3

A Class Approach to Evaluating Organohalogen Flame Retardants: Case Studies

In Chapter 2, the committee described a scoping plan for evaluating nonpolymeric, additive organohalogen flame retardants (OFRs) as a single class for the purpose of hazard assessment.¹ This chapter first discusses creation of an inventory of OFRs and then provides analyses that show that chemicals in the inventory do not represent a single class for a regulatory hazard assessment that uses Consumer Product Safety Commission (CPSC) guidance. However, a science-based approach to creating OFR subclasses is described and recommended. The chapter then provides an example of a literature survey and identifies two case studies that are used to illustrate several steps described in the scoping plan (see Chapter 2, Figure 2-1). Because the case studies are illustrative, not all steps of the scoping plan are conducted nor are any hazard assessments performed. Furthermore, the committee does not provide a comprehensive list of all databases or tools that might be needed to assist with the analyses. The chapter concludes by discussing options for handling discordant data on subclass members and addressing a projected timeline and cost for a class approach to hazard assessment of OFRs.

CAN ORGANOHALOGEN FLAME RETARDANTS BE DEFINED AS A SINGLE CLASS?

The committee used several approaches to answer the question of whether the OFRs can be treated as a single class for hazard assessment. Details of the approaches are provided in Appendix B. As noted in Chapter 2, the main steps are as follows:

• Identify and characterize a “seed” set of chemicals as a working inventory of the class.
• Generate an “expanded” set of chemical analogues of the seed set on the basis of combined functional, structural, and predicted bioactivity information.
• Evaluate the similarity of the seed set to the analogues to evaluate whether the OFRs are distinguishable as a single class.

Box 3-1 presents an overview of the steps used by the committee to develop an OFR inventory. Additional details are provided in Appendix B.

After defining the OFR inventory, the committee identified chemically related analogues that are similar to the seed chemicals (Box 3-2). Analogues can serve several purposes other than comparison with seed chemicals, including identification of chemicals that might be used as OFRs in the future and of chemicals that might have toxicology and other data to support a class-based hazard assessment. Further details are provided in Appendix B.

When an expanded set of chemical analogues had been created, the committee analyzed the chemical space represented by the seed and analogue chemicals to determine whether the OFRs could be distinguished as a single class. The committee’s analyses included the following:

• Prediction of structure–activity relationships (SARs) by using an open-source application called OPEn structure–activity/property Relationship App (OPERA v2.0) (Mansouri et al. 2016a,b; 2018a,b; Kleinstreuer et al. 2018).² The OPERA SAR predictions showed that the seed chemicals exhibited heterogeneity in physicochemical properties, environmental fate, and toxicity end points, including estrogen and androgen receptor activities and acute oral toxicity.
• Principal component analysis (PCA) on OPERA physicochemical properties. The PCA analysis

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¹ The abbreviation OFRs in this report refers specifically to nonpolymeric, additive organohalogen flame retardants.

² See prediction file: pred_OPERA_OFR.csv and list of OPERA models: OPERA2.0_models.xlsx and OFRs.xlsx. Files available at www.nap.edu/25412.

showed that the seed chemicals have similar physicochemical, toxicological and environmental fate properties that were not distinguishable from those of the expanded set of chemical analogues.³

When the analyses were considered collectively (see Appendix B for a detailed discussion), the committee concluded that the seed chemicals do not have a common chemical structure or predicted biologic activity. That conclusion was supported by compiling and reviewing data from the US Environmental Protection Agency (EPA) Dashboard (Williams et al. 2017) and ToxCast and Tox21 databases (Richard et al. 2016), which showed that the OFR seed chemicals had a wide array of biologic activities that varied from chemical to chemical.⁴ Thus, the broad class needs to be divided into subclasses to support a regulatory hazard assessment.

DEFINITION OF SUBCLASSES OF ORGANOHALOGEN FLAME RETARDANTS

The committee used cheminformatic approaches to create OFR subclasses. A public set of chemotypes⁵ and methods that have been developed by Yang et al. (2015) and Richard et al. (2016) were used to identify the chemotypes present in the seed chemicals, which are listed in Figure 3-1. Using the chemotypes, the committee was able to identify several generic classes that represented the entirety of the OFR seed set (Table 3-1). Merging the biology-informed groups with the chemotypes listed in Figure 3-1 led to the formulation of 14 OFR categories for the inventory of 161 OFR chemicals (Table 3-2). Appendix B provides additional details on how the subclasses were formed and evaluated. The committee recommends that CPSC use the subclasses in Table 3-2 at least as a starting point for the class-based hazard assessment of OFRs.

