Potency Ranking of Per- and Polyfluoroalkyl Substances Using High-Throughput Transcriptomic Analysis of Human Liver Spheroids

Identifying novel mechanisms of per- and polyfluoroalkyl substance-induced hepatotoxicity using FRG humanized mice

Per- and polyfluoroalkyl substances (PFAS) such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) and perfluoro-2-methyl-3-oxahexanoic acid (GenX), the new replacement PFAS, are major environmental contaminants. In rodents, these PFAS induce several adverse effects on the liver, including increased proliferation, hepatomegaly, steatosis, hypercholesterolemia, nonalcoholic fatty liver disease and liver cancers. Activation of peroxisome proliferator receptor alpha by PFAS is considered the primary mechanism of action in rodent hepatocyte-induced proliferation. However, the human relevance of this mechanism is uncertain. We investigated human-relevant mechanisms of PFAS-induced adverse hepatic effects using FRG liver-chimeric humanized mice with livers repopulated with functional human hepatocytes. Male FRG humanized mice were treated with 0.067 mg/L of PFOA, 0.145 mg/L of PFOS, or 1 mg/L of GenX in drinking water for 28 days. PFOS caused a significant decrease in total serum cholesterol and LDL/VLDL, whereas GenX caused a significant elevation in LDL/VLDL with no change in total cholesterol and HDL. All three PFAS induced significant hepatocyte proliferation. RNA-sequencing with alignment to the human genome showed a total of 240, 162, and 619 differentially expressed genes after PFOA, PFOS, and GenX exposure, respectively. Upstream regulator analysis revealed that all three PFAS induced activation of p53 and inhibition of androgen receptor and NR1D1, a transcriptional repressor important in circadian rhythm. Further biochemical studies confirmed NR1D1 inhibition and in silico modeling indicated potential interaction of all three PFAS with the DNA-binding domain of NR1D1. In conclusion, our studies using FRG humanized mice have revealed new human-relevant molecular mechanisms of PFAS including their previously unknown effect on circadian rhythm.

Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes

Environmental chemicals may contribute to the global burden of cardiovascular disease, but experimental data are lacking to determine which substances pose the greatest risk. Human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes are a high-throughput cardiotoxicity model that is widely used to test drugs and chemicals; however, most studies focus on exploring electro-physiological readouts. Gene expression data may provide additional molecular insights to be used for both mechanistic interpretation and dose-response analyses. Therefore, we hypothesized that both transcriptomic and functional data in human iPSC-derived cardiomyocytes may be used as a comprehensive screening tool to identify potential cardiotoxicity hazards and risks of the chemicals. To test this hypothesis, we performed concentration-response analysis of 464 chemicals from 12 classes, including both pharmaceuticals and nonpharmaceutical substances. Functional effects (beat frequency, QT prolongation, and asystole), cytotoxicity, and whole transcriptome response were evaluated. Points of departure were derived from phenotypic and transcriptomic data, and risk characterization was performed. Overall, 244 (53%) substances were active in at least one phenotype; as expected, pharmaceuticals with known cardiac liabilities were the most active. Positive chronotropy was the functional phenotype activated by the largest number of tested chemicals. No chemical class was particularly prone to pose a potential hazard to cardiomyocytes; a varying proportion (10-44%) of substances in each class had effects on cardiomyocytes. Transcriptomic data showed that 69 (15%) substances elicited significant gene expression changes; most perturbed pathways were highly relevant to known key characteristics of human cardiotoxicants. The bioactivity-to-exposure ratios showed that phenotypic- and transcriptomic-based POD led to similar results for risk characterization. Overall, our findings demonstrate how the integrative use of in vitro transcriptomic and phenotypic data from iPSC-derived cardiomyocytes not only offers a complementary approach for hazard and risk prioritization, but also enables mechanistic interpretation of the in vitro test results to increase confidence in decision-making.

Modeling HepaRG metabolome responses to pyrrolizidine alkaloid exposure for insight into points of departure and modes of action

The new challenges in toxicology demand novel and innovative in vitro approaches for deriving points of departure (PODs) and determining the mode of action (MOA) of chemicals. Therefore, the aim of this original study was to couple in vitro studies with untargeted metabolomics to model the concentration-response of extra- and intracellular metabolome data on human HepaRG cells treated for 48 h with three pyrrolizidine alkaloids (PAs): heliotrine, retrorsine and lasiocarpine. Modeling revealed that the three PAs induced various monotonic and, importantly, biphasic curves of metabolite content. Based on unannotated metabolites, the endometabolome was more sensitive than the exometabolome in terms of metabolomic effects, and benchmark concentrations (BMCs) confirmed that lasiocarpine was the most hepatotoxic PA. Regarding its MOA, impairment of lipid metabolism was highlighted at a very low BMC (first quartile, 0.003 µM). Moreover, results confirmed that lasiocarpine targets bile acids, as well as amino acid and steroid metabolisms. Analysis of the endometabolome, based on coupling concentration-response and PODs, gave encouraging results for ranking toxins according to their hepatotoxic effects. Therefore, this novel approach is a promising tool for next-generation risk assessment, readily applicable to a broad range of compounds and toxic endpoints.

