Dose-rate effects of ethylene oxide exposure on developmental toxicity

14-Day Nose-Only Inhalation Toxicity and Haber's Rule Study of NNK in Sprague-Dawley Rats

4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is one of the key tobacco-specific nitrosamines that plays an important role in human lung carcinogenesis. However, repeated inhalation toxicity data on NNK, which is more directly relevant to cigarette smoking, are currently limited. In the present study, the subacute inhalation toxicity of NNK was evaluated in Sprague Dawley rats. Both sexes (9-10 weeks age; 16 rats/sex/group) were exposed by nose-only inhalation to air, vehicle control (75% propylene glycol), or 0.8, 3.2, 12.5, or 50 mg/kg body weight (BW)/day of NNK (NNK aerosol concentrations: 0, 0, 0.03, 0.11, 0.41, or 1.65 mg/L air) for 1 hour/day for 14 consecutive days. Toxicity was evaluated by assessing body and organ weights; food consumption; clinical pathology; histopathology observations; blood, urine, and tissue levels of NNK, its major metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and their glucuronides (reported as total NNK, tNNK, and total NNAL, tNNAL, respectively); O6-methylguanine DNA adduct formation; and blood and bone marrow micronucleus frequency. Whether the subacute inhalation toxicity of NNK followed Haber's Rule was also determined using additional animals exposed 4 hours/day. The results showed that NNK exposure caused multiple significant adverse effects, with the most sensitive endpoint being non-neoplastic histopathological lesions in the nose. The lowest-observed-adverse-effect level (LOAEL) was 0.8 mg/kg BW/day or 0.03 mg/L air for 1 hour/day for both sexes. An assessment of Haber's Rule indicated that 14-day inhalation exposure to the same dose at a lower concentration of NNK aerosol for a longer time (4 hours daily) resulted in greater adverse effects than exposure to a higher concentration of NNK aerosol for a shorter time (1 hour daily).

A comparison of Reduced Life Expectancy (RLE) model with Haber's Rule to describe effects of exposure time on toxicity

The Reduced Life Expectancy (RLE) Model (LC50 = [ln(NLE) - ln(LT50)]/d) has been proposed as an alternative to Haber's Rule. The model is based on a linear relationship between LC50 (Lethal Exposure Concentration) and lnLT50 (Lethal Exposure Time) and uses NLE (Normal Life Expectancy) as a limiting point as well as a long term data point (where d is a constant). The purposes of this paper were to compare the RLE Model with Haber's Rule with available toxicity data and to evaluate the strengths and weaknesses of each approach. When LT50 is relatively short and LC50 is high, Haber's Rule is consistent with the RLE model. But the difference between the two was evident in the situation when LT50 is relatively long and LC50 is low where the RLE model is a marked departure from Haber's Rule. The RLE Model can be used to appropriately evaluate long term effects of exposure.

Reduced life expectancy model for effects of long term exposure on lethal toxicity with fish

A model based on the concept of reduction in life expectancy (RLE model) as a result of long term exposure to toxicant has been developed which has normal life expectancy (NLT) as a fixed limiting point for a species. The model is based on the equation (LC₅₀ = a ln(LT₅₀) + b) where a and b are constants. It was evaluated by plotting ln LT₅₀ against LC₅₀ with data on organic toxicants obtained from the scientific literature. Linear relationships between LC₅₀ and ln LT₅₀ were obtained and a Calculated NLT was derived from the plots. The Calculated NLT obtained was in good agreement with the Reported NLT obtained from the literature. Estimation of toxicity at any exposure time and concentration is possible using the model. The use of NLT as a reference point is important since it provides a data point independent of the toxicity data set and limits the data to the range where toxicity occurs. This novel approach, which represents a departure from Haber's rule, can be used to estimate long term toxicity from limited available acute toxicity data for fish exposed to organic biocides.

On determining the BMD from multiple outcomes in developmental toxicity studies when one outcome is intentionally missing

Public health concerns over the occurrence of developmental abnormalities that can occur as a result of prenatal exposure to drugs, chemicals, and other environmental factors has led to a number of developmental toxicity studies and the use of the benchmark dose (BMD) for risk assessment. To characterize risk from multiple sources, more recent analytic methods involve a joint modeling approach, accounting for multiple dichotomous and continuous outcomes. For some continuous outcomes, evaluating all subjects may not be feasible, and only a subset may be evaluated due to limited resources. The subset can be selected according to a prespecified probability model and the unobserved data can be viewed as intentionally missing in the sense that subset selection results in missingness that is experimentally planned. We describe a subset selection model that allows for sampling pups with malformations and healthy pups at different rates, and includes the well-known simple random sample (SRS) as a special case. We were interested in understanding how sampling rates that are selected beforehand influence the precision of the BMD. Using simulations we show how improvements over the SRS can be obtained by oversampling malformations, and how some sampling rates can yield precision that is substantially worse than the SRS. We also illustrate the potential for cost saving with oversampling. Simulations are based on a joint mixed effects model, and to account for subset selection, use of case weights to obtain valid dose-response estimates.

Evaluation of effects of exposure time on aquatic toxicity with zooplanktons using a reduced life expectancy model

Traditionally in toxicological studies time is not studied as quantifiable variable but as a fixed endpoint. The Reduced Life Expectancy (RLE) model which relates exposure time and exposure concentration with lethal toxic effects was tested previously using fish data. In this current paper the effects of exposure time on aquatic toxicity with zooplanktons and various toxicants were evaluated using the RLE model based on ambient exposure concentration. The model was evaluated by plotting lnLT(50) against LC(50) using toxicity data with zooplanktons from the literature for metal, metalloid and organic compounds. Most of the experimental data sets can be satisfactorily correlated by use of the RLE model, but deviations occurred for some data sets. Those data sets were satisfactorily fitted by a two stage RLE model. This model was based on two phases: one in the peripheral system and other in the central system. Both the single and two stage RLE model support the hypothesis that toxicity is time dependent and decreases in a systematic way with increasing exposure time. A calculated normal life expectancy (NLT) can be obtained from the single stage model and is in accord with reported NLT but those obtained from the two stage RLE model are in excellent agreement.

