Lina Mu
Department of Epidemiology and Environmental Health
Background. The metabolome is a collection of exogenous chemicals and metabolites from cellular processes that may reflect the body's response to environmental exposures. Studies of air pollution and metabolomics are limited.
Objectives. To explore changes in the human metabolome before, during, and after the 2008 Beijing Olympics Games, when air pollution was high, low, and high, respectively. Methods. Serum samples were collected before, during, and after the Olympics from 26 participants in an existing panel study. Gas and ultra-high performance liquid chromatography/mass spectrometry were used in metabolomics analysis. Repeated measures ANOVA, network analysis, and enrichment analysis methods were employed to identify metabolites and classes associated with air pollution changes.
Results. A total of 886 molecules were measured in our metabolomics analysis. Network partitioning identified two known modules with 65 known metabolites that significantly changed across the three time points. All known molecules in the first module were lipids. The second module consisted primarily of dipeptides plus 8 metabolites from four other classes. Enrichment analysis of module-identified metabolites indicted significantly overrepresented pathways.
Conclusions. Metabolites in both lipids and dipeptides modules decreased during the 2008 Beijing Olympics, when air pollution was low, and increased after the Olympics, when air pollution returned to normal high levels.
Mu, Lina, et al. "Metabolomics Profiling before, during, and after the Beijing Olympics: A Panel Study of Within-Individual Differences during Periods of High and Low Air Pollution." Environmental health perspectives 127.5 (2019): 057010.
https://ehaniehs.nih.clovidoi/10.1289/EHP3705
This work was supported by the National Institutes of Health/National Institute of Environmental Health Sciences grants awarded to L. M. (grants R01ES018846 and R21ES026429) and National Cancer Institute grant awarded to H. Y. (grant P30CA016056).