Comparison on the mechanism and potency of hepatotoxicity among hemp extract and its four major constituent cannabinoids

Cannabidiol (CBD) has been reported to induce hepatotoxicity in clinical trials and research studies; however, little is known about the safety of other nonintoxicating cannabinoids. New approach methodologies (NAMs) based on bioinformatic analysis of high-throughput transcriptomic data are gaining increasing importance in risk assessment and regulatory decision-making of data-poor chemicals. In the current study, we conducted a concentration response transcriptomic analysis of hemp extract and its four major constituent cannabinoids [CBD, cannabichromene (CBC), cannabigerol (CBG), and cannabinol (CBN)] in hepatocytes derived from human induced pluripotent stem cells (iPSCs). Each compound impacted a distinctive combination of biological functions and pathways. However, all the cannabinoids impaired liver metabolism and caused oxidative stress in the cells. Benchmark concentration (BMC) analysis showed potencies in transcriptional activity of the cannabinoids were in the order of CBN > CBD > CBC > CBG, consistent with the order of their cytotoxicity IC50 values. Patterns of transcriptomic changes induced by hemp extract and its median overall BMC were very similar to CBD but differed significantly from other cannabinoids, suggesting that potential adverse effects of hemp extract were largely due to its major constituent CBD. Lastly, transcriptomic point-of-departure (tPoD) values were determined for each of the compounds, with the value for CBD (0.106 µM) being concordant with a previously reported one derived from apical endpoints of clinical and animal studies. Taken together, the current study demonstrates the potential utility of transcriptomic BMC analysis as a NAM for hazard assessment of data-poor chemicals, improves our understanding of the possible health effects of hemp extract and its constituent cannabinoids, and provides important tPoD data that could contribute to inform human safety assessment of these cannabinoid compounds.

Transcriptomic re-analyses of human hepatocyte spheroids treated with PFAS reveals chain length and dose-dependent modes of action

To identify pathway perturbations and examine biological modes of action (MOAs) for various perfluoroalkyl substances, we re-analyzed published in vitro gene expression studies from human primary liver spheroids. With treatment times ranging from 10 to 14 days, shorter-chain PFAS (those with 6 or fewer fluorinated carbon atoms in the alkyl chain) showed enrichment for pathways of fatty acid metabolism and fatty acid beta-oxidation with upregulated genes. Longer-chain PFAS compounds, specifically PFOS (perfluorooctane sulfonate), PFDS (perfluorodecane sulfonate), and higher doses of PFOA (perfluorooctanoic acid), had enrichment for pathways involved in steroid metabolism, fatty acid metabolism, and biological oxidation for downregulated genes. Although PFNA (perfluorononanoic acid), PFDA (perfluorodecanoic acid), and PFUnDA (perfluoroundecanoic acid) were more toxic and could only be examined after a 1-day treatment, all three had enrichment patterns similar to those observed with PFOS. With PFOA there were dose-dependent changes in pathway enrichment, shifting from upregulation of fatty acid metabolism and downregulation of steroid metabolism to downregulation of both at higher doses. The response to PFHpS (perfluoroheptanesulfonic acid) was similar to the PFOA pattern at the lower treatment dose. Based on results of transcription factor binding sites analyses, we propose that downregulation of pathways of lipid metabolism by longer chain PFAS may be due to inhibitory interactions of PPARD on genes controlled by PPARA and PPARG. In conclusion, our transcriptomic analysis indicates that the biological MOAs of PFAS compounds differ according to chain length and dose, and that risk assessments for PFAS should consider these differences in biological MOAs when evaluating mixtures of these compounds.

In vitro screening of understudied PFAS with a focus on lipid metabolism disruption

Per- and polyfluoroalkyl substances (PFAS) are man-made chemicals used in many industrial applications. Exposure to PFAS is associated with several health risks, including a decrease in infant birth weight, hepatoxicity, disruption of lipid metabolism, and decreased immune response. We used the in vitro cell models to screen six less studied PFAS [perfluorooctane sulfonamide (PFOSA), perfluoropentanoic acid (PFPeA), perfluoropropionic acid (PFPrA), 6:2 fluorotelomer alcohol (6:2 FTOH), 6:2 fluorotelomer sulfonic acid (6:2 FTSA), and 8:2 fluorotelomer sulfonic acid (8:2 FTSA)] for their capacity to activate nuclear receptors and to cause differential expression of genes involved in lipid metabolism. Cytotoxicity assays were run in parallel to exclude that observed differential gene expression was due to cytotoxicity. Based on the cytotoxicity assays and gene expression studies, PFOSA was shown to be more potent than other tested PFAS. PFOSA decreased the gene expression of crucial genes involved in bile acid synthesis and detoxification, cholesterol synthesis, bile acid and cholesterol transport, and lipid metabolism regulation. Except for 6:2 FTOH and 8:2 FTSA, all tested PFAS downregulated PPARA gene expression. The reporter gene assay also showed that 8:2 FTSA transactivated the farnesoid X receptor (FXR). Based on this study, PFOSA, 6:2 FTSA, and 8:2 FTSA were prioritized for further studies to confirm and understand their possible effects on hepatic lipid metabolism.

