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ToxSci Advance Access originally published online on April 21, 2007
Toxicological Sciences 2007 98(1):240-248; doi:10.1093/toxsci/kfm092
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© The Author 2007. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A Method to Integrate Benchmark Dose Estimates with Genomic Data to Assess the Functional Effects of Chemical Exposure

Russell S. Thomas*,1, Bruce C. Allen{dagger}, Andy Nong*, Longlong Yang*, Edilberto Bermudez*, Harvey J. Clewell, III* and Melvin E. Andersen*

* The Hamner Institutes for Health Sciences, Division of Computational Biology, Research Triangle Park, North Carolina 27709-2137 {dagger} Bruce Allen Consulting, 101 Corbin Hill Circle, Chapel Hill, North Carolina 27514

1 To whom correspondence should be addressed at The Hamner Institutes for Health Sciences, Division of Computational Biology, 6 Davis Drive, PO Box 12137, Research Triangle Park, NC 27709-2137. Fax: (919) 558-1300. E-mail: rthomas{at}thehamner.org.

Received February 9, 2007; accepted April 16, 2007


  Abstract

The use of genomic technology for assessing health risks associated with chemical exposure has significant potential, but its direct application has proven to be challenging for the toxicology and risk assessment communities. In this study, a method was established for analyzing dose-response microarray data using benchmark dose (BMD) calculations and gene ontology (GO) classification. Gene expression changes in the rat nasal epithelium following acute formaldehyde exposure were used as a case study. The gene expression data were first analyzed using a one-way ANOVA to identify genes that showed significant dose-response behavior. These genes were then fit to a series of four statistical models (linear, second-degree polynomial, third-degree polynomial, and power models) and the least complex model that best described the data was selected. The genes were matched to their associated GO categories, and the average BMD and benchmark dose lower confidence limit (BMDL) were calculated for each GO category. The results were used to identify doses at which individual cellular processes were altered. For the formaldehyde exposures, the BMD estimates for the GO categories related to cell proliferation and DNA damage were similar to those measured in previous studies using cell labeling indices and DNA-protein cross-links and consistent with the BMD estimated for rat nasal tumors. The method represents a significant advance in applying genomic information to risk assessment by allowing a comprehensive survey of molecular changes associated with chemical exposure and providing the capability to identify reference doses at which particular cellular processes are altered.

Key Words: bioinformatics; methods; dose-response; risk assessment; nose; respiratory toxicology; microarray; methods; regulatory/policy; risk assessment; toxicogenomics; methods.


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