Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure
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Date
2021-01Author
Merid, Simon Kebede
Bustamante, Mariona
Standl, Marie
Sunyer, Jordi
Heinrich, Joachim
Lemonnier, Nathanael
Aguilar, Daniel
Antó, Josep Maria
Bousquet, Jean
Santa Marina, Loreto
Lertxundi Manterola, Aitana
Bergstrom, Anna
Kull, Inger
Wheelock, Asa M.
Koppelman, Gerard H.
Melen, Erik
Gruzieva, Olena
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Environment International 146 : (2021) // Article ID 106248
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 mu m 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.