Trend of PFAS concentrations and prediction of potential risks in Taihu Lake of China by AQUATOX

Per- and polyfluoroalkyl substances (PFAS) are recognized as emerging environmental pollutants due to their high persistence and toxicities to humans and animals. Understanding the temporal trend of PFAS in the environment is important for their pollution control and making appropriate policies. Many studies have reported the PFAS concentrations in Taihu Lake, the third largest lake in China, while their temporal trend during the years was seldom investigated. This study summarizes the PFAS concentrations in the water, sediment and organisms in Taihu Lake from 2009 to 2020 to depict their temporal trends. Meanwhile, the ecological model of AQUATOX was applied to evaluate and predict the potential risks of PFAS from 2012 to 2030. The results showed that the total PFAS concentrations varied but without distinct increase or decrease in both water and sediment during the years, while PFAS concentrations in organisms significantly decreased. The yearly mean concentrations of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) in the water were 21.7-25.4 ng/L and 9.7-26.5 ng/L respectively, lower than the Standards for Drinking Water Quality of China and the suggested water quality criteria to protect the aquatic organisms. In sediment, PFOA and PFOS concentrations were 0.16-0.69 ng/g and 0.15-0.82 ng/g respectively, much lower than the recommended sediment quality guideline values. Based on the AQUATOX prediction, there will be no major threats caused by PFAS to the growth of biota in Taihu Lake in the near future, while the biomass of some species (e.g. carp) will be affected under the perturbation of PFAS. Both field investigation and AQUATOX simulation showed that PFOS concentrations in invertebrates and fish descend steadily, while no remarkable decrease in PFOA concentrations was expected. This study suggests a decreasing ecological risk of PFAS in Taihu Lake, while highlights the necessity of continuous monitoring of PFAS contamination.

Assessment and Comparison of Early Developmental Toxicity of Six Per- and Polyfluoroalkyl Substances with Human Embryonic Stem Cell Models

Per- and polyfluoroalkyl substances (PFAS) are extensively utilized in varieties of products and tend to accumulate in the human body including umbilical cord blood and embryos/fetuses. In this study, we conducted an assessment and comparison of the potential early developmental toxicity of perfluorooctanoic acid (PFOA), undecafluorohexanoic acid (PFHxA), heptafluorobutyric acid, perfluorooctanesulfonate (PFOS), perfluorohexanesulfonate, and perfluorobutyric acid at noncytotoxic concentrations relevant to human exposure using models based on human embryonic stem cells in both three-dimensional embryoid body (EB) and monolayer differentiation configurations. All six compounds influenced the determination of cell fate by disrupting the expression of associated markers in both models and, in some instances, even led to alterations in the formation of cystic EBs. The expression of cilia-related gene IFT122 was significantly inhibited. Additionally, PFOS and PFOA inhibited ciliogenesis, while PFOA specifically reduced the cilia length. Transcriptome analysis revealed that PFOS altered 1054 genes and disrupted crucial signaling pathways such as WNT and TGF-β, which play integral roles in cilia transduction and are critical for early embryonic development. These results provide precise and comprehensive insights into the potential adverse health effects of these six PFAS compounds directly concerning early human embryonic development.

Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches

A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3-1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.

Integrating high-throughput phenotypic profiling and transcriptomic analyses to predict the hepatosteatosis effects induced by per- and polyfluoroalkyl substances

Per- and polyfluoroalkyl substances (PFAS) is a large compound class (n > 12,000) that is extensively present in food, drinking water, and aquatic environments. Reduced serum triglycerides and hepatosteatosis appear to be the common phenotypes for different PFAS chemicals. However, the hepatosteatosis potential of most PFAS chemicals remains largely unknown. This study aims to investigate PFAS-induced hepatosteatosis using in vitro high-throughput phenotype profiling (HTPP) and high-throughput transcriptomic (HTTr) data. We quantified the in vitro hepatosteatosis effects and mitochondrial damage using high-content imaging, curated the transcriptomic data from the Gene Expression Omnibus (GEO) database, and then calculated the point of departure (POD) values for HTPP phenotypes or HTTr transcripts, using the Bayesian benchmark dose modeling approach. Our results indicated that PFAS compounds with fully saturated C-F bonds, sulfur- and nitrogen-containing functional groups, and a fluorinated carbon chain length greater than 8 have the potential to produce biological effects consistent with hepatosteatosis. PFAS primarily induced hepatosteatosis via disturbance in lipid transport and storage. The potency rankings of PFAS compounds are highly concordant among in vitro HTPP, HTTr, and in vivo hepatosteatosis phenotypes (ρ = 0.60-0.73). In conclusion, integrating the information from in vitro HTPP and HTTr analyses can accurately project in vivo hepatosteatosis effects induced by PFAS compounds.

