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Barutcu AR, Black MB, Samuel R, Slattery S, McMullen PD, Nong A. Integrating gene expression and splicing dynamics across dose-response oxidative modulators. Front Genet 2024; 15:1389095. [PMID: 38846964 PMCID: PMC11155298 DOI: 10.3389/fgene.2024.1389095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/06/2024] [Indexed: 06/09/2024] Open
Abstract
Toxicological risk assessment increasingly utilizes transcriptomics to derive point of departure (POD) and modes of action (MOA) for chemicals. One essential biological process that allows a single gene to generate several different RNA isoforms is called alternative splicing. To comprehensively assess the role of splicing dysregulation in toxicological evaluation and elucidate its potential as a complementary endpoint, we performed RNA-seq on A549 cells treated with five oxidative stress modulators across a wide dose range. Differential gene expression (DGE) showed limited pathway enrichment except at high concentrations. However, alternative splicing analysis revealed variable intron retention events affecting diverse pathways for all chemicals in the absence of significant expression changes. For instance, diazinon elicited negligible gene expression changes but progressive increase in the number of intron retention events, suggesting splicing alterations precede expression responses. Benchmark dose modeling of intron retention data highlighted relevant pathways overlooked by expression analysis. Systematic integration of splicing datasets should be a useful addition to the toxicogenomic toolkit. Combining both modalities paint a more complete picture of transcriptomic dose-responses. Overall, evaluating intron retention dynamics afforded by toxicogenomics may provide biomarkers that can enhance chemical risk assessment and regulatory decision making. This work highlights splicing-aware toxicogenomics as a possible additional tool for examining cellular responses.
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2
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Costa E, Johnson KJ, Walker CA, O’Brien JM. Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches. Front Genet 2024; 15:1374791. [PMID: 38784034 PMCID: PMC11112360 DOI: 10.3389/fgene.2024.1374791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/02/2024] [Indexed: 05/25/2024] Open
Abstract
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.
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Affiliation(s)
| | | | | | - Jason M. O’Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, Canada
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Simon TW, Ryman J, Becker RA. Commentary: Value of information case study strongly supports use of the Threshold of Toxicological Concern (TTC). Regul Toxicol Pharmacol 2024; 149:105594. [PMID: 38555099 DOI: 10.1016/j.yrtph.2024.105594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 04/02/2024]
Abstract
A Value of Information (VOI) analysis can play a key role in decision-making for adopting new approach methodologies (NAMs). We applied EPA's recently developed VOI framework to the Threshold of Toxicological Concern (TTC). Obtaining/deriving a TTC value for use as a toxicity reference value (TRV) for substances with limited toxicity data was shown to provide equivalent or greater health protection, immense return on investment (ROI), greater net benefit, and substantially lower costs of delay (CoD) compared with TRVs derived from either traditional human health assessment (THHA) chronic toxicity testing in lab animals or the 5-day in vivo EPA Transcriptomic Assessment Product (ETAP). For all nine exposure scenarios examined, the TTC was more economical terms of CoD and ROI than the ETAP or the THHA; expected net benefit was similar for the TTC and ETAP with both of these more economical than the THHA The TTC ROI was immensely greater (5,000,000-fold on average) than the ROI for THHA and the ETAP ROI (100,000-fold on average). These results support the use of the TTC for substances within its domain of applicability to waive requiring certain in vivo tests, or at a minimum, as an initial screening step before conducting either the ETAP or THHA in vivo studies.
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Rattner BA, Bean TG, Beasley VR, Berny P, Eisenreich KM, Elliott JE, Eng ML, Fuchsman PC, King MD, Mateo R, Meyer CB, O'Brien JM, Salice CJ. Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2024; 20:725-748. [PMID: 37417421 DOI: 10.1002/ieam.4806] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/24/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023]
Abstract
Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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Affiliation(s)
- Barnett A Rattner
- US Geological Survey, Eastern Ecological Science Center, Laurel, Maryland, USA
| | | | - Val R Beasley
- College of Veterinary Medicine, University of Illinois at Urbana, Champaign, Illinois, USA
| | | | - Karen M Eisenreich
- US Environmental Protection Agency, Washington, District of Columbia, USA
| | - John E Elliott
- Environment and Climate Change Canada, Delta, British Columbia, Canada
| | - Margaret L Eng
- Environment and Climate Change Canada, Dartmouth, Nova Scotia, Canada
| | | | - Mason D King
- Simon Fraser University, Burnaby, British Columbia, Canada
| | | | | | - Jason M O'Brien
- Environment and Climate Change Canada, Ottawa, Ontario, Canada
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5
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Tran CM, Ra JS, Rhyu DY, Kim KT. Transcriptome analysis reveals differences in developmental neurotoxicity mechanism of methyl-, ethyl-, and propyl- parabens in zebrafish embryos. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 268:115704. [PMID: 37979356 DOI: 10.1016/j.ecoenv.2023.115704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/26/2023] [Accepted: 11/13/2023] [Indexed: 11/20/2023]
Abstract
Studies on the comparison of developmental (neuro) toxicity of parabens are currently limited, and unharmonized concentrations between phenotypic observations and transcriptome analysis hamper the understanding of their differential molecular mechanisms. Thus, developmental toxicity testing was conducted herein using the commonly used methyl- (MtP), ethyl- (EtP), and propyl-parabens (PrP) in zebrafish embryos. With a benchmark dose of 5%, embryonic-mortality-based point-of-departure (M-POD) values of the three parabens were determined, and changes in locomotor behavior were evaluated at concentrations of 0, M-POD/50, M-POD/10, and M-POD, where transcriptome analysis was conducted to explore the underlying neurotoxicity mechanism. Higher long-chained parabens were more toxic than short-chained parabens, as determined by the M-POD values of 154.1, 72.6, and 24.2 µM for MtP, EtP, and PrP, respectively. Meanwhile, exposure to EtP resulted in hyperactivity, whereas no behavioral effect was observed with MtP and PrP. Transcriptome analysis revealed that abnormal behaviors in the EtP-exposed group were associated with distinctly enriched pathways in signaling, transport, calcium ion binding, and metal binding. In contrast, exposure to MtP and PrP mainly disrupted membranes and transmembranes, which are closely linked to abnormal embryonic development rather than neurobehavioral changes. According to the changes in the expressions of signature mRNAs, tentative transcriptome-based POD values for each paraben were determined as MtP (2.68 µM), EtP (3.85 µM), and PrP (1.4 µM). This suggests that different molecular perturbations initiated at similar concentrations determined the extent and toxicity outcome differently. Our findings provide insight into better understanding the differential developmental neurotoxicity mechanisms of parabens.
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Affiliation(s)
- Cong Minh Tran
- Department of Energy and Environmental Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
| | - Jin-Sung Ra
- Eco-testing and Risk Assessment Center, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Republic of Korea
| | - Dong Young Rhyu
- Department of Biomedicine, Health & Life Convergence Sciences, BK21 FOUR, Mokpo National University, Jeonnam 58554, Republic of Korea
| | - Ki-Tae Kim
- Department of Energy and Environmental Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea; Department of Environmental Engineering, Seoul National University of Sciences and Technology, Seoul 01811, Republic of Korea.
