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Environ Health. 2016 Nov 3;15(1):101.

Gene expression network analyses in response to air pollution exposures in the trucking industry.

Author information

1
Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA. jen-hwa.chu@yale.edu.
2
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
3
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
4
Pulmonary, Allergy, Sleep, and Critical Care Medicine Section, VA Boston Healthcare System, Boston, MA, USA.
5
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
6
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.

Abstract

BACKGROUND:

Exposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk.

METHODS:

To better understand the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at 10 trucking terminals in the northeastern US. We defined genes and gene networks that were differentially activated in response to PM2.5 (particulate matter ≤ 2.5 microns in diameter) and elemental carbon (EC) and organic carbon (OC).

RESULTS:

Multiple transcripts were strongly associated (padj < 0.001) with pollutant levels (48, 260, and 49 transcripts for EC, OC, and PM2.5, respectively), including 63 that were statistically significantly correlated with at least two out of the three exposures. These genes included many that have been implicated in ischemic heart disease, chronic obstructive pulmonary disease (COPD), lung cancer, and other pollution-related illnesses. Through the combination of Gene Set Enrichment Analysis and network analysis (using GeneMANIA), we identified a core set of 25 interrelated genes that were common to all three exposure measures and were differentially expressed in two previous studies assessing gene expression attributable to air pollution. Many of these are members of fundamental cancer-related pathways, including those related to DNA and metal binding, and regulation of apoptosis and also but include genes implicated in chronic heart and lung diseases.

CONCLUSIONS:

These data provide a molecular link between the associations of air pollution exposures with health effects.

KEYWORDS:

Air pollution; Gene expression; Network analysis; Trucking industry

PMID:
27809917
PMCID:
PMC5093980
DOI:
10.1186/s12940-016-0187-z
[Indexed for MEDLINE]
Free PMC Article

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