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Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century
Citation:
MORTENSEN, H. M. AND S. EULING. Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century. TOXICOLOGY AND APPLIED PHARMACOLOGY. Elsevier BV, AMSTERDAM, Netherlands, (Online):1-10, (2011).
Impact/Purpose:
The information that would come from applying this approach would be useful to human health risk assessment in its current form. In the current risk assessment paradigm, information on human genetic susceptibility, when available, is incorporated qualitatively and/or quantitatively. Additionally, differential susceptibility in response to benzene exposure is an example that could be better characterized by including recent human polymorphism data for the gene and pathway perturbations identified after benzene exposure, from a representative global panel. The approach, outlined herein, of combining next generation sequencing data with human mechanistic data for environmental chemicals will inform the relationship between human toxicity pathways, genetic susceptibility, and disease progression (including precursor events) and this information could be applied to risk assessment.
Description:
Response to environmental chemicals can vary widely among individuals and between population groups. In human health risk assessment, data on susceptibility can be utilized by deriving risk levels based on a study of a susceptible population and/or an uncertainty factor may be applied to account for the lack of information about susceptibility. Defining genetic susceptibility in response to environmental chemicals across human populations is an area of interest in the NAS' new paradigm of toxicity pathway-based risk assessment. Data from high-throughput/high content (HT/HC), including -omics (e.g., genomics, transcriptomics, proteomics, metabolomics) technologies, have been integral in the identification and characterization of drug target and disease loci, and have been successfully utilized to inform the mechanism of action for numerous environmental chemicals. Large-scale population genotyping studies may help to characterize levels of variability across human populations at identified target loci implicated in response to environmental chemicals. By combining mechanistic data for a given environmental chemical with next generation sequencing data that provides human population variation information, one can begin to characterize differential susceptibility due to genetic variability to environmental chemicals within and across genetically heterogeneous human populations. The integration of such data sources will be informative to human health risk assessment.