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³ See Appendix B for additional details.

⁴ See OFR_ChemistryDashboard-Batch-Search_2018-12-03_17 _03_39.xls and Appendix C for additional details. File available at www.nap.edu/25412.

⁵ ToxPrint, available at https://chemotyper.org, provides coverage of EPA and Food and Drug Administration inventories and captures chemical features important for chemical safety assessments.

SURVEY OF THE LITERATURE

When the subclasses have been formed, the committee recommends conducting a literature survey (see Chapter 2, Figure 2-1). As discussed in Chapter 2, the goal of the literature survey is to determine the extent, range, and nature of toxicity data (human, animal, in vitro, and other relevant studies) and to identify end points that deserve investigation.⁶ It is distinct from the literature search performed later in the scoping plan in that it is meant to provide a broad understanding of the literature, not to identify every relevant article that might need to be retrieved and evaluated for the hazard assessment of a specific subclass.

To identify subclasses that could serve as case studies, the committee surveyed the literature in several steps. It first conducted an initial mapping exercise to evaluate the types of toxicity data available on each subgroup and then conducted several literature surveys to identify end points of possible interest. Specifically, the committee initially surveyed the literature by using bioinformatically mappable databases, which contain biologic data that can be systematically retrieved by using batch software queries for the chemicals of interest. The committee searched the following databases to determine whether they contained data for the subclass members: Comparative Toxicogenomics Database (CTD), EPA Chemical Dashboard, Hazardous Substances Data Bank (HSDB), Integrated Risk Information System (IRIS), ToxCast/Tox21, Toxicity Reference Database (ToxRefDB), PubChem, and ChEMBL. The committee notes that other databases might also be surveyed, and it simply used the ones listed for illustrative purposes. Results for the OFR subclasses and analogues are shown in Figures 3-2 and 3-3 (see also Appendix C: Figures C-1, C-2, C-3, C-4, and C-5). The survey provided an indication of the amounts and types of information (data coverage) that might be available on each OFR. The mapping exercise, however, did not identify end points of interest. The details of the exercise are provided in Appendix C.

To gain an understanding of possible end points of interest, the committee next used CAS numbers to explore PubChem for toxicity data on each seed chemical. The query focused on chronic toxicity, reproductive and developmental toxicity, mutagenicity, and cancer, which were end points that were specifically listed in the committee’s task statement. Other end points could be considered. The survey results were used to identify subclasses that contained members on which there was relevant toxicity information, including epidemiology, traditional mammalian toxicity, and new approach methodologies (NAM) studies.⁷ One objective in the selection of the two case studies was to illustrate how high-throughput, alternative species, and other NAM data could be used to inform a hazard assessment (Box 3-3). Two relatively

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⁶ As noted in Chapter 2, the term literature is used broadly to refer to scientific literature and databases.

⁷ Completion of the scoping plan does not require that a subclass have each of the data streams noted.

TABLE 3-1 Chemotypes Identified in OFR Seed Chemicals That Have Been Associated with Predicted Biologic Activity^a

^aIndividual OFRs that have a given chemotype might or might not demonstrate the biologic activity indicated here.

Abbreviations: AhR, aryl hydrocarbon receptor; ER/AR, estrogen receptor/androgen receptors; GABA, gamma aminobutyric acid; PPAR, peroxisome proliferator activated receptor; ROS, reactive oxygen species.

TABLE 3-2 OFR Subclasses Formulated by Using Chemotypes and Predicted Biologic Activity

^aSeven chemicals were categorized by using two chemotypes and included in two subclasses. This analysis was performed by using the chemicals in the OFR inventory.

TABLE 3-3 Members of the Polyhalogenated Organophosphate Subclass

^*CAS no. from SciFinder.

data-rich OFR subclasses—polyhalogenated organophosphates (OPs) and polyhalogenated bisphenol aliphatics—were selected to serve as case studies to illustrate various aspects of the hazard-assessment scoping plan.

SEARCH OF THE LITERATURE

After the literature survey and the creation of an analysis plan, the literature is searched to identify all relevant data associated with the subclass members and the end points of interest.⁸ As noted at the beginning of this chapter, the committee did not attempt to complete all steps of its scoping plan and so did not create an analysis plan. It also did not conduct comprehensive, systematic literature searches; the searches were conducted so that the committee could illustrate steps of its scoping plan, and relevant literature could have been missed. The committee did, however, search multiple databases for toxicity data in vertebrates on each member of the subclasses chosen for the case studies.⁹ The searches were intended to gather the available literature on the two subclasses and to illustrate the process that could be used (see Appendix C for details). For the two selected subclasses, the committee searched for English-language, peer-reviewed articles in PubChem and PubMed by CAS number, chemical name and synonyms, and outcomes of interest by using the following search terms:

• Toxicity OR reproductive toxicity OR developmental toxicity.

