Our Stolen Futurea book by Theo Colborn, Dianne Dumanoski, and John Peterson Myers
 
 

  Walker, NJ, P Crockett, A Nyska, A Brix, MP Jokinen, DM Sells, JR Haily, M Easterling, JK Haseman, M Yin, ME Wyde, JR Bucher and CJ Portier. 2004. Dose-additive carcinogenicity of a defined mixture of "dioxin–like compounds." Environmental Health Perspectives, in press.

Walker et al. provide experimental support for a common method used to estimate health risks following exposure to mixtures of dioxin and dioxin-like compounds, in which the contributions of different chemicals in a mixture are added together after adjusting for their relative potency. Their results are the first to specifically test the validity of this method for estimating cancer risks. Their findings re-affirm the need to base health standards on mixtures rather than single compounds.

Dioxin is an environmental contaminant to which all humans are constantly exposed through diet. Because dioxin is highly persistent, once exposure occurs it remains in human tissues, particularly fatty tissues, for extended time periods.

Both the U.S. National Toxicology Program and the International Agency for Research on Cancer have concluded that dioxin is a known human carcinogen. The detailed biochemical pathway that leads to cancer is not understood completely, but scientists are confident that the first step in one pathway leading to cancer takes place when dioxin binds to an intracellular protein known as the aryl hydrocarbon receptor aryl hydrocarbon receptor. When that happens, the Ah receptor can then bind to DNA and alter the expression of certain genes, changing the level of specific proteins and enzymes in the cells. The resulting imbalance then initiates cancer.

 

In addition to dioxin, many other chemicals bind to the Ah receptor, for example some PCBs and furans. Public health officials around the world are concerned about the combined effects of multiple chemicals that work this way, and how health standards can be adjusted to take into account the fact that people are always exposed to mixtures of dioxin-like compounds, not just one at a time.

To address this problem, most agencies assume they can just add—an assumption called ‘additivity’—the exposures for the different chemicals, adjusting for the fact that some compounds are more toxic than others. The standard method used to estimate toxicity of mixtures of dioxin-like compounds is based upon ‘Toxic Equivalency Factors,’ or TEFs (see sidebar).

 

Toxic Equivalency Factors--TEFs

A TEF is weighting factor that takes into account the relative toxicity of a contaminant compared to the most powerful dioxin, TCDD. Tests of individual contaminants are used to establish the potency of each compared to TCDD. Then that relative potency is used to adjust each contaminant’s contribution to the mixture’s toxicity. For a contaminant 1/10th as powerful as TCDD, it would take ten units of the contaminant to add to one equivalent of TCDD. To estimate the overall toxicity of a mixture, the contaminants’ weighted contributions are then added together. This calculation assumes that the effects are additive. This is not necessarily true, as contaminants might enhance or interfere with one another’s effects.

Research on other health endpoints—for example enzyme function and some reproductive effects—have indicated this approach is reasonable. Until this new study by Walker et al., the assumption of additivity had not been tested for cancer endpoints.

What did they do? Walker et al. carried out 4 long-term experiments with rats, exposing them to contaminants via gavage and then identifying cancer cases after death in complete autopsies. When the autopsies revealed lesions, the lesions were removed and examined microscopically. All diagnoses were reviewed by several experts, each of whom reviewed materials from all the studies to maintain quality control.

Animals were exposed for up to 2 years daily (5 days/week) to one or more of 3 different chemicals: the dioxin TCDD, PCB 126 and the furan PeCDF. Each of these contaminants is known to bind with the Ah receptor and initiate gene expression.

The experiments with single chemicals allowed Walker et al. to characterize the dose-response curve for each individual chemical for specific types of cancer detected. Of particular interest was whether the shape of the dose-respose curve was the same for each cancer type for each of the chemicals, as this must be the case if the TEF approach is to be valid. Different shapes of the dose-response curve would indicate that different mechanisms are responsible for causing the same cancer in the different chemicals, invalidating the assumption of additivity.

