New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures

By Harrill, Alison H.; McAllister, Kimberly A. | Environmental Health Perspectives, August 2017 | Go to article overview

New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures


Harrill, Alison H., McAllister, Kimberly A., Environmental Health Perspectives


Introduction

Environmental scientists worldwide are tasked with assessing health risks of environmental exposures to chemicals, and the methodology used to assess risks is continually evolving. Chemical risk assessments involve evaluation of exposure and prediction of health risks and outcomes with the goal to inform decision making to control or otherwise respond to environmental hazards. Biological variability is an important factor in defining human responses to chemical exposures and variability--of various etiologies--can contribute to whether an individual is susceptible or resistant to an adverse outcome. Variation in response to chemicals is determined by both extrinsic (e.g., co-morbidities, exposure dose concentration, co-exposures, nutrition, and psychosocial stressors) and intrinsic (e.g., genetic sequence or epigenetic variation, age/life stage, sex) factors (Zeise et al. 2013).

Because assessment of risk inherently involves variability in responses, the methods used in risk assessment must be designed to quantitatively address population variation with precision. Uncertainties exist, in the estimation of exposures, the identification and measurement of health effects associated with exposures, and the methodologies used to assess and characterize population and occupational risks. The current risk assessment paradigm utilizes a standardized uncertainty or threshold factor to account for variability in cases where population-based data are unavailable (U.S. EPA 2014). As methods for assessing population health risks evolve, an emerging idea is to actively consider multiple determinants of population health and their interactions prior to the design of testing strategies. Advances in molecular methods and an interest in pathway-based risk assessments have driven interest in development of a next generation "NextGen" framework or risk assessment (Cote et al. 2016).

Advanced risk assessment techniques, a population health approach, and the NextGen framework for risk science are crucial elements for the protection of particularly sensitive individuals within exposed populations. Indeed, the challenges and opportunities to address human variability in NextGen risk assessments was recently reviewed extensively by Zeise and coauthors (Zeise et al. 2013). Furthermore, the benefits of understanding gene-environment connections and understanding their implication for risk management has been argued to be an integral component of NextGen risk strategies (Krewski et al. 2014).

To implement this new strategy, new tools are necessary for assessing population-level responses for which the determinants of health outcomes can be multifactorial. Genetic variation contributes substantially to interindividual differences in susceptibility to toxicant-induced adverse health events (Collins et al. 2016). Recent data suggest that an improved understanding of the genetic variability of toxicant responses will enable more accurate chemical toxicity assessments, and methods to enable use of population-level data to predict toxicity risks are an area of active investigation (Eduati et al. 2015). Development of a variety of tools is necessary to identify the range of human responses to chemical hazards.

Epidemiological studies in humans are costly, time consuming, and often confounded by other factors such as age, co-morbidities, and exposures to a wide variety of chemical exposures over the lifetime of the individual. Studies of human populations will always provide the strongest causal evidence of toxicity when they are available, but when they are not, the use of genetically diverse mouse populations can be a powerful tool to model human population responses. When human evidence is limited, experimental models can identify sensitivities of relevance to humans and support or further characterize findings in human populations, strengthening the biological plausibility of the evidence in humans. …

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