A 50-gene biomarker identifies estrogen receptor-modulating chemicals in a microarray compendium

High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells.

Comparing Transcriptomic Points of Departure to Apical Effect Concentrations For Larval Fathead Minnow Exposed to Chemicals with Four Different Modes Of Action

It is postulated that below a transcriptomic-based point of departure, adverse effects are unlikely to occur, thereby providing a chemical concentration to use in screening level hazard assessment. The present study extends previous work describing a high-throughput fathead minnow assay that can provide full transcriptomic data after exposure to a test chemical. One-day post-hatch fathead minnows were exposed to ten concentrations of three representatives of four chemical modes of action: organophosphates, ecdysone receptor agonists, plant photosystem II inhibitors, and estrogen receptor agonists for 24 h. Concentration response modeling was performed on whole body gene expression data from each exposure, using measured chemical concentrations when available. Transcriptomic points of departure in larval fathead minnow were lower than apical effect concentrations across fish species but not always lower than toxic effect concentrations in other aquatic taxa like crustaceans and insects. The point of departure was highly dependent on measured chemical concentration which were often lower than the nominal concentration. Differentially expressed genes between chemicals within modes of action were compared and often showed statistically significant overlap. In addition, reproducibility between identical exposures using a positive control chemical (CuSO4) and variability associated with the transcriptomic point of departure using in silico sampling were considered. Results extend a transcriptomic-compatible fathead minnow high-throughput assay for possible use in ecological hazard screening.

Understanding PFAS toxicity through cell culture metabolomics: Current applications and future perspectives

Per- and polyfluoroalkyl substances (PFAS), ubiquitous environmental contaminants, pose significant challenges to ecosystems and human health. While cell cultures have emerged as new approach methodologies (NAMs) in ecotoxicity research, metabolomics is an emerging technique used to characterize the small-molecule metabolites present in cells and to understand their role in various biological processes. Integration of metabolomics with cell cultures, known as cell culture metabolomics, provides a novel and robust tool to unravel the complex molecular responses induced by PFAS exposure. In vitro testing also reduces reliance on animal testing, aligning with ethical and regulatory imperatives. The current review summarizes key findings from recent studies utilizing cell culture metabolomics to investigate PFAS toxicity, highlighting alterations in metabolic pathways, biomarker identification, and the potential linkages between metabolic perturbations. Additionally, the paper discusses different types of cell cultures and metabolomics methods used for studies of environmental contaminants and particularly PFAS. Future perspectives on the combination of metabolomics with other advanced technologies, such as single-cell metabolomics (SCM), imaging mass spectrometry (IMS), extracellular flux analysis (EFA), and multi-omics are also explored, which offers a holistic understanding of environmental contaminants. The synthesis of current knowledge and identification of research gaps provide a foundation for future investigations that aim to elucidate the complexities of PFAS-induced cellular responses and contribute to the development of effective strategies for mitigating their adverse effects on human health.

Transcriptomics-Based Points of Departure for Daphnia magna Exposed to 18 Per- and Polyfluoroalkyl Substances

Per- and polyfluoroalkyl substances (PFAS) represent a large group of contaminants of concern based on their widespread use, environmental persistence, and potential toxicity. Many traditional models for estimating toxicity, bioaccumulation, and other toxicological properties are not well suited for PFAS. Consequently, there is a need to generate hazard information for PFAS in an efficient and cost-effective manner. In the present study, Daphnia magna were exposed to multiple concentrations of 22 different PFAS for 24 h in a 96-well plate format. Following exposure, whole-body RNA was extracted and extracts, each representing five exposed individuals, were subjected to RNA sequencing. Following analytical measurements to verify PFAS exposure concentrations and quality control on processed cDNA libraries for sequencing, concentration-response modeling was applied to the data sets for 18 of the tested compounds, and the concentration at which a concerted molecular response occurred (transcriptomic point of departure; tPOD) was calculated. The tPODs, based on measured concentrations of PFAS, generally ranged from 0.03 to 0.58 µM (9.9-350 µg/L; interquartile range). In most cases, these concentrations were two orders of magnitude lower than similarly calculated tPODs for human cell lines exposed to PFAS. They were also lower than apical effect concentrations reported for seven PFAS for which some crustacean or invertebrate toxicity data were available, although there were a few exceptions. Despite being lower than most other available hazard benchmarks, D. magna tPODs were, on average, four orders of magnitude greater than the maximum aqueous concentrations of PFAS measured in Great Lakes tributaries. Overall, this high-throughput transcriptomics assay with D. magna holds promise as a component of a tiered hazard evaluation strategy employing new approach methodologies. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Hazard and risk characterization of 56 structurally diverse PFAS using a targeted battery of broad coverage assays using six human cell types

