Changes in the blood metabolome in relation to air pollution exposure

Abstract

S01: Mapping the Air Pollution Metabolome: Applications, Limitations, and the Path Forward, Room 217, Floor 2, August 26, 2019, 10:30 AM - 12:00 PM Background: The peripheral blood might harbor compounds originating from air pollutants and endogenous metabolites influenced by air pollution. Within the EXPOsOMICS project untargeted metabolomics was explored as a tool to detect air pollution related changes in metabolic pathways occurring in peripheral blood. Methods: We applied metabolomic profiling by untargeted, high resolution mass spectrometry in two panel studies (focusing on the association with short-term variation in air pollution) and two cohort studies (focusing the association with long-term variation in air pollution). All blood samples were analyzed in a single laboratory. We applied univariate mixed-effects models, corrected for multiple testing, to investigate the association between metabolomic features and air pollution. Pathway enrichment was explored with bioinformatics approach Mummichog. Results: We identified associations between metabolomic features and estimates of both long- and short-term variation in air pollution metrics, including PM2.5, PM10, NO2, and ultrafine particles. We confirmed the identity of several associated features, including linoleate, octanoic acid, sphingosine, l-carnitine, L-Tyrosine, Phenylalanine, and caffeine. We observed enrichment of linoleate metabolism and fatty acid activation in most EXPOsOMICS studies. Conclusions: In the EXPOsOMICS studies we observed evidence for a potential impact of both long- and short-term variation in air pollution on metabolic changes in peripheral blood. Considerable differences were observed between studies in terms of identified metabolomic features, complicating the identification of those features that are unique to air pollution. Overlap between studies in the identified enriched pathways would suggest the identified associated metabolomic features reflect similar underlying biological mechanisms.