National Center for Computational Toxicology

Key Contact: Jane Gallagher (NHEERL-HSD) FTE: (0.7), gallagher.jane@epa.gov; 919-966-0638

EPA has increasingly used mechanistic and molecular data in risk assessment practices as evidenced in the revised cancer risk assessment guidelines. EPA has begun to move away from reliance on traditional animal toxicology data, in part because advances in biomarker development have improved our ability to detect early changes at the molecular, cellular and pre-clinical level that are often predictive of adverse health outcomes. Integration of human and animal studies will address key concerns about animal-human extrapolation and will provide critical support for quantitative risk assessment. This computational toxicology proposal will integrate rodent and human research across the source-to-outcome continuum to link gene expression with biomarkers of exposure, early effect, and susceptibility for two broad classes of chemicals: polycyclic aromatic hydrocarbons (PAHs) and metals. We believe that gene expression changes will be useful as a predictor of early adverse health effects. Our proposal builds on two significant EPA initiatives in the Detroit Metropolitan Area: the National Exposure Research Laboratory's (NERL) Detroit Exposure Aerosol Research Study (DEARS) and the National Health Effects and Exposure Research Laboratory (NHEERL) Detroit Children's Health Study (DCHS). These studies will characterize exposures and assess the impact of chronic and/or early-life contact with area and mobile source emissions on the initiation of allergic asthma in school-aged children. In addition, investigators at the Michigan State University (MSU) are conducting real-world, urban-air rodent exposures, using a particulate matter (PM) concentrator. This computational toxicology proposal will allow us to leverage against these efforts by adding the following research components: (a) gene expression analyses for the MSU rodent concentrated PM studies, permitting comparison of blood and respiratory tract gene expression changes in relation to concurrently measured systemic and organ-specific blood and lung immunological and inflammatory responses; (b) a comprehensive biomarker study of exposures, early effects, and susceptibility among 200 school children in the DCHS with a range of asthma severity based on in-school lung function measurements. Biomarkers of asthma severity, including cell surface markers and inflammatory markers, will be assessed relative to clinical and spirometric measures of asthma severity. Using urine, blood, nails, and hair samples provided by children, we will establish whether body-burden measures of PAHs and metals correspond to modeled exposure estimates and asthma severity, and whether gene expression data are more sensitive than other indicators of exposure and effect. Aggregate body-burden, biomarkers of exposure, effect, susceptibility, gene expression data, and health outcome will be viewed in relation to changes of "signatures" predictive of toxicological and pathological effects. Our data will be analyzed using a multi-domain data base with pathological, pharmacological, and clinical effects, integrated with micro-array data from drugs, toxicants, and chemicals. Our proposal offers the opportunity to study fundamental interactions between genetic variability, gene expression, and proteomics. For two classes of chemicals that are commonly detected in humans, we will analyze biomarkers of exposure and effect in a systematic way using gene expression analysis, bioinformatics and computational toxicology to provide more meaningful data for risk assessment compared to studies that focus on discrete biological events in a source-to-outcome paradigm.

View Peer Reviewed Publications