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Beal MA, Everett LJ. Editorial: In vitro toxicogenomics (TGx) in hazard and risk assessment. FRONTIERS IN TOXICOLOGY 2023; 5:1284932. [PMID: 37736263 PMCID: PMC10509358 DOI: 10.3389/ftox.2023.1284932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 08/30/2023] [Indexed: 09/23/2023] Open
Affiliation(s)
- Marc A. Beal
- Bureau of Chemical Safety, Health Products and Food Branch, Health Canada, Ottawa, ON, Canada
| | - Logan J. Everett
- Biomolecular and Computational Toxicology Division, Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, United States
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7
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Ji C, Shao K. The Effect of Historical Data-Based Informative Prior on Benchmark Dose Estimation of Toxicogenomics. Chem Res Toxicol 2023; 36:1345-1354. [PMID: 37494567 PMCID: PMC10462436 DOI: 10.1021/acs.chemrestox.3c00088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
High-throughput toxicogenomics as an advanced toolbox of Tox21 plays an increasingly important role in facilitating the toxicity assessment of environmental chemicals. However, toxicogenomic dose-response analyses are typically challenged by limited data, which may result in significant uncertainties in parameter and benchmark dose (BMD) estimation. Integrating historical data via prior distribution using a Bayesian method is a useful but not-well-studied strategy. The objective of this study is to evaluate the effectiveness of informative priors in genomic dose-response modeling and BMD estimation. Specifically, we aim to identify plausible informative priors and evaluate their effects on BMD estimates at both gene and pathway levels. A general informative prior and eight time-specific (from 3 h to 29 d) informative priors for seven commonly used continuous dose-response models were derived. Results suggest that the derived informative priors are sensitive to the specific data sets used for elicitation. Real data-based simulations indicate that BMD estimation with the time-specific informative priors can achieve increased or equivalent accuracy, significantly decreased uncertainty, and a slightly enhanced correlation with the points of departure estimated from apical end points than the counterparts with noninformative priors. Overall, our study systematically examined the effects of historical data-based informative priors on BMD estimates, highlighting the benefits of plausible information priors in advancing the practice of toxicogenomics.
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Affiliation(s)
- Chao Ji
- Department of Environmental and Occupational Health, School of Public Health - Bloomington, Indiana University, Bloomington, Indiana 47405, United States
| | - Kan Shao
- Department of Environmental and Occupational Health, School of Public Health - Bloomington, Indiana University, Bloomington, Indiana 47405, United States
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8
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Tsai HHD, House JS, Wright FA, Chiu WA, Rusyn I. A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo. Toxicol Sci 2023; 193:219-233. [PMID: 37079747 PMCID: PMC10230285 DOI: 10.1093/toxsci/kfad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
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.
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Affiliation(s)
- Han-Hsuan Doris Tsai
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
| | - John S House
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA
| | - Fred A Wright
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Statistics and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, USA
- Department of Biological Sciences and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, USA
| | - Weihsueh A Chiu
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
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Reardon AJF, Farmahin R, Williams A, Meier MJ, Addicks GC, Yauk CL, Matteo G, Atlas E, Harrill J, Everett LJ, Shah I, Judson R, Ramaiahgari S, Ferguson SS, Barton-Maclaren TS. From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow. FRONTIERS IN TOXICOLOGY 2023; 5:1194895. [PMID: 37288009 PMCID: PMC10242042 DOI: 10.3389/ftox.2023.1194895] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/03/2023] [Indexed: 06/09/2023] Open
Abstract
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.
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Affiliation(s)
- Anthony J. F. Reardon
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Reza Farmahin
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Matthew J. Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Gregory C. Addicks
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Carole L. Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Geronimo Matteo
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, ON, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Logan J. Everett
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Imran Shah
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Richard Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Sreenivasa Ramaiahgari
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Stephen S. Ferguson
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Tara S. Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
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10
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Chauhan V, Yu J, Vuong N, Haber LT, Williams A, Auerbach SS, Beaton D, Wang Y, Stainforth R, Wilkins RC, Azzam EI, Richardson RB, Khan MGM, Jadhav A, Burtt JJ, Leblanc J, Randhawa K, Tollefsen KE, Yauk CL. Considerations for application of benchmark dose modeling in radiation research: workshop highlights. Int J Radiat Biol 2023; 99:1320-1331. [PMID: 36881459 DOI: 10.1080/09553002.2023.2181998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 01/18/2023] [Accepted: 02/06/2023] [Indexed: 02/24/2023]
Abstract
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.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Jihang Yu
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Ngoc Vuong
- Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Lynne T Haber
- Department of Environmental and Public Health Sciences, Risk Science Center, University of Cincinnati, Cincinnati, OH, USA
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Science and Research Bureau, Health Canada, Ottawa, Canada
| | - Scott S Auerbach
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Danielle Beaton
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Yi Wang
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Canada
| | | | - Ruth C Wilkins
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Edouard I Azzam
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Radiology, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Richard B Richardson
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Medical Physics Unit, McGill University, Montreal, QC, Canada
| | | | - Ashok Jadhav
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Julie J Burtt
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Julie Leblanc
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Kristi Randhawa
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian University of Life Sciences (NMBU), Ås, Norway
- Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
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11
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Hagiwara S, Paoli GM, Price PS, Gwinn MR, Guiseppi-Elie A, Farrell PJ, Hubbell BJ, Krewski D, Thomas RS. A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:498-515. [PMID: 35460101 PMCID: PMC10515440 DOI: 10.1111/risa.13931] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.
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Affiliation(s)
- Shintaro Hagiwara
- Risk Sciences International, Ottawa, Canada
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | | | - Paul S. Price
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Maureen R. Gwinn
- Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Annette Guiseppi-Elie
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Patrick J. Farrell
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | - Bryan J. Hubbell
- Air, Climate, and Energy Research Program, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Daniel Krewski
- Risk Sciences International, Ottawa, Canada
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
| | - Russell S. Thomas
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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12
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Morash MG, Kirzinger MW, Achenbach JC, Venkatachalam AB, Cooper JP, Ratzlaff DE, Woodland CLA, Ellis LD. The contribution of larval zebrafish transcriptomics to chemical risk assessment. Regul Toxicol Pharmacol 2023; 138:105336. [PMID: 36642323 DOI: 10.1016/j.yrtph.2023.105336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/15/2023]
Abstract
In Canada, the Canadian Environmental Protection Act (1999) requires human health and environmental risk assessments be conducted for new substances prior to their manufacture or import. While this toxicity data is historically obtained using rodents, in response to the international effort to eliminate animal testing, Health Canada is collaborating with the National Research Council (NRC) of Canada to develop a New Approach Method by refining existing NRC zebrafish models. The embryo/larval zebrafish model evaluates systemic (whole body) general toxicity which is currently unachievable with cell-based testing. The model is strengthened using behavioral, toxicokinetic and transcriptomic responses to assess non-visible indicators of toxicity following chemical exposure at sub-phenotypic concentrations. In this paper, the predictive power of zebrafish transcriptomics is demonstrated using two chemicals; Raloxifene and Resorcinol. Raloxifene exposure produced darkening of the liver and malformation of the nose/mandible, while Resorcinol exposure produced increased locomotor activity. Transcriptomic analysis correlated differentially expressed genes with the phenotypic effects and benchmark dose calculations determined that the transcriptomic Point of Departure (POD) occurred at subphenotypic concentrations. Correlating gene expression with apical (phenotypic) effects strengthens confidence in evaluation of chemical toxicity, thereby demonstrating the significant advancement that the larval zebrafish transcriptomics model represents in chemical risk assessment.
