Integrating polygenic and environmental risk factors for asthma in diverse populations

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Project Summary/Abstract Asthma is a complex, inflammatory airway disease that affects millions of people worldwide with striking health disparities. The relatively high heritability of asthma suggests that genetic factors contribute substantially to asthma risk. Our understanding of these genetic risk factors has rapidly expanded in just the past few years, with large-scale genome-wide association studies (GWAS) collectively identifying hundreds of common genetic variants associated with asthma. The wealth of information coming from these studies suggests that genetics may improve asthma risk prediction models, which may be useful in intervention, prevention, and targeted disease management strategies. However, existing models currently have modest clinical potential and primarily draw from only a handful of personal, family, and environmental variables. Therefore, we propose to apply statistical approaches to assess the utility of (a) quantitative indexes of genome-wide genetic risk and (b) aggregated environmental risk exposures, individually and combined, for predicting asthma case status in populations of different ancestries. Specifically, in Aim 1, we will derive polygenic risk scores (PRS) for asthma from the largest and most diverse GWAS of asthma to date. In Aim 2, we will develop asthma PRS that leverage genetic information from correlated diseases and traits. In Aim 3, we will utilize phenome-wide approaches to select and collate environmental exposures relevant to asthma risk from a rich phenotypic resource, with the ultimate goal of building an integrated risk model that considers genetic and environmental risk factors across diverse populations. These Aims will provide insights into the predictive potential of these comprehensive models, as well as tools for constructing PRS and environmental risk scores for asthma in populations underrepresented in genomic studies. Together, the analyses will facilitate the development of more accurate population-based risk prediction tools for asthma. The proposed research will provide the fellowship PI with a rich training experience in the Harvard PhD Program, the Broad Institute of MIT and Harvard, and the Massachusetts General Hospital. With the mentorship of her sponsors and collaborators, she will achieve several training goals that will lay the foundation for her development as an independent researcher and ultimately, a principal investigator.