Design and analysis of experiments on mutagenicity. II. Assays involving microorganisms.

The design and statistical analysis of mutagenicity experiments involving microorganisms and a single dose of mutagen are discussed. Test statistics are derived for use in determining the mutagenicity of a chemical when survival data are available and also when such data are not available. One's likelihood (power) of correctly concluding a chemical is mutagenic is examined, and minimum total sample sizes required for 95% power are presented. It is found that one generally has greater power when survival data are available. Required precision is estimating survival is discussed in reference to type-1 and type-2 errors. The proper use of the formulae and figures presented is illustrated by examples.     

A two-stage test for ordered means in the poisson case with an example from mutagenicity testing

It is shown how two-stage methods developed for continuous distributions can be used to construct two-stage tests for certain hypotheses pertaining to discrete distributions. Specifically, a two-stage test for ordered means in the Poisson case is presented. An example from mutagenicity testing is discussed and data from it are used to illustrate the methodology. Results of a Monte Carlo power study are presented as well as a brief table of critical values.     

Phage T7-inactivation test. A possibility of quantitative mutagenicity screening

A new method is described for the quantitative characterization of the genotoxic effect of chemicals. The method is based on the determination of the inactivation of bacteriophage T7 and on the application of a simple mathematical model valid for the processes during, or at least in the initial stage of the interaction of chemicals and phages. A value characteristic for the chemical is defined and it is determined from the inactivation kinetics. Typical inactivation kinetic curves and some problems of the application of the model as well as the mutagenicity index values determined for about 30 substances are presented. The substances examined have mutagenicity index values covering a range of six orders of magnitude. The obtained values are compared with the results of different mutagenicity/carcinogenicity tests and discussed on the basis of data in the literature. The presented method is proposed to be applied for quantitative mutagenicity screening of chemicals.     

Approaches to genetic control for the use of pesticides

Analysis of data available in literature has shown that 65% of 400 pesticides studied for their mutagenicity exert a mutagenic effect on any test-object. The number of revealed mutagens approaches 100% when four or more test-objects are used. Recommendations for quantitative estimation of genetic risk worked out under conditions of model experiments with standard mutagens are not available for pesticides since they are slight mutagens. The necessity for genetic stage-by-stage monitoring of pesticide use is substantiated. This monitoring should be carried out at the stage of experimental studies by means of classifications by the degree of potential mutagenic danger (the method is described) and at the stage of ecological and genetic investigations--by means of the regulation for application with due regard for the summary mutagenic background.     

Studies on the mutagenic activity of ascorbic acid in vitro and in vivo

In vitro data are presented to show that ascorbic acid does not have intrinsic mutagenicity towards strain TA100 of S. typhimurium if deionized water is used to prepare the incubation medium. The addition of Cu2+ ions to the bacterial medium that contains ascorbic acid, or the use of tap water and ascorbic acid alone, causes a mutagenic and cytotoxic response that is blocked by EDTA. Additional in vitro data demonstrate that hydrogen peroxide is mutagenic to S. typhimurium strain TA100 and it is suggested that ascorbic acid may be mutagenic and cytotoxic through the generation of hydrogen peroxide. In vivo studies using a sensitive intrahepatic host-mediated mutagenicity assay indicate that ascorbic acid is not genotoxic in guinea pigs even when the dietary intake of vitamin C is above the level required for tissue saturation (5000 mg/kg body weight/day).     

A survey of EPA/OPP and open literature on selected pesticide chemicals. II. Mutagenicity and carcinogenicity of selected chloroacetanilides and related compounds.

