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Dent MP, Vaillancourt E, Thomas RS, Carmichael PL, Ouedraogo G, Kojima H, Barroso J, Ansell J, Barton-Maclaren TS, Bennekou SH, Boekelheide K, Ezendam J, Field J, Fitzpatrick S, Hatao M, Kreiling R, Lorencini M, Mahony C, Montemayor B, Mazaro-Costa R, Oliveira J, Rogiers V, Smegal D, Taalman R, Tokura Y, Verma R, Willett C, Yang C. Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients. Regul Toxicol Pharmacol 2021; 125:105026. [PMID: 34389358 PMCID: PMC8547713 DOI: 10.1016/j.yrtph.2021.105026] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 07/22/2021] [Accepted: 08/06/2021] [Indexed: 11/30/2022]
Abstract
Next generation risk assessment (NGRA) is an exposure-led, hypothesis-driven approach that has the potential to support animal-free safety decision-making. However, significant effort is needed to develop and test the in vitro and in silico (computational) approaches that underpin NGRA to enable confident application in a regulatory context. A workshop was held in Montreal in 2019 to discuss where effort needs to be focussed and to agree on the steps needed to ensure safety decisions made on cosmetic ingredients are robust and protective. Workshop participants explored whether NGRA for cosmetic ingredients can be protective of human health, and reviewed examples of NGRA for cosmetic ingredients. From the limited examples available, it is clear that NGRA is still in its infancy, and further case studies are needed to determine whether safety decisions are sufficiently protective and not overly conservative. Seven areas were identified to help progress application of NGRA, including further investments in case studies that elaborate on scenarios frequently encountered by industry and regulators, including those where a ‘high risk’ conclusion would be expected. These will provide confidence that the tools and approaches can reliably discern differing levels of risk. Furthermore, frameworks to guide performance and reporting should be developed.
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Affiliation(s)
- M P Dent
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - E Vaillancourt
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - R S Thomas
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research, Triangle Park, NC, 27711, USA.
| | - P L Carmichael
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - G Ouedraogo
- l'Oréal, Research and Development, Paris, France.
| | - H Kojima
- National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, 158-8501, Tokyo, Japan.
| | - J Barroso
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy.
| | - J Ansell
- US Personal Care Products Council (PCPC), 1620 L St. NW, Suite 1200, Washington, D.C, 20036, USA.
| | - T S Barton-Maclaren
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - S H Bennekou
- National Food Institute, Technical University of Denmark (DTU), Copenhagen, Denmark.
| | - K Boekelheide
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
| | - J Ezendam
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
| | - J Field
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - S Fitzpatrick
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - M Hatao
- Japan Cosmetic Industry Association (JCIA), Metro City Kamiyacho 6F, 5-1-5, Toranomon, Minato-ku, Tokyo, 105-0001 Japan.
| | - R Kreiling
- Clariant Produkte (Deutschland) GmbH, Am Unisyspark 1, 65843, Sulzbach, Germany.
| | - M Lorencini
- Grupo Boticário, Research & Development, São José dos Pinhais, Brazil.
| | - C Mahony
- Procter & Gamble Technical Centres Ltd, Reading, RG2 0RX, UK.
| | - B Montemayor
- Cosmetics Alliance Canada, 420 Britannia Road East Suite 102, Mississauga, ON L4Z 3L5, Canada.
| | - R Mazaro-Costa
- Departament of Pharmacology, Universidade Federal de Goiás, Goiânia, GO, 74.690-900, Brazil.
| | - J Oliveira
- Brazilian Health Regulatory Agency (ANVISA), Gerência de Produtos de Higiene, Perfumes, Cosméticos e Saneantes, Setor de Indústria e Abastecimento (SIA), Trecho 5, Área Especial 57, CEP 71205-050, Brasília, DF, Brazil.
| | - V Rogiers
- Vrije Universiteit Brussel, Brussels, Belgium.
| | - D Smegal
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - R Taalman
- Cosmetics Europe, Avenue Herrmann-Debroux 40, 1160 Auderghem, Belgium.
| | - Y Tokura
- Allergic Disease Research Center, Chutoen General Medical Center, Kakegawa, Japan.
| | - R Verma
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - C Willett
- Humane Society International, Washington, DC, USA.
| | - C Yang
- Taiwan Cosmetic Industry Association (TWCIA), 8F No. 136, Bo'ai Rd., Zhongzheng Dist., Taipei City, 100, Taiwan, ROC.
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52
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Alcaraz AJG, Mikulášek K, Potěšil D, Park B, Shekh K, Ewald J, Burbridge C, Zdráhal Z, Schneider D, Xia J, Crump D, Basu N, Hecker M. Assessing the Toxicity of 17α-Ethinylestradiol in Rainbow Trout Using a 4-Day Transcriptomics Benchmark Dose (BMD) Embryo Assay. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:10608-10618. [PMID: 34292719 DOI: 10.1021/acs.est.1c02401] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
There is an urgent demand for more efficient and ethical approaches in ecological risk assessment. Using 17α-ethinylestradiol (EE2) as a model compound, this study established an embryo benchmark dose (BMD) assay for rainbow trout (RBT; Oncorhynchus mykiss) to derive transcriptomic points-of-departure (tPODs) as an alternative to live-animal tests. Embryos were exposed to graded concentrations of EE2 (measured: 0, 1.13, 1.57, 6.22, 16.3, 55.1, and 169 ng/L) from hatch to 4 and up to 60 days post-hatch (dph) to assess molecular and apical responses, respectively. Whole proteome analyses of alevins did not show clear estrogenic effects. In contrast, transcriptomics revealed responses that were in agreement with apical effects, including excessive accumulation of intravascular and hepatic proteinaceous fluid and significant increases in mortality at 55.1 and 169 ng/L EE2 at later time points. Transcriptomic BMD analysis estimated the median of the 20th lowest geneBMD to be 0.18 ng/L, the most sensitive tPOD. Other estimates (0.78, 3.64, and 1.63 ng/L for the 10th percentile geneBMD, first peak geneBMD distribution, and median geneBMD of the most sensitive over-represented pathway, respectively) were within the same order of magnitude as empirically derived apical PODs for EE2 in the literature. This 4-day alternative RBT embryonic assay was effective in deriving tPODs that are protective of chronic effects of EE2.