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⁸ As noted in Chapter 2, the term literature is used broadly to refer to scientific literature and databases.

⁹ The committee recognizes that OFRs have also been evaluated in invertebrate animal models. For example, the effect of flame retardants on feeding, larval development, reproduction, and motor activity have been evaluated in the nematode Caenorhabditis elegans (Behl et al 2016; Xu et al 2016).

TABLE 3-4 Genotoxicity Data on the Polyhalogenated Organophosphate Subclass

TABLE 3-5 Polyhalogenated Organophosphate Chronic Toxicity Studies

^aThe TDBPP metabolite 2,3-dibromo-1-propanol is carcinogenic in rodents (Eustis et al. 1995).

• Genotoxicity OR mutagenicity.
• Cancer OR carcinogenicity.

The search found a few well-studied chemicals in both classes that could help to anchor the hazard assessment of other subclass members. Each subclass also contained chemicals on which there were few or no relevant traditional (mammalian) toxicity data. An additional PubMed literature search conducted in November 2018 used the search terms “zebrafish” and “flame retardants” and retrieved 118 publications. The committee also considered two publications that reported results of zebrafish assays that were used to screen the large ToxCast chemical library, which included polyhalogenated OPs (Truong et al. 2014; Reif et al. 2016). The committee illustrates the use of zebrafish data in the following case studies because such data were available on several OFRs. Their use is not a statement that zebrafish data will be the best or most useful NAM data to use in all cases.

CASE STUDY 1: POLYHALOGENATED ORGANOPHOSPHATES

The committee identified 22 chemicals in the polyhalogenated OP subclass, which are listed in Table 3-3. Chemical structures for several subclass members are shown in Figure 3-4.

As noted above, literature searches were performed by using each chemical name, CAS number, and relevant toxicity search terms. Studies of genotoxicity, carcinogenicity, and reproductive and developmental toxicity were also sought from authoritative compilations from the European Chemicals Agency (ECHA), EPA, Environment Canada and Health Canada, the World Health Organization’s International Programme on Chemical Safety, and the National Toxicology Program (NTP). The committee found that Tox21 or ToxCast data, rodent reproductive or developmental toxicity data, or zebrafish data on several members of the polyhalogenated OP subclass were available. Some epidemiologic data on several subclass members were available. Genotoxicity data are summarized in Table 3-4. As a subclass, these chemicals have discordant data; that is, some members have been negative in the Ames assay, and others have been positive.

The results of chronic mammalian bioassays are presented in Table 3-5. A metabolite of TDBPP, 2,3-dibromo-1-propanol, has been shown to be carcinogenic in rodents (Eustis et al. 1995). TDBPP has been identified as probably carcinogenic in humans (Group 2A) by the International Agency for Research on Cancer (IARC 1999b) and reasonably expected to be a human carcinogen by NTP (2016) on the basis of animal carcinogenicity data (Reznik et al. 1981). TCEP causes benign and malignant tumors at various organ sites in rats and mice (NTP 1991). A carcinogenicity study with TCPP is underway at NTP.

A third outcome, developmental toxicity, was also identified as an end point of interest in this case study, and the committee chose this end point to illustrate evaluation and integration of data in the scoping plan (Figure 2-1). The committee emphasizes that a hazard assessment of the OPs would consider mutagenicity, carcinogenicity, and developmental toxicity and might also consider neurotoxicity, hepatotoxicity, and other systemic effects; that is, the overall class-based hazard assessment would consider multiple end points of interest. The following subsections discuss the various data streams for developmental toxicity and overall classification for this specific end point.

Developmental Toxicity Data on Polyhalogenated Organophosphates

The committee’s analysis considered three main data streams: epidemiologic, traditional mammalian, and zebrafish studies. Exposures were considered relevant if they occurred during development. Additional toxicity data could also be considered. For example, Farhat et al. (2013) indicated that exposure of chicken embryos to TDCPP lowered free thyroxine (T4) concentrations in the blood and resulted in malformations, including changes in head-to-bill lengths. Similarly, frog (Xenopus tropicalis) embryos exposed to TCPP or TDCPP developed multiple malformations (Zhang et al. 2016).