Per- and poly-fluoroalkyl substances (PFAS) are extensively used in commerce leading to their prevalence in the environment. Due to their chemical stability, PFAS are considered to be persistent and bioaccumulative; they are frequently detected in both the environment and humans. Because of this, PFAS as a class (composed of hundreds to thousands of chemicals) are contaminants of very high concern. Little information is available for the vast majority of PFAS, and regulatory agencies lack safety data to determine whether exposure limits or restrictions are needed. Cell-based assays are a pragmatic approach to inform decision-makers on potential health hazards; therefore, we hypothesized that a targeted battery of human in vitro assays can be used to determine whether there are structure-bioactivity relationships for PFAS, and to characterize potential risks by comparing bioactivity (points of departure) to exposure estimates. We tested 56 PFAS from 8 structure-based subclasses in concentration response (0.1-100 μM) using six human cell types selected from target organs with suggested adverse effects of PFAS - human induced pluripotent stem cell (iPSC)-derived hepatocytes, neurons, and cardiomyocytes, primary human hepatocytes, endothelial and HepG2 cells. While many compounds were without effect; certain PFAS demonstrated cell-specific activity highlighting the necessity of using a compendium of in vitro models to identify potential hazards. No class-specific groupings were evident except for some chain length- and structure-related trends. In addition, margins of exposure (MOE) were derived using empirical and predicted exposure data. Conservative MOE calculations showed that most tested PFAS had a MOE in the 1-100 range; ∼20% of PFAS had MOE<1, providing tiered priorities for further studies. Overall, we show that a compendium of human cell-based models can be used to derive bioactivity estimates for a range of PFAS, enabling comparisons with human biomonitoring data. Furthermore, we emphasize that establishing structure-bioactivity relationships may be challenging for the tested PFAS.

Derivation of Transcriptomics-Based Points of Departure for 20 Per- or Polyfluoroalkyl Substances Using a Larval Fathead Minnow (Pimephales promelas) Reduced Transcriptome Assay

Traditional toxicity testing has been unable to keep pace with the introduction of new chemicals into commerce. Consequently, there are limited or no toxicity data for many chemicals to which fish and wildlife may be exposed. Per- and polyfluoroalkyl substances (PFAS) are emblematic of this issue in that ecological hazards of most PFAS remain uncharacterized. The present study employed a high-throughput assay to identify the concentration at which 20 PFAS, with diverse properties, elicited a concerted gene expression response (termed a transcriptomics-based point of departure [tPOD]) in larval fathead minnows (Pimephales promelas; 5-6 days postfertilization) exposed for 24 h. Based on a reduced transcriptome approach that measured whole-body expression of 1832 genes, the median tPOD for the 20 PFAS tested was 10 µM. Longer-chain carboxylic acids (12-13 C-F); an eight-C-F dialcohol, N-alkyl sulfonamide; and telomer sulfonic acid were among the most potent PFAS, eliciting gene expression responses at concentrations <1 µM. With a few exceptions, larval fathead minnow tPODs were concordant with those based on whole-transcriptome response in human cell lines. However, larval fathead minnow tPODs were often greater than those for Daphnia magna exposed to the same PFAS. The tPODs overlapped concentrations at which other sublethal effects have been reported in fish (available for 10 PFAS). Nonetheless, fathead minnow tPODs were orders of magnitude higher than aqueous PFAS concentrations detected in tributaries of the North American Great Lakes, suggesting a substantial margin of safety. Overall, results broadly support the use of a fathead minnow larval transcriptomics assay to derive screening-level potency estimates for use in ecological risk-based prioritization. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Hepatic Transcriptome Comparative In Silico Analysis Reveals Similar Pathways and Targets Altered by Legacy and Alternative Per- and Polyfluoroalkyl Substances in Mice

Per- and poly-fluoroalkyl substances (PFAS) are a large class of fluorinated carbon chains that include legacy PFAS, such as perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonate (PFHxS). These compounds induce adverse health effects, including hepatotoxicity. Potential alternatives to the legacy PFAS (HFPO-DA (GenX), HFPO4, HFPO-TA, F-53B, 6:2 FTSA, and 6:2 FTCA), as well as a byproduct of PFAS manufacturing (Nafion BP2), are increasingly being found in the environment. The potential hazards of these new alternatives are less well known. To better understand the diversity of molecular targets of the PFAS, we performed a comparative toxicogenomics analysis of the gene expression changes in the livers of mice exposed to these PFAS, and compared these to five activators of PPARα, a common target of many PFAS. Using hierarchical clustering, pathway analysis, and predictive biomarkers, we found that most of the alternative PFAS modulate molecular targets that overlap with legacy PFAS. Only three of the 11 PFAS tested did not appreciably activate PPARα (Nafion BP2, 6:2 FTSA, and 6:2 FTCA). Predictive biomarkers showed that most PFAS (PFHxS, PFOA, PFOS, PFNA, HFPO-TA, F-53B, HFPO4, Nafion BP2) activated CAR. PFNA, PFHxS, PFOA, PFOS, HFPO4, HFPO-TA, F-53B, Nafion BP2, and 6:2 FTSA suppressed STAT5b, activated NRF2, and activated SREBP. There was no apparent relationship between the length of the carbon chain, type of head group, or number of ether linkages and the transcriptomic changes. This work highlights the similarities in molecular targets between the legacy and alternative PFAS.

