In vitro screening for population variability in chemical toxicity

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

A tiered approach to population-based in vitro testing for cardiotoxicity: Balancing estimates of potency and variability

Population-wide in vitro studies for characterization of cardiotoxicity hazard, risk, and population variability show that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a powerful and high-throughput testing platform for drugs and environmental chemicals alike. However, studies in multiple donor-derived hiPSC-CMs, across large libraries of chemicals tested in concentration-response are technically complex, and study design optimization is needed to determine sufficient and fit-for-purpose population size considerations. Therefore, we tested a hypothesis that a computational down-sampling analysis based on the data from hiPSC-CM screening of 136 diverse compounds in a population of 43 non-diseased donors, including multiple replicates of the "standard" donor hiPSC-CMs, will inform optimal study designs depending on the decision context (hazard, risk and/or inter-individual variability in cardiotoxicity). Through 50 independent random subsamples of 5, 10, or 20 donors, we estimated accuracy and precision for quantifying potency, inter-individual variability, and QT prolongation risk; the results were compared to the full 43-donor cohort. We found that for potency and clinical risk of QT prolongation, a cohort of 5 randomly-selected unique donors provides accurate and precise estimates. Larger cohort sizes afforded marginal improvements, and 5 replicates of a single donor performed worse. For estimating inter-individual variability, cohorts of at least 20 donors are needed, with smaller populations on average showing bias towards underestimation in population variance. Collectively, this study shows that a variable-size hiPSC-CM-based population-wide in vitro model can be used in a number of decision scenarios for identifying cardiotoxic hazards of drugs and environmental chemicals in the population context.

CRISPR approach in environmental chemical screening focusing on population variability

A significant barrier to include population variability in risk assessment is our incomplete understanding of inter-individual variability and the differential susceptibility to environmental exposures induced adverse outcomes. By combining genome editing tools with the population diversity model, this article intended to highlight a potential strategy to identify and characterize the inter-individual variability factors, the determinant gene anchoring to a particular phenotype. The goal could be achieved by integrating the perturbed CRISPR-based unbiased functional genomics screening, genome-wide or a focused subset of genes, in a population-based in vitro model system (such as the lymphoblastoid cell lines, LCL, available from HapMap and 1000 Genomes project). Then data can be translated to genetic variability and individual (or subpopulation) susceptibility by incorporating ethnicity and corresponding genome-wide association studies (GWAS) with functional genomics screening results. This approach can provide complementary data for next-generation risk assessment, in particular, for environmental stressors. The current paper outlined the previous work conducted with a population-based in vitro model system, perturbed CRISPR-based functional toxicogenomic screening of environmental chemicals, and finally, the potential strategies to combine these two platforms with their opportunities and challenges to achieve a mechanistic understanding of population variability.

Interindividual Differences in DNA Adduct Formation and Detoxification of 1,3-Butadiene-Derived Epoxide in Human HapMap Cell Lines

Smoking-induced lung cancer is a major cause of cancer mortality in the US and worldwide. While 11-24% of smokers will develop lung cancer, risk varies among individuals and ethnic/racial groups. Specifically, African American and Native Hawaiian cigarette smokers are more likely to get lung cancer as compared to Caucasians, Japanese Americans, and Latinos. It is important to identify smokers who are at the greatest risk of developing lung cancer as they should be candidates for smoking cessation and chemopreventive intervention programs. Among 60+ tobacco smoke carcinogens, 1,3-butadiene (BD) is one of the most potent and abundant (20-75 μg per cigarette in mainstream smoke and 205-361 μg per cigarette in side stream smoke). BD is metabolically activated to 3,4-epoxy-1-butene (EB), which can be detoxified by glutathione S-transferase theta 1 (GSTT1)-mediated conjugation with glutathione, or can react with DNA to form 7-(1-hydroxy-3-buten-2-yl)guanine (EB-GII) adducts. In the present study, we employed EBV-transformed human lymphoblastoid cell lines (HapMap cells) with known GSTT1 genotypes to examine the influence of the GSTT1 gene on interindividual variability in butadiene metabolism, DNA adduct formation/repair, and biological outcomes (apoptosis). We found that GSTT1- HapMap cells treated with EB in culture produced lower levels of glutathione conjugates and were more susceptible to apoptosis but had similar numbers of EB-GII adducts as GSTT1+ cells. Our results suggest that GSTT1 can influence an individual's susceptibility to butadiene-derived epoxides.