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Affiliation(s)
- Michael G Morash
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | - Morgan W Kirzinger
- Aquatic and Crop Resource Development, National Research Council of Canada, Saskatoon, SK S7N 0W9, Canada.
| | - J C Achenbach
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | - Ananda B Venkatachalam
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | | | - Deborah E Ratzlaff
- New Substances Assessment Control Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.
| | - Cindy L A Woodland
- New Substances Assessment Control Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.
| | - Lee D Ellis
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
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13
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Ewald JD, Basu N, Crump D, Boulanger E, Head J. Characterizing Variability and Uncertainty Associated with Transcriptomic Dose-Response Modeling. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:15960-15968. [PMID: 36268973 DOI: 10.1021/acs.est.2c04665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Transcriptomics dose-response analysis (TDRA) has emerged as a promising approach for integrating toxicogenomics data into a risk assessment context; however, variability and uncertainty associated with experimental design are not well understood. Here, we evaluated n = 55 RNA-seq profiles derived from Japanese quail liver tissue following exposure to chlorpyrifos (0, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, and 40 μg/g; n = 5 replicates per group) via egg injection. The full dataset was subsampled 637 times to generate smaller datasets with different dose ranges and spacing (designs A-E) and number of replicates (n = 2-5). TDRA of the 637 datasets revealed substantial variability in the gene and pathway benchmark doses, but relative stability in overall transcriptomic point-of-departure (tPOD) values when tPODs were calculated with the "pathway" and "mode" methods. Further, we found that tPOD values were more dependent on the dose range and spacing than on the number of replicates, suggesting that optimal experimental designs should use fewer replicates (n = 2 or 3) and more dose groups to reduce uncertainty in the results. Finally, tPOD values ranged by over ten times for all surveyed experimental designs and tPOD types, suggesting that tPODs should be interpreted as order-of-magnitude estimates.
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Affiliation(s)
- Jessica D Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa K1A 0H3, Canada
| | - Emily Boulanger
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Jessica Head
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
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14
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Carberry CK, Ferguson SS, Beltran AS, Fry RC, Rager JE. Using liver models generated from human-induced pluripotent stem cells (iPSCs) for evaluating chemical-induced modifications and disease across liver developmental stages. Toxicol In Vitro 2022; 83:105412. [PMID: 35688329 PMCID: PMC9296547 DOI: 10.1016/j.tiv.2022.105412] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 05/20/2022] [Accepted: 06/03/2022] [Indexed: 01/09/2023]
Abstract
The liver is a pivotal organ regulating critical developmental stages of fetal metabolism and detoxification. Though numerous studies have evaluated links between prenatal/perinatal exposures and adverse health outcomes in the developing fetus, the central role of liver to health disruptions resulting from these exposures remains understudied, especially concerning early development and later-in-life health outcomes. While numerous in vitro methods for evaluating liver toxicity have been established, the use of iPSC-derived hepatocytes appears to be particularly well suited to contribute to this critical research gap due to their potential to model a diverse range of disease phenotypes and different stages of liver development. The following key aspects are reviewed: (1) an introduction to developmental liver toxicity; (2) an introduction to embryonic and induced pluripotent stem cell models; (3) methods and challenges for deriving liver cells from stem cells; and (4) applications for iPSC-derived hepatocytes to evaluate liver developmental stages and their associated responses to insults. We conclude that iPSC-derived hepatocytes have great potential for informing liver toxicity and underlying disease mechanisms via the generation of patient-specific iPSCs; implementing large-scale drug and chemical screening; evaluating general biological responses as a potential surrogate target cell; and evaluating inter-individual disease susceptibility and response variability.
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Affiliation(s)
- Celeste K Carberry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephen S Ferguson
- Biomolecular Screening Branch, National Toxicology Program, Research Triangle Park, NC, USA
| | - Adriana S Beltran
- Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Curriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Julia E Rager
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Curriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
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15
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Stainforth R, Vuong N, Adam N, Kuo B, Wilkins RC, Yauk C, Beheshti A, Chauhan V. Benchmark dose modeling of transcriptional data: a systematic approach to identify best practices for study designs used in radiation research. Int J Radiat Biol 2022; 98:1832-1844. [PMID: 35939275 DOI: 10.1080/09553002.2022.2110300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
PURPOSE Benchmark dose (BMD) modeling is a method commonly used in chemical toxicology to identify the point of departure (POD) from a dose-response curve linked to a health-related outcome. Recently, it is being explored on transcriptional data and in adverse outcome pathways (AOPs). As AOPs are informed by diverse data types, it is important to understand the impact of study parameters such as dose selection, number of replicates and dose range on BMD outputs for radiation induced genes and pathways. MATERIALS AND METHODS Data were selected from the Gene Expression Omnibus (GSE52403) that featured gene expression profiles of peripheral blood samples from C57BL/6 mice 6 hours post-exposure to 137Cs gamma-radiation at 0, 1, 2, 3, 4.5, 6, 8 and 10.5 Gy. The dataset comprised a broad dose-range over multiple dose-points with consistent dose spacing and multiple biological replicates. This dataset was ideal for systematically transforming across three categories: (1) dose-range, (2) dose-spacing and (3) number of controls/replicates. Across these categories, 29 transformed datasets were compared to the original dataset to determine the impact of each transformation on the BMD outputs. RESULTS Most of the experimental changes did not impact the BMD outputs. The transformed datasets were largely consistent with the original dataset in terms of number of reproduced genes modeled and absolute BMD values for genes and pathways. Variations in dose selection identified the importance of the absolute value of the lowest and second dose. It was determined that dose selection should include at least two doses <1 Gy and two >5 Gy to achieve meaningful BMD outputs. Changes to the number of biological replicates in the control and non-zero dose groups impacted the overall accuracy and precision of the BMD outputs as well as the ability to fit dose-response models consistent with the original dataset. CONCLUSION Successful application of transcriptomic BMD modeling for radiation datasets requires considerations of the exposure dose and the number of biological replicates. Most important is the selection of the lowest doses and dose spacing. Reflections on these parameters in experimental design will provide meaningful BMD outputs that could correlate well to apical endpoints of relevance to radiation exposure assessment.