Epidemiologic Data

Despite their relatively short half-lives, polyhalogenated OPs likely contribute to continuous exposure concentrations in humans (Dishaw et al. 2014; He et al. 2018; Phillips et al. 2018). Polyhalogenated OPs are hydrolyzed to diester metabolites that undergo urinary excretion (Cequier et al. 2015), and the metabolites have been used as biomarkers of OP flame-retardant exposure of people (Dodson et al. 2014; Hoffman et al. 2014; Cequier et al. 2015; Romano et al. 2017). However, not all OP metabolites can be attributed to the polyhalogenated OP flame retardants; some nonhalogenated OP flame retardants, such as triphenyl phosphate (TPHP), are metabolized to some of the same metabolite diesters as the polyhalogenated OPs (Cequier et al. 2015; Wei et al. 2018).

Some OP flame-retardant metabolites—including diphenyl phosphate (DPHP), bis(1,3-dichloro-2-propyl) phosphate (BDCIPP), isopropylphenyl phenyl phosphate (ip-PPP), and 1-hydroxy-2-propyl bis(1-chloro-2-propyl) phosphate (BCIPHIPP)—are nearly ubiquitous in human samples (Ospina et al. 2018; Doherty et al. 2019; Wang et al. 2019), but few epidemiologic studies have examined associated health outcomes. A few small studies of reproductive-age cohorts have supported the potential of some metabolites to be associated with changes in sex and

TABLE 3-6 Available Human Epidemiologic Data on Organophosphate Flame Retardants^a

^a Polyhalogenated OPs are identified by boldface, and halogenated metabolites are identified by italic type.

^bExposure period for prospective studies of perinatal exposures in relation to later reproductive-developmental outcomes. No study period listed for cross-sectional studies concurrently measuring exposure and outcome.

Abbreviations: DPHP, diphenyl phosphate; ip-PPP, isopropylphenyl phenyl phosphate; BDCIPP, bis(1,3-dichloro-2-propyl) phosphate; BCIPHIPP, 1-hydroxy-2-propyl bis(1-chloro-2-propyl) phosphate; OPFR, organophosphate flame retardant; TDCPP, tris(1,3-dichloro-2propyl) phosphate; TPP, triphenyl phosphate; TSH, thyrotropin; TT4, total thyroxine.

TABLE 3-7 Developmental Toxicity of Polyhalogenated Organophosphates

Abbreviations: LOAEL, lowest observed-adverse-effect level; NOAEL, no-observed-adverse-effect level.

TABLE 3-8 Zebrafish Teratology and Developmental Neurotoxicity Studies of Polyhalogenated Organophosphates

^aMalformations associated with increased mortality.

^bEffects associated with systemic toxicity.

TABLE 3-10 Polyhalogenated Bisphenol Aliphatics

thyroid hormones (Meeker and Stapleton 2010; Preston et al. 2017), but results were imprecise and inconsistent. Disruption of sex and thyroid hormones can adversely affect fertility, birth outcomes (Carignan et al. 2017, 2018; Messerlian et al. 2018), and neurodevelopment (Sarles et al. 1987; Castorina et al. 2017). In two prospective studies of exposure during pregnancy, OP flame retardants were associated with reduced language, cognition, and working memory in the children (Castorina et al. 2017; Doherty et al. 2019), but the specific implicated metabolites differed between the two studies. Table 3-6 provides a summary of the findings of the epidemiologic studies.

Mammalian Toxicity Studies

Developmental toxicity data were available on four of the polyhalogenated OPs (see Table 3-7). Although the four do not appear to be teratogenic, one study of TDCPP reported effects on sexual behavior in male rats exposed during development. Oral exposure (28 consecutive days after birth) of neonatal male rats to TDCPP suppressed male sexual behavior and reduced testis size (Kamishima et al. 2018). In contrast, oral exposure of pregnant Long-Evans rats to TDCPP or TCEP from gestational day 10 to weaning was not associated with thyrotoxicity or developmental neurotoxicity in offspring (Moser et al. 2015).

Zebrafish Studies

Toxicity data on four of the polyhalogenated OPs (TDCPP, TCEP, TCPP, and TDBPP) were available from the zebrafish model system. Depending on the polyhalogenated OP, chemical exposure of zebrafish resulted in malformations or behavioral changes, although contradictory (negative) studies have also been reported (Table 3-8). Study details and key findings from the studies are presented in Appendix D (Table D-1). Other studies of zebrafish in which teratogenic or developmental neurotoxic effects were not assessed were also reviewed and are summarized in Appendix D (Table D-2).

