Air particulate multiomics improves functional annotation of SNPs associated with lung disease

Asthma and chronic obstructive pulmonary disease (COPD) are influenced by interactions between genetic background and environmental exposures such as air pollutants, yet the mechanisms linking genetic variation and pollutant response remain poorly understood. We used nascent RNA run-on sequencing to characterize transcriptional responses of lung cells exposed to wood smoke particles, urban particulate matter, and Afghan dust particles. These datasets provide the first characterization of the nascent transcriptional response to urban particulate matter in primary lung cells and reveal both shared and pollutant-specific regulatory dynamics. Integration with regulatory network inference and genetic association data enables prioritization of noncoding variants and candidate regulatory mechanisms linking environmental exposures to lung disease risk.