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Affiliation(s)
| | - Ngoc Vuong
- Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Nadine Adam
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Byron Kuo
- Exposure and Biomonitoring Division, Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch
| | - Ruth C Wilkins
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Carole Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Afshin Beheshti
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
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Roell K, Koval LE, Boyles R, Patlewicz G, Ring C, Rider CV, Ward-Caviness C, Reif DM, Jaspers I, Fry RC, Rager JE. Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research. FRONTIERS IN TOXICOLOGY 2022; 4:893924. [PMID: 35812168 PMCID: PMC9257219 DOI: 10.3389/ftox.2022.893924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 05/30/2022] [Indexed: 01/09/2023] Open
Abstract
Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health.
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Affiliation(s)
- Kyle Roell
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Lauren E. Koval
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rebecca Boyles
- Research Computing, RTI International, Durham, NC, United States
| | - Grace Patlewicz
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Caroline Ring
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Cynthia V. Rider
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Cavin Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC, United States
| | - David M. Reif
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Ilona Jaspers
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Curriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
- Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
- Department of Pediatrics, Microbiology and Immunology, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
| | - Rebecca C. Fry
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Curriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
| | - Julia E. Rager
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Curriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
- Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
- *Correspondence: Julia E. Rager,
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17
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Johnson KJ, Costa E, Marshall V, Sriram S, Venkatraman A, Stebbins K, LaRocca J. A microRNA or messenger RNA point of departure estimates an apical endpoint point of departure in a rat developmental toxicity model. Birth Defects Res 2022; 114:559-576. [PMID: 35596682 PMCID: PMC9324934 DOI: 10.1002/bdr2.2046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 11/10/2022]
Abstract
Traditional developmental toxicity testing practice examines fetal apical endpoints to identify a point of departure (POD) for risk assessment. A potential new testing paradigm involves deriving a POD from a comprehensive analysis of molecular-level change. Here, the rat ketoconazole endocrine-mediated developmental toxicity model was used to test the hypothesis that maternal epigenomic (miRNA) and transcriptomic (mRNA) PODs are similar to fetal apical endpoint PODs. Sprague-Dawley rats were exposed from gestation day (GD) 6-21 to 0, 0.063, 0.2, 0.63, 2, 6.3, 20, or 40 mg/kg/day ketoconazole. Dam systemic, liver, and placenta PODs, along with GD 21 fetal resorption, body weight, and skeletal apical PODs were derived using BMDS software. GD 21 dam liver and placenta miRNA and mRNA PODs were obtained using three methods: a novel individual molecule POD accumulation method, a first mode method, and a gene set method. Dam apical POD values ranged from 2.0 to 38.6 mg/kg/day; the lowest value was for placenta histopathology. Fetal apical POD values were 10.9-20.3 mg/kg/day; the lowest value was for fetal resorption. Dam liver miRNA and mRNA POD values were 0.34-0.69 mg/kg/day, and placenta miRNA and mRNA POD values were 2.53-6.83 mg/kg/day. Epigenomic and transcriptomic POD values were similar across liver and placenta. Deriving a molecular POD from dam liver or placenta was protective of a fetal apical POD. These data support the conclusion that a molecular POD can be used to estimate, or be protective of, a developmental toxicity apical POD.
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Affiliation(s)
| | | | - Valerie Marshall
- Labcorp Early Development Laboratories, Inc., Greenfield, Indiana, USA
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18
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Speen AM, Murray JR, Krantz QT, Davies D, Evansky P, Harrill JA, Everett LJ, Bundy JL, Dailey LA, Hill J, Zander W, Carlsten E, Monsees M, Zavala J, Higuchi MA. Benchmark Dose Modeling Approaches for Volatile Organic Chemicals using a Novel Air-Liquid Interface In Vitro Exposure System. Toxicol Sci 2022; 188:88-107. [PMID: 35426944 DOI: 10.1093/toxsci/kfac040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Inhalation is the most relevant route of volatile organic chemical (VOC) exposure; however, due to unique challenges posed by their chemical properties and poor solubility in aqueous solutions, in vitro chemical safety testing is predominantly performed using direct application dosing/submerged exposures. To address the difficulties in screening toxic effects of VOCs, our cell culture exposure system permits cells to be exposed to multiple concentrations at air-liquid interface (ALI) in a 24-well format. ALI exposure methods permit direct chemical-to-cell interaction with the test article at physiological conditions. In the present study, BEAS-2B and primary normal human bronchial epithelial cells (pHBEC) are used to assess gene expression, cytotoxicity, and cell viability responses to a variety of volatile chemicals including acrolein, formaldehyde, 1,3-butadiene, acetaldehyde, 1-bromopropane, carbon tetrachloride, dichloromethane, and trichloroethylene. BEAS-2B cells were exposed to all the test agents, while pHBECs were only exposed to the latter four listed above. The VOC concentrations tested elicited only slight cell viability changes in both cell types. Gene expression changes were analyzed using benchmark dose (BMD) modeling. The BMD for the most sensitive gene set was within one order of magnitude of the threshold-limit value reported by the American Conference of Governmental Industrial Hygienists, and the most sensitive gene sets impacted by exposure correlate to known adverse health effects recorded in epidemiologic and in vivo exposure studies. Overall, our study outlines a novel in vitro approach for evaluating molecular-based points-of-departure in human airway epithelial cell exposure to volatile chemicals.
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Affiliation(s)
- Adam M Speen
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee 37830, USA
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Jessica R Murray
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Quentin Todd Krantz
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - David Davies
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Paul Evansky
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Joshua A Harrill
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Logan J Everett
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Joseph L Bundy
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Lisa A Dailey
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Jazzlyn Hill
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Wyatt Zander
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Elise Carlsten
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Michael Monsees
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Jose Zavala
- MedTec BioLab Inc., Hillsborough, North Carolina 27278, USA
| | - Mark A Higuchi
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
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19
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Case study: Targeted RNA-sequencing of aged formalin-fixed paraffin-embedded samples for understanding chemical mode of action. Toxicol Rep 2022; 9:883-894. [DOI: 10.1016/j.toxrep.2022.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 11/19/2022] Open
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20
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Jin Y, Qi G, Shou Y, Li D, Liu Y, Guan H, Zhang Q, Chen S, Luo J, Xu L, Li C, Ma W, Chen N, Zheng Y, Yu D. High throughput data-based, toxicity pathway-oriented development of a quantitative adverse outcome pathway network linking AHR activation to lung damages. JOURNAL OF HAZARDOUS MATERIALS 2022; 425:128041. [PMID: 34906874 DOI: 10.1016/j.jhazmat.2021.128041] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 12/05/2021] [Accepted: 12/06/2021] [Indexed: 06/14/2023]
Abstract
The quantitative adverse outcome pathway (qAOP) is proposed to inform dose-responses at multiple biological levels for the purpose of toxicity prediction. So far, qAOP models concerning human health are scarce. Previously, we proposed 5 key molecular pathways that led aryl hydrogen receptor (AHR) activation to lung damages. The present study assembled an AOP network based on the gene expression signatures of these toxicity pathways, and validated the network using publicly available high throughput data combined with machine learning models. In addition, the AOP network was quantitatively evaluated with omics approaches and bioassays, using 16HBE-CYP1A1 cells exposed to benzo(a)pyrene (BaP), a prototypical AHR activator. Benchmark dose (BMD) analysis of transcriptomics revealed that AHR gene held the lowest BMD value, whereas AHR pathway held the lowest point of departure (PoD) compared to the other 4 pathways. Targeted bioassays were further performed to quantitatively understand the cellular responses, including ROS generation, DNA damage, interleukin-6 production, and extracellular matrix increase marked by collagen expression. Eventually, response-response relationships were plotted using nonlinear model fitting. The present study developed a highly reliable AOP model concerning human health, and validated as well as quantitatively evaluated it, and such a method is likely to be adoptable for risk assessment.