A Novel Application of a Bivariate Regression Model for Binary and Continuous Outcomes to Studies of Fetal Toxicity

Public health concerns over the occurrence of birth defects and developmental abnormalities that may occur as a result of prenatal exposure to drugs, chemicals, and other environmental factors has led to an increasing number of developmental toxicity studies. Because fetal pups are commonly evaluated for multiple outcomes, data analysis frequently involves a joint modeling approach. In this paper, we focus on modelling clustered binary and continuous outcomes in the setting where both outcomes are potentially observable in all offspring but, due to practical limitations, the continuous outcome is only observed in a subset of offspring. The subset is not a simple random sample (SRS) but is selected by the experimenter under a prespecified probability model.While joint models for binary and continuous outcomes have been developed when both outcomes are available for every fetus, many existing approaches are not directly applicable when the continuous outcome is not observed in a SRS. We adapt a likelihood-based approach for jointly modelling clustered binary and continuous outcomes when the continuous response is missing by design and missingness depends on the binary trait. The approach takes into account the probability that a fetus is selected in the subset. Through the use of a partial likelihood, valid estimates can be obtained by a simple modification to the partial likelihood score. Data involving the herbicide 2,4,5-T are analyzed. Simulation results confirm the approach.

A lifestage-specific approach to hazard and dose-response characterization for children's health risk assessment

In 2006, the U.S. EPA published a report entitled A Framework for Assessing Health Risks of Environmental Exposures to Children (hereafter referred to as the "Framework") describing a lifestage approach to risk assessment that includes the evaluation of existing data from a temporal perspective (i.e., the timing of both the exposure and the outcome). This article summarizes the lifestage-specific issues discussed in the Framework related to the qualitative and the quantitative hazard and dose-response characterization. Lifestage-specific hazard characterization includes an evaluation of relevant human and experimental animal studies, focusing on the identification of critical windows of development (i.e., exposure intervals of maximum susceptibility) for observed outcomes, evaluation of differential exposure at individual lifestages, the relevance and impact of lifestage-specific toxicokinetic and toxicodynamic data, mode of action information, variability and latency of effects from early lifestage exposure, and describing uncertainties. The interpretation of the hazard data to determine the strength of association between early life exposures and the timing and type of outcomes depends upon the overall weight of evidence. Lifestage-specific dose-response characterization relies on the identification of susceptible lifestages in order to quantify health risk, information on the point of departure, key default assumptions, and descriptions of uncertainty, sensitivity, and variability. Discussion of the strength and limitations of the hazard and dose-response data provides a basis for confidence in risk determinations. Applying a lifestage approach to hazard and dose-response characterization is likely to improve children's health risk assessment by identifying data gaps and providing a better understanding of sources of uncertainty.

Use of Haber's Rule to estimate the risk of diabetes from background exposures to dioxin-like compounds

Recent publications have reported a weak but consistent correlation between diabetes incidence and occupational or accidental exposure to dioxins. As with most work involving environmental xenobiotics, these studies suffered from the analytical problem that the reference populations had some degree of exposure. We have used Haber's Rule to relate the integrated exposure of subjects involved in an industrial exposure to dioxins, reported by Sweeney et al. [Teratog. Carcinog. Mutagen. 17 (1998) 241], to the incremental probability of diabetes incidence. We estimated that background exposure to dioxin-like compounds by the referents contributed <1% of their diabetes risk, suggesting that background exposure to dioxins is not a significant risk factor for individuals who have not been occupationally or accidentally exposed.

Haber's rule: a special case in a family of curves relating concentration and duration of exposure to a fixed level of response for a given endpoint

The concept that the product of the concentration (C) of a substance and the length of time (t) it is administered produces a fixed level of effect for a given endpoint has been ascribed to Fritz Haber, who was a German scientist in the early 1900s. He contended that the acute lethality of war gases could be assessed by the amount of the gas in a cubic meter of air (i.e. the concentration) multiplied by the time in min that the animal had to breathe the air before death ensued (i.e. C x t=k). While Haber recognized that C x t=k was applicable only under certain conditions, many toxicologists have used his rule to analyze experimental data whether or not their chemicals, biological endpoints, and exposure scenarios were suitable candidates for the rule. The fact that the relationship between C and t is linear on a log-log scale and could easily be solved by hand, led to early acceptance among toxicologists, particularly in the field of entomology. In 1940, a statistician named Bliss provided an elegant treatment on the relationships among exposure time, concentration, and the toxicity of insecticides. He proposed solutions for when the log-log plot of C and t was composed of two or more rectilinear segments, for when the log-log plot was curvilinear, and for when the slope of the dosage-mortality curve was a function of C. Despite the fact that Haber's rule can underestimate or overestimate effects (and consequently risks), it has been used in various settings by regulatory bodies. Examples are presented from the literature of data sets that follow Haber's rule as well as those that do not. Haber's rule is put into perspective by showing that it is simply a special case in a family of power law curves relating concentration and duration of exposure to a fixed level of response for a given endpoint. Also shown is how this power law family can be used to examine the three-dimensional surface relating C, t, and varying levels of response. The time has come to move beyond the limited view of C and t relationships inferred by Haber's rule to the use of the broader family of curves of which this rule is a special case.