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Affiliation(s)
- Alper James G Alcaraz
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Kamil Mikulášek
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - David Potěšil
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - Bradley Park
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Kamran Shekh
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Jessica Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Connor Burbridge
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 0W9
| | - Zbyněk Zdráhal
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - David Schneider
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 0W9
- School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5C8
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Doug Crump
- Environment and Climate Change Canada, National Wildlife Research Centre, Ottawa, Ontario, Canada K1A 0H3
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Markus Hecker
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
- School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5C8
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53
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Ewald J, Soufan O, Xia J, Basu N. FastBMD: an online tool for rapid benchmark dose-response analysis of transcriptomics data. Bioinformatics 2021; 37:1035-1036. [PMID: 32761065 PMCID: PMC8128449 DOI: 10.1093/bioinformatics/btaa700] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 07/07/2020] [Accepted: 07/28/2020] [Indexed: 12/13/2022] Open
Abstract
MOTIVATION Transcriptomics dose-response analysis is a promising new approach method for toxicity testing. While international regulatory agencies have spent substantial effort establishing a standardized statistical approach, existing software that follows this approach is computationally inefficient and must be locally installed. RESULTS FastBMD is a web-based tool that implements standardized methods for transcriptomics benchmark dose-response analysis in R. It is >60 times faster than the current leading software, supports transcriptomics data from 13 species, and offers a comprehensive analytical pipeline that goes from processing and normalization of raw gene expression values to interactive exploration of pathway-level benchmark dose results. AVAILABILITY AND IMPLEMENTATION FastBMD is freely available at www.fastbmd.ca. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jessica Ewald
- Department of Natural Resource Sciences, McGill University, Montreal, QC H9X 3V9, Canada
| | - Othman Soufan
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
| | - Niladri Basu
- Department of Natural Resource Sciences, McGill University, Montreal, QC H9X 3V9, Canada
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Crizer DM, Ramaiahgari SC, Ferguson SS, Rice JR, Dunlap PE, Sipes NS, Auerbach SS, Merrick BA, DeVito MJ. Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models. Toxicol Sci 2021; 181:175-186. [PMID: 33749773 PMCID: PMC8163038 DOI: 10.1093/toxsci/kfab036] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Interpretation of untargeted metabolomics data from both in vivo and physiologically relevant in vitro model systems continues to be a significant challenge for toxicology research. Potency-based modeling of toxicological responses has served as a pillar of interpretive context and translation of testing data. In this study, we leverage the resolving power of concentration-response modeling through benchmark concentration (BMC) analysis to interpret untargeted metabolomics data from differentiated cultures of HepaRG cells exposed to a panel of reference compounds and integrate data in a potency-aligned framework with matched transcriptomic data. For this work, we characterized biological responses to classical human liver injury compounds and comparator compounds, known to not cause liver injury in humans, at 10 exposure concentrations in spent culture media by untargeted liquid chromatography-mass spectrometry analysis. The analyte features observed (with limited metabolites identified) were analyzed using BMC modeling to derive compound-induced points of departure. The results revealed liver injury compounds produced concentration-related increases in metabolomic response compared to those rarely associated with liver injury (ie, sucrose, potassium chloride). Moreover, the distributions of altered metabolomic features were largely comparable with those observed using high throughput transcriptomics, which were further extended to investigate the potential for in vitro observed biological responses to be observed in humans with exposures at therapeutic doses. These results demonstrate the utility of BMC modeling of untargeted metabolomics data as a sensitive and quantitative indicator of human liver injury potential.
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Affiliation(s)
- David M Crizer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Sreenivasa C Ramaiahgari
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Stephen S Ferguson
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Julie R Rice
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Paul E Dunlap
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Nisha S Sipes
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Bruce Alex Merrick
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Michael J DeVito
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
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55
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Ring C, Sipes NS, Hsieh JH, Carberry C, Koval LE, Klaren WD, Harris MA, Auerbach SS, Rager JE. Predictive modeling of biological responses in the rat liver using in vitro Tox21 bioactivity: Benefits from high-throughput toxicokinetics. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2021; 18:100166. [PMID: 34013136 PMCID: PMC8130852 DOI: 10.1016/j.comtox.2021.100166] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Computational methods are needed to more efficiently leverage data from in vitro cell-based models to predict what occurs within whole body systems after chemical insults. This study set out to test the hypothesis that in vitro high-throughput screening (HTS) data can more effectively predict in vivo biological responses when chemical disposition and toxicokinetic (TK) modeling are employed. In vitro HTS data from the Tox21 consortium were analyzed in concert with chemical disposition modeling to derive nominal, aqueous, and intracellular estimates of concentrations eliciting 50% maximal activity. In vivo biological responses were captured using rat liver transcriptomic data from the DrugMatrix and TG-Gates databases and evaluated for pathway enrichment. In vivo dosing data were translated to equivalent body concentrations using HTTK modeling. Random forest models were then trained and tested to predict in vivo pathway-level activity across 221 chemicals using in vitro bioactivity data and physicochemical properties as predictor variables, incorporating methods to address imbalanced training data resulting from high instances of inactivity. Model performance was quantified using the area under the receiver operator characteristic curve (AUC-ROC) and compared across pathways for different combinations of predictor variables. All models that included toxicokinetics were found to outperform those that excluded toxicokinetics. Biological interpretation of the model features revealed that rather than a direct mapping of in vitro assays to in vivo pathways, unexpected combinations of multiple in vitro assays predicted in vivo pathway-level activities. To demonstrate the utility of these findings, the highest-performing model was leveraged to make new predictions of in vivo biological responses across all biological pathways for remaining chemicals tested in Tox21 with adequate data coverage (n = 6617). These results demonstrate that, when chemical disposition and toxicokinetics are carefully considered, in vitro HT screening data can be used to effectively predict in vivo biological responses to chemicals.
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Affiliation(s)
- Caroline Ring
- ToxStrategies, Inc., Austin, TX 78751, United States
| | - Nisha S. Sipes
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Durham, NC 27709, United States
| | - Celeste Carberry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Lauren E. Koval
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - William D. Klaren
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77840, United States
| | | | - Scott S. Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States
| | - 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 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- Curriculum in Toxicology and Environmental Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
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56
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Harrill JA, Everett LJ, Haggard DE, Sheffield T, Bundy JL, Willis CM, Thomas RS, Shah I, Judson RS. High-Throughput Transcriptomics Platform for Screening Environmental Chemicals. Toxicol Sci 2021; 181:68-89. [PMID: 33538836 DOI: 10.1093/toxsci/kfab009] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
New approach methodologies (NAMs) that efficiently provide information about chemical hazard without using whole animals are needed to accelerate the pace of chemical risk assessments. Technological advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chemicals. In this study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chemicals in the human-derived MCF7 cell model. Our experimental design included a variety of reference samples and reference chemical treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate analysis of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response analysis of transcriptomics data using BMDExpress. Analysis of reference samples and reference chemical treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biological pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening assays. Often these identified signatures were associated with the known molecular target of the chemicals in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high-throughput hazard evaluation of environmental chemicals.
