Lynne T. Haber

Copper and Human Health: Biochemistry, Genetics, and Strategies for Modeling Dose-response Relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

Altering the conserved nucleotide binding motif in the Salmonella typhimurium MutS mismatch repair protein affects both its ATPase and mismatch binding activities.

The Salmonella typhimurium and Escherichia coli MutS protein is one of several methyl‐directed mismatch repair proteins that act together to correct replication errors. MutS is homologous to the Streptococcus pneumoniae HexA mismatch repair protein and to the Duc1 and Rep1 proteins of human and mouse. Homology between the deduced amino acid sequence of both MutS and HexA, and the type A nucleotide binding site consensus sequence, suggested that ATP binding and hydrolysis play a role in their mismatch repair functions. We found that MutS does indeed weakly hydrolyze ATP to ADP and Pi, with a Km of 6 microM and kcat of 0.26. To show that this activity is intrinsic to MutS, we made a site‐directed mutation, which resulted in the invariant lysine of the nucleotide binding consensus sequence being changed to an alanine. The mutant MutS allele was unable to complement a mutS::Tn10 mutation in vivo, and was dominant over wild type when present in high copy number. The purified mutant protein had reduced ATPase activity, with the Km affected more severely than the kcat. Like the wild type MutS protein, the mutant protein is able to bind heteroduplex DNA specifically, but the mutant protein does so with a reduced affinity.

Linear low-dose extrapolation for noncancer health effects is the exception, not the rule

The nature of the exposure-response relationship has a profound influence on risk analyses. Several arguments have been proffered as to why all exposure-response relationships for both cancer and noncarcinogenic endpoints should be assumed to be linear at low doses. We focused on three arguments that have been put forth for noncarcinogens. First, the general “additivity-to-background” argument proposes that if an agent enhances an already existing disease-causing process, then even small exposures increase disease incidence in a linear manner. This only holds if it is related to a specific mode of action that has nonuniversal properties—properties that would not be expected for most noncancer effects. Second, the “heterogeneity in the population” argument states that variations in sensitivity among members of the target population tend to “flatten out and linearize” the exposure-response curve, but this actually only tends to broaden, not linearize, the dose-response relationship. Third, it has been argued that a review of epidemiological evidence shows linear or no-threshold effects at low exposures in humans, despite nonlinear exposure-response in the experimental dose range in animal testing for similar endpoints. It is more likely that this is attributable to exposure measurement error rather than a true nonthreshold association. Assuming that every chemical is toxic at high exposures and linear at low exposures does not comport to modern-day scientific knowledge of biology. There is no compelling evidence-based justification for a general low-exposure linearity; rather, case-specific mechanistic arguments are needed.

Data for Physiologically Based Pharmacokinetic Modeling in Neonatal Animals: Physiological Parameters in Mice and Sprague-Dawley Rats

ABSTRACTRecent scientific and policy initiatives have resulted in increased interest in risk to fetuses, infants, and children and consideration of how such risks should be evaluated. A useful way of addressing this issue is to use physiologically based pharmacokinetic (PBPK) models to compare the tissue dose that children and adults receive for a given amount of a chemical ingested or inhaled. The response in children and adults for a given tissue dose can also be compared. To aid in the development of age-specific PBPK models for experimental animals, we have collected information on physiological parameters in neonates and young animals, through 60 days of age. Our effort focused on generic physiological values, such as tissue weight (termed tissue volume in the context of PBPK modeling), intake (alveolar ventilation, food intake, water intake), and flows (blood flows to tissues, bile flow, creatinine clearance, and glomerular filtration rate). To date, parameters for Sprague-Dawley rats and mice of mu...

Advancing human health risk assessment: integrating recent advisory committee recommendations.

Abstract Over the last dozen years, many national and international expert groups have considered specific improvements to risk assessment. Many of their stated recommendations are mutually supportive, but others appear conflicting, at least in an initial assessment. This review identifies areas of consensus and difference and recommends a practical, biology-centric course forward, which includes: (1) incorporating a clear problem formulation at the outset of the assessment with a level of complexity that is appropriate for informing the relevant risk management decision; (2) using toxicokinetics and toxicodynamic information to develop Chemical Specific Adjustment Factors (CSAF); (3) using mode of action (MOA) information and an understanding of the relevant biology as the key, central organizing principle for the risk assessment; (4) integrating MOA information into dose–response assessments using existing guidelines for non-cancer and cancer assessments; (5) using a tiered, iterative approach developed by the World Health Organization/International Programme on Chemical Safety (WHO/IPCS) as a scientifically robust, fit-for-purpose approach for risk assessment of combined exposures (chemical mixtures); and (6) applying all of this knowledge to enable interpretation of human biomonitoring data in a risk context. While scientifically based defaults will remain important and useful when data on CSAF or MOA to refine an assessment are absent or insufficient, assessments should always strive to use these data. The use of available 21st century knowledge of biological processes, clinical findings, chemical interactions, and dose–response at the molecular, cellular, organ and organism levels will minimize the need for extrapolation and reliance on default approaches.

