Linking air pollution exposure to blood-based metabolic features in a community-based aging cohort

Long-term exposure to air pollution has been associated with changes in levels of several metabolites measured in the peripheral blood. However, most work has been conducted in ethnically homogenous populations. We studied the relationship between the plasma metabolome and long-term exposure to three air pollutants: particulate matter (PM) less than 2.5 m in aero diameter (PM2.5), PM less than 10 m in aero diameter (PM10) and nitrogen dioxide (NO2) among 107 participants of the Washington Heights and Inwood Community Aging Project (WHICAP) in New York City. Plasma metabolomic profiles were generated using untargeted liquid chromatography coupled with high-resolution mass spectrometry. We estimated the association between each metabolic feature and predicted annual mean exposure to the air pollutants using three approaches: 1. A metabolome-wide association study (MWAS) framework; 2. Feature selection using elastic net regression; and 3. A multivariate approach using partial least squares discriminant analysis. Additionally, we identified the pathways enriched by metabolic features associated with exposure through pathway analysis. The samples were collected from 1995-2015 and included non-Hispanic white, Caribbean Hispanic, and non-Hispanic Black older adults. Through the MWAS, we found 79 features associated with exposure to PM2.5 (false discovery rate at 5%) but none associated with PM10 or NO2. Pathway analysis revealed that PM2.5 exposure was associated with altered amino acid metabolism, energy production, and oxidative stress response. Six features were found to be associated with PM2.5 exposure through all three approaches, annotated as: cysteinylglycine disulfide, a diglyceride, and a dicarboxylic acid. Additionally, we found that the relationship between several features and PM2.5 exposure was modified by diet and metabolic diseases. These signals, identified in a neighborhood-representative older population, could help understand the mechanisms through which PM2.5 exposure can lead to altered metabolic outcomes in an older population.