Using omics in the risk assessment of benzene

Introduction:   Benzene is an important industrial chemical and ubiquitous environmental contaminant that is known to cause leukemia.  Workers in shipping, automobile repair, shoe manufacture, driving, and refining/transportation of oil and gasoline are routinely exposed to benzene. Benzene was first identified as a hematotoxic agent over 100 years ago and the U.S. occupational standard has declined from 100 ppm in 1930s to 1 ppm in 1987. The TLV is currently 0.5 ppm. However, concern remains over safety as we have shown that benzene produces hematological changes and effects on gene expression at airborne concentrations lower than 1 ppm.  We have now extensively examined the dose-response for the effects of benzene exposure on the human blood transcriptome as part of a systems biology approach to understanding the health risks posed by benzene.    

Methods:   We have applied a variety of omic technologies in populations of benzene exposed workers. In the current study, we have statistically modeled microarray data published in McHale et al. (2011) Environ. Health Perspect. 119(5):628-34 and other data from our studies using SuperLearner estimates of E[Y|Dose,W].    

Results:   Dose-response curves for various KEGG pathways, including the one for acute myeloid leukemia, were generated. These show a supra-linear dose response that is linear in the low-dose region then plateaus at higher levels of exposure. These data are in agreement with toxicokinetic models of reactive metabolite formation following benzene exposure.    

Conclusion:   Omic technologies can be used to biomonitor workers exposed to benzene and other substances and can inform the risk assessment process through dose-response modeling.