With this effort, we continue our examination of data on selected pesticide chemicals and their related analogues that have been presented to the U.S. Environmental Protection Agency's (USEPA's) Office of Pesticide Programs (OPP). This report focuses on a group of selected chloroacetanilides and a few related compounds. As part of the registration process for pesticidal chemicals, interested parties (registrants) must submit toxicity information to support the registration including both mutagenicity and carcinogenicity data. Although this information is available to the public via Freedom of Information (FOI) requests to the OPP, publication in the scientific literature allows greater dissemination and examination of the data. For this Special Issue, graphic profiles have been prepared of the mutagenicity and carcinogenicity data available in the submissions to OPP. Also, a discussion is presented about how toxicity data are used to help establish tolerances (limits of pesticide residues in foods). The mutagenicity results submitted by registrants are supplemented by data on these chemicals from the open literature to provide a full perspective of their genetic toxicology. The group of chloroacetanilides reviewed here display a consistent pattern of mutagenic activity, probably mediated via metabolites. This mutagenic activity is a mechanistically plausible factor in the development of tumors seen in experimental animals exposed to this class of chemicals.     

Design and analysis of experiments on mutagenicity : I. Minimal sample sizes

The probability (power) of collecting sufficient data to demonstrate statistically that a chemical is mutagenic is examined. A formula is derived with which one may calculate the likelihood of correctly concluding a chemical is mutagenic based upon (1) the total sample size, (2) the relative size of the experimental group, (3) the spontaneous mutation rate and (4) the minimal increase in mutation rate that one is concerned in detecting. Figures are also presented which allow one to determine the minimal total sample size required to assure oneself a reasonable chance of successfully demonstrating a chemical to be mutagenic.

It is found that the best designed (most powerful) experiments are those with approximately equal numbers of indviduals in the experimental and control groups. Those experiments in which excess numbers of individuals are allotted to either the experimental or control groups suffer a substantial reduction in power. In addition, caution should be exercised when concluding that a chemical is not mutagenic. The inability to collect sufficient data to demonstrate the mutagenicity of a chemical might be attributable to one's using too small a total sample size rather than to lack of mutagenic activity, especially in mutagenicity assay systems involving very small spontaneous mutation rates.     

SAR modeling of genotoxic phenomena: the effect of supplementation with physiological chemicals

Structure-activity relationship (SAR) modeling of toxicological phenomena is optimal when the ratio of toxicants to non-toxicants included in the model is unity. Frequently, however, the experimental data available are enriched with toxicants, this appears to be especially true for genotoxicity data sets. It is demonstrated herein, using a Salmonella mutagenicity data set, that when there is a paucity of non-toxicants, the learning set may be augmented with physiological chemicals on the assumption that they are non-genotoxic.     

Structure-based methods for predicting mutagenicity and carcinogenicity: are we there yet?

There is a great deal of current interest in the use of commercial, automated programs for the prediction of mutagenicity and carcinogenicity based on chemical structure. However, the goal of accurate and reliable toxicity prediction for any chemical, based solely on structural information remains elusive. The toxicity prediction challenge is global in its objective, but limited in its solution, to within local domains of chemicals acting according to similar mechanisms of action in the biological system; to predict, we must be able to generalize based on chemical structure, but the biology fundamentally limits our ability to do so. Available commercial systems for mutagenicity and/or carcinogenicity prediction differ in their specifics, yet most fall in two major categories: (1) automated approaches that rely on the use of statistics for extracting correlations between structure and activity; and (2) knowledge-based expert systems that rely on a set of programmed rules distilled from available knowledge and human expert judgement. These two categories of approaches differ in the ways that they represent, process, and generalize chemical-biological activity information. An application of four commercial systems (TOPKAT, CASE/MULTI-CASE, DEREK, and OncoLogic) to mutagenicity and carcinogenicity prediction for a particular class of chemicals—the haloacetic acids (HAs)—is presented to highlight these differences. Some discussion is devoted to the issue of gauging the relative performance of commercial prediction systems, as well as to the role of prospective prediction exercises in this effort. And finally, an alternative approach that stops short of delivering a prediction to a user, involving structure-searching and data base exploration, is briefly considered.     