Several laboratories conducted zebrafish studies with multiple polyhalogenated OPs that allowed more direct comparisons between subclass members. Exposure concentrations of polyhalogenated OPs varied among chemicals. Noyes et al. (2015) reported that TDBPP (3.3 µM) and TDCPP (10 µM) had overt toxicity thresholds, and none was found for TCEP or TCPP up to 100 µM. A similar trend was observed for neurotoxicity with effect thresholds at 0.56 µM for TDBPP, 3.14 µM for TDCPP, 31.4 µM for TCEP, and 100 µM for TCPP (Noyes et al. 2015). McGee et al. (2012), Du et al. (2015), and Alzualde et al. (2018) likewise noted greater toxicity of TDCPP than of TCEP or TCPP. Differences in responses were also seen among the four chemicals. Dishaw et

al. (2014) found that TCEP, TCPP, and TDBPP were not teratogenic, whereas TDCPP was teratogenic. Noyes et al. (2015) concluded that TCEP and TCPP exhibited similar neurotoxicity, but the neurotoxicity of TDCPP differed from that of TCEP and TCPP. Dach et al. (2019) observed hypoactivity as an effect of TCPP and TCEP at 30 µM 96 and 120 h after fertilization and detected no malformations up to this test concentration. In adult fish, TDCPP and TCEP were found to undergo metabolism through a dechlorination pathway, but TDCPP had a longer half-life in tissues than TCEP (Wang et al. 2017). The data also indicate that differences among the chemicals regarding neurotoxic, teratogenic, and developmental toxicity depend on the exposure period.

Hazard Assessment of the Polyhalogenated Organophosphates

After data evaluation, the next step in the scoping plan is integration of the analyses for each end point of interest, for example, mutagenicity, carcinogenicity, and developmental toxicity. Regarding developmental toxicity, the committee considered the best-studied chemicals in the polyhalogenated OP subclass (Table 3-9). Oral exposure of pregnant rats to TDCPP, TCEP, TCPP, or TDBPP did not produce teratogenic or developmental neurotoxicity in their offspring. However, studies of the same chemicals in zebrafish found positive results for teratogenic effects of TDCPP and TCEP and developmental neurotoxicity for all four; this suggests developmental effects. A TDCPP metabolite, BDCIPP (Hoffman et al. 2017), has not been associated with changes in working memory or IQ deficits in children (Castorina et al. 2017).

The developmental toxicity data on the four chemicals are discordant. Several options for handling the discordant data are discussed after the next case study.

CASE STUDY 2: POLYHALOGENATED BISPHENOL ALIPHATICS

The committee identified 11 chemicals in the subclass of polyhalogenated bisphenol aliphatics (Table 3-10). The subclass members have bisphenol A as the core structure.

TBBPA is the base structure of this subclass, and TCBPA is the chlorinated analogue (Figure 3-5). Ten of the bisphenol A-based OFRs contain bromines in the 3,3’,5,5’ positions. There is a comprehensive traditional toxicology database on TBBPA. TBBPA and TCBPA are active against several biological targets in in vitro assay systems. Other members of the subclass have various R group substitutions on the phenolic carbons, and these substitutions might alter targets of activity in in vitro studies in contrast with TBBPA. In mammals and other vertebrates, conjugation with glucuronic acid or sulfate on

TABLE 3-11 Genotoxicity Data on Polyhalogenated Bisphenol Aliphatics

Note: (+), positive results; (-), negative results; (+/-), conflicting results.

^aToxtree, http://toxtree.sourceforge.net/ames.html; http://toxtree.sourceforge.net/mic.html.

^bNTP (2014).

^cIARC (2018).

^dIPCS (1995b).

^eEPA (2015c).

^fECHA (2018a).

TABLE 3-12 Subchronic and Chronic Toxicity Studies of Polyhalogenated Bisphenol Aliphatics

Abbreviations: NOAEL, no-observed-adverse-effect level; GLP, good laboratory practices; T4, thyroxine; T3, triiodothyronine; TSH, thyroid-stimulating hormone.

TABLE 3-14 Mammalian Developmental Toxicity Studies of Polyhalogenated Bisphenol Aliphatics

^aPrimary references are MPI Research (2001), Noda et al. (1985), and Velsicol Corporation (1978).

^bPrimary reference is ACC (2002).

^cPrimary references are Goldenthal et al. (1978), Noda et al. (1985), MPI Research (2001), ACC (2002), Darnerud (2003), Tada et al. (2006), and Saegusa et al. (2009).

the TBBPA and TCBPA phenolic rings leads to (or is predicted to lead to) relatively rapid excretion. Metabolism of other subclass members might occur on the phenolic substitutions and possibly lead to metabolic and toxicologic divergence.

