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

Particulate matter exposure has a direct impact on airways diseases, such as asthma and chronic obstructive pulmonary disease (COPD), and over the next 30 years, rising particulate air pollution is expected to increasingly affect disease outcomes. We identified transcriptional mechanisms of particulate exposure in the airway epithelium that connect with disease risk using genetics and multiomics. We first defined and compared rapid-transient nascent transcription responses across particulate exposures. Using hyaluronic acid metabolism as a prototype, we showed that rapid-transient responses to particulates were relevant to steady-state mRNA expression and COPD pathobiology. We then found genetic links between nascent transcription responses and asthma or COPD risk by associating single nucleotide polymorphisms (SNPs) with disease in the All of Us study. By combining nominal association statistics, pre- and post-association filters, and rigorous external validation, we identified SNPs associated with disease across multiple ancestries and cohorts. We then derived epigenetic and gene regulatory mechanisms from these SNPs. Our results highlighted plausible transcriptional mechanisms of disease, such as regulation of TOMM7 expression by rs13243243. By applying detailed transcriptional analysis to study particulate exposures, we identified novel SNPs and genes that define gene-environment interactions for airways disease.