Impact of Chemical Proportions on the Acute Neurotoxicity of a Mixture of Seven Carbamates in Preweanling and Adult Rats

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose additivity for two mixtures of seven N-methylcarbamates (carbaryl, carbofuran, formetanate, methomyl, methiocarb, oxamyl, and propoxur). The best-fitting models were selected for the single-chemical dose-response data and used to develop a combined prediction model, which was then compared with the experimental mixture data. We evaluated behavioral (motor activity) and cholinesterase (ChE)-inhibitory (brain, red blood cells) outcomes at the time of peak acute effects following oral gavage in adult and preweanling (17 days old) Long-Evans male rats. The mixtures varied only in their mixing ratios. In the relative potency mixture, proportions of each carbamate were set at equitoxic component doses. A California environmental mixture was based on the 2005 sales of each carbamate in California. In adult rats, the relative potency mixture showed dose additivity for red blood cell ChE and motor activity, and brain ChE inhibition showed a modest greater-than additive (synergistic) response, but only at a middle dose. In rat pups, the relative potency mixture was either dose-additive (brain ChE inhibition, motor activity) or slightly less-than additive (red blood cell ChE inhibition). On the other hand, at both ages, the environmental mixture showed greater-than additive responses on all three endpoints, with significant deviations from predicted at most to all doses tested. Thus, we observed different interactive properties for different mixing ratios of these chemicals. These approaches for studying pesticide mixtures can improve evaluations of potential toxicity under varying experimental conditions that may mimic human exposures.

Analysis of in vivo mutation data can inform cancer risk assessment

Under the new U.S. Environmental Protection Agency (EPA) Cancer Risk Assessment Guidelines [U.S. EPA, 2005. Guidelines for Carcinogen Risk Assessment. EPA/630/P-03/001B, March 2005], the quantitative model chosen for cancer risk assessment is based on the mode-of-action (MOA) of the chemical under consideration. In particular, the risk assessment model depends on whether or not the chemical causes tumors through a direct DNA-reactive mechanism. It is assumed that direct DNA-reactive carcinogens initiate carcinogenesis by inducing mutations and have low-dose linear dose-response curves, whereas carcinogens that operate through a nonmutagenic MOA may have nonlinear dose-responses. We are currently evaluating whether the analysis of in vivo gene mutation data can inform the risk assessment process by better defining the MOA for cancer and thus influencing the choice of the low-dose extrapolation model. This assessment includes both a temporal analysis of mutation induction and a dose-response concordance analysis of mutation with tumor incidence. Our analysis of published data on riddelliine in rats and dichloroacetic acid in mice indicates that our approach has merit. We propose an experimental design and graphical analysis that allow for assessing time-to-mutation and dose-response concordance, thereby optimizing the potential for in vivo mutation data to inform the choice of the quantitative model used in cancer risk assessment.

Incorporation of pharmacokinetic and pharmacodynamic data into risk assessments.

Risk assessment methodologies are being updated to allow the inclusion of numerical values for variance in pharmacokinetic (PK) measures and pharmacodynamic (PD) processes related to toxicity. The key PK measures and PD processes are identified from the results of carefully conducted and adequately reported studies. In some instances, studies with humans are not possible, and so the development of data useful for human PK evaluations and on PD processes in vitro or in silico represent an alternative. These results can be integrated under physiologic, anatomic, and biochemical constraints of the intact body through physiologically based pharmacokinetic (PBPK) modeling. This manuscript presents the rational for and key considerations related to the inclusion of quantitative PK and PD data in assessing chemical risks.

A Bayesian Network Model for Biomarker-Based Dose Response

A Bayesian network model was developed to integrate diverse types of data to conduct an exposure-dose-response assessment for benzene-induced acute myeloid leukemia (AML). The network approach was used to evaluate and compare individual biomarkers and quantitatively link the biomarkers along the exposure-disease continuum. The network was used to perform the biomarker-based dose-response analysis, and various other approaches to the dose-response analysis were conducted for comparison. The network-derived benchmark concentration was approximately an order of magnitude lower than that from the usual exposure concentration versus response approach, which suggests that the presence of more information in the low-dose region (where changes in biomarkers are detectable but effects on AML mortality are not) helps inform the description of the AML response at lower exposures. This work provides a quantitative approach for linking changes in biomarkers of effect both to exposure information and to changes in disease response. Such linkage can provide a scientifically valid point of departure that incorporates precursor dose-response information without being dependent on the difficult issue of a definition of adversity for precursors.

Evaluation of concentration―response options for diacetyl in support of occupational risk assessment

The current emphasis on occupational exposures to diacetyl has led to new research on its effects. We evaluated whether the data are sufficient to support a transition from a hazard-based risk management approach to a quantitative occupational risk assessment approach, characterized by developing a health-based occupational exposure limit (OEL). Inhalation health effects data were evaluated and issues and uncertainties related to occupational risk assessment needs were identified. A systematic hazard characterization, supported by both the toxicology and epidemiology literature, showed that the respiratory tract effects of diacetyl are the primary end points of relevance for developing an OEL. In an effort to provide a systematic approach for the analysis of the issues that need to be considered in developing an occupational risk assessment for diacetyl, a potential OEL was derived. A concentration-response assessment was completed using tracheobronchial effects in mice as the critical effect. The resulting benchmark concentration (lower bound estimate or BMCL) was adjusted to a human equivalent concentration of 1.8 ppm. A composite uncertainty factor of 10 was recommended to account for extrapolation from an adjusted BMCL from an animal study and for human variability in sensitivity and taking into account other uncertainties in the overall database. The resulting OEL recommendation of 0.2 ppm as a time-weighted average (TWA) was supported by the current occupational epidemiology literature. This evaluation showed that a health-based OEL value can be derived for diacetyl with moderate to high confidence.