TBBPA and related subclass members have been assessed by several authoritative bodies (IPCS 1995b; ECB 2006; Environment Canada and Health Canada 2013; EFSA 2011a; NTP 2014; EPA 2015b). As noted above, the committee searched for additional traditional toxicology data and NAM data that might be incorporated to facilitate bridging from the well-studied chemicals to the poorly studied ones. PubChem, SciFinder, and ChemID plus were searched along with the European Food Safety Authority, ECHA, EPA, Environment Canada and Health Canada, and International Programme on Chemical Safety Web sites. Primary searches were restricted to sources indexed by CAS number. Additional focused searches were conducted for identified biologic targets of subclass members to locate comparative data on at least two subclass members. Genotoxicity data are provided in Table 3-11. As a subclass, these chemicals have been negative in the Ames assay and generally lack structural alerts that suggest a mutagenic potential. Data on the subclass from mammalian subchronic and chronic studies are presented in Table 3-12. Only one subclass member, TBBPA, has been tested for carcinogenicity.

As with the first case study, the hazard assessment of the polyhalogenated bisphenol aliphatics would consider multiple end points of interest. To provide another example of data evaluation and integration, the committee focused its evaluation of this OFR subclass on its ability to

alter thyroid hormone homeostasis in adults or neonates and to produce morphologic or behavioral developmental effects. The committee considered epidemiologic, mammalian toxicity, and zebrafish data and considered exposures relevant if they occurred during development. The following subsections discuss the various data streams and their evaluation and integration for the specific end points noted.

Epidemiologic Studies

Two studies have investigated the polyhalogenated bisphenol aliphatics in relation to health outcomes in human samples (Table 3-13). One small study of mother–infant pairs at delivery suggested that TBBPA might be associated with higher free T4 in serum but not other endocrine markers in peripartum women; the effect was not observed in their infants (Kim and Oh 2014). A cross-sectional study of adolescents did not find contemporary TBBPA concentrations to be associated with attention, working memory, or thyroid hormone concentrations; however, studies of neurodevelopment ideally investigate exposure during earlier windows of brain development, such as the prenatal period or early childhood, rather than contemporary exposure during adolescence (Kiciński et al. 2012). The current epidemiology literature contributes little to hazard assessment, but assays of TBBPA and other subclass members could complement cohort studies with stored prenatal or early life samples.

Mammalian Toxicity Studies

In subchronic studies, TBBPA has been shown to decrease circulating T4 concentrations with no change in either triiodothyronine (T3) or thyroid-stimulating hormone (TSH) concentrations, increase liver weight, and decrease spleen weight in rats and mice (NTP 2014). Additional evidence from animal studies suggests that exposure to TBBPA can alter thyroid homeostasis in rodents (Lilienthal et al. 2008; Van der Ven et al. 2008; Cope et al. 2015). Lai et al. (2015) proposed that the thyroid effects are mediated by induction of UGT1A that results in increased T4 catabolism. Sanders et al. (2016) reported decreased serum T4 concentration and increased hepatic and uterine expression of Thra gene that encodes TRα in rats 24 h after 5 days of oral administration of TBBPA. They also noted UGT1A was upregulated in the liver and uterus after TBBPA administration; however, they concluded that the mechanism for changes in T4 is uncertain. TBBPA can displace T4 from its plasma transport protein (Hamers et al. 2006) and inhibits binding of T3 to the thyroid receptor TRβ1 and binding of T4 to transthyretin

TABLE 3-15 Summary of Evidence on TBBPA and Changes in Thyroid Homeostasis

(Meerts et al. 2000; Sun et al. 2009). Meerts et al. (2000) found that TCBPA inhibits T4 binding to transthyretin but with less potency than TBBPA. Despite effects on thyroid metabolism, the polyhalogenated bisphenol aliphatic subclass, however, has minimal developmental effects in mammals (Table 3-14).

Zebrafish Studies

TBBPA is toxic to zebrafish embryos, and there is a database on TBBPA-related effects on thyroid hormone concentrations and actions in zebrafish that suggest that the zebrafish assay might be a useful model for assessing similarities and differences within the structural class. For example, Chen et al. (2016) reported an increase in the expression of UGT genes after TBBPA exposure, which they note could affect T4 metabolism and then lead to neurobehavioral changes. Zebrafish studies of TBBPA, TCBPA, TBBPA-BHEE, TBBPA-BDBPE, and TBBPA-BME are available. Effects of this subclass on thyroid and development (including behavior) are summarized in Appendix D (Tables D-3 and D-4). Additional zebrafish studies are summarized in Table D-5.

