Exposure to fine particulate matter in adults is associated with immune cell gene expression related to inflammation, the electron transport chain, and cell cycle regulation.

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 (PM_2.5), 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. PM_2.5 had the strongest gene expression associations, while only a few significant associations were observed for the other environmental exposures. In both populations, exposure to PM_2.5 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 PM_2.5 resulted in the maximum number of associations with gene expression. In conclusion, PM_2.5 is strongly associated with various gene expression profiles, which provide information about the underlying mechanisms of the detrimental health effects of exposure to PM_2.5.