find context-dependent eQTL, which will improve identification of susceptible individuals and inform policy regarding safe levels of

exposure.