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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, North Carolina 27709, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Thomas Sheffield
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Joseph L Bundy
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Clinton M Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
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Zhan J, Wang S, Li F, Ji C, Wu H. Global characterization of dose-dependent effects of cadmium in clam Ruditapes philippinarum. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 273:116443. [PMID: 33486241 DOI: 10.1016/j.envpol.2021.116443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 12/20/2020] [Accepted: 12/28/2020] [Indexed: 06/12/2023]
Abstract
Cadmium (Cd) is being frequently detected in marine organisms. However, dose-dependent effects of Cd challenged unraveling the toxicological mechanisms of Cd to marine organisms and developing biomarkers. Here, the dose-dependent effects of Cd on clams Ruditapes philippinarum following exposure to 5 doses of Cd (3, 9, 27, 81, 243 μg/L) were investigated using benchmark dose (BMD) method. By model fitting, calculation of BMD values was performed on transcriptomic profiles, metals concentrations, and antioxidant indices. Cd exposure induced not only significant Cd accumulation in clams, but also marked alterations of essential metals such as Ca, Cu, Zn, Mn, and Fe. Gene regulation posed little influence on essential metal homeostasis, indicated by poor enrichment of differentially expressed genes (DEGs) associated with metal binding and metal transport in lower concentrations of Cd-treated groups. BMD analysis on biological processes and pathways showed that peptide cross-linking was the most sensitive biological process to Cd exposure, followed by focal adhesion, ubiquitin mediated proteolysis, and apoptosis. Occurrence of apoptosis was also confirmed by TUENL-positive staining in gills and hepatopancreas of clams treated with Cd. Furthermore, many DEGs, such as transglutaminases (TGs), metallothionein (MT), STEAP2-like and laccase, which presented linear or monotonic curves and relatively low BMD values, were potentially preferable biomarkers in clams to Cd. Overall, BMD analysis on transcriptomic profiles, metals concentrations and biochemical endpoints unraveled the sensitiveness of key events in response to Cd treatments, which provided new insights in exploring the toxicological mechanisms of Cd in clams as well as biomarker selection.
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Affiliation(s)
- Junfei Zhan
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, 264003, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China
| | - Shuang Wang
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, 264003, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China
| | - Fei Li
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, 264003, PR China; Center for Ocean Mega-Science, Chinese Academy of Sciences (CAS), Qingdao, 266071, PR China
| | - Chenglong Ji
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, 264003, PR China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, PR China; Center for Ocean Mega-Science, Chinese Academy of Sciences (CAS), Qingdao, 266071, PR China
| | - Huifeng Wu
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, 264003, PR China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, PR China; Center for Ocean Mega-Science, Chinese Academy of Sciences (CAS), Qingdao, 266071, PR China.
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58
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Chang Y, Huynh CTT, Bastin KM, Rivera BN, Siddens LK, Tilton SC. Classifying polycyclic aromatic hydrocarbons by carcinogenic potency using in vitro biosignatures. Toxicol In Vitro 2020; 69:104991. [PMID: 32890658 PMCID: PMC7572825 DOI: 10.1016/j.tiv.2020.104991] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/15/2020] [Accepted: 08/29/2020] [Indexed: 01/26/2023]
Abstract
One of the most difficult challenges for risk assessment is evaluation of chemicals that predominately co-occur in mixtures like polycyclic aromatic hydrocarbons (PAHs). We previously developed a classification model in which systems biology data collected from mice short-term after chemical exposure accurately predict tumor outcome. The present study demonstrates translation of this approach into a human in vitro model in which chemical-specific bioactivity profiles from 3D human bronchial epithelial cells (HBEC) classify PAHs by carcinogenic potency. Gene expression profiles were analyzed from HBEC exposed to carcinogenic and non-carcinogenic PAHs and classification accuracies were identified for individual pathway-based gene sets. Posterior probabilities of best performing gene sets were combined via Bayesian integration resulting in a classifier with four gene sets, including aryl hydrocarbon receptor signaling, regulation of epithelial mesenchymal transition, regulation of angiogenesis, and cell cycle G2-M. In addition, transcriptional benchmark dose modeling of benzo[a]pyrene (BAP) showed that the most sensitive gene sets to BAP regulation were largely dissimilar from those that best classified PAH carcinogenicity challenging current assumptions that BAP carcinogenicity (and subsequent mode of action) is reflective of overall PAH carcinogenicity. These results illustrate utility of using systems toxicology approaches to analyze global gene expression towards carcinogenic hazard assessment.
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Affiliation(s)
- Yvonne Chang
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA
| | - Celine Thanh Thu Huynh
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA
| | - Kelley M Bastin
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA
| | - Brianna N Rivera
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA
| | - Lisbeth K Siddens
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA; Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Susan C Tilton
- Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA; Superfund Research Program, Oregon State University, Corvallis, OR, USA.
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Martínez R, Codina AE, Barata C, Tauler R, Piña B, Navarro-Martín L. Transcriptomic effects of tributyltin (TBT) in zebrafish eleutheroembryos. A functional benchmark dose analysis. JOURNAL OF HAZARDOUS MATERIALS 2020; 398:122881. [PMID: 32474318 DOI: 10.1016/j.jhazmat.2020.122881] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/03/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
Exposure to the antifouling tributyltin (TBT) has been related to imposex in mollusks and to obesogenicity, adipogenesis and masculinization in fish. To understand the underlying molecular mechanisms, we evaluated dose-response effects of TBT (1.7-56 nM) in zebrafish eleutheroembryos transcriptome exposed from 2 to 5 days post-fertilization. RNA-sequencing analysis identified 3238 differentially expressed transcripts in eleutheroembryos exposed to TBT. Benchmark dose analyses (BMD) showed that the point of departure (PoD) for transcriptomic effects (9.28 nM) was similar to the metabolomic PoD (11.5 nM) and about one order of magnitude lower than the morphometric PoD (67.9 nM) or the median lethal concentration (LC50: 93.6 nM). Functional analysis of BMD transcriptomic data identified steroid metabolism and cholesterol and vitamin D3 biosynthesis as the most sensitive pathways to TBT (<50% PoD). Conversely, transcripts related to general stress and DNA damage became affected only at doses above the PoD. Therefore, our results indicate that transcriptomes can act as early molecular indicators of pollutant exposure, and illustrates their usefulness for the mechanistic identification of the initial toxic events. As the estimated molecular PoDs are close to environmental levels, we concluded that TBT may represent a substantial risk in some natural environments.
