E Drizik1, S Corbett2, Y Zheng3, R Vermeulen4, Y Dai5, W Hu6, D Ren7, H Duan5, Y Niu5, J Xu8, W Fu7, K Meliefste4, B Zhou5, Xiaohui Zhang1, J Yang7, Bryan Bassig6, Hanqiao Liu1, M Ye5, Gang Liu1, X Jia5, T Meng5, P Bin5, J Zhang9, D Silverman6, A Spira10, N Rothman6, M E Lenburg11, Q Lan6. 1. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA. 2. Bioinformatics Program, Boston University, Boston, MA, USA. 3. Key Laboratory of Chemical Safety and Health, National Institute of Occupational, Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China. Electronic address: yxzheng@qdu.edu.cn. 4. Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands. 5. Key Laboratory of Chemical Safety and Health, National Institute of Occupational, Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China. 6. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. 7. Chaoyang Center for Disease Control and Prevention, Chaoyang, China. 8. Hong Kong University, Hong Kong, China. 9. Nicholas School of the Environment and Duke Global Health Institute, Duke University, Durham, NC, USA; Global Health Research Center, Duke Kunshan University, Kunshan City, Jiangsu Province, China. 10. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA; Bioinformatics Program, Boston University, Boston, MA, USA; The Lung Cancer Initiative at Johnson & Johnson, Cambridge, MA, USA. 11. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA; Bioinformatics Program, Boston University, Boston, MA, USA. Electronic address: mlenburg@bu.edu.
Abstract
BACKGROUND: Diesel engine exhaust (DEE) exposure causes lung cancer, but the molecular mechanisms by which this occurs are not well understood. OBJECTIVES: To assess transcriptomic alterations in nasal epithelium of DEE-exposed factory workers to better understand the cellular and molecular effects of DEE. METHODS: Nasal epithelial brushings were obtained from 41 diesel engine factory workers exposed to relatively high levels of DEE (17.2-105.4 μg/m3), and 38 unexposed workers from factories without DEE exposure. mRNA was profiled for gene expression using Affymetrix microarrays. Linear modeling was used to identify differentially expressed genes associated with DEE exposure and interaction effects with current smoking status. Pathway enrichment among differentially expressed genes was assessed using EnrichR. Gene Set Enrichment Analysis (GSEA) was used to compare gene expression patterns between datasets. RESULTS: 225 genes had expression associated with DEE exposure after adjusting for smoking status (FDR q < 0.25) and were enriched for genes in pathways related to oxidative stress response, cell cycle pathways such as MAPK/ERK, protein modification, and transmembrane transport. Genes up-regulated in DEE-exposed individuals were enriched among the genes most up-regulated by cigarette smoking in a previously reported bronchial airway smoking dataset. We also found that the DEE signature was enriched among the genes most altered in two previous studies of the effects of acute DEE on PBMC gene expression. An exposure-response relationship was demonstrated between air levels of elemental carbon and the first principal component of the DEE signature. CONCLUSIONS: A gene expression signature was identified for workers occupationally exposed to DEE that was altered in an exposure-dependent manner and had some overlap with the effects of smoking and the effects of acute DEE exposure. This is the first study of gene expression in nasal epithelial cells of workers heavily exposed to DEE and provides new insights into the molecular alterations that occur with DEE exposure.
BACKGROUND: Diesel engine exhaust (DEE) exposure causes lung cancer, but the molecular mechanisms by which this occurs are not well understood. OBJECTIVES: To assess transcriptomic alterations in nasal epithelium of DEE-exposed factory workers to better understand the cellular and molecular effects of DEE. METHODS: Nasal epithelial brushings were obtained from 41 diesel engine factory workers exposed to relatively high levels of DEE (17.2-105.4 μg/m3), and 38 unexposed workers from factories without DEE exposure. mRNA was profiled for gene expression using Affymetrix microarrays. Linear modeling was used to identify differentially expressed genes associated with DEE exposure and interaction effects with current smoking status. Pathway enrichment among differentially expressed genes was assessed using EnrichR. Gene Set Enrichment Analysis (GSEA) was used to compare gene expression patterns between datasets. RESULTS: 225 genes had expression associated with DEE exposure after adjusting for smoking status (FDR q < 0.25) and were enriched for genes in pathways related to oxidative stress response, cell cycle pathways such as MAPK/ERK, protein modification, and transmembrane transport. Genes up-regulated in DEE-exposed individuals were enriched among the genes most up-regulated by cigarette smoking in a previously reported bronchial airway smoking dataset. We also found that the DEE signature was enriched among the genes most altered in two previous studies of the effects of acute DEE on PBMC gene expression. An exposure-response relationship was demonstrated between air levels of elemental carbon and the first principal component of the DEE signature. CONCLUSIONS: A gene expression signature was identified for workers occupationally exposed to DEE that was altered in an exposure-dependent manner and had some overlap with the effects of smoking and the effects of acute DEE exposure. This is the first study of gene expression in nasal epithelial cells of workers heavily exposed to DEE and provides new insights into the molecular alterations that occur with DEE exposure.
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Authors: Denise N Slenter; Martina Kutmon; Kristina Hanspers; Anders Riutta; Jacob Windsor; Nuno Nunes; Jonathan Mélius; Elisa Cirillo; Susan L Coort; Daniela Digles; Friederike Ehrhart; Pieter Giesbertz; Marianthi Kalafati; Marvin Martens; Ryan Miller; Kozo Nishida; Linda Rieswijk; Andra Waagmeester; Lars M T Eijssen; Chris T Evelo; Alexander R Pico; Egon L Willighagen Journal: Nucleic Acids Res Date: 2018-01-04 Impact factor: 16.971