Citation:

BENCIC, D. C., A. D. BIALES, R. W. FLICK, E. R. WAITS, TIM COLLETTE, D. GETER, M. OKINO, AND R. TORNERO-VELEZ. LINKING 'OMIC AND GENETIC DATA TO PHYSIOLOGICALLY-BASED PHARMACOKINETIC AND PHARMACODYNAMIC MODELING TO ENHANCE ECOLOGICAL AND HUMAN HEALTH RISK ASSESSMENT. Presented at 2005 EPA Science Forum, Washington, DC, May 16 - 18, 2005.

Impact/Purpose:

The indeterminate condition of exposure indicator research stands to change markedly with the ability to connect molecular biological technologies with cellular or tissue effects and outcomes. Three focal areas of ecological research aim to develop a sequence of approaches where "the earliest recognizable signatures of exposure" (i.e., unique patterns of up- and down-regulated genes and proteins) are identified for numerous stressors, demonstrable in case studies and incorporated into Agency, State and Regional studies supported by EMAP and other programs.

Area 1, Computational Toxicology Research: Exposure assessment has historically been based on use of chemical analysis data to generate exposure models. While biological activity of chemicals has been recognized to be important for exposure risk assessments, measurement of such activity has been limited to whole organism toxicity tests. Use of molecular approaches will:

improve extrapolation between components of source-to-outcome continuum (source , exposure , dose , effect , outcome)

Using a systems modeling approach, gene and protein expression data, in small fish models (fathead minnow and zebrafish), will be integrated with metabolomic and histopathological data. This will assist in prediction of environmental transformation and chemical effects based on structural characteristics, and enhance quantitative risk assessments, including areas of uncertainty such as a basis for extrapolation of effects of endocrine disrupting chemicals, interspecies extrapolation, complex chemical mixtures and dose-response assessment.

Area 2, Ecological Research-Environmental Diagnostics: Development of molecular diagnostic indicators contributes to several of the GPRA Diagnostic Research Goals. Methods will employ DNA microarray technology and expression proteomics, focusing on species of relevance to aquatic ecosystem risk assessment. Significantly, these diagnostic indicators will open the door to understanding subcellular interactions resulting from exposure to complex chemical mixtures.

define relationship between genetic disposition of populations and degree/specificity of stressor-specific gene transcriptional response in aquatic organisms (fish and invertebrates)

identify of chemical mixture induced transcriptional "patterns" using microarrays and hyperspectral scanning - via collaboration with DOE Sandia National Labs

apply molecular indicators to watershed level stressor study, including pilot studies with targeted pesticides and toxins indicators

develop molecular indicators of exposure for invertebrates (Daphnia, Lumbriculus, Chironomus)

Area 3, Exposure Research in Endocrine Disruptors:

Subobjective 1: Develop exposure methods, measurement protocols, and models for assessment of risk management practices of endocrine disrupting compounds. As risk management approaches are identified and developed, there will be a need to identify, adapt and develop bioassay screening tools and other analytical methods to assess their efficacy. Measurements research will be performed to define management needs. This effort will entail cross-lab participation from NRMRL, NERL and NHEERL.

Subobjective 2: Determine extent of environmental and human exposures to EDCs, characterize sources and factors influencing these exposures, develop and evaluate risk management strategies to reduce exposures. In order to develop effective risk management strategies, it is important to understand the extent of exposures to endocrine disrupting compounds and factors influencing source-to-exposure-to-dose relationships.

apply molecular indicators of exposure to estrogenic compounds in selected wastewater treatment plants located in ten USEPA Regions

identify differential gene expression following exposure of fathead minnows to environmental androgens and androgen-like compounds

apply molecular indicators of exposu

Description:

A great deal of academic, private sector, and government research has been initiated to apply advanced molecular biological methods to the discovery of toxicity pathways in wildlife and humans. One aim is the prediction of health outcomes based on the combination of refined chemical structure analysis with mechanistic data from systems biology studies. Quantitative ecological and human health risk assessments are expected to improve significantly. However, up to now, much less investment has been made in understanding the molecular mechanisms underlying the distribution, metabolism, and eventual excretion of stressors (i.e., pharmacokinetics and dose metrics).

A collaborative project across the U.S. Environmental Protection Agency (EPA)/ORD is being developed to use omic (genomic, proteomic, and metabolomic) and genetic technologies to provide data that would be directly incorporated into physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) models. The approach for this project integrates expertise across ecological and human health research sciences. Molecular as well as tissue-level and whole organism endpoints will be measured to reveal dose phenomena in model aquatic organisms, the water flea Daphnia pulex (invertebrate), and the zebrafish Danio rerio (vertebrate) to a prototypical chemical. These models have been and are presently the focus of considerable genome sequencing efforts that the U.S. EPA/ORD can use as a resource. In addition, genetic technologies (measurement of DNA sequence polymorphisms) will provide an opportunity to study the extent to which variation in pharmacologic parameters can be explained by genetics. The combination of all techniques will allow us to identify and compare novel dose- and time-dependent indicators across multiple biological and taxonomic levels while simultaneously critically evaluating the relevance and linkage of biological data generated from multiple experimental platforms. Integration of U.S. EPA/ORD bioinformatics capabilities with those of dose modelers has the potential to reduce the uncertainty in the exposure component of both ecological and human health risk assessments. Partnered with other researchers within the ORDs Computational Toxicology Program, this project has the additional potential of forming linkages across a considerable portion of the source-to-outcome continuum that is within the purview of the U.S. EPAs risk assessment mission.

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