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Affiliation(s)
- Rubén Martínez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain; Universitat de Barcelona (UB), Barcelona, Catalunya 08007, Spain.
| | - Anna E Codina
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain; Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.
| | - Carlos Barata
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Romà Tauler
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Benjamin Piña
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Laia Navarro-Martín
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
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Korchevskiy A. Using benchmark dose modeling for the quantitative risk assessment: Carbon nanotubes, asbestos, glyphosate. J Appl Toxicol 2020; 41:148-160. [PMID: 33040390 DOI: 10.1002/jat.4063] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/20/2020] [Accepted: 08/20/2020] [Indexed: 11/12/2022]
Abstract
Benchmark dose method is one of the most famous quantitative approaches available for toxicological risks prediction. However, it is not fully clear how occupational health professionals can use it for specific workplace scenarios requiring carcinogen risk assessment. The paper explores the hypothesis that benchmark dose method allows to effectively approximate dose-response data on carcinogenic response, providing reasonable estimations of risks in the situations when a choice between more complex models is not warranted for practical purposes. Three case studies were analyzed for the agents with different levels of scientific confidence in human carcinogenicity: carbon nanotubes, amosite asbestos, and glyphosate. For each agent, a critical study was determined, and a dose-response slope factor was quantified, based on the weighted average lower bound benchmark dose. The linear slope factors of 0.111 lifetime excess cases of lung carcinoma per mg/m3 of MWCNT-7 (in rats exposure equivalent), 0.009 cases of mesothelioma per f/cc-years of cumulative exposure to amosite asbestos, and 0.000094 cases of malignant lymphoma per mg/kg/day of glyphosate (in mice equivalent) were determined. The correlations between the proposed linear predictive models and observed data points were R = 0.96 (R2 = 0.92) for carbon nanotubes, R = 0.97 (R2 = 0.95) for amosite asbestos, and R = 0.89 (R2 = 0.79) for glyphosate. In all three cases, the linear extrapolation yielded comparable level of risk estimations with the "best fit" nonlinear model; for nanoparticles and amosite asbestos, linear estimations were more conservative. By performing a simulation study, it was demonstrated that a weighted average benchmark dose expressed the highest correlation with multistage and quantal-linear models.
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Pain G, Hickey G, Mondou M, Crump D, Hecker M, Basu N, Maguire S. Drivers of and Obstacles to the Adoption of Toxicogenomics for Chemical Risk Assessment: Insights from Social Science Perspectives. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:105002. [PMID: 33112659 PMCID: PMC7592882 DOI: 10.1289/ehp6500] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND Some 20 y ago, scientific and regulatory communities identified the potential of omics sciences (genomics, transcriptomics, proteomics, metabolomics) to improve chemical risk assessment through development of toxicogenomics. Recognizing that regulators adopt new scientific methods cautiously given accountability to diverse stakeholders, the scope and pace of adoption of toxicogenomics tools and data have nonetheless not met the ambitious, early expectations of omics proponents. OBJECTIVE Our objective was, therefore, to inventory, investigate, and derive insights into drivers of and obstacles to adoption of toxicogenomics in chemical risk assessment. By invoking established social science frameworks conceptualizing innovation adoption, we also aimed to develop recommendations for proponents of toxicogenomics and other new approach methodologies (NAMs). METHODS We report findings from an analysis of 56 scientific and regulatory publications from 1998 through 2017 that address the adoption of toxicogenomics for chemical risk assessment. From this purposeful sample of toxicogenomics discourse, we identified major categories of drivers of and obstacles to adoption of toxicogenomics tools and data sets. We then mapped these categories onto social science frameworks for conceptualizing innovation adoption to generate actionable insights for proponents of toxicogenomics. DISCUSSION We identify the most salient drivers and obstacles. From 1998 through 2017, adoption of toxicogenomics was understood to be helped by drivers such as those we labeled Superior scientific understanding, New applications, and Reduced cost & increased efficiency but hindered by obstacles such as those we labeled Insufficient validation, Complexity of interpretation, and Lack of standardization. Leveraging social science frameworks, we find that arguments for adoption that draw on the most salient drivers, which emphasize superior and novel functionality of omics as rationales, overlook potential adopters' key concerns: simplicity of use and compatibility with existing practices. We also identify two perspectives-innovation-centric and adopter-centric-on omics adoption and explain how overreliance on the former may be undermining efforts to promote toxicogenomics. https://doi.org/10.1289/EHP6500.
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Affiliation(s)
- Guillaume Pain
- Faculté des sciences de l’administration, Université Laval, Sainte-Foy, Québec, Canada
| | - Gordon Hickey
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte Anne de Bellevue, Quebec, Canada
| | - Matthieu Mondou
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte Anne de Bellevue, Quebec, Canada
| | - Doug Crump
- National Wildlife Research Center, Environment and Climate Change Canada, Ottawa, Ontario, Canada
| | - Markus Hecker
- Toxicology Center and School of the Environment & Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte Anne de Bellevue, Quebec, Canada
| | - Steven Maguire
- University of Sydney Business School and University of Sydney Nano Institute, Sydney, New South Wales, Australia; Department of Chemistry, Faculty of Science, McGill University, Montreal, Quebec, Canada
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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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Baltazar MT, Cable S, Carmichael PL, Cubberley R, Cull T, Delagrange M, Dent MP, Hatherell S, Houghton J, Kukic P, Li H, Lee MY, Malcomber S, Middleton AM, Moxon TE, Nathanail AV, Nicol B, Pendlington R, Reynolds G, Reynolds J, White A, Westmoreland C. A Next-Generation Risk Assessment Case Study for Coumarin in Cosmetic Products. Toxicol Sci 2020; 176:236-252. [PMID: 32275751 PMCID: PMC7357171 DOI: 10.1093/toxsci/kfaa048] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven risk assessment approach that integrates new approach methodologies (NAMs) to assure safety without the use of animal testing. These principles were applied to a hypothetical safety assessment of 0.1% coumarin in face cream and body lotion. For the purpose of evaluating the use of NAMs, existing animal and human data on coumarin were excluded. Internal concentrations (plasma Cmax) were estimated using a physiologically based kinetic model for dermally applied coumarin. Systemic toxicity was assessed using a battery of in vitro NAMs to identify points of departure (PoDs) for a variety of biological effects such as receptor-mediated and immunomodulatory effects (Eurofins SafetyScreen44 and BioMap Diversity 8 Panel, respectively), and general bioactivity (ToxCast data, an in vitro cell stress panel and high-throughput transcriptomics). In addition, in silico alerts for genotoxicity were followed up with the ToxTracker tool. The PoDs from the in vitro assays were plotted against the calculated in vivo exposure to calculate a margin of safety with associated uncertainty. The predicted Cmax values for face cream and body lotion were lower than all PoDs with margin of safety higher than 100. Furthermore, coumarin was not genotoxic, did not bind to any of the 44 receptors tested and did not show any immunomodulatory effects at consumer-relevant exposures. In conclusion, this case study demonstrated the value of integrating exposure science, computational modeling and in vitro bioactivity data, to reach a safety decision without animal data.
