Feiby L Nassan1, Rachel S Kelly2, Anna Kosheleva3, Petros Koutrakis3, Pantel S Vokonas4, Jessica A Lasky-Su2, Joel D Schwartz3,2,5. 1. Department of Environmental Health, Harvard T. H. Chan School of Public Health, Landmark Center, Room 414C, 401 Park Dr, Boston, MA, 02215, USA. fen769@mail.harvard.edu. 2. Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02129, USA. 3. Department of Environmental Health, Harvard T. H. Chan School of Public Health, Landmark Center, Room 414C, 401 Park Dr, Boston, MA, 02215, USA. 4. VA Normative Aging Study, VA Boston Healthcare System, School of Medicine and School of Public Health, Boston University, Boston, MA, 02215, USA. 5. Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.
Abstract
BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS:Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
Entities:
Keywords:
Air pollution; Metabolomics; Normative aging study (NAS); Particulate matter; Temperature
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