P-0011 - Transcriptome-wide analyses of the effects of ambient PM2.5 and carbonaceous constituents: results of the AIRLESS project

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Background: Transcriptome-wide analyses is emerging as a useful tool to investigate the unclear mechanism behind the well-documented health effects of air pollution. However, the evidence remains limited in human based studies and mainly focused on the ambient fine particles (PM2.5). Methods: This study investigated the changes in gene expression profiles in response to acute exposure to ambient PM2.5 and its carbonaceous constituents. Based on the AIRLESS panel study, 251 nonsmoking senior participants living in urban (N=123) and rural (N=128) Beijing, China have undergone 4 times blood drawn. Total RNA was sequenced with RNA-seq technology by Hi-seq X10. Daily average concentrations of PM2.5, elemental carbon (EC), and organic carbon (OC) in ambient air were measured at a nearby monitoring site. Linear mixed-effects model was used to screen differentially expressed genes in association with exposure to air pollutants with adjustment for demographic, socio-economic and lifestyle variables, and consideration of false discovery rate (FDR) < 0.05. Pathway enrichment analyses were performed with Metacore platform. Results: The numbers of significantly changed genes associated with the exposure to PM2.5, EC, and OC were 1841, 1719, and 1670, respectively. Large proportions of changed genes were overlapped among the three pollutants, and the number of genes that only associated with PM2.5 was 9. Top 50 significantly up-regulated genes were mostly involved in cell differentiation and inflammatory response (e.g. EVIB2, C5AR1, CD52, CSF2RB and CSF3R), while down-regulated genes mainly related to mitochondrial function and protein synthesis (e.g. UQCRH, UQCRB, ATP5E, COX6C and FAU). Pathway enrichment analyses suggested potential mechanisms including inflammatory response, oxidative stress, apoptosis and survival, and neurogenesis, e.g. IL-3 signaling via ERK and PI3K, were strongly associated with PM2.5, OC, and EC. Conclusions: EC and OC might play key roles in PM-induced health effects. Transcriptome-wide analyses helped to unveil the potential molecular mechanisms of such effects.