Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.
The use of genomic technology for assessing health risks associated with chemical exposure has significant potential, but its direct application has proven to be challenging for the toxicology and risk assessment communities. In this study, a method was established for analyzing dose-response microarray data using benchmark dose (BMD) calculations and gene ontology (GO) classification. Gene expression changes in the rat nasal epithelium following acute formaldehyde exposure were used as a case study. The gene expression data were first analyzed using a one-way ANOVA to identify genes that showed significant dose-response behavior. These genes were then fit to a series of four statistical models (linear, second-degree polynomial, third-degree polynomial, and power models) and the least complex model that best described the data was selected. The genes were matched to their associated GO categories, and the average BMD and benchmark dose lower confidence limit (BMDL) were calculated for each GO category. The results were used to identify doses at which individual cellular processes were altered. For the formaldehyde exposures, the BMD estimates for the GO categories related to cell proliferation and DNA damage were similar to those measured in previous studies using cell labeling indices and DNA-protein cross-links and consistent with the BMD estimated for rat nasal tumors. The method represents a significant advance in applying genomic information to risk assessment by allowing a comprehensive survey of molecular changes associated with chemical exposure and providing the capability to identify reference doses at which particular cellular processes are altered.
There is increasing interest in the use of quantitative transcriptomic data to determine benchmark dose (BMD) and estimate a point of departure (POD) for human health risk assessment. Although studies have shown that transcriptional PODs correlate with those derived from apical endpoint changes, there is no consensus on the process used to derive a transcriptional POD. Specifically, the subsets of informative genes that produce BMDs that best approximate the doses at which adverse apical effects occur have not been defined. To determine the best way to select predictive groups of genes, we used published microarray data from dose–response studies on six chemicals in rats exposed orally for 5, 14, 28, and 90 days. We evaluated eight approaches for selecting genes for POD derivation and three previously proposed approaches (the lowest pathway BMD, and the mean and median BMD of all genes). The relationship between transcriptional BMDs derived using these 11 approaches and PODs derived from apical data that might be used in chemical risk assessment was examined. Transcriptional BMD values for all 11 approaches were remarkably aligned with corresponding apical PODs, with the vast majority of toxicogenomics PODs being within tenfold of those derived from apical endpoints. We identified at least four approaches that produce BMDs that are effective estimates of apical PODs across multiple sampling time points. Our results support that a variety of approaches can be used to derive reproducible transcriptional PODs that are consistent with PODs produced from traditional methods for chemical risk assessment.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-016-1886-5) contains supplementary material, which is available to authorized users.
Per- and poly-fluoroalkyl substances (PFAS) are widely found in the environment because of their extensive use and persistence. Although several PFAS are well studied, most lack toxicity data to inform human health hazard and risk assessment. This study focussed on four model PFAS: perfluorooctanoic acid (PFOA; 8 carbon), perfluorobutane sulfonate (PFBS; 4 carbon), perfluorooctane sulfonate (PFOS; 8 carbon), and perfluorodecane sulfonate (PFDS; 10 carbon). Human primary liver cell spheroids (pooled from 10 donors) were exposed to 10 concentrations of each PFAS and analyzed at four time-points. The approach aimed to: (1) identify gene expression changes mediated by the PFAS; (2) identify similarities in biological responses; (3) compare PFAS potency through benchmark concentration analysis; and (4) derive bioactivity exposure ratios (ratio of the concentration at which biological responses occur, relative to daily human exposure). All PFAS induced transcriptional changes in cholesterol biosynthesis and lipid metabolism pathways, and predicted PPARα activation. PFOS exhibited the most transcriptional activity and had a highly similar gene expression profile to PFDS. PFBS induced the least transcriptional changes and the highest benchmark concentration (i.e., was the least potent). The data indicate that these PFAS may have common molecular targets and toxicities, but that PFOS and PFDS are the most similar. The transcriptomic bioactivity exposure ratios derived here for PFOA and PFOS were comparable to those derived using rodent apical endpoints in risk assessments. These data provide a baseline level of toxicity for comparison with other known PFAS using this testing strategy.
Concerns for potential vulnerability to manganese (Mn) neurotoxicity during fetal and neonatal development have been raised due to increased needs for Mn for normal growth, different sources of exposure to Mn, and pharmacokinetic differences between the young and adults. A physiologically based pharmacokinetic (PBPK) model for Mn during human gestation and lactation was developed to predict Mn in fetal and neonatal brain using a parallelogram approach based upon extrapolation across life stages in rats and cross-species extrapolation to humans. Based on the rodent modeling, key physiological processes controlling Mn kinetics during gestation and lactation were incorporated, including alterations in Mn uptake, excretion, tissue-specific distributions, and placental and lactational transfer of Mn. Parameters for Mn kinetics were estimated based on human Mn data for milk, placenta, and fetal/neonatal tissues, along with allometric scaling from the human adult model. The model was evaluated by comparison with published Mn levels in cord blood, milk, and infant blood. Maternal Mn homeostasis during pregnancy and lactation, placenta and milk Mn, and fetal/neonatal tissue Mn were simulated for normal dietary intake and with inhalation exposure to environmental Mn. Model predictions indicate similar or lower internal exposures to Mn in the brains of fetus/neonate compared with the adult at or above typical environmental air Mn concentrations. This PBPK approach can assess expected Mn tissue concentration during early life and compares contributions of different Mn sources, such as breast or cow milk, formula, food, drinking water, and inhalation, with tissue concentration.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.