Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure
Simon Kebede Merid, Mariona Bustamante, Marie Standl, Jordi Sunyer, Joachim Heinrich, Nathanaël Lemonnier, Daniel Aguilar, Josep M. Antó, Jean Bousquet, Loreto Santa‐Marina, Aitana Lertxundi, Anna Bergström, Inger Kull, Åsa M. Wheelock, Gerard H. Koppelman, Erik Melén, Olena Gruzieva
Abstract
Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM2.5 exposure.