Detection of mutagenic pollution of natural environment using microbiological assays

One of the most important and serious ecological problems is mutagenic pollution of the natural environment. Therefore, detection of mutagenic compounds in samples taken from natural habitats is of special interest. Microbiological mutagenicity tests seem to be very useful tools for such detection. In this review article, a general view on the tests employing genetically modified bacterial strains designed for detection of low concentrations of mutagenic compounds is presented. Moreover, a comparison of advantages and disadvantages of selected assays, developed early on and more recently, and features of these assays are discussed. It appears that none of the currently available mutagenicity tests is perfect or optimal for all purposes. Thus, a choice for the particular assay must depend on the nature of studies and specific tasks of the experiments to be performed.     

Evaluating statistical analyses and reproducibility of microbial mutagenicity assays

The NCI/NTP has completed the first phase of a 4-laboratory study on the reproducibility of testing chemicals for mutagenicity in the Salmonella/microsome assay. This paper is report of the statistical analysis of some of that data. This analysis involved (1) identifying and removing spurious data; (2) determining the adequacy of the remaining data in making a decision on the mutagenicity of the test chemical; (3) performing the statistical tests; and (4) interpreting the results. Using this procedure, 7 approaches were used to determine the mutagenicity of a test. These approaches were the (1) 2-fold rule, (2) modified 2-fold rule, (3) one-way analysis of variance (homogeneity test), (4) test for linear trend, (5) combination of 3 and 4, (6) 97.5th percentile threshold rule and (7) confidence interval threshold rule. The conclusions drawn by each rule were compared to the microbiologists' interpretation, and the results of these comparisons were presented. In addition, the strengths and weaknesses of each rule were discussed. The reproducibility of the assay in this study was examined, and a discussion of the significance of these results was presented.     

A review of the genetic toxicology of chlorinated dibenzo-p-dioxins

Information from both published and unpublished sources considered relevant to the understanding of the genetic toxicology of chlorinated dibenzo-p-dioxins is summarized in this review. Interest in writing this paper was stimulated by the fact that this class of compounds, particularly 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), has gained notoriety as an extreme environmental and industrial hazard. The potential for human exposure occurs in the work place when dioxins are formed during the synthesis of a number of commercially important compounds such as 2,4,5-trichlorophenoxyacetic acid, hexachlorophene, and pentachlorophenol. Environmental contamination may result from manufacturing processes and from dioxin contaminants in marketed products.Research on dioxins as potential mutagens was initiated because of their structural similarity to acridines, a class of known intercalating agents. To date, only 4 dioxin compounds have been evaluated for mutagenicity: the di-, tetra-, and octa-chlorinated derivatives and the unsubstituted dibenzo-p-dioxin. Since only a few of the many possible structural forms of dioxins have been tested, no definite conclusions can be made about their potential mutagenicity. Furthermore, the positive mutagenicity and cytological effects reported thus far with the few dioxin isomers examined seems to depend on the position of chlorine substitution. The most active form of the molecule is the 2,3,7,8-derivative (TCDD).Data available for assessing the mutagenic potential of TCDD are conflicting and scarce. Differences in testing results reported in these studies could be attributed to solubility problems with the test chemical, treatment protocols, purity of test samples, or toxicity. Because there are conflicting data, additional experiments are needed before the mutagenic potential of TCDD and other dioxins can be determined. Studies exploring the promoting effect of dioxins on the mutagenicity of other compounds are also recommended because experiments have shown TCDD to be an extremely active liver enzyme inducing agent that enhances the mutagenicity of certain polycyclic hydrocarbons such as 3-methylcholanthrene in vitro.The importance of discerning the hazards to human health from dioxin compounds became apparent after an accidental release of TCDD from a chemical plant contaminated the Seveso, Italy area in July 1976¹. This accident revealed that insufficient data were available to properly evaluate the long-term health risks posed by dioxin compounds. Several research projects were therefore initiated after the Seveso incident; it is hoped that many of the questions concerning the mutagenicity of TCDD and possibly of other dioxin congeners will be answered as a result of this work.     