Methods for evaluating variability in human health dose-response characterization

The Reference Dose (RfD) and Reference Concentration (RfC) are human health reference values (RfVs) representing exposure concentrations at or below which there is presumed to be little risk of adverse effects in the general human population. The 2009 National Research Council report Science and Decisions recommended redefining RfVs as "a risk-specific dose (for example, the dose associated with a 1 in 100,000 risk of a particular end point)." Distributions representing variability in human response to environmental contaminant exposures are critical for deriving risk-specific doses. Existing distributions estimating the extent of human toxicokinetic and toxicodynamic variability are based largely on controlled human exposure studies of pharmaceuticals. New data and methods have been developed that are designed to improve estimation of the quantitative variability in human response to environmental chemical exposures. Categories of research with potential to provide new database useful for developing updated human variability distributions include controlled human experiments, human epidemiology, animal models of genetic variability, in vitro estimates of toxicodynamic variability, and in vitro-based models of toxicokinetic variability. In vitro approaches, with further development including studies of different cell types and endpoints, and approaches to incorporate non-genetic sources of variability, appear to provide the greatest opportunity for substantial near-term advances.

The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives

The field of experimental toxicology is rapidly advancing by incorporating novel techniques and methods that provide a much more granular view into the mechanisms of potential adverse effects of chemical exposures on human health. The data from various in vitro assays and computational models are useful not only for increasing confidence in hazard and risk decisions, but also are enabling better, faster and cheaper assessment of a greater number of compounds, mixtures, and complex products. This is of special value to the field of green chemistry where design of new materials or alternative uses of existing ones is driven, at least in part, by considerations of safety. This article reviews the state of the science and decision-making in scenarios when little to no data may be available to draw conclusions about which choice in green chemistry is "safer." It is clear that there is no "one size fits all" solution and multiple data streams need to be weighed in making a decision. Moreover, the overall level of familiarity of the decision-makers and scientists alike with new assessment methodologies, their validity, value and limitations is evolving. Thus, while the "impact" of the new developments in toxicology on the field of green chemistry is great already, it is premature to conclude that the data from new assessment methodologies have been widely accepted yet.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

The US Federal Tox21 Program: A strategic and operational plan for continued leadership

The traditional approaches to toxicity testing have posed multiple challenges for evaluating the safety of commercial chemicals, pesticides, food additives/contaminants, and medical products.The challenges include number of chemicals that need to be tested, time and resource intensive nature of traditional toxicity tests, and unexpected adverse effects that occur in pharmaceutical clinical trials despite the extensive toxicological testing.Over a decade ago, the U.S. Environmental Protection Agency (EPA), National Toxicology Program (NTP), National Center for Advancing Translational Sciences (NCATS), and the Food and Drug Administration (FDA) formed a federal consortium for "Toxicology in the 21st Century" (Tox21) with a focus on developing and evaluating in vitro high-throughput screening (HTS) methods for hazard identification and providing mechanistic insights.The Tox21 consortium generated data on thousands of pharmaceuticals and datapoor chemicals, developed better understanding of the limits and applications of in vitro methods, and enabled incorporation of HTS data into regulatory decisions. To more broadly address the challenges in toxicology, Tox21 has developed a new strategic and operational plan that expands the focus of its research activities. The new focus areas include developing an expanded portfolio of alternative test systems, addressing technical limitations of in vitrotest systems, curating legacy in vivo toxicity testing data, establishing scientific confidence in the in vitrotest systems, and refining alternative methods for characterizing pharmacokinetics and in vitro assay disposition.The new Tox21 strategic and operational plan addresses key challenges to advance toxicology testing and will benefit both the organizations involved and the toxicology community.

Incorporating population-level genetic variability within laboratory models in toxicology: From the individual to the population

Humans respond to chemical exposures differently due to many factors, such as previous and concurrent stressors, age, sex, and genetic background. The vast majority of laboratory-based toxicology studies, however, have not considered the impact of population-level variability within dose-response relationships. The lack of data dealing with the influence of genetic diversity on the response to chemical exposure provides a difficult challenge for risk assessment as individuals within the population will display a wide-range of responses following toxicant challenge. Notably, the genetic background of individuals plays a major role in the variability seen in a population-level response to a drug or chemical and, thus, there is growing interest in including genetic diversity into laboratory-models. Here we outline several laboratory-based models that can be used to assay the influence of genetic variability on an individual's response to chemicals: 1) genetically-diverse cell lines, 2) human primary cells, 3) and genetically-diverse mouse panels. We also provide a succinct review for several seminal studies to highlight the capability, feasibility, and power of each of these models. This article is intended to highlight the need to include population-level genetic diversity into toxicological study designs via laboratory-based models with the goal to provide and supplement evidence in assessing the risk posed by chemicals to the human population. As such, incorporation of genetic variability will positively impact human-based risk assessment and provide empirical data to aid and influence decision-making processes in relation to chemical exposures.