Class Hazard Assessment Based on Effects on Thyroid Homeostasis

The committee’s initial evaluation considered TBBPA, which is the best-studied chemical in the polyhalogenated bisphenol aliphatic subclass (Table 3-15). TBBPA can alter thyroid homeostasis so as to result in inconsistent changes in T3 and T4 concentrations. The data are discordant between rodent and zebrafish. Additional in vitro, zebrafish, and other thyroid-homeostasis studies of the polyhalogenated bisphenol aliphatics could provide confidence that thyroid function can serve as a key end point for hazard classification.

Class Hazard Assessment Based on Developmental Toxicity

The committee’s evaluation initially considered the best-studied chemicals in the polyhalogenated bisphenol aliphatic subclass (Table 3-16). Each chemical has been studied in zebrafish, and the results are discordant. The rodent developmental toxicity studies of two subclass members have also resulted in mixed findings. Overall, the data on the four best-studied chemicals in the subclass are discordant for this specific end point. Analysis of other end points might support a hazard assessment of the subclass. The next section discusses the committee’s recommendations for dealing with discordant data.

ADDRESSING DISCORDANT DATA

Both case studies had discordant data on developmental toxicity between species (for example, rodent vs zebrafish), within a species, or both. Table 3-17 presents the options that could be considered when discordant data are identified: performing analyses, collecting new data, reclassifying the subclass, or making policy decisions. The approaches listed in Table 3-17 for the various options are offered as examples and are not meant to constitute a comprehensive list of all approaches that might be useful or appropriate.

Analyses

One possible explanation for discordant data within an OFR subclass might be differences in pharmacokinetics. For example, an analysis of the pharmacokinetic data on two members of the polyhalogenated bisphenol aliphatic subclass (TBBPA and TBBPA-DBPE) showed different bioavailabilty in rodents after oral exposure. Unlike TBBPA, TBBPA-DBPE is poorly absorbed from the gastrointestinal tract (Hakk et al. 2000; Kuester et al. 2007; NTP 2017). That observation might partly account for the lack of effects seen in rodent developmental toxicity studies. Metabolism data could also help to identify chemicals within a subgroup that share metabolic intermediates and, by extension, toxicity profiles.

Another approach to resolving discordant data is to explore the mechanisms of action of subclass members. One method of collecting mechanistic data is to collect NAM data on subclass members (Box 3-3). Such data can help to identify OFR biologic targets of interest. Mechanistic data have many possible applications, including the following:

• Inform additional approaches to grouping the chemicals. For example, several members of the polyhalogenated OP subclass are structurally similar to some nonpolyhalogenated OP counterparts used as agrochemicals. The nonhalogenated OPs are associated with diverse toxicity mechanisms, including cholinesterase inhibition, endocrine disruption, and neurotoxicity. In vitro assays and other NAM data could be used to evaluate whether some polyhalogenated OPs inhibit acetylcholinesterase and could therefore be associated with cholinergic neurotoxicity.
• Determine the most appropriate animal models for human risk assessment.
• Identify analogues, including nonhalogenated chemicals, that have a common mechanism of action. Data on those chemicals can help to inform the risk assessment of the subclass.

It is not uncommon for different responses to occur among studies that use different species (such as rats, mice, and zebrafish), different strains within a species (such as strains of rats or mice), or different exposure windows. Assessing the human relevance of different species or strains can be useful for understanding which data would be expected to be more predictive of a selected effect, such as changes in thyroid hormones or mutagenicity. No single strain or species is expected to be predictive of all human health effects of interest, and nonmammalian species are increasingly recognized as providing reasonable predictions of selected effects in humans. However, using nonmammalian species can pose additional challenges. For example, both case studies used zebrafish data, which often were discordant. One possible explanation of discordance between zebrafish data and rodent data is that ex vivo exposure of zebrafish embryos or larvae to the parent OFR might not reflect in vivo metabolism that might occur in the rodent species. Further testing with OFR metabolites might be necessary for appropriate comparisons and yield concordance of data among species. A possible explanation for discordance among zebrafish data might be that different study protocols were used to expose the zebrafish to OFRs. Although a standardized OECD guideline (Test No. 236: Fish Embryo Acute Toxicity Test) was published in 2013, many laboratories do not use it. As a result, there are variations in developmental toxicity study designs, especially regarding the exposure window. There are also challenges in using zebrafish data, including extrapolation of water concentrations to doses that are suitable for human health assessment, but there has been progress in addressing this challenge in recent studies in which total chemical mass (based on exposure concentration and volume) relative to the mass of embryo immersed in the exposure solution is calculated. Those values can then be compared with human exposure values to determine whether a hazard would be expected to be associated with an environmentally relevant exposure.