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Affiliation(s)
- Yuan Jin
- School of Public Health, Qingdao University, Qingdao, China
| | - Guangshuai Qi
- School of Public Health, Qingdao University, Qingdao, China
| | - Yingqing Shou
- School of Public Health, Qingdao University, Qingdao, China
| | - Daochuan Li
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yuzhen Liu
- School of Public Health, Qingdao University, Qingdao, China
| | - Heyuan Guan
- School of Public Health, Qingdao University, Qingdao, China
| | - Qianqian Zhang
- School of Public Health, Qingdao University, Qingdao, China
| | - Shen Chen
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jiao Luo
- School of Public Health, Qingdao University, Qingdao, China
| | - Lin Xu
- School of Public Health, Qingdao University, Qingdao, China
| | - Chuanhai Li
- School of Public Health, Qingdao University, Qingdao, China
| | - Wanli Ma
- School of Public Health, Qingdao University, Qingdao, China
| | - Ningning Chen
- School of Public Health, Qingdao University, Qingdao, China
| | - Yuxin Zheng
- School of Public Health, Qingdao University, Qingdao, China
| | - Dianke Yu
- School of Public Health, Qingdao University, Qingdao, China.
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21
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Ji C, Weissmann A, Shao K. A computational system for Bayesian benchmark dose estimation of genomic data in BBMD. ENVIRONMENT INTERNATIONAL 2022; 161:107135. [PMID: 35151117 PMCID: PMC8934139 DOI: 10.1016/j.envint.2022.107135] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/16/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Existing studies have revealed that the benchmark dose (BMD) estimates from short-term in vivo transcriptomics studies can approximate those from long-term guideline toxicity assessments. Existing software applications follow this trend by analyzing omics data through the maximum likelihood estimation and choosing the "best" model for BMD estimates. However, this practice ignores the model uncertainty and may result in over-confident inferences and predictions, leading to an inadequate decision. OBJECTIVE By generally following the National Toxicology Program Approach to Genomic Dose-Response Modeling, we developed a web-based dose-response modeling and BMD estimation system, Bayesian BMD (BBMD), for genomic data to quantitatively address uncertainty from various sources. The performances of BBMD are compared with BMDExpress. METHODS The system is primarily based on the previously developed BBMD system and further developed in a genomic perspective. Bayesian model averaging method is applied to BMD estimation and pathways analyses. Generally, the system is unique regarding the flexibility in preparing/storing data and in characterizing uncertainties. RESULTS This system was tested and validated versus 24 previously published in-vivo microarray dose-response datasets (GSE45892) and 64 molecules data from the Open TG-Gates database. Short term transcriptional BMD values for the median pathway in BBMD are highly correlated with the long-term apical BMD values (R = 0.78-0.91). The BMD estimates obtained by BBMD were compared to those by BMDExpress. The results indicate that BBMD provides more adequate results in terms of less extreme values and no failure in BMD and BMDL calculations. Also, the pathway analysis in BBMD provides a conservative estimate because a broader confidence interval is established. DISCUSSION Overall, this study demonstrates that dose-response modeling using genomic data can play a substantial role in support of chemical risk assessment. BBMD represents a robust and user-friendly alternative for genomic dose-response data analysis with outstanding functionalities to quantify uncertainty from various sources.
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Affiliation(s)
- Chao Ji
- Department of Environmental and Occupational Health, School of Public Health, Indiana University - Bloomington, Bloomington, IN 47405, USA
| | | | - Kan Shao
- Department of Environmental and Occupational Health, School of Public Health, Indiana University - Bloomington, Bloomington, IN 47405, USA.
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22
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Felter SP, Bhat VS, Botham PA, Bussard DA, Casey W, Hayes AW, Hilton GM, Magurany KA, Sauer UG, Ohanian EV. Assessing chemical carcinogenicity: hazard identification, classification, and risk assessment. Insight from a Toxicology Forum state-of-the-science workshop. Crit Rev Toxicol 2022; 51:653-694. [DOI: 10.1080/10408444.2021.2003295] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
| | | | | | - David A. Bussard
- U.S. Environmental Protection Agency, Office of the Science Advisor, Policy and Engagement, Washington, DC, USA
| | - Warren Casey
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - A. Wallace Hayes
- University of South Florida College of Public Health, Tampa, FL, USA
| | - Gina M. Hilton
- PETA Science Consortium International e.V., Stuttgart, Germany
| | | | | | - Edward V. Ohanian
- United States Environmental Protection Agency, Office of Water, Washington, DC, USA
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23
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Desforges JP, Legrand E, Boulager E, Liu P, Xia J, Butler H, Chandramouli B, Ewald J, Basu N, Hecker M, Head J, Crump D. Using Transcriptomics and Metabolomics to Understand Species Differences in Sensitivity to Chlorpyrifos in Japanese Quail and Double-Crested Cormorant Embryos. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:3019-3033. [PMID: 34293216 DOI: 10.1002/etc.5174] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 05/06/2021] [Accepted: 07/16/2021] [Indexed: 06/13/2023]
Abstract
Modern 21st-century toxicity testing makes use of omics technologies to address critical questions in toxicology and chemical management. Of interest are questions relating to chemical mechanisms of toxicity, differences in species sensitivity, and translation of molecular effects to observable apical endpoints. Our study addressed these questions by comparing apical outcomes and multiple omics responses in early-life stage exposure studies with Japanese quail (Coturnix japonica) and double-crested cormorant (Phalacrocorax auritus), representing a model and ecological species, respectively. Specifically, we investigated the dose-dependent response of apical outcomes as well as transcriptomics and metabolomics in the liver of each species exposed to chlorpyrifos, a widely used organophosphate pesticide. Our results revealed a clear pattern of dose-dependent disruption of gene expression and metabolic profiles in Japanese quail but not double-crested cormorant at similar chlorpyrifos exposure concentrations. The difference in sensitivity between species was likely due to higher metabolic transformation of chlorpyrifos in Japanese quail compared to double-crested cormorant. The most impacted biological pathways after chlorpyrifos exposure in Japanese quail included hepatic metabolism, oxidative stress, endocrine disruption (steroid and nonsteroid hormones), and metabolic disease (lipid and fatty acid metabolism). Importantly, we show consistent responses across biological scales, suggesting that significant disruption at the level of gene expression and metabolite profiles leads to observable apical responses at the organism level. Our study demonstrates the utility of evaluating effects at multiple biological levels of organization to understand how modern toxicity testing relates to outcomes of regulatory relevance, while also highlighting important, yet poorly understood, species differences in sensitivity to chemical exposure. Environ Toxicol Chem 2021;40:3019-3033. © 2021 SETAC.