Toxicological Mechanisms and Potencies of Organophosphate Esters in KGN Human Ovarian Granulosa Cells as Revealed by High-throughput Transcriptomics

Despite the growing number of studies reporting potential risks associated with exposure to organophosphate esters (OPEs), their molecular mechanisms of action remain poorly defined. We used the high-throughput TempO-Seq™ platform to investigate the effects of frequently detected OPEs on the expression of ∼3000 environmentally responsive genes in KGN human ovarian granulosa cells. Cells were exposed for 48 h to one of five OPEs (0.1 to 50 μM): tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), triphenyl phosphate (TPHP), or tris(2-butoxyethyl) phosphate (TBOEP). The sequencing data indicate that four OPEs induced transcriptional changes, whereas TBOEP had no effect within the concentration range tested. Multiple pathway databases were used to predict alterations in biological processes based on differentially expressed genes. At lower concentrations, inhibition of the cholesterol biosynthetic pathway was the predominant effect of OPEs; this was likely a consequence of intracellular cholesterol accumulation. At higher concentrations, BPDP and TPHP had distinct effects, primarily affecting pathways involved in cell cycle progression and other stress responses. Benchmark concentration (BMC) modelling revealed that BPDP had the lowest transcriptomic point of departure. However, in vitro to in vivo extrapolation modeling indicated that TMPP was bioactive at lower concentrations than the other OPEs. We conclude that these new approach methodologies provide information on the mechanism(s) underlying the effects of data-poor compounds and assist in the derivation of protective points of departure for use in chemical read-across and decision-making.

Extracellular Vesicles altered by a Per- and Polyfluoroalkyl Substance Mixture: In Vitro Dose-Dependent Release, Chemical Content, and MicroRNA Signatures involved in Liver Health

Per- and polyfluoroalkyl substances (PFAS) have emerged as high priority contaminants due to their ubiquity and pervasiveness in the environment. Numerous PFAS co-occur across sources of drinking water, including areas of North Carolina (NC) with some detected concentrations above the Environmental Protection Agency's health advisory levels. While evidence demonstrates PFAS exposure induces harmful effects in the liver, the involvement of extracellular vesicles (EVs) as potential mediators of these effects has yet to be evaluated. This study set out to evaluate the hypothesis that PFAS mixtures induce dose-dependent release of EVs from liver cells, with exposures causing differential loading of microRNAs (miRNAs) and PFAS chemical signatures. To test this hypothesis, a defined PFAS mixture was prioritized utilizing data collected by the NC PFAS Testing Network. This mixture contained three substances, PFOS, PFOA, and PFHxA, selected based upon co-occurrence patterns and the inclusion of both short-chain (PFHxA) and long-chain (PFOA and PFOS) substances. HepG2 liver cells were exposed to equimolar PFAS, and secreted EVs were isolated from conditioned media and characterized for count and molecular content. Exposures induced a dose-dependent release of EVs carrying miRNAs that were differentially loaded upon exposure. These altered miRNA signatures were predicted to target mRNA pathways involved in hepatic fibrosis and cancer. Chemical concentrations of PFOS, PFOA, and PFHxA were also detected in both parent HepG2 cells and their released EVs, specifically within a 15-fold range after normalizing for protein content. This study therefore established EVs as novel biological responders and measurable endpoints for evaluating PFAS-induced toxicity.

Cross-Species Transcriptomics Analysis Highlights Conserved Molecular Responses to Per- and Polyfluoroalkyl Substances

In recent decades, per- and polyfluoroalkyl substances (PFASs) have garnered widespread public attention due to their persistence in the environment and detrimental effects on the health of living organisms, spurring the generation of several transcriptome-centered investigations to understand the biological basis of their mechanism. In this study, we collected 2144 publicly available samples from seven distinct animal species to examine the molecular responses to PFAS exposure and to determine if there are conserved responses. Our comparative transcriptional analysis revealed that exposure to PFAS is conserved across different tissues, molecules and species. We identified and reported several genes exhibiting consistent and evolutionarily conserved transcriptional response to PFASs, such as ESR1, HADHA and ID1, as well as several pathways including lipid metabolism, immune response and hormone pathways. This study provides the first evidence that distinct PFAS molecules induce comparable transcriptional changes and affect the same metabolic processes across inter-species borders. Our findings have significant implications for understanding the impact of PFAS exposure on living organisms and the environment. We believe that this study offers a novel perspective on the molecular responses to PFAS exposure and provides a foundation for future research into developing strategies for mitigating the detrimental effects of these substances in the ecosystem.