Differential toxicity between perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA)

Perfluoroalkyl substances (PFASs) are persistent environmental contaminants. Perfluorooctane sulfonate (PFOS) and Perfluorooctanoic acid (PFOA) are representatives of PFASs. Recently, the U.S. Environmental Protection Agency (US EPA) set the health advisory level as 70 parts per trillion for lifetime exposure to PFOS and PFOA from drinking water, based on the EPA's 2016 Health Effects Support Documents. Then, a monograph on PFOA was made available online by the International Agency for Research on Cancer, where the agency classified PFOA as "possibly carcinogenic to humans" (Group 2B). The distinction between PFOS and PFOA, however, may not be easily understood from the above documents. This paper discussed differential toxicity between PFOS and PFOA focusing on neurotoxicity, developmental toxicity and carcinogenicity, mainly based on these documents. The conclusions are as follows: Further mechanistic studies may be necessary for ultrasonic-induced PFOS-specific neurotoxicity. To support the hypothesis for PFOS-specific neonatal death that PFOS interacts directly with components of natural lung surfactant, in vivo studies to relate the physicochemical effects to lung collapse may be required. PFOA-induced DNA damage secondary to oxidative stress may develop to mutagenicity under the condition where PFOA-induced apoptosis is not sufficient to remove the damaged cells. A study to find whether PFOA induces apoptosis in normal human cells may contribute to assessment of human carcinogenicity. Studies for new targets such as hepatocyte nuclear factor 4α (HNF4α) may help clarify the underlying mechanism for PFOA-induced carcinogenicity.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions

BACKGROUND

The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions.

OBJECTIVE

Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures.

METHODS

New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling.

DISCUSSION

NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams.

CONCLUSIONS

While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

In vitro screening for population variability in toxicity of pesticide-containing mixtures

Population-based human in vitro models offer exceptional opportunities for evaluating the potential hazard and mode of action of chemicals, as well as variability in responses to toxic insults among individuals. This study was designed to test the hypothesis that comparative population genomics with efficient in vitro experimental design can be used for evaluation of the potential for hazard, mode of action, and the extent of population variability in responses to chemical mixtures. We selected 146 lymphoblast cell lines from 4 ancestrally and geographically diverse human populations based on the availability of genome sequence and basal RNA-seq data. Cells were exposed to two pesticide mixtures - an environmental surface water sample comprised primarily of organochlorine pesticides and a laboratory-prepared mixture of 36 currently used pesticides - in concentration response and evaluated for cytotoxicity. On average, the two mixtures exhibited a similar range of in vitro cytotoxicity and showed considerable inter-individual variability across screened cell lines. However, when in vitro-to-in vivo extrapolation (IVIVE) coupled with reverse dosimetry was employed to convert the in vitro cytotoxic concentrations to oral equivalent doses and compared to the upper bound of predicted human exposure, we found that a nominally more cytotoxic chlorinated pesticide mixture is expected to have greater margin of safety (more than 5 orders of magnitude) as compared to the current use pesticide mixture (less than 2 orders of magnitude) due primarily to differences in exposure predictions. Multivariate genome-wide association mapping revealed an association between the toxicity of current use pesticide mixture and a polymorphism in rs1947825 in C17orf54. We conclude that a combination of in vitro human population-based cytotoxicity screening followed by dosimetric adjustment and comparative population genomics analyses enables quantitative evaluation of human health hazard from complex environmental mixtures. Additionally, such an approach yields testable hypotheses regarding potential toxicity mechanisms.

Chemical Safety Assessment Using Read-Across: Assessing the Use of Novel Testing Methods to Strengthen the Evidence Base for Decision Making

BACKGROUND

Safety assessment for repeated dose toxicity is one of the largest challenges in the process to replace animal testing. This is also one of the proof of concept ambitions of SEURAT-1, the largest ever European Union research initiative on alternative testing, co-funded by the European Commission and Cosmetics Europe. This review is based on the discussion and outcome of a workshop organized on initiative of the SEURAT-1 consortium joined by a group of international experts with complementary knowledge to further develop traditional read-across and include new approach data.

