Academic journal article Environmental Health Perspectives

Addressing Human Variability in Next-Generation Human Health Risk Assessments of Environmental Chemicals

Academic journal article Environmental Health Perspectives

Addressing Human Variability in Next-Generation Human Health Risk Assessments of Environmental Chemicals

Article excerpt

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.

KEY WORDS: environmental agents, genetics, human health risk assessment, modeling, omics technologies, susceptible populations, variability. Environ Health Perspect 121:23-31 (2013). [Online 19 October 2012]

Human variability underlies differences in the degrees and ways in which people respond to environmental chemicals, and addressing these differences is a key consideration in human health risk assessments for chemicals [Guyton et al. 2009; Hattis et al. 2002; National Research Council (NRC) 2009]. A large array of possible health outcomes is of concern for such assessments, and many sources of variation can influence the severity and frequency of the adverse effects at different exposure levels. These sources may be intrinsic (e.g., heritable traits, life stage, aging), or extrinsic, exogenous, and acquired (e.g., background health conditions, co-occurring chemical exposures, food and nutrition status, psychosocial stressors). Interactions between inherent and extrinsic factors create the large range of biological variation exhibited in response to a chemical exposure (NRC 2009). Given that biological variability in susceptibility is context-dependent, so too is the extent to which it needs to be described and quantified to inform any particular environmental decision. The salience of variability information for specific choices is affected by the range of available risk management options; the regulatory authority; the available time, resources, and expertise to collect data and conduct analyses; and stakeholder concerns.

Over the past decade, efforts to systematically "map" human variability have expanded dramatically, focusing mainly on genetic variation (Schadt and Bjorkegren 2012). In addition to genetic differences, omics studies have examined the impact of epigenetic, transcriptomic, proteomic, and metabolomic variation on disease susceptibility, prognosis, or options for pharmacotherapy (Chen et al. 2008; Emilsson et al. 2008; Illig et al. 2010; Manolio 2010; Schadt 2009). Tailored chemotherapy treatment based on patient (Phillips and Mallal 2010) or tumor (La Thangue and Kerr 2011) genetics is an example of a significant success in applying such discoveries; however, for many diseases, the substantial nongenetic variation in disease or treatment outcomes has limited their utility. …

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