A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo

Hazard evaluation of substances of "unknown or variable composition, complex reaction products and biological materials" (UVCBs) remains a major challenge in regulatory science because their chemical composition is difficult to ascertain. Petroleum substances are representative UVCBs and human cell-based data have been previously used to substantiate their groupings for regulatory submissions. We hypothesized that a combination of phenotypic and transcriptomic data could be integrated to make decisions as to selection of group-representative worst-case petroleum UVCBs for subsequent toxicity evaluation in vivo. We used data obtained from 141 substances from 16 manufacturing categories previously tested in 6 human cell types (induced pluripotent stem cell [iPSC]-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, and MCF7 and A375 cell lines). Benchmark doses for gene-substance combinations were calculated, and both transcriptomic and phenotype-derived points of departure (PODs) were obtained. Correlation analysis and machine learning were used to assess associations between phenotypic and transcriptional PODs and to determine the most informative cell types and assays, thus representing a cost-effective integrated testing strategy. We found that 2 cell types-iPSC-derived-hepatocytes and -cardiomyocytes-contributed the most informative and protective PODs and may be used to inform selection of representative petroleum UVCBs for further toxicity evaluation in vivo. Overall, although the use of new approach methodologies to prioritize UVCBs has not been widely adopted, our study proposes a tiered testing strategy based on iPSC-derived hepatocytes and cardiomyocytes to inform selection of representative worst-case petroleum UVCBs from each manufacturing category for further toxicity evaluation in vivo.

From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow

The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.

Determination of in vitro hepatotoxic potencies of a series of perfluoroalkyl substances (PFASs) based on gene expression changes in HepaRG liver cells

Per- and polyfluoroalkyl substances (PFASs) are omnipresent and have been shown to induce a wide range of adverse health effects, including hepatotoxicity, developmental toxicity, and immunotoxicity. The aim of the present work was to assess whether human HepaRG liver cells can be used to obtain insight into differences in hepatotoxic potencies of a series of PFASs. Therefore, the effects of 18 PFASs on cellular triglyceride accumulation (AdipoRed assay) and gene expression (DNA microarray for PFOS and RT-qPCR for all 18 PFASs) were studied in HepaRG cells. BMDExpress analysis of the PFOS microarray data indicated that various cellular processes were affected at the gene expression level. From these data, ten genes were selected to assess the concentration-effect relationship of all 18 PFASs using RT-qPCR analysis. The AdipoRed data and the RT-qPCR data were used for the derivation of in vitro relative potencies using PROAST analysis. In vitro relative potency factors (RPFs) could be obtained for 8 PFASs (including index chemical PFOA) based on the AdipoRed data, whereas for the selected genes, in vitro RPFs could be obtained for 11-18 PFASs (including index chemical PFOA). For the readout OAT5 expression, in vitro RPFs were obtained for all PFASs. In vitro RPFs were found to correlate in general well with each other (Spearman correlation) except for the PPAR target genes ANGPTL4 and PDK4. Comparison of in vitro RPFs with RPFs obtained from in vivo studies in rats indicate that best correlations (Spearman correlation) were obtained for in vitro RPFs based on OAT5 and CXCL10 expression changes and external in vivo RPFs. HFPO-TA was found to be the most potent PFAS tested, being around tenfold more potent than PFOA. Altogether, it may be concluded that the HepaRG model may provide relevant data to provide insight into which PFASs are relevant regarding their hepatotoxic effects and that it can be applied as a screening tool to prioritize other PFASs for further hazard and risk assessment.

Single-Walled vs. Multi-Walled Carbon Nanotubes: Influence of Physico-Chemical Properties on Toxicogenomics Responses in Mouse Lungs

Single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) are nanomaterials with one or multiple layers of carbon sheets. While it is suggested that various properties influence their toxicity, the specific mechanisms are not completely known. This study was aimed to determine if single or multi-walled structures and surface functionalization influence pulmonary toxicity and to identify the underlying mechanisms of toxicity. Female C57BL/6J BomTac mice were exposed to a single dose of 6, 18, or 54 μg/mouse of twelve SWCNTs or MWCNTs of different properties. Neutrophil influx and DNA damage were assessed on days 1 and 28 post-exposure. Genome microarrays and various bioinformatics and statistical methods were used to identify the biological processes, pathways and functions altered post-exposure to CNTs. All CNTs were ranked for their potency to induce transcriptional perturbation using benchmark dose modelling. All CNTs induced tissue inflammation. MWCNTs were more genotoxic than SWCNTs. Transcriptomics analysis showed similar responses across CNTs at the pathway level at the high dose, which included the perturbation of inflammatory, cellular stress, metabolism, and DNA damage responses. Of all CNTs, one pristine SWCNT was found to be the most potent and potentially fibrogenic, so it should be prioritized for further toxicity testing.