OBJECTIVES

The aim of the suggested strategy for chemical read-across is to show how a traditional read-across based on structural similarities between source and target substance can be strengthened with additional evidence from new approach data--for example, information from in vitro molecular screening, "-omics" assays and computational models--to reach regulatory acceptance.

METHODS

We identified four read-across scenarios that cover typical human health assessment situations. For each such decision context, we suggested several chemical groups as examples to prove when read-across between group members is possible, considering both chemical and biological similarities.

CONCLUSIONS

We agreed to carry out the complete read-across exercise for at least one chemical category per read-across scenario in the context of SEURAT-1, and the results of this exercise will be completed and presented by the end of the research initiative in December 2015.

Population-based in vitro hazard and concentration-response assessment of chemicals: the 1000 genomes high-throughput screening study

BACKGROUND

Understanding of human variation in toxicity to environmental chemicals remains limited, so human health risk assessments still largely rely on a generic 10-fold factor (10½ each for toxicokinetics and toxicodynamics) to account for sensitive individuals or subpopulations.

OBJECTIVES

We tested a hypothesis that population-wide in vitro cytotoxicity screening can rapidly inform both the magnitude of and molecular causes for interindividual toxicodynamic variability.

METHODS

We used 1,086 lymphoblastoid cell lines from the 1000 Genomes Project, representing nine populations from five continents, to assess variation in cytotoxic response to 179 chemicals. Analysis included assessments of population variation and heritability, and genome-wide association mapping, with attention to phenotypic relevance to human exposures.

RESULTS

For about half the tested compounds, cytotoxic response in the 1% most "sensitive" individual occurred at concentrations within a factor of 10½ (i.e., approximately 3) of that in the median individual; however, for some compounds, this factor was > 10. Genetic mapping suggested important roles for variation in membrane and transmembrane genes, with a number of chemicals showing association with SNP rs13120371 in the solute carrier SLC7A11, previously implicated in chemoresistance.

CONCLUSIONS

This experimental approach fills critical gaps unaddressed by recent large-scale toxicity testing programs, providing quantitative, experimentally based estimates of human toxicodynamic variability, and also testable hypotheses about mechanisms contributing to interindividual variation.

A cellular genetics approach identifies gene-drug interactions and pinpoints drug toxicity pathway nodes

New approaches to toxicity testing have incorporated high-throughput screening across a broad-range of in vitro assays to identify potential key events in response to chemical or drug treatment. To date, these approaches have primarily utilized repurposed drug discovery assays. In this study, we describe an approach that combines in vitro screening with genetic approaches for the experimental identification of genes and pathways involved in chemical or drug toxicity. Primary embryonic fibroblasts isolated from 32 genetically-characterized inbred mouse strains were treated in concentration-response format with 65 compounds, including pharmaceutical drugs, environmental chemicals, and compounds with known modes-of-action. Integrated cellular responses were measured at 24 and 72 h using high-content imaging and included cell loss, membrane permeability, mitochondrial function, and apoptosis. Genetic association analysis of cross-strain differences in the cellular responses resulted in a collection of candidate loci potentially underlying the variable strain response to each chemical. As a demonstration of the approach, one candidate gene involved in rotenone sensitivity, Cybb, was experimentally validated in vitro and in vivo. Pathway analysis on the combined list of candidate loci across all chemicals identified a number of over-connected nodes that may serve as core regulatory points in toxicity pathways.

Physiologically based pharmacokinetic (PBPK) modeling of interstrain variability in trichloroethylene metabolism in the mouse

BACKGROUND

Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data.

OBJECTIVES

We evaluated the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study.

METHODS

We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and 1 hybrid mouse strains to calibrate and extend existing physiologically based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). We used a Bayesian population analysis of interstrain variability to quantify variability in TCE metabolism.

RESULTS

Concentration-time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation were less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production were less variable (2-fold range) than DCA production (5-fold range), although the uncertainty bounds for DCA exceeded the predicted variability.

CONCLUSIONS

Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability.

FutureTox: building the road for 21st century toxicology and risk assessment practices

This article reports on the outcome of FutureTox, a Society of Toxicology (SOT) Contemporary Concepts in Toxicology (CCT) workshop, whose goal was to address the challenges and opportunities associated with implementing 21st century technologies for toxicity testing, hazard identification, and risk assessment. One goal of the workshop was to facilitate an interactive multisector and discipline dialog. To this end, workshop invitees and participants included stakeholders from governmental and regulatory agencies, research institutes, academia, and the chemical and pharmaceutical industry in Europe and the United States. The workshop agenda was constructed to collectively review and discuss the state-of-the-science in these fields, better define the problems and challenges, outline their collective goals for the future, and identify areas of common agreement key to advancing these technologies into practice.

