Journal
ENVIRONMENTAL HEALTH PERSPECTIVES
Volume 121, Issue 1, Pages 23-31Publisher
US DEPT HEALTH HUMAN SCIENCES PUBLIC HEALTH SCIENCE
DOI: 10.1289/ehp.1205687
Keywords
environmental agents; genetics; human health risk assessment; modeling; omics technologies; susceptible populations; variability
Ask authors/readers for more resources
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 inter-individual 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 inter-individual variability in the human population. CONCLUSIONS: Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing inter-individual variability in a range of decision-making contexts.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available