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Affiliation(s)
- Maria T Baltazar
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Sophie Cable
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Paul L Carmichael
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Richard Cubberley
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Tom Cull
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Mona Delagrange
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Matthew P Dent
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Sarah Hatherell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Jade Houghton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Mi-Young Lee
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Sophie Malcomber
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Alistair M Middleton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Thomas E Moxon
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Alexis V Nathanail
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Beate Nicol
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Ruth Pendlington
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Georgia Reynolds
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Joe Reynolds
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Andrew White
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Carl Westmoreland
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
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64
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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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65
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Hartwig A, Arand M, Epe B, Guth S, Jahnke G, Lampen A, Martus HJ, Monien B, Rietjens IMCM, Schmitz-Spanke S, Schriever-Schwemmer G, Steinberg P, Eisenbrand G. Mode of action-based risk assessment of genotoxic carcinogens. Arch Toxicol 2020; 94:1787-1877. [PMID: 32542409 PMCID: PMC7303094 DOI: 10.1007/s00204-020-02733-2] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 03/31/2020] [Indexed: 12/16/2022]
Abstract
The risk assessment of chemical carcinogens is one major task in toxicology. Even though exposure has been mitigated effectively during the last decades, low levels of carcinogenic substances in food and at the workplace are still present and often not completely avoidable. The distinction between genotoxic and non-genotoxic carcinogens has traditionally been regarded as particularly relevant for risk assessment, with the assumption of the existence of no-effect concentrations (threshold levels) in case of the latter group. In contrast, genotoxic carcinogens, their metabolic precursors and DNA reactive metabolites are considered to represent risk factors at all concentrations since even one or a few DNA lesions may in principle result in mutations and, thus, increase tumour risk. Within the current document, an updated risk evaluation for genotoxic carcinogens is proposed, based on mechanistic knowledge regarding the substance (group) under investigation, and taking into account recent improvements in analytical techniques used to quantify DNA lesions and mutations as well as "omics" approaches. Furthermore, wherever possible and appropriate, special attention is given to the integration of background levels of the same or comparable DNA lesions. Within part A, fundamental considerations highlight the terms hazard and risk with respect to DNA reactivity of genotoxic agents, as compared to non-genotoxic agents. Also, current methodologies used in genetic toxicology as well as in dosimetry of exposure are described. Special focus is given on the elucidation of modes of action (MOA) and on the relation between DNA damage and cancer risk. Part B addresses specific examples of genotoxic carcinogens, including those humans are exposed to exogenously and endogenously, such as formaldehyde, acetaldehyde and the corresponding alcohols as well as some alkylating agents, ethylene oxide, and acrylamide, but also examples resulting from exogenous sources like aflatoxin B1, allylalkoxybenzenes, 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline (MeIQx), benzo[a]pyrene and pyrrolizidine alkaloids. Additionally, special attention is given to some carcinogenic metal compounds, which are considered indirect genotoxins, by accelerating mutagenicity via interactions with the cellular response to DNA damage even at low exposure conditions. Part C finally encompasses conclusions and perspectives, suggesting a refined strategy for the assessment of the carcinogenic risk associated with an exposure to genotoxic compounds and addressing research needs.
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Affiliation(s)
- Andrea Hartwig
- Department of Food Chemistry and Toxicology, Institute of Applied Biosciences (IAB), Karlsruhe Institute of Technology (KIT), Adenauerring 20a, 76131, Karlsruhe, Germany.
| | - Michael Arand
- Institute of Pharmacology and Toxicology, University of Zurich, 8057, Zurich, Switzerland
| | - Bernd Epe
- Institute of Pharmacy and Biochemistry, University of Mainz, 55099, Mainz, Germany
| | - Sabine Guth
- Department of Toxicology, IfADo-Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund, Ardeystr. 67, 44139, Dortmund, Germany
| | - Gunnar Jahnke
- Department of Food Chemistry and Toxicology, Institute of Applied Biosciences (IAB), Karlsruhe Institute of Technology (KIT), Adenauerring 20a, 76131, Karlsruhe, Germany
| | - Alfonso Lampen
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), 10589, Berlin, Germany
| | - Hans-Jörg Martus
- Novartis Institutes for BioMedical Research, 4002, Basel, Switzerland
| | - Bernhard Monien
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), 10589, Berlin, Germany
| | - Ivonne M C M Rietjens
- Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Simone Schmitz-Spanke
- Institute and Outpatient Clinic of Occupational, Social and Environmental Medicine, University of Erlangen-Nuremberg, Henkestr. 9-11, 91054, Erlangen, Germany
| | - Gerlinde Schriever-Schwemmer
- Department of Food Chemistry and Toxicology, Institute of Applied Biosciences (IAB), Karlsruhe Institute of Technology (KIT), Adenauerring 20a, 76131, Karlsruhe, Germany
| | - Pablo Steinberg
- Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131, Karlsruhe, Germany
| | - Gerhard Eisenbrand
- Retired Senior Professor for Food Chemistry and Toxicology, Kühler Grund 48/1, 69126, Heidelberg, Germany.
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66
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Nicolaidou V, Koufaris C. Application of transcriptomic and microRNA profiling in the evaluation of potential liver carcinogens. Toxicol Ind Health 2020; 36:386-397. [PMID: 32419640 DOI: 10.1177/0748233720922710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Hepatocarcinogens are agents that increase the incidence of liver cancer in exposed animals or humans. It is now established that carcinogenic exposures have a widespread impact on the transcriptome, inducing both adaptive and adverse changes in the activities of genes and pathways. Chemical hepatocarcinogens have also been shown to affect expression of microRNA (miRNA), the evolutionarily conserved noncoding RNA that regulates gene expression posttranscriptionally. Considerable effort has been invested into examining the involvement of mRNA in chemical hepatocarcinogenesis and their potential usage for the classification and prediction of new chemical entities. For miRNA, there has been an increasing number of studies reported over the past decade, although not to the same degree as for transcriptomic studies. Current data suggest that it is unlikely that any gene or miRNA signature associated with short-term carcinogen exposure can replace the rodent bioassay. In this review, we discuss the application of transcriptomic and miRNA profiles to increase mechanistic understanding of chemical carcinogens and to aid in their classification.
