A case study on the application of an expert-driven read-across approach in support of quantitative risk assessment of p,p'-dichlorodiphenyldichloroethane

Abstract

Deriving human health risk estimates for environmental chemicals has traditionally relied on in vivo toxicity databases to characterize potential adverse health effects and associated dose-response relationships. In the absence of in vivo toxicity information, new approach methods (NAMs) such as read-across have the potential to fill the required data gaps. This case study applied an expert-driven read-across approach to identify and evaluate analogues to fill non-cancer oral toxicity data gaps for p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), an organochlorine contaminant known to occur at contaminated sites in the U.S. The source analogue p,p'-dichlorodiphenyltrichloroethane (DDT) and its no-observed-adverse-effect level of 0.05 mg/kg-day were proposed for the derivation of screening-level health reference values for the target chemical, p,p'-DDD. Among the primary similarity contexts (structure, toxicokinetics, and toxicodynamics), toxicokinetic considerations were instrumental in separating p,p'-DDT as the best source analogue from other potential candidates (p,p'-DDE and methoxychlor). In vitro high-throughput screening (HTS) assays from ToxCast were used to evaluate similarity in bioactivity profiles and make inferences toward plausible mechanisms of toxicity to build confidence in the read-across approach. This work demonstrated the value of NAMs such as read-across and in vitro HTS in human health risk assessment of environmental contaminants with the potential to inform regulatory decision-making.

Keywords: In vitro high-throughput screening; Quantitative risk assessment; Read-across; Toxicokinetics.

Figure 1.. Basic Metabolic Scheme for p,p’-DDT.

Conversation of p,p’-DDT to p,p’-DDD via reductive dechlorination occurs more readily than dehydrochlorination of p,p’-DDT to p,p’-DDE. Both, p,p’-DDD and p,p’-DDE, can be oxidized to the primary urinary metabolite, of 2,2-bis(p-chlorophenyl) acetic acid (DDA). Figure has been adapted from ATSDR (2002a).

Figure 2.. Range of Effect levels for Noncancer Oral Toxicity for p,p’-DDD and Analogues from Repeated-Dose Animal Studies.

Graph displays the range of effect levels (no-observed-adverse-effect levels [NOAEL] and lowest-observed-adverse-effect levels [LOAEL]) for noncancer endpoints from repeated-dose animal toxicity studies via oral administration reported by ATSDR (2002a, b) and U.S. EPA (2017 b, c). Studies for DDT, DDD, and methoxychlor include technical grade and analytical formulations of the p,p’ isomers. Circles note PODs used in the derivation of oral reference doses (RfDs) and minimal risk levels (MRLs) for these chemicals described in more detail in Table 5.

Figure 3.. Bioactivity data for p,p’-DDD and Analogues in ToxCast Assays Conducted in Human Hepatoma HepG2 Cells and Primary Human Hepatocytes.

Scatterplots show AC50 and scaled activity values for p,p’-DDD, p,p’-DDT, p,p’-DDE and methoxychlor from in vitro assays visualized according to the type of biological response or biological target. AC50 values refer to the concentration that elicits half maximal response and the scaled activity refers to the response value divided by the activity cutoff (U.S. EPA, 2015). Metabolism enzyme-related assays were conducted in human primary hepatocytes and all other in vitro assays were measured in HepG2 cells. Assays for which chemicals were inactive are not displayed. Further information on AC50 values for individual assays can be found in Table A-3.

Figure 4.. ToxCast Assays Evaluating Regulation of Nuclear Receptor Activity for p,p’-DDD and Analogues in Human Hepatoma HepG2 Cells.

Panel A shows radar plots for p,p’-DDD, p,p’-DDT, p,p’-DDE and methoxychlor, summarizing active calls from nuclear receptor assays conducted in HepG2 cells and mapped to specific target genes. The shaded area of the pie slice represents the number of active assays and the size of the pie slice refers to the total number of assays within a given nuclear receptor target gene. Further details on assay activity results can be found in Table A-4. Bar graphs compare AC50 values (concentration at half maximal response) for active assays (panel B). The scale for the AC50 values is shown in reverse order to visualize the most sensitive nuclear receptor activities (the higher bar indicates a lower AC50 value).