Circulating metabolomics revealed novel associations between multiple ambient air pollutants exposure and chronic obstructive pulmonary disease incidence: Evidence from a prospective cohort study

Abstract

The mechanisms underlying relationships between ambient air pollution and chronic obstructive pulmonary disease (COPD) risk remained largely uncertain. In this study, we aim to evaluate whether metabolic signature comprising multiple circulating metabolites can characterize metabolic response to the multiple air pollution; and to assess whether the identified metabolic signature contribute to COPD risk. A total of 227,962 participants with complete data were included from the UK biobank study. Concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), and particulate matter (PM2.5 and PM10) were evaluated by land-use regression models. We newly computed an air pollution score to reflect joint exposure to multiple air pollutants. Circulating metabolome was quantified by nuclear magnetic resonance (NMR) spectroscopy. During a median of 12.78 years of follow-up, a total of 8685 incident COPD cases were documented. After multiple correction, the Cox regression models showed that 102 of 143 metabolites were significantly associated with COPD risk. Utilizing elastic net regularized regressions, we identified a metabolic signature comprising 106 metabolites (including lipid, fatty acids, glycolysis and amino acids et al.) were robustly related to air pollution score. In the multivariate-adjusted Cox regression models, the derived metabolic signature showed a positive correlation with incident COPD [HR per SD = 1.20 (95% CI: 1.17–1.22)]. Casual mediation analysis further noted that the constructed metabolic signature mediated 10.5 % (8.3%–13.1%) of the air pollution-COPD associations. Taken together, our findings identified a metabolic signature that captured metabolic response to various air pollutants exposure jointly, and predicted future COPD risk independent of known risk factors.