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Affiliation(s)
- Vicky Nicolaidou
- Department of Life and Health Sciences, University of Nicosia, Nicosia, Cyprus
| | - Costas Koufaris
- Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus
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67
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Mezencev R, Auerbach SS. The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization. PLoS One 2020; 15:e0232955. [PMID: 32413060 PMCID: PMC7228135 DOI: 10.1371/journal.pone.0232955] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 04/25/2020] [Indexed: 11/25/2022] Open
Abstract
Whole-genome expression data generated by microarray studies have shown promise for quantitative human health risk assessment. While numerous approaches have been developed to determine benchmark doses (BMDs) from probeset-level dose responses, sensitivity of the results to methods used for normalization of the data has not yet been systematically investigated. Normalization of microarray data converts raw hybridization signals to expression estimates that are expected to be proportional to the amounts of transcripts in the profiled specimens. Different approaches to normalization have been shown to greatly influence the results of some downstream analyses, including biological interpretation. In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs. We demonstrate using in vivo data that the use of alternative pipelines for normalization of Affymetrix microarray data can have a considerable impact on the number of detected differentially expressed genes and pathways (processes) determined to be treatment responsive, which may lead to alternative interpretations of the data. In addition, we found that normalization can have a considerable effect (as much as ~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure). We argue for consideration of alternative normalization methods and their data-informed selection to most effectively interpret microarray data for use in human health risk assessment.
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Affiliation(s)
- Roman Mezencev
- Center for Public Health and Environmental Assessment, Office of Research and Development, US EPA, Washington DC, United States of America
| | - Scott S. Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, Durham, NC, United States of America
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68
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Ha MK, Kwon SJ, Choi JS, Nguyen NT, Song J, Lee Y, Kim YE, Shin I, Nam JW, Yoon TH. Mass Cytometry and Single-Cell RNA-seq Profiling of the Heterogeneity in Human Peripheral Blood Mononuclear Cells Interacting with Silver Nanoparticles. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e1907674. [PMID: 32163679 DOI: 10.1002/smll.201907674] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 02/17/2020] [Accepted: 02/18/2020] [Indexed: 06/10/2023]
Abstract
Understanding the interactions between nanoparticles (NPs) and human immune cells is necessary for justifying their utilization in consumer products and biomedical applications. However, conventional assays may be insufficient in describing the complexity and heterogeneity of cell-NP interactions. Herein, mass cytometry and single-cell RNA-sequencing (scRNA-seq) are complementarily used to investigate the heterogeneous interactions between silver nanoparticles (AgNPs) and primary immune cells. Mass cytometry reveals the heterogeneous biodistribution of the positively charged polyethylenimine-coated AgNPs in various cell types and finds that monocytes and B cells have higher association with the AgNPs than other populations. scRNA-seq data of these two cell types demonstrate that each type has distinct responses to AgNP treatment: NRF2-mediated oxidative stress is confined to B cells, whereas monocytes show Fcγ-mediated phagocytosis. Besides the between-population heterogeneity, analysis of single-cell dose-response relationships further reveals within-population diversity for the B cells and naïve CD4+ T cells. Distinct subsets having different levels of cellular responses with respect to their cellular AgNP doses are found. This study demonstrates that the complementary use of mass cytometry and scRNA-seq is helpful for gaining in-depth knowledge on the heterogeneous interactions between immune cells and NPs and can be incorporated into future toxicity assessments of nanomaterials.
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Affiliation(s)
- My Kieu Ha
- Center for Next Generation Cytometry, Hanyang University, Seoul, 04763, Republic of Korea
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul, 04763, Republic of Korea
| | - Sook Jin Kwon
- Center for Next Generation Cytometry, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul, 04763, Republic of Korea
| | - Jang-Sik Choi
- Center for Next Generation Cytometry, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul, 04763, Republic of Korea
| | - Nguyen Thanh Nguyen
- Center for Next Generation Cytometry, Hanyang University, Seoul, 04763, Republic of Korea
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul, 04763, Republic of Korea
| | - Jaewoo Song
- Department of Laboratory Medicine, College of Medicine, Yonsei University, Seoul, 03722, Republic of Korea
| | - Yangsoon Lee
- Department of Laboratory Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Young-Eun Kim
- Department of Laboratory Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Incheol Shin
- Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, 04763, Republic of Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, 04763, Republic of Korea
| | - Tae Hyun Yoon
- Center for Next Generation Cytometry, Hanyang University, Seoul, 04763, Republic of Korea
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul, 04763, Republic of Korea
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Wei F, Wang D, Li H, Xia P, Ran Y, You J. Toxicogenomics provides insights to toxicity pathways of neonicotinoids to aquatic insect, Chironomus dilutus. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:114011. [PMID: 31991362 DOI: 10.1016/j.envpol.2020.114011] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Revised: 01/03/2020] [Accepted: 01/16/2020] [Indexed: 06/10/2023]
Abstract
Neonicotinoid insecticides have posed a great threat to non-target organisms, yet the mechanisms underlying their toxicity are not well characterized. Major modes of action (MoAs) of imidacloprid were analyzed in an aquatic insect Chironomus dilutus. Lethal and sublethal outcomes were assessed in the midges after 96-h exposure to imidacloprid. Global transcriptomic profiles were determined using de novo RNA-sequencing to more holistically identify toxicity pathways. Transcriptional 10% biological potency values derived from ranked KEGG pathways and GO terms were 0.02 (0.01-0.08) (mean (95% confidence interval) and 0.05 (0.04-0.06) μg L-1, respectively, which were more sensitive than those from phenotypic traits (10% lethal concentration: 0.44 (0.23-0.79) μg L-1; 10% burrowing behavior concentration: 0.30 (0.22-0.43) μg L-1). Major MoAs of imidacloprid in aquatic species were identified as follows: the activation of nicotinic acetylcholine receptors (nAChRs) induced by imidacloprid impaired organisms' nerve system through calcium ion homeostasis imbalance and mitochondrial dysfunction, which posed oxidative stress and DNA damage and eventually caused death of organisms. The current investigation highlighted that imidacloprid affected C. dilutus at environmentally relevant concentrations, and elucidated toxicity pathways derived from gene alteration to individual outcomes, calling for more attention to toxicity of neonicotinoids to aquatic organisms.
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Affiliation(s)
- Fenghua Wei
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China; Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dali Wang
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Huizhen Li
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Pu Xia
- Department of Biology, University of Ottawa, Ontario, K1N 6N5, Canada
| | - Yong Ran
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Jing You
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China.
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70
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Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects. NANOMATERIALS 2020; 10:nano10040750. [PMID: 32326418 PMCID: PMC7221878 DOI: 10.3390/nano10040750] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 02/07/2023]
Abstract
The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.
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71
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Serra A, Fratello M, Cattelani L, Liampa I, Melagraki G, Kohonen P, Nymark P, Federico A, Kinaret PAS, Jagiello K, Ha MK, Choi JS, Sanabria N, Gulumian M, Puzyn T, Yoon TH, Sarimveis H, Grafström R, Afantitis A, Greco D. Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E708. [PMID: 32276469 PMCID: PMC7221955 DOI: 10.3390/nano10040708] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/30/2022]
Abstract
Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation of accurate and stable predictive models. In this review, we present the state-of-the-art of data modelling applied to transcriptomics data in TGx. We show how the benchmark dose (BMD) analysis can be applied to TGx data. We review read across and adverse outcome pathways (AOP) modelling methodologies. We discuss how network-based approaches can be successfully employed to clarify the mechanism of action (MOA) or specific biomarkers of exposure. We also describe the main AI methodologies applied to TGx data to create predictive classification and regression models and we address current challenges. Finally, we present a short description of deep learning (DL) and data integration methodologies applied in these contexts. Modelling of TGx data represents a valuable tool for more accurate chemical safety assessment. This review is the third part of a three-article series on Transcriptomics in Toxicogenomics.
