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Addressing human variability in next-generation human health risk assessments of environmental chemicals
Lauren Zeise1, Frederic Y Bois, Weihsueh A Chiu
1Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, Oakland, California 94612, USA. Lauren.Zeise@oehha.ca.gov
Background:
Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment.
Objective:
Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum.
Methods:
This review was informed by a National Research Council workshop titled "Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making." We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals.
Discussion:
One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population.
Conclusions:
Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts.
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