Epigenomic partitioning of a polygenic risk score for asthma reveals distinct genetically driven disease pathways.

ABSTRACT

BACKGROUND: Individual differences in susceptibility to develop asthma, a heterogeneous chronic inflammatory lung disease, are poorly understood. It remains debated whether genetics can predict asthma risk and how genetic variants modulate the complex pathophysiology of asthma. AIM: To build polygenic risk scores (PRSs) for asthma risk prediction and epigenomically link predictive genetic variants to pathophysiological mechanisms. METHODS: Restricted PRSs were constructed using single nucleotide variants derived from genome-wide association studies and validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14 926 individuals. Outcomes used were asthma, childhood-onset asthma (COA), adulthood-onset asthma (AOA), eosinophilic asthma, and asthma exacerbations. Genome-wide chromatin analysis data from 19 disease-relevant cell types were used for epigenomic PRS partitioning. RESULTS: PRSs obtained predicted asthma and related outcomes, with the strongest associations observed for COA (2.55 odds ratios per PRS standard deviation, area under the curve of 0.760). PRSs allowed for the classification of individuals into high and low-risk groups. PRS partitioning using epigenomic profiles identified 5 clusters of variants within putative gene regulatory regions linked to specific asthma-relevant cells, genes, and biological pathways. CONCLUSIONS: PRSs were associated with asthma(-related traits) in a Dutch prospective cohort, with substantially higher predictive power observed for COA than for AOA. Importantly, PRS variants could be epigenomically partitioned into clusters of regulatory variants with different pathophysiological association patterns and effect estimates, which likely represent distinct genetically driven disease pathways. Our findings have potential implications for personalized risk mitigation and treatment strategies.