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Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Luca Cattelani
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Irene Liampa
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (I.L.); (H.S.)
| | - Georgia Melagraki
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus; (G.M.); (A.A.)
| | - Pekka Kohonen
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Pia Anneli Sofia Kinaret
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
- Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
| | - Karolina Jagiello
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (K.J.); (T.P.)
- University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - My Kieu Ha
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Jang-Sik Choi
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Natasha Sanabria
- National Institute for Occupational Health, Johannesburg 30333, South Africa; (N.S.); (M.G.)
| | - Mary Gulumian
- National Institute for Occupational Health, Johannesburg 30333, South Africa; (N.S.); (M.G.)
- Haematology and Molecular Medicine Department, School of Pathology, University of the Witwatersrand, Johannesburg 2050, South Africa
| | - Tomasz Puzyn
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (K.J.); (T.P.)
- University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Tae-Hyun Yoon
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (I.L.); (H.S.)
| | - Roland Grafström
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Antreas Afantitis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus; (G.M.); (A.A.)
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
- Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
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Ewald JD, Soufan O, Crump D, Hecker M, Xia J, Basu N. EcoToxModules: Custom Gene Sets to Organize and Analyze Toxicogenomics Data from Ecological Species. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:4376-4387. [PMID: 32106671 DOI: 10.1021/acs.est.9b06607] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Traditional results from toxicogenomics studies are complex lists of significantly impacted genes or gene sets, which are challenging to synthesize down to actionable results with a clear interpretation. Here, we defined two sets of 21 custom gene sets, called the functional and statistical EcoToxModules, in fathead minnow (Pimephales promelas) to (1) re-cast predefined molecular pathways into a toxicological framework and (2) provide a data-driven, unsupervised grouping of genes impacted by exposure to environmental contaminants. The functional EcoToxModules were identified by re-organizing KEGG pathways into biological processes that are more relevant to ecotoxicology based on the input from expert scientists and regulators. The statistical EcoToxModules were identified using co-expression analysis of publicly available microarray data (n = 303 profiles) measured in livers of fathead minnows after exposure to 38 different conditions. Potential applications of the EcoToxModules were demonstrated with two case studies that represent exposure to a pure chemical and to environmental wastewater samples. In comparisons to differential expression and gene set analysis, we found that EcoToxModule responses were consistent with these traditional results. Additionally, they were easier to visualize and quantitatively compare across different conditions, which facilitated drawing conclusions about the relative toxicity of the exposures within each case study.
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Affiliation(s)
- Jessica D Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue H9X 3V9, Canada
| | - Othman Soufan
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue H9X 3V9, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, National Wildlife Research Centre, Ottawa K1A 0H3, Canada
| | - Markus Hecker
- School of the Environment & Sustainability and Toxicology Centre, University of Saskatchewan, Saskatoon S7N 5B3, Canada
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue H9X 3V9, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue H9X 3V9, Canada
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73
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LaRocca J, Costa E, Sriram S, Hannas BR, Johnson KJ. Short-term toxicogenomics as an alternative approach to chronic in vivo studies for derivation of points of departure: A case study in the rat with a triazole fungicide. Regul Toxicol Pharmacol 2020; 113:104655. [PMID: 32268158 DOI: 10.1016/j.yrtph.2020.104655] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 03/30/2020] [Accepted: 04/02/2020] [Indexed: 01/17/2023]
Abstract
The derivation of an apical endpoint point of departure (POD) from animal-intensive testing programs has been the traditional cornerstone of human health risk assessment. Replacement of in vivo chronic studies with novel approaches, such as toxicogenomics, holds promise for future alternative testing paradigms that significantly reduce animal testing. We hypothesized that a toxicogenomic POD following a 14 day exposure in the rat would approximate the most sensitive apical endpoint POD derived from a battery of chronic, carcinogenicity, reproduction and endocrine guideline toxicity studies. To test this hypothesis, we utilized myclobutanil, a triazole fungicide, as a model compound. In the 14 day study, male rats were administered 0 (vehicle), 30, 150, or 400 mg/kg/day myclobutanil via oral gavage. Endpoints evaluated included traditional apical, hormone, and liver and testis transcriptomic (whole genome RNA sequencing) data. From the transcriptomic data, liver and testis biological effect POD (BEPOD) values were derived. Myclobutanil exposure for 14 days resulted in increased liver weight, altered serum hormones, liver histopathology, and differential gene expression in liver and testis. The liver and testis BEPODs from the short-term study were 22.2 and 25.4 mg/kg/day, respectively. These BEPODs were approximately an order of magnitude higher than the most sensitive apical POD identified from the two year cancer bioassay based on testis atrophy (1.4 mg/kg/day). This study demonstrates the promise of using a short-term study BEPOD to derive a POD for human health risk assessment while substantially reducing animal testing.
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74
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Xia P, Zhang H, Peng Y, Shi W, Zhang X. Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach. ENVIRONMENT INTERNATIONAL 2020; 136:105455. [PMID: 31945694 DOI: 10.1016/j.envint.2019.105455] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 12/12/2019] [Accepted: 12/26/2019] [Indexed: 05/23/2023]
Abstract
The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.
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Affiliation(s)
- Pu Xia
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Hanxin Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Ying Peng
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Wei Shi
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China.
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75
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Nault R, Bals B, Teymouri F, Black MB, Andersen ME, McMullen PD, Krishnan S, Kuravadi N, Paul N, Kumar S, Kannan K, Jayachandra KC, Alagappan L, Patel BD, Bogen KT, Gollapudi BB, Klaunig JE, Zacharewski TR, Bringi V. A toxicogenomic approach for the risk assessment of the food contaminant acetamide. Toxicol Appl Pharmacol 2020; 388:114872. [PMID: 31881176 PMCID: PMC7014822 DOI: 10.1016/j.taap.2019.114872] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 12/10/2019] [Accepted: 12/20/2019] [Indexed: 12/26/2022]
Abstract
Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.
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Affiliation(s)
- Rance Nault
- Institute for Integrative Toxicology, Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States of America
| | - Bryan Bals
- Michigan Biotechnology Institute, Lansing, MI, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Tim R Zacharewski
- Institute for Integrative Toxicology, Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States of America
| | - Venkataraman Bringi
- Chemical Engineering & Materials Science, Michigan State University, East Lansing, MI, USA.