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Affiliation(s)
- Jean-Pierre Desforges
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Elena Legrand
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Emily Boulager
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Peng Liu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | | | | | - Jessica Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Markus Hecker
- Toxicology Centre and School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Jessica Head
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, Environment Canada, National Wildlife Research Centre, Carleton University, Ottawa, Ontario, Canada
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24
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Buick JK, Williams A, Meier MJ, Swartz CD, Recio L, Gagné R, Ferguson SS, Engelward BP, Yauk CL. A Modern Genotoxicity Testing Paradigm: Integration of the High-Throughput CometChip® and the TGx-DDI Transcriptomic Biomarker in Human HepaRG™ Cell Cultures. Front Public Health 2021; 9:694834. [PMID: 34485225 PMCID: PMC8416458 DOI: 10.3389/fpubh.2021.694834] [Citation(s) in RCA: 147] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/14/2021] [Indexed: 12/14/2022] Open
Abstract
Higher-throughput, mode-of-action-based assays provide a valuable approach to expedite chemical evaluation for human health risk assessment. In this study, we combined the high-throughput alkaline DNA damage-sensing CometChip® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq®, as an integrated genotoxicity testing approach. We used metabolically competent differentiated human HepaRG™ cell cultures to enable the identification of chemicals that require bioactivation to cause genotoxicity. We studied 12 chemicals (nine DDI, three non-DDI) in increasing concentrations to measure and classify chemicals based on their ability to damage DNA. The CometChip® classified 10/12 test chemicals correctly, missing a positive DDI call for aflatoxin B1 and propyl gallate. The poor detection of aflatoxin B1 adducts is consistent with the insensitivity of the standard alkaline comet assay to bulky lesions (a shortcoming that can be overcome by trapping repair intermediates). The TGx-DDI biomarker accurately classified 10/12 agents. TGx-DDI correctly identified aflatoxin B1 as DDI, demonstrating efficacy for combined used of these complementary methodologies. Zidovudine, a known DDI chemical, was misclassified as it inhibits transcription, which prevents measurable changes in gene expression. Eugenol, a non-DDI chemical known to render misleading positive results at high concentrations, was classified as DDI at the highest concentration tested. When combined, the CometChip® assay and the TGx-DDI biomarker were 100% accurate in identifying chemicals that induce DNA damage. Quantitative benchmark concentration (BMC) modeling was applied to evaluate chemical potencies for both assays. The BMCs for the CometChip® assay and the TGx-DDI biomarker were highly concordant (within 4-fold) and resulted in identical potency rankings. These results demonstrate that these two assays can be integrated for efficient identification and potency ranking of DNA damaging agents in HepaRG™ cell cultures.
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Affiliation(s)
- Julie K Buick
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Matthew J Meier
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Carol D Swartz
- Integrated Laboratory Systems Inc. (ILS), Research Triangle Park, Durham, NC, United States
| | - Leslie Recio
- Integrated Laboratory Systems Inc. (ILS), Research Triangle Park, Durham, NC, United States
| | - Rémi Gagné
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Stephen S Ferguson
- National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC, United States
| | - Bevin P Engelward
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.,Department of Biology, University of Ottawa, Ottawa, ON, Canada
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25
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Lee F, Shah I, Soong YT, Xing J, Ng IC, Tasnim F, Yu H. Reproducibility and robustness of high-throughput S1500+ transcriptomics on primary rat hepatocytes for chemical-induced hepatotoxicity assessment. Curr Res Toxicol 2021; 2:282-295. [PMID: 34467220 PMCID: PMC8384775 DOI: 10.1016/j.crtox.2021.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 07/15/2021] [Accepted: 07/31/2021] [Indexed: 11/06/2022] Open
Abstract
TempO-Seq assays of rat hepatocytes in collagen sandwich are highly reproducible. Gene expression analysis shows S1500+ is representative of the whole transcriptome. Connectivity mapping shows consistency between TempO-Seq and Affymetrix data. Gene set enrichment shows consistency between S1500+ and the whole transcriptome. Gene set enrichment using hallmark gene sets informs hepatotoxicity.
Cell-based in vitro models coupled with high-throughput transcriptomics (HTTr) are increasingly utilized as alternative methods to animal-based toxicity testing. Here, using a panel of 14 chemicals with different risks of human drug-induced liver injury (DILI) and two dosing concentrations, we evaluated an HTTr platform comprised of collagen sandwich primary rat hepatocyte culture and the TempO-Seq surrogate S1500+ (ST) assay. First, the HTTr platform was found to exhibit high reproducibility between technical and biological replicates (r greater than 0.85). Connectivity mapping analysis further demonstrated a high level of inter-platform reproducibility between TempO-Seq data and Affymetrix GeneChip data from the Open TG-GATES project. Second, the TempO-Seq ST assay was shown to be a robust surrogate to the whole transcriptome (WT) assay in capturing chemical-induced changes in gene expression, as evident from correlation analysis, PCA and unsupervised hierarchical clustering. Gene set enrichment analysis (GSEA) using the Hallmark gene set collection also demonstrated consistency in enrichment scores between ST and WT assays. Lastly, unsupervised hierarchical clustering of hallmark enrichment scores broadly divided the samples into hepatotoxic, intermediate, and non-hepatotoxic groups. Xenobiotic metabolism, bile acid metabolism, apoptosis, p53 pathway, and coagulation were found to be the key hallmarks driving the clustering. Taken together, our results established the reproducibility and performance of collagen sandwich culture in combination with TempO-Seq S1500+ assay, and demonstrated the utility of GSEA using the hallmark gene set collection to identify potential hepatotoxicants for further validation.