Walker et al. exposed another group of rats to a mixture of the three chemicals. The concentration of each chemicals in the mixture was adjusted based on their relative potency, specifically so that each contaminant contributed approximately one-third of the total toxicity of the mixture. Of the three, TCDD was the most potent (TEF=1) compared to PeCDF (TEF= 0.5) and PCB 126 (TEF=0.1). Hence each mixture contained 1 part TCDD to 2 parts PeCDF to 10 parts PCB 126 (see sidebar, above). Different subsets of this group of rats were exposed to different concentrations of the mixture, to allow construction of a dose-response curve. Total toxicity of the mixture used in this round of experiments, calculated in TEQs, ranged from 10 ng TEQ/kg to 100 ng TEQ/kg. The levels used in the experiment are extremely low, ranging from 10 parts per trillion to 100 parts per trillion TEQ.

What did they find? The contaminants caused significant increases in cancers in exposed animals compared to controls. Four types of cancer were observed in all studies: two in liver (cholangiocarcinoma and hepatocellular adenoma), one in lung tissue (cystic keratinizing epithelioma), and one in the mouth (gingival squamous cell carcinoma).

Animals exposed to TCDD, PCB 126 and to the mixtures showed a dose-related increase in cancer rates for all four cancer types: higher doses produced more cancers. Animals exposed to PeCDF showed an dose-response pattern for cholangiocarcinoma and hepatocellular adenoma, but not the other two cancers.

Two of the cancer types, cystic keratinizing epithelioma and cholangiocarcinoma, were never seen in control animals from any of these studies.

A statistical analysis of the dose-response curves of each cancer type led Walker et al. to conclude that the overall shapes of these relationships were the same for each contaminant for a given cancer type. As noted above, this must be the case for the TEF-additivity approach to be valid. Specifically, they determined that they could predict the number of cancers caused in each experiment by using a model that assumed the dose response curve was the same shape for each contaminant --corrected for potency-- just as well as from models in developed separately for each contaminant.

Analysis of cancer cases in animals exposed to mixtures was also consistent with additivity. The numbers of cases of different cancer types was not statistically distinguishable from what they anticipated, based on the relative potency of each contaminant and its concentration within the mixture.

In a final analysis, they determined that World Health Organization values for TEFs led to accurate predictions of two cancer types--hepatocellular adenoma and gingival SCC, but that they overestimated the number of cases of cholangiocarcinoma and CKE. This appeared to be a result of PeCDF not being as potent as would be expected from WHO's TEF, and PCB 126 being more potent.

What does it mean? Walker et al.'s results provide empirical support for using additivity as an assumption in assessing the toxicity of mixtures of dioxin and dioxin-like chemicals that share in common action via the Ah receptor.

These results provide good and bad news for efforts to develop safety standards for dioxin exposures.

  • The bad—but not unexpected—news is that this study reaffirms the need to base health standards on mixtures, rather than on single exposures. Mixtures are a complicated, ubiquitous reality that have rarely been incorporated into health standards for chemical exposures.
  • The good news is that the results support the appropriateness of assuming additivity of ‘Toxic Equivalency Factors’ in assessing cancer risk of dioxin exposures. TEFs offer a straight-forward, tractable way to estimate overall toxicity of a mixture, when data on relative potency are available. Results contradicting this assumption would have undermined a large amount of prior work to establish standards for dioxin mixtures, developed using untested assumptions about additivity.

It is important to bear in mind that dioxin and dioxin-like compounds almost always occur in more complicated mixtures, including with dioxins and similar contaminants that don't act via the Ah receptor. This work does not address how to assess total toxicity of such combinations. Hence toxic estimates based on TEF/TEQ calculations provide minimum estimates of toxicity. Whether they account for a small or a large portion of the mixture's overall toxicity will depend completely upon its constituents.

 

 
   
   

 

 

 

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