Long-Term Goal 3-10: Research Description

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Research Descriptions and Posters

Title: How is ORD Leading the Effort to Improve Our Understanding of the Aging Population's Susceptibility to Environmental Stressors?

Presenters: Chris Corton (NHEERL), Bob MacPhail (NHEERL) and Tom McCurdy (NERL)

Contributors: Vernon Benignus (NHEERL), Will Boyes (NHEERL), Mike DeVito (NHEERL), Christopher Gordon (NHEERL), Elaina Kenyon (NHEERL), Prasada Kodavanti (NHEERL), Urmila Kodavanti (NHEERL), Janice S Lee (NCEA), Anna Lowit (OPP), Ginger Moser (NHEERL), Joyce Royland (NHEERL), Kent Thomas (NERL), Nicolle Tulve (NERL), Jim Raymer (RTI), Jan Busby-Whitehead (UNC), Harvey Clewell (Hamner Institutes), Miyoung Yoon (Hamner Institutes).

Science Questions:

What is ORD doing to improve our knowledge base?
What have we found?
What still needs to be done?

The Research:

What is ORD doing to improve our knowledge base?

ORD is delineating exposure-dose-response relationships for aging individuals.
Exposure efforts are consolidating data on human activity patterns, physiological parameters affecting dose, and stratifying the older adult population to identify at-risk subgroups.
Animal models of aging are being used to determine the effects and disposition of environmental chemicals in multiple target organs (brain, heart and liver), and at multiple levels of biological organization ranging from gene expression to physiology and behavior.

What have we found?

Analyses of NHANES and NHEXAS data bases have identified differences between older and younger adults in toxicants found in biological samples and/or environmental media; NHANES biomarker data indicate information on age, health status, activity, diet, and medications may be useful to stratify the aging population for risk assessment.
Data on physiological parameters for the aging population and subgroups has been extracted from the literature for application in exposure models.
New activity data for individuals 60+ years old have been added to ORD's Consolidated Human Activity Database (CHAD); analyses highlight the importance of longitudinal data for accurate exposure assessment.
Changes with age in liver metabolic activity appear small, but could lead to prolonged toxicant-tissue residence and increased toxicity when coupled with reduced renal clearance.
Age comparisons of gene expression in mouse, rat and human livers indicate little overlap in individual genes, but differential regulation of gene classes involved in toxicant transport.
Age increases susceptibility to toxic substances but is endpoint dependent; effects are either greater than or equal to those in young-adult animals, but not less.
In some cases, variability in toxicant response increases in older animals; analyses of these data have resulted in a novel method that explicitly incorporates effect variability into risk estimates.

What still needs to be done?

Complete open-access quantitative human physiology (QHP) and PBPK models that incorporate age-dependent changes in organ function and metabolic activity to estimate target-tissue dose, reconstruct dose for exposure assessment, and link to adverse outcomes.
Conduct longitudinal studies to identify early biomarkers and/or predisposing events, increase statistical power and reduce uncertainty in exposure and dose-response estimates for older adults.
Extend exposure-dose-response models to explicitly incorporate variability and uncertainty, and allow stratification of at-risk subgroups when necessary. This is consonant with research in LTG 2 on the propagation of uncertainty and variability estimates along the pathway from exposure to outcome.

Impact and Outcomes:

The EPA must explicitly incorporate variability and uncertainty in exposure (including activity pattern), dose and response models in assessing the risks to older adults; even a small shift in mean sensitivity for this age group could dramatically increase risk if the variance also increased.
CHAD data have been used in several NAAQS standards and reviews. An expanded CHAD database and open-access database of physiological parameters for older adults will allow direct consideration of the potential susceptibility of older adults in developing exposure and tissue dosimetry models for risk assessment.
The creation of publicly accessible databases and other tools for modeling the potential risks of exposure of older adults to environmental contaminants complements those of ORD's partners in OCHPEE on disseminating educational materials for risk awareness and mitigation in this growing aging population.

Key Products:

EPA's Aging Research. Response to the U.S. Senate Special Committee on Aging request for descriptions of U.S. EPA research for the Report on Recognition of Excellence in Aging Research, June 27, 2008.

Frazier, E.L., McCurdy, T., Williams, R. et al. Intra- and inter-individual variability in location data for two U.S. health-compromised elderly cohorts. J. Expo. Sci. Environ. Epidemiol. 2008 August 27. [Epub ahead of print]

Graham S and McCurdy T. Developing meaningful cohorts for human exposure models. J. Expos. Anal. Environ. Epidemiol. 14:23-43 (2004).

Lee J.S., Ward, W.O., Wolf, D.C. et al. Coordinated changes in xenobiotic metabolizing enzyme gene expression in aging male rats. Toxicol. Sci. 106:263-283 (2008).

Li, Z. Wright, F.A., Royland, J. Age-dependent variability in gene expression in male Fisher 344 rat retina. Toxicol. Sci. 2008 October 20. [Epub ahead of print]

McCurdy T., Glen, L., Smith, L. and Smith, L. The National Exposure Research Laboratory's Consolidated Human Activity Database (CHAD). J. Expos. Anal. Environ. Epidemiol. 10:566-578 (2000).

McCurdy T. and Graham S. Using activity data in exposure models: Analysis of discriminating factors. J. Expos. Anal. Environ. Epidemiol. 13:294-317 (2003).

Rodriguez C.E., Mahle, D.A., Gearhart, J.M. et al. Predicting age-appropriate pharmacokinetics of six volatile organic compounds in the rat utilizing physiologically based pharmacokinetic modeling. Toxicol. Sci 98:43-56 (2007).

Yokley K.A. and Evans M.V. Physiological changes associated with aging result in lower internal doses of toluene and perchloroethylene in simulations using pharmacokinetic modeling. Toxicol. Environ. Chem. 90:475-492 (2008).

Long-Term Goal 3-10: Research Description

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