Evaluation of ATSDR's MRL and EPA's RfCs/RfDs: Similarities, Differences, and Rationales

Objectives

The Agency for Toxic Substances and Disease Registry (ATSDR) and the Environmental Protection Agency (EPA) derive minimal risk levels (MRLs) and reference concentrations and doses (RfCs and RfDs), respectively, for environmental contaminants to help identify potential health risks to exposed populations. MRLs, RfDs, and RfCs involve similar derivation methods, but the values sometimes differ for the same chemical. The objectives of this manuscript are to quantitatively assess similarities and differences between MRLs, RfCs, and RfDs, qualitatively describe how a number of factors can influence the development of the health guidance values (HGVs) and identify ongoing collaborations and opportunities for increased coordination of efforts.

Materials and Methods

We collected MRLs and RfCs/RfDs, assessment date, and description of the derivation process from ATSDR's toxicological profiles and EPA's Integrated Risk Information System (IRIS) and Office of Pesticide Program (OPP) and identified reasons for differences between MRLs and RfCs/RfDs.

Results

The most frequent types of differences in values that we found in our analysis included use of different methodologies, use of different studies, and/or completion of a more recent chemical evaluation. These can stem from differences in scientific judgement.

Conclusion

To avoid confusion when disparate HGVs occur between government agencies, a keen understanding of these differences can be helpful for appropriate risk characterization and communication when applying HGVs.

Site specific risk assessment of an energy-from-waste thermal treatment facility in Durham Region, Ontario, Canada. Part A: Human health risk assessment

The regions of Durham and York in Ontario, Canada have partnered to construct an energy-from-waste thermal treatment facility as part of a long term strategy for the management of their municipal solid waste. This paper presents the results of a comprehensive human health risk assessment for this facility. This assessment was based on extensive sampling of baseline environmental conditions (e.g., collection and analysis of air, soil, water, and biota samples) as well as detailed site specific modeling to predict facility-related emissions of 87 identified contaminants of potential concern. Emissions were estimated for both the approved initial operating design capacity of the facility (140,000 tonnes per year) and for the maximum design capacity (400,000 tonnes per year). For the 140,000 tonnes per year scenario, this assessment indicated that facility-related emissions are unlikely to cause adverse health risks to local residents, farmers, or other receptors (e.g., recreational users). For the 400,000 tonnes per year scenarios, slightly elevated risks were noted with respect to inhalation (hydrogen chloride) and infant consumption of breast milk (dioxins and furans), but only during predicted 'upset conditions' (i.e. facility start-up, shutdown, and loss of air pollution control) that represent unusual and/or transient occurrences. However, current provincial regulations require that additional environmental screening would be mandatory prior to expansion of the facility beyond the initial approved capacity (140,000 tonnes per year). Therefore, the potential risks due to upset conditions for the 400,000 tonnes per year scenario should be more closely investigated if future expansion is pursued.

Use of comparative genomics approaches to characterize interspecies differences in response to environmental chemicals: challenges, opportunities, and research needs

A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionary biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended.

Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century

Response to environmental chemicals can vary widely among individuals and between population groups. In human health risk assessment, data on susceptibility can be utilized by deriving risk levels based on a study of a susceptible population and/or an uncertainty factor may be applied to account for the lack of information about susceptibility. Defining genetic susceptibility in response to environmental chemicals across human populations is an area of interest in the NAS' new paradigm of toxicity pathway-based risk assessment. Data from high-throughput/high content (HT/HC), including -omics (e.g., genomics, transcriptomics, proteomics, metabolomics) technologies, have been integral to the identification and characterization of drug target and disease loci, and have been successfully utilized to inform the mechanism of action for numerous environmental chemicals. Large-scale population genotyping studies may help to characterize levels of variability across human populations at identified target loci implicated in response to environmental chemicals. By combining mechanistic data for a given environmental chemical with next generation sequencing data that provides human population variation information, one can begin to characterize differential susceptibility due to genetic variability to environmental chemicals within and across genetically heterogeneous human populations. The integration of such data sources will be informative to human health risk assessment.

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes.