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Keywords:

  • Mixture toxicity;
  • Dose-response;
  • Causality;
  • Experimental guidance;
  • Confounding factors

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Experimental designs for evaluating complex mixture toxicity in aquatic environments can be highly variable and, if not appropriate, can produce and have produced data that are difficult or impossible to interpret accurately. We build on and synthesize recent critical reviews of mixture toxicity using lessons learned from 4 case studies, ranging from binary to more complex mixtures of primarily polycyclic aromatic hydrocarbons and petroleum hydrocarbons, to provide guidance for evaluating the aquatic toxicity of complex mixtures of organic chemicals. Two fundamental requirements include establishing a dose-response relationship and determining the causative agent (or agents) of any observed toxicity. Meeting these 2 requirements involves ensuring appropriate exposure conditions and measurement endpoints, considering modifying factors (e.g., test conditions, test organism life stages and feeding behavior, chemical transformations, mixture dilutions, sorbing phases), and correctly interpreting dose-response relationships. Specific recommendations are provided. Integr Environ Assess Manag 2012; 8: 217–230. © 2011 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Aquatic toxicology originally focused on the exposure of organisms to individual chemicals or simple mixtures (Sprague, 1969, 1970, 1971, 1973; Waldichuk and Hegre 1973). Historically, the dose was the concentration of the toxicant in the exposure water. Chemical mixtures containing only a few compounds were treated by summing the toxic units (TU, the ratio of concentration in solution to response threshold concentration for the individual chemical) at different exposure times because the toxicity of many organic mixtures was believed to be additive (Sprague 1970). Later, the concentration of the toxicant at the site and/or sites of toxic action in the organism (McCarty 1991) was recognized as the appropriate dose metric. However, external exposure concentrations continued to be used because they formed the basis for derivation of water quality regulatory benchmarks (Stephan et al. 1985), and because analytical methods for toxicants were more sensitive and reliable for water than for tissues (Waldichuk and Hegre 1973; McCarty 1991).

As analytical methods improved, evidence accumulated that bioaccumulation and toxicity of hydrophobic and some polar organic chemicals were related to their affinity for tissue lipids in the organism. It was recognized that measuring the dose in terms of body residues was a better surrogate for the concentration at the site of toxic action than water concentration (Abernethy et al. 1986, 1988; McCarty 1986, 1991; Landrum et al. 1991; McCarty et al. 1992, 1993; McCarty and Mackay 1993). Specifically, it was recognized that toxicity is controlled by toxicokinetics that govern the bioaccumulation and distribution of the chemical and/or chemicals in tissues (based on their physical and chemical properties and facility for biotransformation) and by toxicodynamics, which govern the biochemical and physiological response of the organism (Figure 1). The closer the relationship between the concentration of the toxicant in whole tissues and the concentration at the site of toxic action, the better the interpretation of the dose-response relationship (McCarty et al. 2011).

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Figure 1. Processes affecting organism uptake of external substances via biological membranes, their internal distribution, and possible effects.

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Mixture toxicity usually is assessed either by treating the mixture as though it were a single substance or by tests of the components of the mixture to establish individual contributions to the observed mixture toxicity and summing the toxicity of the components assuming additive or independent action models. Both approaches have limitations. When treating the mixture as a single substance, all results are confined to that particular mixture. Application of the results to other conditions, for instance other mixtures containing similar ingredients but at different relative concentrations, cannot be carried out accurately. Additionally, the results cannot be applied readily to conditions other than those of the experiment. When the individual chemicals in the mixture are evaluated, the threshold responses for each compound must be established. This is of minimal concern for binary mixtures but becomes experimentally demanding or impossible for mixtures of multiple components.

Several excellent reviews of the mixture toxicity literature have focused on how the compounds in mixtures interact to produce a toxic response (McCarty and Borgert 2006a, 2006b; Kortenkamp et al. 2009; Dyer et al. 2011; McCarty et al. 2011). Although additivity, independent action, synergism, and antagonism are possible when addressing a specific endpoint response, additivity and independent action dominate the toxicity interactions. Furthermore, many chemical mixtures contain groups of compounds with a similar mode and/or mechanism of action whereas other groups within the mixture have different modes and/or mechanisms of action, such that combined use of additivity and independent action models often is best for evaluating the toxicity of a mixture. For the most part, additivity has been found to be a conservative model for toxicant interaction when addressing each specific endpoint (Kortenkamp et al. 2009). Finally, interpretation of the data is complicated and can result in other than additivity when mixtures are studied in the presence of exposure modifying factors such as organism behavior, dissolved and particulate organic carbon, suspended particles in the exposure medium, temporal variation in mixture composition, variations of mixture composition among treatment levels, and multiple mechanisms of action of the components (Lydy et al. 2004).

Experimental designs for evaluating effects of complex mixtures in freshwater and marine environments can be highly variable and, if not appropriate, can give (and have given) data that are difficult or impossible to interpret. Lessons learned from the following 4 case studies, that focus on binary to more complex mixtures of primarily polycyclic aromatic hydrocarbons and petroleum hydrocarbons, provide the basis for recommending technically defensible guidance for evaluating complex mixtures in aquatic toxicology.

CASE STUDIES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Four case studies of mixture toxicity are presented, ranging from relatively simple binary mixtures to complex mixtures. We recognize that there are myriad studies that could have been selected as case studies, but we have limited the number of studies so that specific, key issues such as establishing dose-response and causality are emphasized.

Case study one: Binary mixture

Two freshwater arthropods, Hyalella azteca and Chironomus dilutus (previously named C. tentans), were exposed to mixtures of fluoranthene and pentachlorobenzene in aqueous exposures without changing or measuring the water concentrations (Schuler et al. 2009). The 2 chemicals have similar log octanol–water partition coefficients (KOW, 5.18–5.20) but different toxicokinetics, because fluoranthene is biotransformed whereas there is no measurable biotransformation of pentachlorobenzene (Schuler et al. 2004). The endpoint selected was mortality at 4 and 10 d based on body residue as the dose metric. Residues in the 2 invertebrates were similar at 4 and 10 d for both substances, suggesting that the concentrations in organisms were near steady state. The use of body residue as the dose metric overcomes the difficulty of interpreting the toxicokinetics but does require that biotransformation be explicitly addressed because metabolites can contribute to toxicity. Thus, organic extractable metabolites were included in the calculation of TU and the molar sum of body residues for toxic response. The chemical characteristics of the metabolites were not established. The assumption that the authors used was that organic extractable metabolites would contribute directly to the mortality endpoint at 4 and 10 d.

The toxicity of pentachlorobenzene and fluoranthene were also determined under the same conditions so that the toxic potential of each compound would be available for assessing mixture response. The lethal residue for 50% mortality (LR50) was 1.73 and 1.51 µmol/g as the molar sum of the components in the binary mixture in H. azteca at 4 and 10 d respectively. These values are similar to the expected concentration required to produce mortality by nonpolar narcosis. For C. dilutus, the molar concentrations for the LR50 for the binary mixture were somewhat lower at 0.93 and 0.75 µmol/g, suggesting that the toxicity may not be due strictly to nonpolar narcosis. The lower body residue was driven by the sensitivity of C. dilutus to fluoranthene likely due to the presence of a nonnarcotic or polar narcotic metabolite (Schuler et al. 2006). When the individual potencies were addressed using a TU model, the LR50 values for both organisms were near 1 and showed additivity in TU contributions to the observed mortality. However, for C. dilutus, the molar contribution of fluoranthene and its metabolites to the toxicity was lower than that of the pentachlorobenzene for the same TU. Thus, in this study, there was a clear dose metric that produced monotonic dose-response relationships.

In the case of H. azteca, either molar additivity or TU would have been an acceptable model for examining causality so long as the contributions of organic extractable metabolites were included. Both of these approaches demonstrated additivity. For C. dilutus, the TU model addressed differences in toxic potentials of the 2 compounds, again incorporating the importance of organic extractable metabolites. For C. dilutus, the mode of toxicity was not as clear, but the contribution of the 2 compounds to the toxicity was clear. Thus, in both cases causality was relatively clear except that the chemical identity of the toxic metabolites was not identified and their potencies were not determined.

Measuring the toxic thresholds of the mixture's components was critical to interpreting the mixture interactions. It was particularly critical to understand the complication of biotransformation and account for the toxicity of metabolites to interpret the toxicity of these compounds. A negative feature was the failure to identify the specific toxic metabolite and/or metabolites. However, a TU model including total concentrations of extractable metabolites demonstrated additive interactions of the 2 compounds. The additivity of the 2 compounds was well demonstrated, and their contribution to the toxicity well understood, except that the identity of the fluoranthene metabolites was missing. Because the toxicity was based on body residues for the dose metric, translating the results to environmental concentrations for regulation of water concentrations would require using bioconcentration factors (Schuler et al. 2004, 2006). However, direct measures of environmental residues would be interpretable.

Case study two: Moderately complex mixture

The toxicity to marine copepods of 10 polycyclic aromatic hydrocarbons (PAH), characteristic of those in the heavy fuel oil released by the 2002 Prestige oil spill was determined for narcosis and mortality endpoints by Barata et al. (2005). The authors specifically assumed that PAH were responsible for most of the toxicity of spilled oil (Neff et al. 1976). Exposures to aqueous concentrations were for a period of 48 h to single PAH or equitoxic combinations of PAH mixtures. Chemical analyses of exposure media were done at the beginning and end of the exposure and were restricted to 1 and 3 exposure levels for single-substance and mixture-toxicity assays, respectively. The measured aqueous concentrations declined over time, particularly for the more volatile PAH. The concentrations used for assessment assumed that PAH concentrations that were not measured declined in the same manner. Thus, the concentration for assessment used the average value between the beginning and end of the exposure as the exposure concentration with a similar extrapolation for the nominal concentrations assuming the same relative decline for each compound. The authors also compared the toxicity of each compound to a nonpolar narcosis model fit to the KOW. A TU approach was used to evaluate the combined toxicity of the mixture components for compounds that produced measurable lethal concentrations for 50% mortality (LC50) values within the solubility limit. Dimethylphenanthrene was not included in the mixture study because it did not produce an LC50 or effective toxic concentration for 50% response (EC50) within its solubility limit.

No tissue residue measurements were made, resulting in the assumption that the compounds were taken up in proportion to their aqueous concentration. Measuring tissue residues would have been difficult for such small organisms, but it would have enabled a more direct dose-response determination and would have allowed inclusion of the contribution of more hydrophobic contaminants to the mixture study. By using the aqueous concentration, contributing biotransformation products were implicitly included but not specifically determined; thus, understanding causality was incomplete. A similar approach for evaluating PAH has suggested that metabolites are part of the contribution to the mortality endpoint (DiToro et al. 2000).

Although the authors focused on those mixture components that were toxic below the water solubility limit in individual tests, they did examine the ability of those compounds to fit a quantitative structure activity (QSAR) model for nonpolar narcosis. With the exception of methylphenanthrene, all of the individual compounds fit the QSAR model for nonpolar narcosis, supporting narcosis as the mode of action for most of the components in the mixture. Furthermore, the components of the mixture, including the methylphenanthrene, showed additivity to produce dose-response curves that had 50% response at total TU values that were not different from 1.0. The approach used here does not allow examination of the potential toxicity contribution of less soluble PAH to mixture toxicity. High molecular weight PAH undoubtedly contribute to the toxicity of spilled oil (Neff 2002; Hodson et al. 2007). The failure to explicitly examine body residues or the potential impact of biotransformation products may have contributed to the limited understanding of the mode of action for methylphenanthrene because marine copepods apparently are able to metabolize and excrete PAH rapidly (Sole and Livingston 2005; Berrojalbiz et al. 2009). Because the exposures were short and the mean exposure concentration was used as the dose metric, extrapolation to environmental conditions is possible.

Comparing the experimental results to known modes of action through the use of a QSAR model and the demonstration of additivity was an excellent approach for establishing the contribution of the individual components to the toxicity and to establishing causality for most of the components in the mixture. A negative feature was the failure to measure body residues of PAH and biotransformation products. Measures of body residues might have led to better understanding of the mode of toxic action for the methylphenanthrene and allowed the evaluation of contributions from compounds that do not exhibit acute toxicity within their solubility limit but may contribute to the same mode of toxic action. The investigation was also limited because the authors assumed that PAH were the causative agents for toxicity of spilled oil. However, this does not account for all components of oil and perhaps misses important contributions from other compounds. Although the compounds did fit an expected QSAR model except for methylphenanthrene, there is a need to examine a broader range of compounds from oil that may be contributing either as additive to the narcosis mechanism or producing toxicity by separate mechanisms.

Case study three: Environmental complex mixture

Mixture components contribute to toxicity in a variety of ways and with different interactions. When the number of compounds contributing to environmental mixtures is large and there are multiple mechanisms and/or modes of toxic action, the difficulty in establishing the causative agents or even groups of compounds for each specific endpoint is challenging.

To advance an approach for establishing the contribution of different organic chemicals in a contaminated sediment to mixture toxicity, Sundberg et al. (2005, 2006) used a bio-effect directed fractionation approach to measure the contribution of several organic chemicals to the toxicities of toluene extracts of sediments collected from a reference and contaminated site. The toluene extracts were cleaned up and fractionated into 3 primary fractions that contained aliphatic and monoaromatic hydrocarbons (MAC), diaromatic hydrocarbons (DAC) mostly polychlorinated biphenyls (PCBs), and polycyclic aromatic compounds (PAC = PAH). The PAC fraction was further subfractionated into 10 fractions that contained different mixtures of PAH. The concentrations of PCBs and PAHs in the total extract and all fractions and the amount dosed to the eggs were measured. The toxicity of each fraction was evaluated by injection into rainbow trout (Oncorhynchus mykiss) eggs. Endpoints included egg and larval mortality, teratogenicity, aryl hydrocarbon receptor (AhR) mediated toxicity, hepatic ethoxyresorufin O-deethylase (EROD) activity, and larval malformations. Injection into eggs provided a clearly defined single dose but bypassed potential bioavailability limitations and absorption kinetics expected in environmental exposures. Dose-response relationships were used as part of the evaluation of differences between fractions and to compare the contributions of the fractions relative to total extract response.

The toxicity of the reference site extract and the carrier control were not different at the low exposure concentration and were similar to exposure to a reference compound (benzo[a]pyrene) dosed at 2900 µg/kg egg. The total extract of the reference site sediment containing 210 µg total PAH/kg egg and the contaminated site sediment containing 840 µg PAH/kg egg showed deviation from control, with the reference site only significant for edema, and larval mortality, whereas the contaminated site extract produced high egg and larval mortality and significant responses for all teratogenic endpoints.

When the contaminated site sediment extract was fractionated, the MAC subfraction was not mutagenic and did not induce EROD. The sum of EROD induction demonstrated by the individual DAC and PAH subfractions was greater than that of the total extract and gave dose-response relationships that were parallel, indicating nonadditive effects when eggs were exposed to the whole mixture. All 10 PAH subfractions induced significant EROD activity and 2 subfractions were mutagenic. The greatest induction was produced by the subfraction that contained 5- and 6-ring PAH and the fractions containing 3- and 4-ring and 4- and 5-ring PAH were mutagenic. The DAC fraction induced a higher EROD activity than a similar dose of the PAH fraction but was less mutagenic and teratogenic than the PAH fraction. Thus, there was not a clear relationship between EROD induction and mutagenicity or teratogenicity in these fish larvae (Sundberg et al. 2005).

Because most larval malformations occurred with the PAC subfractions, the eggs were exposed to a synthetic mixture of 17 PAH, and responses were compared to those elicited by exposure to the sediment PAH fractions (Sundberg et al. 2006). The synthetic PAH mixture, composed primarily of high molecular weight nonalkylated PAH, could not explain all the toxic effects and could explain only 4% of the EROD induction demonstrated by the sediment PAC fraction. Thus, not all PAH were acting with equal potency to produce the observed toxicity or there were other unmeasured chemicals (possibly alkyl-PAH and PAH degradation products) in the sediment organic extracts that contributed to toxic effects. Specific PAH contributing to the observed toxicity were not identified, although inferences can be made based on the contributions of different fractions or the synthetic PAH mixture to observed toxic effects.

The use of bio-effect directed fractionation helped to identify important groups of toxic compounds in complex environmental mixtures but was limited, in this case, in that only subfractions of the complex mixture of compounds producing the results could be isolated, not the specific causative compounds. The approach demonstrated the importance of compound interactions, e.g., the lower EROD induction for the whole extract compared to the fractions. However, the findings were limited because the potential limitations of bioavailability of sediment-associated contaminants and the corresponding toxicokinetics of uptake were bypassed. Although the injections provided a clearly defined dose, the exposures could not be directly related to field exposures but might be surrogates for tissue–residue concentrations. Finally, the work demonstrated that all PAH are not equally toxic with respect to different measurement endpoints; thus, more effort is required to identify causative compounds among PAH for specific endpoints.

Case study four: Simulated environmental complex mixture

Heintz et al. (1999) carried out laboratory experiments in 1993 using cylindrical vertical columns containing gravel to which different amounts of weathered Alaska North Slope crude oil had been applied to simulate the exposure of pink salmon (Oncorhynchus gorbuscha) eggs in a tidal environment to hydrocarbons leaching from weathered crude oil in intertidal sediments. Alternating freshwater and seawater, to mimic tidal mixing of fresh and salt water in the salmon stream, were pumped upward through the columns to produce oil in water fractions that served as exposure media for the fertilized eggs.

Two types of weathered oil were used. The first was an oil that had been artificially weathered by heating at 70° C overnight (AWO) The second was a very weathered oil (VWO) on gravel reused (without separation of the VWO from the gravel) from a similar 1992 study (Marty et al. 1997) after the oil on gravel had been water washed in columns for 9 months and then stored outside for 3 summer months.

For the AWO treatments, 7 AWO-dose levels on gravel were used, ranging from 0 to 2450 mg/kg dry wt total extractable organic matter (oil). For the VWO, there was a single treatment using the further degraded oil on gravel from 1992. The initial 1992 oil concentration of this VWO on gravel had dropped from 4510 mg/kg dry wt in 1992 to 2860 mg/kg dry wt in 1993 (Heintz et al. 1995) and after approximately 1 y of natural biodegradation and oil loss, had a very different hydrocarbon composition from the AWO. In addition, the different dose levels of AWO gravels had different initial relative PAH compositions (EVOSTC 2009).

Eggs were placed directly in the gravel for the VWO treatment and all AWO treatments. In addition, there were 3 indirect exposures to AWO at doses of 0, 74, and 717 mg/kg oil on gravel, in which eggs were place on a perforated aluminum plate suspended over the gravel.

Measurements of PAH exposure (as PAH concentration in exposure water and egg–alevin tissues) and egg–alevin responses to the different exposures were made at different times after initiation of the approximately 200-day exposures. Response measurements included egg mortality at eyeing, larva mortality at emergence, and selected sublethal effects in emergent larvae (alevins) (Heintz et al. 1995, 1999). Exposure measurements included the concentration of total extractable organic matter (parts per million, mg/kg) in the gravel at the start of the experiment and the concentrations of alkanes, total polycyclic aromatic hydrocarbon (TPAH), and individual PAH concentrations in water, tissue, and oiled gravel samples taken at time intervals during each experiment. These data are available in the public Exxon Valdez Oil Spill Trustee Council Hydrocarbon Database (EVOSTC 2009). There were no measurements of microbial degradation products, biotransformation products produced by eggs–alevins, or other organic chemicals in column effluents or fish tissues.

Total PAH concentration in the column effluent decreased rapidly during exposure, and tissue PAH concentrations also decreased from an (unknown) initial peak value. Loss of the more volatile compounds was greater at lower treatment concentrations (EVOSTC 2009). Thus, the exposures were time variable in terms of both the concentration and composition of PAH in the effluent water such that a true dilution series of the exposure mixture did not occur.

The time-variable nature of each exposure was equivalent to a single addition exposure with a rapid decline in exposure concentration and changes in composition over time in each treatment, with mixtures of different initial compositions and concentrations over all treatments. Evaluation of the response should have been based on a dose metric that specifically addressed the contribution of the individual ingredients of the mixture with a TU model and/or models for each endpoint. Such TU model and/or models could have been based on 1) the concentrations of each chemical in the mixture in the effluent water using the initial concentration, 2) an integrated external dose approach using peak concentration of mixture components in embryo tissues (the body residue approach), or 3) some measure integrating these 2 exposure metrics. Development of a TU model would have required estimation or measurement of threshold concentrations for the various components of the mixture.

The exposure metric for estimating the dose-response was the loading of total extractable oil on the gravel in the columns, as shown in Figure 2 of Heintz et al. (1999), which is clearly not appropriate as the loading does not reflect the differences in the resulting PAH concentration and composition in exposure water or tissues among the treatments. More important, this dose metric does not reflect differences in the apparent bioavailability of different hydrocarbons in the AWO and VWO treatments (Heintz et al. 1999), even though tissue PAH concentrations were measured. The authors then based conclusions on the initial total PAH concentration in the water as the surrogate exposure dose even though such measures were not used to establish a dose-response (Heintz et al. 1999).

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Figure 2. Dose-response curves for Heintz et al. (1999) day 36 embryo mortality data with the dose given as (A) initial water alkyl-phenanthrenes concentration (EVOSTC 2009), and (B) day 36 egg alkyl-phenanthrenes concentration (EVOSTC 2009). Using tissue or water TPAH as the dose metric yields similar graphs. Because the toxicant concentration (PAH or alkyl-phenanthrenes) for the VWO experiment is in the same range as those showing no toxic effect, the toxicity observed in the VWO experiment was not PAH-related.

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Tissue residue data were used subsequently to evaluate the dose-response (Barron et al. 2004). However, the time point selected for evaluation of the Heintz et al. (1999) body residue data was the PAH concentration in the eggs after 36 d exposure. This concentration probably was below the peak concentration, which likely occurred before 36 d, thus likely underestimating exposure to the un-metabolized PAH (Mathew et al. 2008) and did not incorporate contributions from biotransformation products.

Heintz et al. (1999) reported that an initial 18 µg/L aqueous TPAH concentration was toxic to embryos in the AWO treatment and a 1 µg/L aqueous TPAH was toxic to embryos in the VWO treatment, where toxicity was expressed as mortality and growth reduction. They concluded that toxicity of the AWO and VWO was likely caused by the higher molecular weight PAH (alkyl-phenanthrenes and chrysenes) because the relative concentration (fraction of total PAH) of these higher molecular weight PAH was higher in the VWO than the AWO water. Actually, measured concentrations of all PAH, including alkyl-phenanthrenes, were much lower in the 1 µg/L aqueous dose of VWO than in the 18 µg/L toxic dose of AWO (EVOSTC 2009). As a result, the subsequent evaluation of tissue data did not yield a monotonic dose-response relationship when the VWO treatment was included (Barron et al. 2004). An attempt to replicate the results of the VWO exposure, using gravel columns containing naturally weathered oil collected from the shore of Prince William Sound after the Exxon Valdez spill, demonstrated that the concentrations of aqueous TPAH in the effluent from the naturally weathered oil at 8.27 µg/L did not exhibit mortality or elevated blue sac disease (Brannon et al. 2006). The egg and larvae mortality reported by Heintz et al. (1999) in the VWO treatment occurred at tissue PAH concentrations (EVOSTC 2009) below those showing no mortality for AWO treatments (Figure 2), indicating a lack of a dose-response relationship for the VWO treatment. Alkyl-phenanthrene concentrations, which are approximately proportional to TPAH concentrations, are plotted as the dose in Figure 2 because Heintz et al. (1999) assumed, but did not prove, that they represent the toxic components of the VWO.

Causality of the observed toxicity was not established. The authors seem to have assumed that dissolved PAH were the only toxicants of concern and that all target PAH were acting with equal potency for all endpoints investigated, based on use of TPAH in their conclusions. The authors did acknowledge the potential for different modes of toxicity by different PAH in the mixture but failed to follow-up with experiments or models to support this possibility, including demonstration of dose-response. They also suggested that metabolites and biodegradation products could be contributing to toxicity but did not measure or estimate metabolite concentrations in the embryos or even all organic components in the column effluents, including other hydrocarbons, phenols, and microbial biodegradation products.

If the apparent dose-response for the AWO is evaluated independent of the VWO, there is a suggested monotonic dose-response relationship when using either total PAH or total alkyl-phenathrenes (see Figure 2 for the alkyl-phenanthrene curve). However, the observation of an apparent dose-response for the AWO exposures does not prove causality. In the work of Barron et al. (2004), where selected models were examined to attempt to establish causality, it is clear that there were not high enough concentrations in the tissue to cause mortality by narcosis for total PAH. The best model was an alkyl-phenanthrene model based on retene as the denominator for creating the TU. This model may have overestimated the TU of some of the alkyl-phenanthrenes because retene is the most toxic of this class, whereas other alkyl-phenanthrenes are less toxic based on their EC50 values (Turcotte et al. 2011). Thus, if the species specific toxicities of each of the alkyl-phenanthrenes were used, the number of TU may have been lower, which would have altered the assessment of the contribution of these potential causative agents. However, these models lay a foundation for establishing that alkyl-phenanthrenes were substantial contributors to the toxicity for the AWO studies. This conclusion would need to be supported with confirmative toxicity tests containing only alkyl-phenanthrenes. Furthermore, the use of models that explain most of the toxicity with only a portion of the PAH signature, alkyl-phenanthrenes, demonstrate that conclusions cannot be made on the basis of TPAH in either water or tissues, because the composition of the PAH mixtures vary substantially and TPAH would not necessarily retain the same proportion to the alkyl-phenanthrene fraction for all potential environmental mixtures. Finally, the results of the modeling would still be deficient for the VWO exposure, which seems to be an outlier for all the models and suggests that other compounds or stressors than just PAH or alkyl-phenthrenes in the gravel column effluents were participating in the VWO toxicity.

It is particularly difficult to meet the 2 fundamental criteria for mixture studies with complex mixtures and exposures. Failure to fully characterize the mixture composition and concentration over time including biotransformation products in tissues as well as exposure water and to establish an appropriate dose metric limits the interpretation of the experimental results. Finding that some of the treatments do not fall on a dose-response curve when applying the appropriate dose metric, e.g., aqueous or tissue concentrations, prevents interpreting the results from that outlying treatment relative to the dose metrics used. This emphasizes the need to consider all stressors that may contribute to the observed responses. In addition, the failure to establish dose-response for all treatments based on a consistent and meaningful surrogate and to establish causality, limits the conclusions that can be drawn and makes extrapolation of the data to environmental conditions impossible. Furthermore, correlation creating a dose-response relationship only provides inference of toxicity and does not confirm causality; thus, it is critical to perform definitive tests to determine actual causality rather than making assumptions about which compounds are contributing to specific toxic responses.

Case study summary

From the above case studies, it is clear that establishing dose-response usually is possible. However, care must be taken to ensure that the surrogate dose is consistent with a dilution of the mixture and that toxicokinetics or other interactions are not complicating the relationship. Furthermore, all compounds and potential confounding factors that are likely significant contributors to the dose-response must be included in the investigation. Because foreknowledge of the significant contributors usually is limited, measurement of all components of the mixture along with potential major metabolites is the best course of action. Establishing causality is the most difficult and least investigated of the 2 major elements for understanding mixture toxicity. Even in the simplest situation where the mixture was binary and biotransformation was explored, the identification of the specific toxic metabolites was not accomplished. As the mixtures increased in complexity, the definitive evaluation of causality was more difficult and was never fully satisfied. This area is one that requires more thought and study in the exploration of mixture toxicology.

TWO FUNDAMENTAL REQUIREMENTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

The case studies clearly illustrate that there are 2 fundamental requirements to correctly interpret mixture toxicity. First, a dose-response relationship must be established. Specifically, the test organisms must be exposed to a uniform dilution series of concentrations of the components of the mixture under investigation that leads to a gradient of toxic response and the exposure conditions must be defined quantitatively. The target dose (internal concentration), not just the external concentration, of all the potentially toxic chemicals in the mixture is best used as the dose metric (Escher and Hermens 2002, 2004).

Second, the cause and/or causes, the responsible compounds, and/or nonchemical stressors of any observed toxicity must be determined to the extent possible. Measurements of toxicity must be based on appropriate receptors and measurement endpoints because different toxicants in the mixture could influence different receptors and endpoints. Endpoints should be evaluated separately when evaluating the toxicity of mixtures to avoid confusion about the appropriate causative agent (Kortenkamp et al. 2009; Dyer et al. 2011). Identification of causation must not depend solely on correlation. Additional data supporting the action of each of the component chemicals to the specific mode/mechanism of action is required to support causality. Potential interfering or modifying factors must be understood and addressed so that it is clear what is and what is not influencing an observed gradient of toxic response. Ultimately, the data must fit the conclusions, and uncertainties affecting the study conclusions must be clearly presented.

EXPOSURE CONDITIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Establishing a mixture dose-response relationship depends on the duration and timing of exposure (particularly for sensitive life stages such as embryos that are rapidly undergoing developmental changes) and the role and significance of any physical, chemical, and/or biological modifying factors. Exposure and resulting toxicity also can be modified by interactions among mixture components, where toxicity is altered by changes in mixture composition that alter the toxicokinetics and/or toxicodynamics or where not all of the mixture's components affect a specific endpoint response.

Duration of exposure

Because the toxicokinetics of different chemicals vary widely, which for organic chemicals varies with their relative solubility in water and tissues, proportional to the KOW (Hawker and Connell 1986; Baussant, Sanni, Jonsson et al. 2001; Baussant, Sanni, Skadsheim et al. 2001), accurate estimation of the actual exposure to the mixture components is difficult when the dose metric is the concentration of the mixture as a whole or of the individual chemicals in the mixture in the exposure medium. However, if median effect-time is compared to the tissue concentrations over time for the different chemicals in the mixture, a more accurate assessment of the toxic dose and ultimately the causes of toxicity can be obtained by accounting for the different toxicokinetics of compounds in the mixture and modes of toxic action.

The exposure does not need to be strictly constant and a time-weighted average can provide a reasonable description of exposure if the elimination rate is slow relative to the dose pulse interval (Lee et al. 2003; Landrum et al. 2004). In these cases, the organism will reach steady state, and tissue concentrations will be based on the time-weighted average of the exposure. Furthermore, if pulsed exposures are separated by sufficient time, the organisms may respond as if the exposures are independent, precluding the need for interpreting exposure to multiple pulses (Zhao and Newman 2006). In single pulse exposure experiments, where exposure concentrations can decline rapidly during initial periods of exposure, toxicologically relevant maximum body burdens can occur before the first experimental measurements of body burdens (Mathew et al. 2008). This makes it possible that initial tissue concentrations measured at some time after the initiation of single pulse experiments can underestimate the body burden actually related to the toxic effect (see the case studies above). Because of the rapidly declining exposure concentrations in a single pulse exposure, the use of aqueous exposure concentrations, whether initial or some mean, to define dose is not an adequate representation of dose (Mathew et al. 2008). Ashauer et al. (2007a, 2007b, 2007c) have proposed a process-based model, the Threshold Damage Model, to simulate survival of aquatic invertebrates after exposure to pulses of organic contaminants alone and in mixtures. This becomes particularly critical when some compounds such as organophosphate compounds have very long recovery times and challenges with other compounds acting by the same mechanism can show anomalous toxicity if organisms are challenged before recovery is complete.

In addition, timing of the exposure in relation to test organism life cycle needs to be understood when establishing the dose-response. For instance, if exposure is during reproduction or early life stages, the measurement endpoints (and the inferred population-level effects) will be very different than if exposure is only to adult organisms. For single pulse exposure experiments, the confounding effects of rapidly changing exposure concentrations are particularly problematic with exposures to early life stages of target organisms that are also rapidly undergoing developmental changes during the exposure period and where timing of exposure during development is critical in defining effect.

The susceptibility of a developing embryo to a toxicant depends on the stage of development at which exposure takes place, and embryo-larval toxicity tests are well established tools in assessing risk of chronic exposure to toxicants (Birge et al. 1985). For example, the toxicity, measured as a set of lethal and sublethal endpoints, of a weathered crude oil water accommodated fraction (WAF) to Atlantic herring was a function of the exposure concentration, duration of exposure, and life stage at which exposure was initiated (McIntosh et al. 2010). Newly fertilized eggs (fertilization to blastulation) were the most sensitive, and sensitivity decreased as the eggs developed and then increased again on hatching and yoke absorption. Gametes and newly hatched yoke sac larvae were the most sensitive to brief exposures (<24 h). Newly fertilized embryos were the most sensitive to greater than 24-h exposures. These results are consistent with the observation that the permeability of the egg chorion to inorganic ions and nonpolar xenobiotics is high at fertilization and decreases markedly with egg hardening and the development of the perivitelline space between the chorion and the vitelline membranes shortly after fertilization (Villalobos et al. 2000; Finn 2007). Rates of bioconcentration of nonpolar organic chemicals in fish embryos and/or larvae are high shortly after fertilization, decrease at egg hardening, and then rise at hatching (Petersen and Kristensen 1998; Finn 2007). A large fraction of the nonpolar organic chemicals bioconcentrated during embryonic development accumulate in the lipid-rich yolk and then are released into the tissues of the yolk sac larvae as the yolk is resorbed (Finn 2007). This pattern of embryo and/or larvae response to exposure to dissolved nonpolar organic chemicals seems to be most pronounced for species with larger eggs with thicker chorions (Stene and Lonning 1984; Finn 2007).

Whether exposure is constant or intermittent, toxicity can continue beyond the exposure period (Zhao and Newman 2004, 2006) as “carry-over toxicity” (Ashauer et al. 2010), probably due to the additional time required for elimination or detoxification of the toxicant and biochemical repair. For some substances, such as organophosphate pesticides, the integrated exposure of the organism is the critical dose metric because toxicity is based on cumulative binding of the toxicant to a specific site of toxic action (Legierse et al. 1999).

Factors modifying exposure

In the environment, exposure can be modified by where animals live and feed and how they behave (Chapman 2008). However, in toxicity tests, such exposure modification is generally controlled. Below, we discuss modifications of exposure that can occur in toxicity tests and that can affect the results of those tests.

Exposure concentration and composition of a mixture at the site of toxic action can be modified by biotransformation of chemicals within the test organism, increasing the parent compound elimination rate and decreasing the equilibrium concentration of the parent chemicals in tissues (Baussant et al. 2001a,b2001). Biotransformation changes the inherent toxicity of the parent compound because metabolites can be more or less toxic (Schuler et al. 2006; Carney et al. 2008). In addition, microbial transformation in the exposure medium (Middaugh et al. 1998, 2002; Shelton et al. 1999; Melbye et al. 2009) can increase toxicity as demonstrated for herring embryos and larvae exposed to the biodegraded WAF of Alaskan North Slope crude oil (Middaugh et al. 1998; see case study 4). In either case, the alteration of the toxicant can result in changes in the toxic effect (Middaugh et al. 1998; Billiard et al. 2008). When the mechanism and/or mechanisms of toxic action, exposure, and biotransformation are known, time-dependent mixture effects can be evaluated through modeling (Lee and Landrum 2006a, 2006b). For example, a time-variable model of PAH bioaccumulation in fish embryos found that inclusion of PAH metabolism improved estimates of bioaccumulation of un-metabolized PAH (Mathew et al. 2008).

External (microbial) and internal biotransformation are generally thought to lead to reduced toxicity by making compounds more polar, reducing bioaccumulation, or increasing excretion rates. However, the products of microbial growth and general metabolism not related to toxicant metabolism have also been shown to produce toxic effects through the production of microbial toxins and/or pathogenic action (Grisolia et al. 2009; Hamm et al. 2006; Marty and Heintz 2010). Biotransformation can also switch the mechanism of toxic action by creating products with specific modes of toxic action (McElroy et al. 2011). For instance, biotransformation can alter the observed toxicity of hydrophobic chemicals, such as some chlorinated hydrocarbons and PAH (Middaugh et al. 1998; Lee and Landrum 2006b; Akcha et al. 2003; Schuler et al. 2004, 2009). Biotransformation can act to reduce or increase toxicity depending on the mechanism of action, the endpoint under consideration, and the substance being biotransformed (Escher et al. 2011). Thus, without evoking external factors such as partitioning to phases that alter bioavailability, the effective dose can be complicated by the biotransformation rate differences of the various mixture components. Approaches that address the accumulated dose using body residues and address biotransformation explicitly will provide the best possible understanding of the toxicity of mixture components (McCarty et al. 2011).

Exposure can also be modified by dilution of the mixture. When studying mixtures, the bioaccumulation of each of the components is generally considered to be independent of the other components in the mixture. Although there is some evidence of this for exposures to contaminated sediments (Landrum 1989), this assumption is rarely tested, and there is evidence to the contrary with aqueous exposure to PAH exhibiting reduced bioavailability in the presence of more hydrophilic aromatic and aliphatic compounds (Landrum 1982). Furthermore, exposure and response are generally considered to be to all of the components of the mixture. Thus, features that could affect the bioavailability of individual mixture components with serial dilution could influence the expected toxicology of the mixture. Therefore, it is critical that mixture dilutions not have different relative compositions; in other words, that bioavailability is not affected by more than dilution. Toxic unit approaches based on internal body residues, assuming additivity, can provide necessary information to determine whether dilution has inappropriately changed bioavailability and thus toxicity (McCarty et al. 2011).

Sorbing phases, such as dissolved organic carbon, suspended organic colloids, fine-grained mineral particles (such as suspended clay), and oil or other nonaqueous phase liquid phases complicate the exposure environment (Landrum et al. 1996). The most bioavailable form of organic chemicals is the freely dissolved fraction, and the most bioavailable forms of most metals are the free ions and aquo ions (Neff 2002; Chapman 2008). Complex formation, speciation (metals), and the presence of sorbing phases, as well as environmental parameters such as salinity and temperature, can change the size or composition of these bioavailable fractions, thus affecting exposure. For instance, whereas substances sorbed to particles are typically not available for uptake via respiratory surfaces, they sometimes are available for uptake via ingestion (e.g., by filter- or suspension-feeding organisms). Assimilation efficiencies, uptake, and the toxicokinetics of adsorbed organic chemicals are much lower than those of dissolved organic chemicals (Wang and Fisher 1999; Borgå et al. 2004), although the concentrations on particulate phases can be much greater than in water allowing for similar mass accumulation rates if the contaminants are not tightly bound to the particles. Therefore, it is important to measure dissolved, sorbed, and potentially suspended proportions of toxicants when determining actual exposure concentrations. Thus, all potential routes of exposure need to be considered when evaluating mixtures in the environment. When there are multiple exposure routes, tissue concentrations will be superior measures of exposure.

What to measure in mixtures

If a mixture is relatively simple and if biotransformation is negligible, then determining the appropriate chemicals to measure is not difficult. However, when a mixture is complex, such as mixtures of dissolved and dispersed petroleum products, researchers have to choose what to measure. For instance in the case of petroleum exposure, analytical methods are sufficiently robust to allow the reliable measurement of normal and some branched and cyclic alkanes and unsubstituted and alkyl-substituted PAH and related heterocyclic compounds in water, sediment, and tissues (Wang and Stout 2007). When the mixture is simple, measures of specific biotransformation products are readily accomplished (Lotufo et al. 2001) and when mixtures are more complex the contribution of metabolites to the exposure can still be established (Mathew et al. 2008) even if specific metabolites are not measured. For PAH mixtures, biodegradation products and/or metabolites in tissues of aquatic vertebrates can be quantified indirectly as biliary excretion products (Beyer et al. 2010) that can serve as a surrogate measure of internal dose in fish (Meador et al. 2008). The more specific the measure of biotransformation and the information about the toxicity of the biotransformation products, the more accurate the assessment of this component of mixture toxicology. For instance, the toxicity of fluoranthene to C. dilutus was found to be substantially influenced by biotransformation, suggesting that 1 or more biotransformation products was responsible for the enhanced toxicity (Schuler et al. 2006).

Other factors associated with the bioassay regime can produce confounding effects and should be measured and considered when analyzing the data. For instance, Heintz et al. (1999) (see case study 4) and Carls et al. (1999, 2005) chose to measure exposure of salmon and herring eggs to aqueous extracts of weathered crude oil as aqueous concentrations of total PAH that varied in concentration as well as composition during the exposure period. These exposures are best described as a double exponential decay (Mathew et al. 2008). However, Heintz et al. (1999) and Carls et al. (1999, 2005) implicitly assumed that PAH were the only toxic compounds in the aqueous extracts of weathered crude petroleum. These studies ignored the possibility that other components of the weathered oil, products of microbial degradation of the oil, or other organic compounds, biotransformation products in the embryos, and other organic matter in the dosing apparatus may have contributed to the toxic response. Such confounding components have been recognized as contributing factors in other petroleum-exposure experiments (Wolfe et al. 1995; Middaugh et al. 1998, 2002; Barron et al. 1999; Shelton et al. 1999; Carney et al. 2008; Melbye et al. 2009). Although there are no perfect choices of the appropriate compounds to measure in such situations, it is critical that the rationale for the choices made be transparently documented, along with associated uncertainties, before drawing conclusions from experimental results.

Timing of the dose and induction of the organism's biotransformation system will dictate the response observed, particularly if biotransformation leads to more toxic components. Thus, identifying the appropriate chemicals to measure in mixtures and the appropriate processes to be addressed become critical for determining both dose-response and causation.

MEASUREMENT ENDPOINTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Measurement endpoints comprise the specific toxic response and/or responses observed. Toxicity observed as different endpoints can occur by different mechanisms or result from different chemical concentrations or mixture components. Thus, separation of the assessment of the dose-response for different endpoints is required to ensure that modes and/or mechanisms of action are not mixed in the dose-response analysis (Kortenkamp et al. 2009; Dyer et al. 2011).

The most studied and understood mechanism of aquatic toxicity for organic compounds is mortality by nonpolar narcosis (McCarty et al. 1992, 1993). Narcosis demonstrates additive toxicity of individual mixture components. Internal concentrations in the range of 2–8 mmol/kg represent the acute critical body residue for 50% mortality; chronic critical body residues are approximately equal to 10% of acute values (0.2–0.8 mmol/kg) (McCarty and Mackay 1993). Interpretation of critical body residues across species is more precise when the data are normalized to tissue-lipid concentration, because storage lipids and to some extent membrane lipids govern compound accumulation, and membrane lipids are the site of action for narcosis (McCarty et al. 2011; Landrum and Fisher, 1999). If the dose-response is based on body residues, then the contribution of metabolites must be included. The development of mixture criteria for PAH implicitly included the role of metabolites for mortality by narcosis (DiToro et al. 2000). Although progress is being made and databases are being compiled for biotransformation rates in fish (Arnot et al. 2009), there are few studies of the toxicology of metabolites (Carney et al. 2008). The measurement and consideration of metabolites for both single compounds and mixtures require more research.

Acute and chronic critical body residues for organic compounds, with specific modes of toxic action for both mortality and other endpoints, often occur at much lower concentrations than for acute mortality via nonpolar narcosis (McCarty and Mackay 1993). Individual chemicals comprising a mixture may exert different modes of toxic action depending on the exposure time frame and endpoint under consideration. For instance, acute exposure to high concentrations of 1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) can result in mortality by narcosis (Lee et al. 2009), whereas reproductive effects occur during chronic exposure to far lower concentrations (Hwang et al. 2004). Toxic responses can and do occur at different concentrations depending on the mode and/or mechanism of toxicity and the endpoint and/or endpoints investigated (Hwang et al. 2001, 2003, 2004; Schuler et al. 2007a, 2007b).

INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

The appropriate measure of dose must be determined to accurately interpret dose-response relationships in mixture toxicity studies. In the case of a constant water exposure, the dose may be the water concentration, assuming that accumulated dose as dictated by toxicokinetics will be proportionally the same among exposure water dilutions. For intermittent or pulse exposures, internal body residues provide the best information for interpreting dose-response when toxicant elimination is primarily by passive partitioning and metabolic transformation is slow of all toxicants in the bioaccumulated mixture. If, however, toxicokinetics are relatively rapid and the external exposure concentration is time variable, then the relative internal accumulated doses of individual components of the mixture can change significantly over the time course of the exposure. In this case, a surrogate dose should be determined, based on mechanisms of toxic action, tissue concentrations of each component of the mixture, and the time variation of the exposure concentration of each component. Peak internal body residue concentrations of each component of the mixture can be appropriate surrogates for a conservative evaluation for intermittent or pulsed exposures that are not independent if the timing of the first of multiple samplings of tissues for analysis is sufficiently close to the onset of exposure. If this is not the case, then measured tissue concentrations can underestimate the true peak exposure concentrations in the target tissue, particularly if the log KOW values of the chemicals in the mixture span a wide range (Mathew et al. 2008).

When the mechanisms of toxic action, exposure, and biotransformation are known, time-dependent mixture effects can be evaluated through a modeling approach (Lee and Landrum 2006a, 2006b; Belden et al. 2007; Mathew et al. 2008). Approaches that address the accumulated dose using body residues and address biotransformation explicitly will provide the best possible understanding of the contribution of each component to mixture toxicity. However, a danger associated with a modeling approach is that a “good fit” does not necessarily define an actual process. For example, the improvement of a model prediction of bioavailability of unmetabolized PAH by the inclusion of a rate factor describing toxicant loss due to metabolism does not give information on the modes and sites of toxic action or the contribution of metabolites that are most affected by that change due to toxicokinetics (Mathew et al. 2008).

The basic assumption in studies of mixture toxicity is that the quantitative effects of a mixture of chemicals can be inferred from knowledge about the toxicity of the individual components of the mixture (Kortenkamp et al. 2009). This usually is true if the chemicals in the mixture act in concert by similar toxic mechanisms (additive) without diminishing (antagonism) or enhancing (synergism) each others' toxicity. When the toxicants in the mixture act by different mechanisms of action, independent action (response addition) can be a more accurate model (Kortenkamp et al. 2009). However, because most mixtures contain groups of compounds that act additively within the group but independently between the groups, a mixed model would be more appropriate (Kortenkamp et al. 2009).

Significant deviations from additivity often are observed at relatively high exposure concentrations (McCarty and Borgert 2006a, 2006b) or when different components in a mixture have different mechanisms of toxicity (Billiard et al. 2008). Toxicokinetic interactions, such as inhibition or potentiation of detoxification enzymes by mixture components are known to cause deviations from additivity (Wassenberg et al. 2005; Billiard et al. 2006; Vrabie et al. 2009). However, as the number of components in a mixture increases, the range of deviation from additivity decreases, particularly when considering the mortality endpoint (Warne and Hawker 1995). Thus, it may be difficult to determine whether the toxicity of chemicals in mixtures is truly additive or caused by a few more toxic compounds, especially if some compounds are present at concentrations lower than others in the mixture or are accumulated less rapidly (because of slower bioaccumulation or faster biotransformation) in tissues.

When mortality is the endpoint and the components of mixtures are below thresholds for specific mechanisms of toxic action, additivity of components works well to describe the toxicity of the mixture (McCarty and Borgert 2006a, 2006b) and a TU additivity model can also be appropriate (Lotufo et al. 2000, 2001; Verbruggen and Van der Brink 2010). However, an independent action model or toxicity equivalency model may also describe the toxicity when the mixture has compounds that are acting by different mechanisms (McCarty and Borgert 2006a, 2006b; Kortenkamp et al. 2009; Dyer et al. 2011). These approaches are only feasible if the toxic thresholds for all the mixture components are known. Furthermore, mixture toxicity seems to approximate the toxicity of the most toxic component or group of components acting by the same mechanism of action when the components are acting at different receptor sites or are acting at the same site by different mechanisms (McCarty and Borgert 2006a, 2006b). At present, it seems that the conservative approach is to assume additivity among compounds acting by the same mode of toxic action (Kortenkamp et al. 2009), but this requires that the compounds are sorted by mode and/or mechanism of action for assessment, a complication identified by McCarty and Borgert (2006a, 2006b).

Establishing causality

Determining causation requires that the dose-response be established relative to not just the total mixture but to the compounds in the mixture that are likely contributing to the observed toxicity. Correlations observed during toxicity testing between specific measured mixture components and observed toxicity responses can be useful for designing further studies to determine causality but do not by themselves prove causality.

Toxicity identification evaluation (TIE) can be used in environmental studies to sort the toxicants into groups that can be identified as contributors to the toxicity of the mixture (USEPA 1991, 1993a, 1993b). For the most part, these methods are not sufficient to identify specific compounds, but they can identify the fractions of the mixture contributing to toxicity, and so provide a good initial approach for sorting out causality for complex environmental mixtures. The general TIE approach can be augmented by approaches such as bio-directed (effect directed) fractionation studies (Kortenkamp et al. 2009; Brack et al. 2008) and followed up with exposure of organisms to synthetic mixtures to verify the hypothesis of causative agents (Sundberg et al. 2005, 2006). Although the approach used by Sundberg et al. (2005, 2006) did not progress to identify the specific toxic components in the PAH fraction of a contaminated marine sediment, it did demonstrate that specific effects on fish larvae, including teratogenic effects, could not be attributed to a mixture of 17 parent and alkyl-PAH used in the synthetic mixtures. Similarly, the exposure of Japanese medaka embryos to crude oil PAH fractions prepared by low temperature vacuum distillation, acetone precipitation, and high pressure liquid chromatography demonstrated that toxicity was associated with fractions containing 3- and 4-ringed alkylated PAH (Hodson et al. 2007). If the internal dose of each component of the mixture is known, it may be possible to identify whether the observed toxicity belongs to a set of specific mixture components (Landrum et al. 2003). Without exposing organisms to specific known components of the mixture to verify the toxic response, the best that can be achieved from a mixture study is to identify inferences about the causes of total mixture toxicity. This inference becomes more tenuous when only a portion of the mixture components is considered.

Another approach to help establish causality is to examine such models as sum of TU or summation of body residues to better show that the compounds under consideration are the major contributors to the response. In the case of mortality by narcosis, there is sufficient information to examine the summation of molar concentrations to determine whether the response lies within the observed concentrations that have been found for acute or chronic mortality (McCarty and Mackay 1993). Finding that the molar sum of body residues was in the accepted range of response would suggest that all the compounds of major concern had been addressed. Likewise, if the sum of TU for mortality fell near 1 for 50% mortality, one could presume that the compounds of major concern had been addressed. Thus, a combination of correlation with other supporting data helps ensure that compounds of significance have not been missed in the evaluation of the compounds that are causing the observed responses.

DATA INTERPRETATION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

The importance of establishing causation cannot be overemphasized (see the case studies). If causation has not been established, all that can be concluded is that some compound and/or compounds in the mixture and/or modifying factor and/or factors resulted in the observed toxicity. Without establishing causation, it is inappropriate to arbitrarily assume that all or a specific set of the compounds in the mixture are contributing equally to the observed toxicity, particularly because analytical measurements will likely be specific to certain specific components of the mixture, rather than measuring all compounds and other confounding factors that could contribute to toxicity.

All compounds in a mixture that could potentially be responsible for the observed toxicity should be analyzed such that no potential toxicants, including metabolites, microbial degradation products, or abiotic oxidation-reduction products, are missed. If all of the potentially contributing toxicants cannot be characterized, causality cannot be definitively established.

The dose metric must then be addressed after all potential contributing toxicants have been determined and measured. Toxicokinetics can be driven by external factors as well as by differences in the characteristics of individual mixture components. Thus, both the concentration of mixture chemicals in the exposure medium, focusing on freely dissolved or bioavailable concentrations, and the concentration of mixtures of chemicals in the organism over time should be measured to establish the appropriate surrogate dose for the study.

If exposure is constant or near constant, toxicity can be evaluated under steady state conditions. If exposure is not constant (the usual situation in the laboratory and field) and the concentrations in the exposure media and or organism vary over time, contributions to mixture toxicity can be evaluated if there is parallelism between concentrations of each chemical in the exposure medium and animal tissues (Beckmann et al. 2004; Jonsson et al. 2004). If external and internal concentrations are not measured frequently during exposure, it may be possible to use the constant area under the exposure curve, a time-weighted average, or the peak exposure concentration as a surrogate dose. However, in this case the evaluation is experiment-specific and extrapolation to other conditions usually will not be possible.

If toxicity depends on some biological timing event such as a critical development step or the absorption of yolk in embryos, it may only be possible to evaluate toxicity based on the toxicant concentration in the organism measured as close to the time of the event as possible. Because the permeability of the vitelline membranes and chorion of fish eggs varies during development (Finn 2007), the concentration in the exposure water is not a good dose metric in fish early life stage tests and internal dose must be used when examining the toxicity of complex mixtures to fish embryos. To obtain the peak dose in the organism, sufficient samples must have been taken over the course of the exposure so that temporal variation in the internal dose is known.

If mixture compositions are equivalent except for concentration across dilutions, a dose-response can be evaluated. However, if mixture composition varies across dilutions, dose must be evaluated based on the TU or toxic equivalent factor model, which requires knowledge of the threshold toxicity concentration of each component in the mixture for each endpoint under consideration.

In summary, the data should dictate interpretation of the study findings. All uncertainties need to be explicitly and transparently discussed. And the final study conclusions must consider all the data with no unexplained or unexplored inconsistencies.

CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

Without adequate thought and attention to the following basic requirements for establishing a dose-response relationship and determining the causative agent (s) for any observed toxicity (cf. Figure 3), study results will not be technically defensible or environmentally relevant.

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Figure 3. Some of the complex interactions that must be considered when determining cause-and-effect. See text for more detailed information.

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Establishing a dose-response relationship

  • Separate all dose-response analyses by endpoint.

  • Differentiate constant exposures from pulsed or intermittent exposures as these result in different temporal exposures to organisms.

  • Identify potential biotransformation products that may ultimately be responsible for the observed effect and/or effects.

  • Measure both external concentration and internal (body residue) dose for mixture components, including biotransformation products, to determine differences between exposure concentrations and internal doses at which different toxicity endpoints are observed and to help identify potential biotransformation products that may ultimately be responsible for the observed effect and/or effects.

  • If possible, measure body residues for all chemicals in the mixture suspected of contributing to mixture toxicity; this provides more certainty than measures of external concentrations for actual target site concentrations, particularly when there are multiple exposure routes.

  • If all mixture components are not or cannot be analyzed, transparently document the associated uncertainties so that surety of cause is not assumed.

  • Ensure that measurement endpoints are appropriate to the mechanisms of toxic action of the mixture and its components so that comparisons are not “apples to oranges.”

  • Consider and account for toxicity modifying factors that can confound apparent conclusions, including environmental conditions of the test, life stages and behavior of the test organisms, possible external or internal biotransformation of mixture components, and temporal dilution or variation in concentration of mixture components in the exposure medium (water, diet) or in tissues of test organisms.

Determining causation

  • Do not assume that correlation proves causation; it does not.

  • Consider all data and do not ignore inconsistencies that may well provide critical information to assist in determining causation.

  • Determine causation relative not just to the mixture but to its constituent components including biotransformation products—such products can sometimes be more toxic than the parent compounds.

  • Conduct confirmation studies, such as bio-effect directed fractionation, or tests with individual or surrogate mixtures of mixture components, and/or perform modeling based on known mechanisms such as molar or TU addition.

  • Discuss any and all uncertainties explicitly and transparently—do not overstate the cause of the toxicity when only inference has been established by focusing on portion and/or portions of a mixture.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES

We thank 2 anonymous referees for useful review comments. Funding for this work was provided by Exxon Mobil Corporation, Houston, TX; however, the conclusions are those of the authors and do not necessarily represent those of Exxon Mobil.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. CASE STUDIES
  5. TWO FUNDAMENTAL REQUIREMENTS
  6. EXPOSURE CONDITIONS
  7. MEASUREMENT ENDPOINTS
  8. INTERPRETATION OF DOSE-RESPONSE RELATIONSHIPS
  9. DATA INTERPRETATION
  10. CONCLUSIONS: GUIDANCE FOR TESTING THE AQUATIC TOXICITY OF ORGANIC MIXTURES
  11. Acknowledgements
  12. REFERENCES
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