Matthew Dapas, William Wentworth-Sheilds, Emma E. Thompson, Rajesh Kumar, Elizabeth Lippner, Robert A. Wood, George T. O’Connor, Gurjit K. Khurana Hershey, Rebecca S. Gruchalla, Andrew H. Liu, Edward M. Zoratti, Leonard B. Bacharier, Stephanie Lovinsky-Desir, Michele A. Gill, William J. Sheehan, Shilpa J. Patel, Matthew C. Altman, James E. Gern, Cynthia M. Visness, Peter J. Gergen, Patrice M. Becker, Daniel J. Jackson, Carole Ober
Background: Childhood-onset asthma is highly heritable, with nearly 200 risk loci identified in genome-wide association studies. Aggregated polygenic risk scores (PRSs) can be used to quantify genetic predisposition to asthma, but their power to predict asthma severity in multiancestral groups has not been previously evaluated. Objective: Our aim was to examine the predictive power of biobank-derived asthma PRSs in 4 multiancestry asthma study cohorts of children living in US urban environments. Methods: We generated PRSs for asthma, derived from a large-scale genome-wide association meta-analysis, and assessed genetic predictions across different subphenotypes of asthma and tested for associations between genetic asthma risk and measures of asthma severity. Results: < .001). Conclusion: Cumulative genetic risk for asthma is associated with disease severity and exacerbation risk in children with asthma.