Better utilization of omics data to inform precision medicine for asthma throughout the life course

PROJECT SUMMARY Asthma exacerbations are a major cause of disease morbidity and lead to progressive loss of lung function, airway remodeling, and enhanced disease severity. Their associated economic burden is substantial, totaling approximately 15 million outpatient visits, 2 million emergency room visits, and 500,000 hospitalizations each year in the United States alone. Predisposition to asthma exacerbations is influenced by genetics and triggered by environmental exposures that result in a dysregulated immune response. Viral and bacterial infections are the leading risk factors for asthma exacerbations. While a few virulent species have been well-studied, a comprehensive assessment across a range of viral and bacterial stimuli, as well as their interactions with multiple omics, to understand how these are linked to individual susceptibility has not been performed. Recent technological advances in Phage ImmunoPrecipitation Sequencing (PhIP-Seq) have facilitated a high- throughput, cost-effective evaluation of global virulent exposures, enabling for the first the estimation of cumulative exposures in the context of asthma exacerbations. As such, our overarching objective is to identify the impact of prior viral, bacterial, and other virulent exposures on asthma exacerbations and severity by employing PhIP-Seq profiling coupled with multiple omics (genetics, epigenetics, and metabolomics). Our overall hypothesis is viral and bacterial exposures interact with host genetics and downstream omics differentially across individuals; these relationships are relevant to disease exacerbations and will differ across the life course. We will first characterize lifetime virulent exposures through PhIP-Seq profiling, then identify exposures and multi- omic variants associated with asthma exacerbations- as well as interactions between these complementary omic layers- and finally, construct universal and personalized predictive models of the impact of these exposures on asthma severity through a cooperative learning methodological approach. We will leverage four well- characterized child and adult asthma cohorts, totaling 4,000 individuals, with existing genetic, epigenetic, and metabolomic data, and apply novel approaches to data integration. The demographic diversity of these cohorts allows us to interrogate both life course effects, as well as sex as a biological variable and differences by race and ethnicity. These results hold unprecedented potential to enlighten the complex relationships between virulent exposures, omic profiles, and asthma exacerbations, providing novel avenues for more personalized therapeutic targets and management strategies.