Addressing human variability in next-generation human health risk assessments of environmental chemicals

BACKGROUND

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment.

OBJECTIVE

Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum.

METHODS

This review was informed by a National Research Council workshop titled "Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making." We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals.

DISCUSSION

One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population.

CONCLUSIONS

Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts.

7α-Hydroxy-β-Sitosterol from Chisocheton tomentosus Induces Apoptosis via Dysregulation of Cellular Bax/Bcl-2 Ratio and Cell Cycle Arrest by Downregulating ERK1/2 Activation

In continuation of our interest towards the elucidation of apoptotic pathways of cytotoxic phytocompounds, we have embarked upon a study on the anticancer effects of 7α-hydroxy-β-sitosterol (CT1), a rare natural phytosterol oxide isolated from Chisocheton tomentosus. CT1 was found to be cytotoxic on three different human tumor cell lines with minimal effects on normal cell controls, where cell viability levels were maintained ≥80% upon treatment. Our results showed that cell death in MCF-7 breast tumor cells was achieved through the induction of apoptosis via downregulation of the ERK1/2 signaling pathway. CT1 was also found to increase proapoptotic Bax protein levels, while decreasing anti-apoptotic Bcl-2 protein levels, suggesting the involvement of the intrinsic pathway. Reduced levels of initiator procaspase-9 and executioner procaspase-3 were also observed following CT1 exposure, confirming the involvement of cytochrome c-mediated apoptosis via the mitochondrial pathway. These results demonstrated the cytotoxic and apoptotic ability of 7α-hydroxy-β-sitosterol and suggest its potential anti-cancer use particularly on breast adenocarcinoma cells.

Mitochondrial bioenergetics and drug-induced toxicity in a panel of mouse embryonic fibroblasts with mitochondrial DNA single nucleotide polymorphisms

Mitochondrial DNA (mtDNA) variations including single nucleotide polymorphisms (SNPs) have been proposed to be involved in idiosyncratic drug reactions. However, current in vitro and in vivo models lack the genetic diversity seen in the human population. Our hypothesis is that different cell strains with distinct mtDNA SNPs may have different mitochondrial bioenergetic profiles and may therefore vary in their response to drug-induced toxicity. Therefore, we used an in vitro system composed of four strains of mouse embryonic fibroblasts (MEFs) with mtDNA polymorphisms. We sequenced mtDNA from embryonic fibroblasts isolated from four mouse strains, C57BL/6J, MOLF/EiJ, CZECHII/EiJ and PERA/EiJ, with the latter two being sequenced for the first time. The bioenergetic profile of the four strains of MEFs was investigated at both passages 3 and 10. Our results showed that there were clear differences among the four strains of MEFs at both passages, with CZECHII/EiJ having a lower mitochondrial robustness when compared to C57BL/6J, followed by MOLF/EiJ and PERA/EiJ. Seven drugs known to impair mitochondrial function were tested for their effect on the ATP content of the four strains of MEFs in both glucose- and galactose-containing media. Our results showed that there were strain-dependent differences in the response to some of the drugs. We propose that this model is a useful starting point to study compounds that may cause mitochondrial off-target toxicity in early stages of drug development, thus decreasing the number of experimental animals used.

Extreme sensitivity and the practical implications of risk assessment thresholds

Traditional risk-assessment theory assumes the existence of a threshold for non-cancer health effects. However, a recent trend in environmental regulation rejects this assumption in favor of non-threshold linearity for these endpoints. This trend is driven largely by two related concepts: (1) a theoretical assumption of wide-ranging human sensitivity, and (2) inability to detect thresholds in epidemiologic models. Wide-ranging sensitivity assumes a subpopulation with extreme background vulnerability, so that even trivial environmental exposures are hazardous to someone somewhere. We use examples from the real world of clinical medicine to show that this theoretical assumption is inconsistent with the biology of mammalian systems and the realities of patient care. Using examples from particulate-matter air-pollution research, we further show that failure to reject linearity is usually driven by statistical rather than biological considerations, and that nonlinear/threshold models often have a similar or better fit than their linear counterparts. This evidence suggests the existence of practical, real-world thresholds for most chemical exposures.

Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR-like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage.