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Affiliation(s)
- Fan Lee
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Imran Shah
- Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States
| | - Yun Ting Soong
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Jiangwa Xing
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Inn Chuan Ng
- Department of Physiology and Mechanobiology Institute, National University of Singapore, Singapore
| | - Farah Tasnim
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Hanry Yu
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore.,Department of Physiology and Mechanobiology Institute, National University of Singapore, Singapore.,Critical Analytics for Manufacturing Personalized-Medicine, Singapore-MIT Alliance for Research and Technology, Singapore
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26
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Benbrook C, Perry MJ, Belpoggi F, Landrigan PJ, Perro M, Mandrioli D, Antoniou MN, Winchester P, Mesnage R. Commentary: Novel strategies and new tools to curtail the health effects of pesticides. Environ Health 2021; 20:87. [PMID: 34340709 PMCID: PMC8330079 DOI: 10.1186/s12940-021-00773-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/18/2021] [Indexed: 05/02/2023]
Abstract
BACKGROUND Flaws in the science supporting pesticide risk assessment and regulation stand in the way of progress in mitigating the human health impacts of pesticides. Critical problems include the scope of regulatory testing protocols, the near-total focus on pure active ingredients rather than formulated products, lack of publicly accessible information on co-formulants, excessive reliance on industry-supported studies coupled with reticence to incorporate published results in the risk assessment process, and failure to take advantage of new scientific opportunities and advances, e.g. biomonitoring and "omics" technologies. RECOMMENDED ACTIONS Problems in pesticide risk assessment are identified and linked to study design, data, and methodological shortcomings. Steps and strategies are presented that have potential to deepen scientific knowledge of pesticide toxicity, exposures, and risks. We propose four solutions: (1) End near-sole reliance in regulatory decision-making on industry-supported studies by supporting and relying more heavily on independent science, especially for core toxicology studies. The cost of conducting core toxicology studies at labs not affiliated with or funded directly by pesticide registrants should be covered via fees paid by manufacturers to public agencies. (2) Regulators should place more weight on mechanistic data and low-dose studies within the range of contemporary exposures. (3) Regulators, public health agencies, and funders should increase the share of exposure-assessment resources that produce direct measures of concentrations in bodily fluids and tissues. Human biomonitoring is vital in order to quickly identify rising exposures among vulnerable populations including applicators, pregnant women, and children. (4) Scientific tools across disciplines can accelerate progress in risk assessments if integrated more effectively. New genetic and metabolomic markers of adverse health impacts and heritable epigenetic impacts are emerging and should be included more routinely in risk assessment to effectively prevent disease. CONCLUSIONS Preventing adverse public health outcomes triggered or made worse by exposure to pesticides will require changes in policy and risk assessment procedures, more science free of industry influence, and innovative strategies that blend traditional methods with new tools and mechanistic insights.
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Affiliation(s)
- Charles Benbrook
- Heartland Health Research Alliance, 10526 SE Vashon Vista Drive, Port Orchard, WA 98367 USA
| | - Melissa J. Perry
- Department of Environmental and Occupational Health, George Washington University, Washington, DC USA
| | | | - Philip J. Landrigan
- Schiller Institute for Integrated Science and Society, Boston College, Newton, MA 02467 USA
| | | | | | - Michael N. Antoniou
- Gene Expression and Therapy Group, Department of Medical and Molecular Genetics, King’s College London, Faculty of Life Sciences and Medicine, Guy’s Hospital, London, UK
| | - Paul Winchester
- School of Medicine, Department of Pediatrics, Indiana University, Indianapolis, IN USA
| | - Robin Mesnage
- Gene Expression and Therapy Group, Department of Medical and Molecular Genetics, King’s College London, Faculty of Life Sciences and Medicine, Guy’s Hospital, London, UK
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27
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Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, Beger RD, Bouhifd M, O'Brien J, Burgoon L, Caiment F, Carpi D, Chen T, Chorley BN, Colbourne J, Corvi R, Debrauwer L, O'Donovan C, Ebbels TMD, Ekman DR, Faulhammer F, Gribaldo L, Hilton GM, Jones SP, Kende A, Lawson TN, Leite SB, Leonards PEG, Luijten M, Martin A, Moussa L, Rudaz S, Schmitz O, Sobanski T, Strauss V, Vaccari M, Vijay V, Weber RJM, Williams AJ, Williams A, Thomas RS, Whelan M. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 2021; 125:105020. [PMID: 34333066 DOI: 10.1016/j.yrtph.2021.105020] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 12/12/2022]
Abstract
Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.
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Affiliation(s)
- Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States.
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom.
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, K1N 6N5, Canada.
| | - Magdalini Sachana
- Organisation for Economic Co-operation and Development (OECD), Environment Health and Safety Division, Paris, France
| | - Timothy W Gant
- Centre for Radiation, Chemical and Environmental Hazards (CRCE), Public Health England (PHE), Harwell Science Campus, Oxfordshire, United Kingdom
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Richard D Beger
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | | | - Jason O'Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, K1A 0H3, Canada
| | - Lyle Burgoon
- US Army Engineer Research and Development Center, 3909 Halls Ferry Rd, Vicksburg, MS, 39180, USA
| | - Florian Caiment
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229, ER, Maastricht, the Netherlands
| | - Donatella Carpi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Tao Chen
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | - Brian N Chorley
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - John Colbourne
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Raffaella Corvi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Laurent Debrauwer
- Toxalim (Research Centre in Food Toxicology), INRAE UMR 1331, ENVT, INP-Purpan, Paul Sabatier University (UPS), Toulouse, France; MetaToul-AXIOM Platform, MetaboHUB, National Infrastructure for Metabolomics and Fluxomics, Toulouse, France
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Timothy M D Ebbels
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, United Kingdom
| | - Drew R Ekman
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Athens, GA, 30605, United States
| | | | - Laura Gribaldo
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Gina M Hilton
- PETA Science Consortium International e.V., Friolzheimer Str. 3, 70499, Stuttgart, Germany
| | - Stephanie P Jones
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, K1A 0H3, Canada
| | - Aniko Kende
- Syngenta Jealott's Hill International Research Centre, Bracknell, RG42 6EY, United Kingdom
| | - Thomas N Lawson
- Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Sofia B Leite
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Pim E G Leonards
- Department of Environment and Health, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HV, Amsterdam, the Netherlands
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | | | - Laura Moussa
- US Food and Drug Administration, Center for Veterinary Medicine, Rockville, MD, United States
| | - Serge Rudaz
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland; Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland; Swiss Centre for Applied Human Toxicology (SCAHT), Switzerland
| | - Oliver Schmitz
- BASF Metabolome Solutions, Metabolome Data Science, Tegeler Weg 33, 10589, Berlin, Germany
| | | | - Volker Strauss
- BASF SE, Toxicology and Ecology, 67056, Ludwigshafen, Germany
| | - Monica Vaccari
- Center for Environmental Health and Prevention, Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Bologna, Italy
| | - Vikrant Vijay
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Antony J Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
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28
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Chappell GA, Heintz MM, Haws LC. Transcriptomic analyses of livers from mice exposed to 1,4-dioxane for up to 90 days to assess potential mode(s) of action underlying liver tumor development. Curr Res Toxicol 2021; 2:30-41. [PMID: 34345848 PMCID: PMC8320614 DOI: 10.1016/j.crtox.2021.01.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 01/06/2021] [Accepted: 01/07/2021] [Indexed: 12/11/2022] Open
Abstract
1,4-Dioxane is a volatile organic compound with industrial and commercial applications as a solvent and in the manufacture of other chemicals. 1,4-Dioxane has been demonstrated to induce liver tumors in chronic rodent bioassays conducted at very high doses. The available evidence for 1,4-dioxane-induced liver tumors in rodents aligns with a threshold-dependent mode of action (MOA), with the underlying mechanism being less clear in the mouse than in rats. To gain a better understanding of the underlying molecular mechanisms related to liver tumor development in mice orally exposed to 1,4-dioxane, transcriptomics analysis was conducted on liver tissue collected from a 90-day drinking water study in female B6D2F1/Crl mice (Lafranconi et al., 2020). Using tissue samples from female mice exposed to 1,4-dioxane in the drinking water at concentrations of 0, 40, 200, 600, 2,000 or 6,000 ppm for 7, 28, and 90 days, transcriptomic analyses demonstrate minimal treatment effects on global gene expression at concentrations below 600 ppm. At higher concentrations, genes involved in phase II metabolism and mitotic cell cycle checkpoints were significantly upregulated. There was an overall lack of enrichment of genes related to DNA damage response. The increase in mitotic signaling is most prevalent in the livers of mice exposed to 1,4-dioxane at the highest concentrations for 90 days. This finding aligns with phenotypic changes reported by Lafranconi et al. (2020) after 90-days of exposure to 6,000 ppm 1,4-dioxane in the same tissues. The transcriptomics analysis further supports overarching study findings demonstrating a non-mutagenic, threshold-based, mitogenic MOA for 1,4-dioxane-induced liver tumors.