Development of new structural alerts suitable for chemical category formation for assigning covalent and non-covalent mechanisms relevant to DNA binding

The need to assess the ability of a chemical to act as a mutagen is one of the primary requirements in regulatory toxicology. Several pieces of legislation have led to an increased interest in the use of in silico methods, specifically the formation of chemical categories and read-across for the assessment of toxicological endpoints. One of the key steps in the development of chemical categories for mutagenicity is defining the mechanistic organic chemistry associated with the formation of a covalent bond between DNA and an exogenous chemical. To this end this study has analysed, by use of a large set of mutagenicity data (Ames test), the mechanistic coverage of a recently published set of in silico structural alerts developed for category formation. The results show that the majority of chemicals with a positive result in the Ames test were assigned at least one covalent binding mechanism related to the formation of a DNA adduct. The remaining chemicals with positive data in the Ames assay were subjected to a detailed mechanistic analysis from which 26 new structural alerts relating to covalent binding mechanisms were developed. In addition, structural alerts for radical and non-covalent intercalation mechanisms were also defined. The structural alerts outlined in this study are not intended to predict mutagenicity but rather to identify mechanisms associated with covalent and non-covalent DNA binding. This mechanistic profiling information can then be used to form chemical categories suitable for filling data gaps via read-across. A strategy for chemical category formation for mutagenicity is also presented.     

The mutagenic activity and structure of pesticides

The data on mutagenicity of pesticides as to their chemical structure are summarized and discussed. The results from investigation of cytogenetic action of 55 pesticides and their metabolites in somatic human and animal cells are presented. Some structure fragments of molecule related to genotoxic effects are selected.     

Considerations in the U.S. Environmental Protection Agency's testing approach for mutagenicity.

OPP: This paper provides the rationale and support for the decisions the OPP will make in requiring and reviewing mutagenicity information. The regulatory requirement for mutagenicity testing to support a pesticide registration is found in the 40 CFR Part 158. The guidance as to the specific mutagenicity testing to be performed is found in the OPP's Pesticide Assessment Guidelines, Subdivision F, Hazard Evaluation: Human and Domestic Animals (referred to as the Subdivision F guideline). A revised Subdivision F guideline has been presented that becomes the current guidance for submitters of mutagenicity data to the OPP. The decision to revise the guideline was the result of close examination of the version published in 1982 and the desire to update the guidance based on developments since then and current state-of-the-science. After undergoing Agency and public scrutiny, the revised guideline is to be published in 1991. The revised guideline consists of an initial battery of tests (the Salmonella assay, an in vitro mammalian gene mutation assay and an in vivo cytogenetics assay which may be either a bone marrow assay for chromosomal aberrations or for micronuclei formation) that should provide an adequate initial assessment of the potential mutagenicity of a chemical. Follow-up testing to clarify results from the initial testing may be necessary. After this information as well as all other relevant information is obtained, a weight-of-evidence decision will be made about the possible mutagenicity concern a chemical may present. Testing to pursue qualitative and/or quantitative evidence for assessing heritable risk in relation to human beings will then be considered if a mutagenicity concern exists. This testing may range from tests for evidence of gonadal exposure to dominant lethal testing to quantitative tests such as the specific locus and heritable translocation assays. The mutagenicity assessment will be performed in accordance with the Agency's Mutagenicity Risk Assessment Guidelines. The mutagenicity data would also be used in the weight-of-evidence consideration for the potential carcinogenicity of a chemical in accordance with the Agency's Carcinogen Risk Assessment Guidelines. In instances where there are triggers for carcinogenicity testing, mutagenicity data may be used as one of the triggers after a consideration of available information. It is felt that the revised Subdivision F guideline will provide appropriate, and more specific, guidance concerning the OPP approach to mutagenicity testing for the registration of a pesticide. It also provides a clearer understanding of how the OPP will proceed with its evaluation and decision making concerning the potential heritable effects of a test chemical.(ABSTRACT TRUNCATED AT 400 WORDS)     