Quantitative high-throughput screening for chemical toxicity in a population-based in vitro model

A shift in toxicity testing from in vivo to in vitro may efficiently prioritize compounds, reveal new mechanisms, and enable predictive modeling. Quantitative high-throughput screening (qHTS) is a major source of data for computational toxicology, and our goal in this study was to aid in the development of predictive in vitro models of chemical-induced toxicity, anchored on interindividual genetic variability. Eighty-one human lymphoblast cell lines from 27 Centre d'Etude du Polymorphisme Humain trios were exposed to 240 chemical substances (12 concentrations, 0.26nM-46.0μM) and evaluated for cytotoxicity and apoptosis. qHTS screening in the genetically defined population produced robust and reproducible results, which allowed for cross-compound, cross-assay, and cross-individual comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited interindividual differences in cytotoxicity. Specifically, the qHTS in a population-based human in vitro model system has several unique aspects that are of utility for toxicity testing, chemical prioritization, and high-throughput risk assessment. First, standardized and high-quality concentration-response profiling, with reproducibility confirmed by comparison with previous experiments, enables prioritization of chemicals for variability in interindividual range in cytotoxicity. Second, genome-wide association analysis of cytotoxicity phenotypes allows exploration of the potential genetic determinants of interindividual variability in toxicity. Furthermore, highly significant associations identified through the analysis of population-level correlations between basal gene expression variability and chemical-induced toxicity suggest plausible mode of action hypotheses for follow-up analyses. We conclude that as the improved resolution of genetic profiling can now be matched with high-quality in vitro screening data, the evaluation of the toxicity pathways and the effects of genetic diversity are now feasible through the use of human lymphoblast cell lines.

Mechanistic considerations for human relevance of cancer hazard of di(2-ethylhexyl) phthalate

Di(2-ethylhexyl) phthalate (DEHP) is a peroxisome proliferator agent that is widely used as a plasticizer to soften polyvinylchloride plastics and non-polymers. Both occupational (e.g., by inhalation during its manufacture and use as a plasticizer of polyvinylchloride) and environmental (medical devices, contamination of food, or intake from air, water and soil) routes of exposure to DEHP are of concern for human health. There is sufficient evidence for carcinogenicity of DEHP in the liver in both rats and mice; however, there is little epidemiological evidence on possible associations between exposure to DEHP and liver cancer in humans. Data are available to suggest that liver is not the only target tissue for DEHP-associated toxicity and carcinogenicity in both humans and rodents. The debate regarding human relevance of the findings in rats or mice has been informed by studies on the mechanisms of carcinogenesis of the peroxisome proliferator class of chemicals, including DEHP. Important additional mechanistic information became available in the past decade, including, but not limited to, sub-acute, sub-chronic and chronic studies with DEHP in peroxisome proliferator-activated receptor (PPAR) α-null mice, as well as experiments utilizing several transgenic mouse lines. Activation of PPARα and the subsequent downstream events mediated by this transcription factor represent an important mechanism of action for DEHP in rats and mice. However, additional data from animal models and studies in humans exposed to DEHP from the environment suggest that multiple molecular signals and pathways in several cell types in the liver, rather than a single molecular event, contribute to the cancer in rats and mice. In addition, the toxic and carcinogenic effects of DEHP are not limited to liver. The International Agency for Research on Cancer working group concluded that the human relevance of the molecular events leading to cancer elicited by DEHP in several target tissues (e.g., liver and testis) in rats and mice can not be ruled out and DEHP was classified as possibly carcinogenic to humans (Group 2B).

Human lymphoblastoid cell lines: a goldmine for the biobankomics era

Biobanking became a necessity for translating genetic discoveries into clinical practice. Approaches to personalized medicine require a new model system for functional and pharmacogenomic studies of a variety of accumulating genetic variations, as well as new research environments such as biobankomics. Human lymphoblastoid cell lines (LCLs) will provide a valuable tool to meet such new demands in the biobankomics era. The National Biobank of Korea (NBK), which is leading the Korea Biobank Project, has a large collection of LCLs derived mostly from population-based cohort samples. Using a special long-term subculture collection of NBK LCLs, biological characteristics of early passage LCLs and terminally immortalized LCLs have been investigated to promote the utilization of LCLs and provide well quality-controlled LCLs for genetic and pharmacogenomic studies. As LCLs have been successfully phenotyped for cytotoxicity in response to various stimulators, including chemotherapeutic agents, environmental chemicals and irradiation, the utility of LCLs will increase in the future. Here, we discuss current and future applications of NBK LCLs for the biobankomics era.