Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution
| Autor: | Howard H. Chang, Dean P. Jones, Donghai Liang, Megan M. Niedzwiecki, Jennifer L. Moutinho, Jeremy A. Sarnat, Roby Greenwald, Douglas I. Walker, Stefanie Ebelt Sarnat, Rachel Golan, Chandresh Ladva, Armistead G. Russell, Tianwei Yu |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Air pollution High resolution Traffic emission 010501 environmental sciences medicine.disease_cause 01 natural sciences Article 03 medical and health sciences Metabolomics Air Pollution Environmental health medicine Humans Saliva Students lcsh:Environmental sciences Vehicle Emissions 0105 earth and related environmental sciences General Environmental Science Pollutant lcsh:GE1-350 Air Pollutants Metabolic biomarkers Traffic pollution Environmental Exposure 030104 developmental biology Metabolome Environmental science |
| Zdroj: | Environment International, Vol 120, Iss, Pp 145-154 (2018) |
| ISSN: | 0160-4120 |
| Popis: | Background: High-resolution metabolomics (HRM) is emerging as a sensitive tool for measuring environmental exposures and biological responses. The aim of this analysis is to assess the ability of high-resolution metabolomics (HRM) to reflect internal exposures to complex traffic-related air pollution mixtures. Methods: We used untargeted HRM profiling to characterize plasma and saliva collected from participants in the Dorm Room Inhalation to Vehicle Emission (DRIVE) study to identify metabolic pathways associated with traffic emission exposures. We measured a suite of traffic-related pollutants at multiple ambient and indoor sites at varying distances from a major highway artery for 12 weeks in 2014. In parallel, 54 students living in dormitories near (20 m) or far (1.4 km) from the highway contributed plasma and saliva samples. Untargeted HRM profiling was completed for both plasma and saliva samples; metabolite and metabolic pathway alternations were evaluated using a metabolome-wide association study (MWAS) framework with pathway analyses. Results: Weekly levels of traffic pollutants were significantly higher at the near dorm when compared to the far dorm (p |
| Databáze: | OpenAIRE |
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