Leveraging Epidemiology to Improve Risk Assessment.

The field of environmental public health is at an important crossroad. Our current biomonitoring efforts document widespread exposure to a host of chemicals for which toxicity information is lacking. At the same time, advances in the fields of genomics, proteomics, metabolomics, genetics and epigenetics are yielding volumes of data at a rapid pace. Our ability to detect chemicals in biological and environmental media has far outpaced our ability to interpret their health relevance, and as a result, the environmental risk paradigm, in its current state, is antiquated and ill-equipped to make the best use of these new data. In light of new scientific developments and the pressing need to characterize the public health burdens of chemicals, it is imperative to reinvigorate the use of environmental epidemiology in chemical risk assessment. Two case studies of chemical assessments from the Environmental Protection Agency Integrated Risk Information System database are presented to illustrate opportunities where epidemiologic data could have been used in place of experimental animal data in dose-response assessment, or where different approaches, techniques, or studies could have been employed to better utilize existing epidemiologic evidence. Based on the case studies and what can be learned from recent scientific advances and improved approaches to utilizing human data for dose-response estimation, recommendations are provided for the disciplines of epidemiology and risk assessment for enhancing the role of epidemiologic data in hazard identification and dose-response assessment

Application of a Key Events Dose-Response Analysis to Nutrients: A Case Study with Vitamin A (Retinol)

The methodology used to establish tolerable upper intake levels (UL) for nutrients borrows heavily from risk assessment methods used by toxicologists. Empirical data are used to identify intake levels associated with adverse effects, and Uncertainty Factors (UF) are applied to establish ULs, which in turn inform public health decisions and standards. Use of UFs reflects lack of knowledge regarding the biological events that underlie response to the intake of a given nutrient, and also regarding the sources of variability in that response. In this paper, the Key Events Dose-Response Framework (KEDRF) is used to systematically consider the major biological steps that lead from the intake of the preformed vitamin A to excess systemic levels, and subsequently to increased risk of adverse effects. Each step is examined with regard to factors that influence whether there is progression toward the adverse effect of concern. The role of homeostatic mechanisms is discussed, along with the types of research needed to improve understanding of dose-response for vitamin A. This initial analysis illustrates the potential of the KEDRF as a useful analytical tool for integrating current knowledge regarding dose-response, generating questions that will focus future research efforts, and clarifying how improved knowledge and data could be used to reduce reliance on UFs

A Parametric Model for Detecting Hormetic Effects in Developmental Toxicity Studies

Hormetic effects have been observed at low exposure levels based on the dose-response pattern of data from developmental toxicity studies. This indicates that there might actually be a reduced risk of exhibiting toxic effects at low exposure levels. Hormesis implies the existence of a threshold dose level and there are dose-response models that include parameters that account for the threshold. We propose a function that introduces a parameter to account for hormesis. This function is a subset of the set of all functions that could represent a hormetic dose-response relationship at low exposure levels to toxic agents. We characterize the overall dose-response relationship with a piecewise function that consists of a hormetic u-shape curve at low dose levels and a logistic curve at high dose levels. We apply our model to a data set from an experiment conducted at the National Toxicology Program (NTP). We also use the beta-binomial distribution to model the litter response data. It can be seen by observing the structure of these data that current experimental designs for developmental studies employ a limited number of dose groups. These designs may not be satisfactory when the goal is to illustrate the existence of hormesis. In particular, increasing the number of low-level doses improves the power for detecting hormetic effects. Therefore, we also provide the results of simulations that were done to characterize the power of current designs in detecting hormesis and to demonstrate how this power can be improved upon by altering these designs with the addition of only a few low exposure levels