In assessing discordant data, it is important to consider study design and implementation, which could influence observed results and might explain the discordance. For example, studies can have different powers to detect outcomes depending on the numbers of subjects or the exposure periods in reproductive-developmental studies. The doses or concentrations used in studies also can influence outcomes, and assessment of chemical purity can be important to ensure that effects do not arise from a contaminant.

Collection of New Data

Chapter 2 (Box 2-3) outlined a tiered approach for the collection of new data when there are no relevant data on any member of a subclass. That tiered approach could also be applied to the discordant-data scenario. However, the assessment that resulted in the conclusion of discordant data should have illuminated data gaps that should be useful in directing the data-collection effort.

Reclassification of the Subgroup

As mentioned above, mechanistic and pharmacokinetic data might suggest that a subgroup formed primarily on the basis of chemical structure needs to be parsed into two or more smaller subgroups. In some cases, chemicals that have multiple chemotypes are included in more than one subclass, and these chemicals might be the source of discordant data in one of the subclasses. Removing the

chemical from the subclass might be appropriate then. As mentioned in Chapter 2, however, the committee advises that reclassification should be performed judiciously to obviate a never-ending cycle of reclassification.

The committee also recognizes that alternative approaches have been used to generate OFR subclasses. For example, a study conducted by the Danish EPA (2016) grouped 67 brominated flame retardants on the basis of their chemical structures and then made QSAR predictions of selected environmental and health effects. Despite the existence of alternative classification schemes, the committee recommends that CPSC begin its analyses with the subclasses described earlier in this chapter.

Policy Decisions

The class approach relies on using data on tested chemicals to draw inferences about the potential hazard associated with class members that have not been tested. That approach is scientifically supported most strongly when many of the available data support a single conclusion (for example, when a specific toxicity is observed). When class members on which there are data appear to yield discordant findings on an end point, a key question is how to evaluate class members on which there are no data. Several inferences would be possible from the discordant findings, although they will have greater uncertainty than if the findings were concordant. Inferences would include the idea that the class members on which there are no data are similar in toxicity to class members on which there are data—for example, similar to the most toxic chemical or similar to a distribution of observed findings. Each inference could be considered in developing a hazard assessment of the class that would use policy choices to provide appropriate protection of public health. Ideally, the approach would create incentives for stakeholders to collect additional data and reduce the uncertainty in analyses.

PROJECTED TIMELINE AND COSTS

Traditional hazard-assessment methods take years and are too expensive to cover all chemicals under production. The committee has proposed a class-based hazard assessment of OFRs as an efficient alternative to traditional approaches. The proposed class-based process conveys time and cost savings in that one is no longer conducting separate hazard assessments of each individual chemical, and traditional hazard-assessment methods can be complemented by new approaches that take advantage of existing data (read-across) and require less de novo testing.

The next steps in completing class-based hazard assessments of the OFR subclasses will involve literature surveys and data-mapping for relevant toxicity end points. That process will likely require months for a research team to complete. The goal of the initial step is to evaluate whether well-studied subclass members can be used to anchor the assessment. When no such anchor chemical can be identified, it will be necessary to obtain minimal datasets on some subclass members. The committee’s initial literature survey exercise suggests that this could be the case for several OFR subclasses. For subclasses on which there are adequate data, there might be a need to create one or more chronic hazard advisory panels (CHAPs) that have specific chemical and end-point expertise. On the basis of CPSC’s experience with the CHAP that was formed to address phthalates, completion of that step could take several years.

CONCLUSIONS

This report proposes the use of emerging cheminformatic approaches to systematically expanding and refining the chemical and toxicologic information traditionally considered in assessing possible health hazards posed by a structurally or functionally related chemical class. The larger information base might reveal biologic activities of concern, such as effects on thyroid hormone homeostasis or neurodevelopment at one or more biologic organizational levels (for example, cells, zebrafish, laboratory mammals, and humans). The choices of which health end points are most important, how choices are made in the presence of uncertainty, and the relative importance of health end points require value judgments in the hazard-assessment process. Therefore, the committee recommends that CPSC consider providing both philosophic and regulatory-policy guidance to any CHAP that is charged with carrying out a class-based hazard assessment that uses the approaches described in this document.

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