Comparison of methods for analysis of selective genotyping survival data

Survival traits and selective genotyping datasets are typically not normally distributed, thus common models used to identify QTL may not be statistically appropriate for their analysis. The objective of the present study was to compare models for identification of QTL associated with survival traits, in particular when combined with selective genotyping. Data were simulated to model the survival distribution of a population of chickens challenged with Marek disease virus. Cox proportional hazards (CPH), linear regression (LR), and Weibull models were compared for their appropriateness to analyze the data, ability to identify associations of marker alleles with survival, and estimation of effects when all individuals were genotyped (full genotyping) and when selective genotyping was used. Little difference in power was found between the CPH and the LR model for low censoring cases for both full and selective genotyping. The simulated data were not transformed to follow a Weibull distribution and, as a result, the Weibull model generally resulted in less power than the other two models and overestimated effects. Effect estimates from LR and CPH were unbiased when all individuals were genotyped, but overestimated when selective genotyping was used. Thus, LR is preferred for analyzing survival data when the amount of censoring is low because of ease of implementation and interpretation. Including phenotypic data of non-genotyped individuals in selective genotyping analysis increased power, but resulted in LR having an inflated false positive rate, and therefore the CPH model is preferred for this scenario, although transformation of the data may also make the Weibull model appropriate for this case. The results from the research presented herein are directly applicable to interval mapping analyses.     

Correlations between 15 polycyclic aromatic hydrocarbons (PAH) and the mutagenicity of the total PAH fraction in ambient air particles in La Spezia (Italy)

Airborne particulate matter has been monitored 4 times a month for 1 year (1988) in the city of La Spezia (Italy). The polycyclic aromatic hydrocarbon (PAH) fractions were extracted, purified and characterized for the content of 15 individual PAH. In general when concentrations of individual PAH were compared statistical correlation was obtained. Mutagenicity studies were performed by the use of the Ames plate test with the Salmonella strains TA98, TA100, TA98NR and TA98DNP6 with and without metabolic activation (S9 mix). The TA98 strain was by far the most responsive and the S9 mix was absolutely required as expected when PAH are assayed. Besides mutagenicity, toxicity was also considered and it proved to be correlated with mutagenicity in TA98, +S9. The TA98NR and TA98DNP6 strains showed no appreciable differences from the parental strain TA98 indicating the absence of significant amounts of direct-acting nitro derivatives in our PAH samples. Of the 15 PAH considered in this study the amounts of cyclopental[c,d]pyrene (CPP) correlated best with mutagenicity. The role of CPP in contributing to the indirect mutagenicity of urban air PAH samples is discussed.     

A test for linkage and association in general pedigrees: the pedigree disequilibrium test

Family-based tests of linkage disequilibrium typically are based on nuclear-family data including affected individuals and their parents or their unaffected siblings. A limitation of such tests is that they generally are not valid tests of association when data from related nuclear families from larger pedigrees are used. Standard methods require selection of a single nuclear family from any extended pedigrees when testing for linkage disequilibrium. Often data are available for larger pedigrees, and it would be desirable to have a valid test of linkage disequilibrium that can use all potentially informative data. In this study, we present the pedigree disequilibrium test (PDT) for analysis of linkage disequilibrium in general pedigrees. The PDT can use data from related nuclear families from extended pedigrees and is valid even when there is population substructure. Using computer simulations, we demonstrated validity of the test when the asymptotic distribution is used to assess the significance, and examined statistical power. Power simulations demonstrate that, when extended pedigree data are available, substantial gains in power can be attained by use of the PDT rather than existing methods that use only a subset of the data. Furthermore, the PDT remains more powerful even when there is misclassification of unaffected individuals. Our simulations suggest that there may be advantages to using the PDT even if the data consist of independent families without extended family information. Thus, the PDT provides a general test of linkage disequilibrium that can be widely applied to different data structures.