Affiliation:
1. Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo , Oslo 0317,
2. Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam , Rotterdam 3015,
3. Department of Pharmacology and Toxicology, University of Toronto , Toronto, ON M5S1A8,
4. Norwegian National Advisory Unit on Familial Hypercholesterolemia, Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital , Oslo 0424,
Abstract
Abstract
Exposure to air pollution and an unhealthy built environment increase disease risk by impacting metabolic risk factors and inflammation, potentially via epigenetic modifications and effects on gene expression. We aimed to explore associations between fine particulate matter (PM2.5), black carbon, ozone, nitrogen dioxide, distance to nearest water body, normalized difference vegetation index, and impervious surface and gene expression profiles in adults. This study is a part of the LongITools project and includes cross-sectional data from the Rotterdam Study, a population-based cohort study, and NoMa, a randomized controlled trial. Environmental exposures were assigned using land-use regression (LUR) models and satellite data. Gene expression was assessed with whole blood RNA sequencing (Rotterdam Study, n = 758) and microarray analyses in peripheral blood mononuclear cells (NoMa, n = 100). We analysed transcriptomic profiles and enriched pathways associated with each of the environmental exposures. PM2.5 had the strongest gene expression associations, while only a few significant associations were observed for the other environmental exposures. In both populations, exposure to PM2.5 was associated with genes and pathways related to inflammation, oxidative stress, DNA metabolism, cell cycle regulation, histones, electron transport chain, oxidative phosphorylation, and neural signalling. This study is limited by different methods for RNA quantification, a cross-sectional design, and a small sample size. However, in both populations, exposure to PM2.5 resulted in the maximum number of associations with gene expression. In conclusion, PM2.5 is strongly associated with various gene expression profiles, which provide information about the underlying mechanisms of the detrimental health effects of exposure to PM2.5.
Funder
Erasmus Medical Center and Erasmus University, Rotterdam
Throne Holst foundation for nutrition research, University of Oslo
the Municipality of Rotterdam.
European Union’s Horizon 2020
the Research Institute for Diseases in the Elderly
the Ministry of Education, Culture and Science, NL
Netherlands Organization for the Health Research and Development
Publisher
Oxford University Press (OUP)