Considerations for application of benchmark dose modeling in radiation research: workshop highlights

BACKGROUND

Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples.

CONCLUSIONS

Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.

In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals

Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005-100 µM) for 48 h. TempO-Seq (BioSpyder Inc) was used to examine global transcriptomic changes and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify 2 global transcriptomic points of departure: (1) the lowest pathway median gene BMC and (2) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific transcriptomic point of departure was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and 8 alternative chemicals as ERα active. Global and ERα transcriptomic points of departure produced highly similar potency rankings with bisphenol AF as the most potent chemical tested, followed by BPA and bisphenol C. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA.

Identifying Human Specific Adverse Outcome Pathways of Per- and Polyfluoroalkyl Substances Using Liver-Chimeric Humanized Mice

Background

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants with myriad adverse effects. While perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are the most common contaminants, levels of replacement PFAS, such as perfluoro-2-methyl-3-oxahexanoic acid (GenX), are increasing. In rodents, PFOA, PFOS, and GenX have several adverse effects on the liver, including nonalcoholic fatty liver disease.

Objective

We aimed to determine human-relevant mechanisms of PFAS induced adverse hepatic effects using FRG liver-chimeric humanized mice with livers repopulated with functional human hepatocytes.

Methods

Male humanized mice were treated with 0.067 mg/L of PFOA, 0.145 mg/L of PFOS, or 1 mg/L of GenX in drinking water for 28 days. Liver and serum were collected for pathology and clinical chemistry, respectively. RNA-sequencing coupled with pathway analysis was used to determine molecular mechanisms.

Results

PFOS caused a significant decrease in total serum cholesterol and LDL/VLDL, whereas GenX caused a significant elevation in LDL/VLDL with no change in total cholesterol and HDL. PFOA had no significant changes in serum LDL/VLDL and total cholesterol. All three PFAS induced significant hepatocyte proliferation. RNA-sequencing with alignment to the human genome showed a total of 240, 162, and 619 differentially expressed genes after PFOA, PFOS, and GenX exposure, respectively. Upstream regulator analysis revealed inhibition of NR1D1, a transcriptional repressor important in circadian rhythm, as the major common molecular change in all PFAS treatments. PFAS treated mice had significant nuclear localization of NR1D1. In silico modeling showed PFOA, PFOS, and GenX potentially interact with the DNA-binding domain of NR1D1.

Discussion

These data implicate PFAS in circadian rhythm disruption via inhibition of NR1D1. These studies show that FRG humanized mice are a useful tool for studying the adverse outcome pathways of environmental pollutants on human hepatocytes in situ.

New approach methodologies: A quantitative in vitro to in vivo extrapolation case study with PFASs

PER: and polyfluoroalkyl substances (PFASs) have been associated with increased blood lipids in humans. Perfluorooctanoic acid (PFOA) has been also linked with elevated alanine transferase (ALT) serum levels in humans, and in rodents the liver is a main target organ for many PFASs. With the focus on New Approach Methodologies, the chronic oral equivalent effect doses were calculated for PFOA, PFNA (perfluorononanoic acid), PFHxS (perfluorohexanesulfonic acid) and PFOS (perfluorooctane sulfonic acid) based on in vitro effects measured in the HepaRG cell line. Selected in vitro readouts were considered biomarkers for lipid disturbances and hepatotoxicity. Concentration-response data obtained from HepaRG cells on triglyceride (TG) accumulation and expression changes of 12 selected genes (some involved in cholesterol homeostasis) were converted into corresponding human dose-response data, using physiologically based kinetic (PBK) model-facilitated reverse dosimetry. Next to this, the biokinetics of the chemicals were studied in the cell system. The current European dietary PFASs exposure overlaps with the calculated oral equivalent effect doses, indicating that the latter may lead to interference with hepatic gene expression and lipid metabolism. These findings illustrate an in vitro-in silico methodology, which can be applied for more PFASs, to select those that should be prioritized for further hazard characterization.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B₁, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B₁, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.

Advances in computational methods along the exposure to toxicological response paradigm

Human health risk assessment is a function of chemical toxicity, bioavailability to reach target biological tissues, and potential environmental exposure. These factors are complicated by many physiological, biochemical, physical and lifestyle factors. Furthermore, chemical health risk assessment is challenging in view of the large, and continually increasing, number of chemicals found in the environment. These challenges highlight the need to prioritize resources for the efficient and timely assessment of those environmental chemicals that pose greatest health risks. Computational methods, either predictive or investigative, are designed to assist in this prioritization in view of the lack of cost prohibitive in vivo experimental data. Computational methods provide specific and focused toxicity information using in vitro high throughput screening (HTS) assays. Information from the HTS assays can be converted to in vivo estimates of chemical levels in blood or target tissue, which in turn are converted to in vivo dose estimates that can be compared to exposure levels of the screened chemicals. This manuscript provides a review for the landscape of computational methods developed and used at the U.S. Environmental Protection Agency (EPA) highlighting their potentials and challenges.