Serena Fossati1, Andrea Baccarelli, Antonella Zanobetti, Mirjam Hoxha, Pantel S Vokonas, Robert O Wright, Joel Schwartz. 1. From the Departments of aEnvironmental Health and cEpidemiology, Harvard School of Public Health, Boston, MA; bDepartment of Biomedical and Clinical Sciences "Luigi Sacco," University of Milan, Milan, Italy; dLaboratory of Environmental Epigenetics, Department of Environmental and Occupational Health, University of Milan, Milan, Italy; eVA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, MA; and fGenetic Epidemiology Unit, Channing Laboratory, Brigham and Women's Hospital, Boston, MA.
Abstract
BACKGROUND: Ambient particulate matter (PM) has been associated with mortality and morbidity for cardiovascular disease. MicroRNAs control gene expression at a posttranscriptional level. Altered microRNA expression has been reported in processes related to cardiovascular disease and PM exposure, such as systemic inflammation, endothelial dysfunction, and atherosclerosis. Polymorphisms in microRNA-related genes could influence response to PM. METHODS: We investigated the association of exposure to ambient particles in several time windows (4-hour to 28-day moving averages) and blood leukocyte expression changes in 14 candidate microRNAs in 153 elderly males from the Normative Aging Study (examined 2005-2009). Potential effect modification by six single nucleotide polymorphisms (SNPs) in three microRNA-related genes was investigated. Fine PM (PM2.5), black carbon, organic carbon, and sulfates were measured at a stationary ambient monitoring site. Linear regression models, adjusted for potential confounders, were used to assess effects of particles and SNP-by-pollutant interaction. An in silico pathway analysis was performed on target genes of microRNAs associated with the pollutants. RESULTS: We found a negative association for pollutants in all moving averages and miR-1, -126, -135a, -146a, -155, -21, -222, and -9. The strongest associations were observed with the 7-day moving averages for PM2.5 and black carbon and with the 48-hour moving averages for organic carbon. The association with sulfates was stable across the moving averages. The in silico pathway analysis identified 18 pathways related to immune response shared by at least two microRNAs; in particular, the "high-mobility group protein B1/advanced glycosylation end product-specific receptor signaling pathway" was shared by miR-126, -146a, -155, -21, and -222. No important associations were observed for miR-125a-5p, -125b, -128, -147, -218, and -96. We found significant SNP-by-pollutant interactions for rs7813, rs910925, and rs1062923 in GEMIN4 and black carbon and PM2.5 for miR-1, -126, -146a, -222, and -9, and for rs1640299 in DGCR8 and SO4 for miR-1 and -135a. CONCLUSIONS: Exposure to ambient particles could cause a downregulation of microRNAs involved in processes related to PM exposure. Polymorphisms in GEMIN4 and DGCR8 could modify these associations.
BACKGROUND: Ambient particulate matter (PM) has been associated with mortality and morbidity for cardiovascular disease. MicroRNAs control gene expression at a posttranscriptional level. Altered microRNA expression has been reported in processes related to cardiovascular disease and PM exposure, such as systemic inflammation, endothelial dysfunction, and atherosclerosis. Polymorphisms in microRNA-related genes could influence response to PM. METHODS: We investigated the association of exposure to ambient particles in several time windows (4-hour to 28-day moving averages) and blood leukocyte expression changes in 14 candidate microRNAs in 153 elderly males from the Normative Aging Study (examined 2005-2009). Potential effect modification by six single nucleotide polymorphisms (SNPs) in three microRNA-related genes was investigated. Fine PM (PM2.5), black carbon, organic carbon, and sulfates were measured at a stationary ambient monitoring site. Linear regression models, adjusted for potential confounders, were used to assess effects of particles and SNP-by-pollutant interaction. An in silico pathway analysis was performed on target genes of microRNAs associated with the pollutants. RESULTS: We found a negative association for pollutants in all moving averages and miR-1, -126, -135a, -146a, -155, -21, -222, and -9. The strongest associations were observed with the 7-day moving averages for PM2.5 and black carbon and with the 48-hour moving averages for organic carbon. The association with sulfates was stable across the moving averages. The in silico pathway analysis identified 18 pathways related to immune response shared by at least two microRNAs; in particular, the "high-mobility group protein B1/advanced glycosylation end product-specific receptor signaling pathway" was shared by miR-126, -146a, -155, -21, and -222. No important associations were observed for miR-125a-5p, -125b, -128, -147, -218, and -96. We found significant SNP-by-pollutant interactions for rs7813, rs910925, and rs1062923 in GEMIN4 and black carbon and PM2.5 for miR-1, -126, -146a, -222, and -9, and for rs1640299 in DGCR8 and SO4 for miR-1 and -135a. CONCLUSIONS: Exposure to ambient particles could cause a downregulation of microRNAs involved in processes related to PM exposure. Polymorphisms in GEMIN4 and DGCR8 could modify these associations.
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