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Affiliation(s)
- G A Chappell
- ToxStrategies, Inc., Asheville, NC, United States
| | - M M Heintz
- ToxStrategies, Inc., Asheville, NC, United States
| | - L C Haws
- ToxStrategies, Inc., Austin, TX, United States
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29
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Bianchi E, Costa E, Yan ZJ, Murphy L, Howell J, Anderson D, Mukerji P, Venkatraman A, Terry C, Johnson KJ. A rat subchronic study transcriptional point of departure estimates a carcinogenicity study apical point of departure. Food Chem Toxicol 2020; 147:111869. [PMID: 33217531 DOI: 10.1016/j.fct.2020.111869] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 10/28/2020] [Accepted: 11/12/2020] [Indexed: 11/16/2022]
Abstract
Considerations of human relevance and animal use are driving research to identify new approaches to inform risk assessment of chemicals and replace guideline-based rodent carcinogenicity tests. Here, the hypothesis was tested across four agrochemicals that 1) a rat 90-day transcriptome-based BEPOD is protective of a rat carcinogenicity study and 2) a subchronic liver or kidney BEPOD would approximate a cancer bioassay apical POD derived from other organs and a rat subchronic BEPOD would approximate a mouse cancer bioassay apical POD. Using RNA sequencing and BMDExpress software, liver and/or kidney BEPOD values were generated in male rats exposed for 90 days to either Triclopyr Acid, Pronamide, Sulfoxaflor, or Fenpicoxamid. BEPOD values were compared to benchmark dose-derived apical POD values generated from rat 90-day and rodent carcinogenicity studies. Across all four agrochemicals, findings showed that a rat 90-day study BEPOD approximated the most sensitive apical POD (within 10-fold) generated from the 90-day rat study and long-term rodent carcinogenicity studies. This study supports the conclusion that a subchronic transcriptome-based BEPOD could be utilized to estimate an apical POD within a risk-based approach of chronic toxicity and carcinogenicity agrochemical assessment, abrogating the need for time- and resource-intensive rodent carcinogenicity studies and minimizing animal testing.
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30
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Chauhan V, Adam N, Kuo B, Williams A, Yauk CL, Wilkins R, Stainforth R. Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment. Int J Radiat Biol 2020; 97:31-49. [PMID: 32687419 DOI: 10.1080/09553002.2020.1798543] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
PURPOSE Benchmark dose (BMD) modeling is used to determine the dose of a stressor at which a predefined increase in any biological effect above background occurs (e.g. 10% increase from control values). BMD analytical tools have the capacity to model transcriptional dose-response data to derive BMDs for genes, pathways and gene ontologies. We recently demonstrated the value of this approach to support various areas of radiation research using predominately 'in-house' generated datasets. MATERIALS AND METHODS As a continuation of this work, transcriptomic studies of relevance to ionizing radiation were retrieved through the Gene Expression Omnibus (GEO). The datasets were compiled and filtered, then analyzed using BMDExpress. The objective was to determine the reproducibility of BMD values in relation to pathways and genes across different exposure scenarios and compare to those derived using cytogenetic endpoints. A number of graphic visualization approaches were used to determine if BMD outputs could be correlated to parameters such as dose-rate, radiation quality and cell type. RESULTS Curated studies were diverse and derived from experiments with varied design and intent. Despite this, common genes and pathways were identified with low and high dose thresholds. The higher BMD values were associated with immune response and cell death, while transcripts with lower BMD values were generally related to the classic DNA damage response/repair processes, centered on TP53 signaling. Analysis of datasets with relatively similar dose-ranges under comparable experimental conditions showed a bi-modal distribution with a high degree of consistency in BMD values across shared genes and pathways, particularly for those below the 25th percentile of total distribution by dose. The median BMD values were noted to be approximately 0.5 Gy for genes/pathways that comprised mode 1. Furthermore, transcriptional BMD values derived from a subset of genes using in vivo and in vitro datasets were in accord to those using cytogenetic endpoints. CONCLUSION Overall, the results from this work highlight the value of the BMD methodology to derive meaningful outputs that are consistent across different models, provided the studies are conducted using a similar dose-range.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Nadine Adam
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Ruth Wilkins
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Robert Stainforth
- Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
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Johnson KJ, Auerbach SS, Costa E. A Rat Liver Transcriptomic Point of Departure Predicts a Prospective Liver or Non-liver Apical Point of Departure. Toxicol Sci 2020; 176:86-102. [PMID: 32384157 PMCID: PMC7357187 DOI: 10.1093/toxsci/kfaa062] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Identifying a toxicity point of departure (POD) is a required step in human health risk characterization of crop protection molecules, and this POD has historically been derived from apical endpoints across a battery of animal-based toxicology studies. Using rat transcriptome and apical data for 79 molecules obtained from Open TG-GATES (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) (632 datasets), the hypothesis was tested that a short-term exposure, transcriptome-based liver biological effect POD (BEPOD) could estimate a longer-term exposure "systemic" apical endpoint POD. Apical endpoints considered were body weight, clinical observation, kidney weight and histopathology and liver weight and histopathology. A BMDExpress algorithm using Gene Ontology Biological Process gene sets was optimized to derive a liver BEPOD most predictive of a systemic apical POD. Liver BEPODs were stable from 3 h to 29 days of exposure; the median fold difference of the 29-day BEPOD to BEPODs from earlier time points was approximately 1 (range: 0.7-1.1). Strong positive correlation (Pearson R = 0.86) and predictive accuracy (root mean square difference = 0.41) were observed between a concurrent (29 days) liver BEPOD and the systemic apical POD. Similar Pearson R and root mean square difference values were observed for comparisons between a 29-day systemic apical POD and liver BEPODs derived from 3 h to 15 days of exposure. These data across 79 molecules suggest that a longer-term exposure study apical POD from liver and non-liver compartments can be estimated using a liver BEPOD derived from an acute or subacute exposure study.
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Affiliation(s)
- Kamin J Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, Indiana
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina
| | - Eduardo Costa
- Data Science and Informatics, Corteva Agriscience, Mogi Mirim, Sao Paulo, Brazil
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