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76
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Krewski D, Andersen ME, Tyshenko MG, Krishnan K, Hartung T, Boekelheide K, Wambaugh JF, Jones D, Whelan M, Thomas R, Yauk C, Barton-Maclaren T, Cote I. Toxicity testing in the 21st century: progress in the past decade and future perspectives. Arch Toxicol 2019; 94:1-58. [DOI: 10.1007/s00204-019-02613-4] [Citation(s) in RCA: 124] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 11/05/2019] [Indexed: 12/19/2022]
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77
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Finding synergies for the 3Rs – Repeated Dose Toxicity testing: Report from an EPAA Partners' Forum. Regul Toxicol Pharmacol 2019; 108:104470. [DOI: 10.1016/j.yrtph.2019.104470] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/30/2019] [Accepted: 08/30/2019] [Indexed: 11/21/2022]
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78
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Soufan O, Ewald J, Viau C, Crump D, Hecker M, Basu N, Xia J. T1000: a reduced gene set prioritized for toxicogenomic studies. PeerJ 2019; 7:e7975. [PMID: 31681519 PMCID: PMC6824333 DOI: 10.7717/peerj.7975] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 10/02/2019] [Indexed: 12/12/2022] Open
Abstract
There is growing interest within regulatory agencies and toxicological research communities to develop, test, and apply new approaches, such as toxicogenomics, to more efficiently evaluate chemical hazards. Given the complexity of analyzing thousands of genes simultaneously, there is a need to identify reduced gene sets. Though several gene sets have been defined for toxicological applications, few of these were purposefully derived using toxicogenomics data. Here, we developed and applied a systematic approach to identify 1,000 genes (called Toxicogenomics-1000 or T1000) highly responsive to chemical exposures. First, a co-expression network of 11,210 genes was built by leveraging microarray data from the Open TG-GATEs program. This network was then re-weighted based on prior knowledge of their biological (KEGG, MSigDB) and toxicological (CTD) relevance. Finally, weighted correlation network analysis was applied to identify 258 gene clusters. T1000 was defined by selecting genes from each cluster that were most associated with outcome measures. For model evaluation, we compared the performance of T1000 to that of other gene sets (L1000, S1500, Genes selected by Limma, and random set) using two external datasets based on the rat model. Additionally, a smaller (T384) and a larger version (T1500) of T1000 were used for dose-response modeling to test the effect of gene set size. Our findings demonstrated that the T1000 gene set is predictive of apical outcomes across a range of conditions (e.g., in vitro and in vivo, dose-response, multiple species, tissues, and chemicals), and generally performs as well, or better than other gene sets available.
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Affiliation(s)
- Othman Soufan
- Institute of Parasitology, McGill University, Montreal, Canada
| | - Jessica Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Canada
| | - Charles Viau
- Institute of Parasitology, McGill University, Montreal, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, National Wildlife Research Centre, Carleton University, Ottawa, Canada
| | - Markus Hecker
- School of the Environment & Sustainability and Toxicology Centre, University of Saskatchewan, Saskatoon, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Canada
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, Canada.,Department of Animal Science, McGill University, Montreal, Canada
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Hasselgren C, Ahlberg E, Akahori Y, Amberg A, Anger LT, Atienzar F, Auerbach S, Beilke L, Bellion P, Benigni R, Bercu J, Booth ED, Bower D, Brigo A, Cammerer Z, Cronin MTD, Crooks I, Cross KP, Custer L, Dobo K, Doktorova T, Faulkner D, Ford KA, Fortin MC, Frericks M, Gad-McDonald SE, Gellatly N, Gerets H, Gervais V, Glowienke S, Van Gompel J, Harvey JS, Hillegass J, Honma M, Hsieh JH, Hsu CW, Barton-Maclaren TS, Johnson C, Jolly R, Jones D, Kemper R, Kenyon MO, Kruhlak NL, Kulkarni SA, Kümmerer K, Leavitt P, Masten S, Miller S, Moudgal C, Muster W, Paulino A, Lo Piparo E, Powley M, Quigley DP, Reddy MV, Richarz AN, Schilter B, Snyder RD, Stavitskaya L, Stidl R, Szabo DT, Teasdale A, Tice RR, Trejo-Martin A, Vuorinen A, Wall BA, Watts P, White AT, Wichard J, Witt KL, Woolley A, Woolley D, Zwickl C, Myatt GJ. Genetic toxicology in silico protocol. Regul Toxicol Pharmacol 2019; 107:104403. [PMID: 31195068 PMCID: PMC7485926 DOI: 10.1016/j.yrtph.2019.104403] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 05/20/2019] [Accepted: 06/05/2019] [Indexed: 01/23/2023]
Abstract
In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.
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Affiliation(s)
| | - Ernst Ahlberg
- Predictive Compound ADME & Safety, Drug Safety & Metabolism, AstraZeneca IMED Biotech Unit, Mölndal, Sweden
| | - Yumi Akahori
- Chemicals Evaluation and Research Institute, 1-4-25 Kouraku, Bunkyo-ku, Tokyo, 112-0004, Japan
| | - Alexander Amberg
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926, Frankfurt am Main, Germany
| | - Lennart T Anger
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926, Frankfurt am Main, Germany
| | - Franck Atienzar
- UCB BioPharma SPRL, Chemin du Foriest, B-1420 Braine-l'Alleud, Belgium
| | - Scott Auerbach
- The National Institute of Environmental Health Sciences, Division of the National Toxicology Program, Research Triangle Park, NC, 27709, USA
| | - Lisa Beilke
- Toxicology Solutions Inc., San Diego, CA, USA
| | | | | | - Joel Bercu
- Gilead Sciences, 333 Lakeside Drive, Foster City, CA, USA
| | - Ewan D Booth
- Syngenta, Product Safety Department, Jealott's Hill International Research Centre, Bracknell, Berkshire, RG42 6EY, UK
| | - Dave Bower
- Leadscope, Inc, 1393 Dublin Rd, Columbus, OH, 43215, USA
| | - Alessandro Brigo
- Roche Pharmaceutical Research & Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Zoryana Cammerer
- Janssen Research & Development, 1400 McKean Road, Spring House, PA, 19477, USA
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Ian Crooks
- British American Tobacco, Research and Development, Regents Park Road, Southampton, Hampshire, SO15 8TL, UK
| | - Kevin P Cross
- Leadscope, Inc, 1393 Dublin Rd, Columbus, OH, 43215, USA
| | - Laura Custer
- Bristol-Myers Squibb, Drug Safety Evaluation, 1 Squibb Dr, New Brunswick, NJ, 08903, USA
| | - Krista Dobo
- Pfizer Global Research & Development, 558 Eastern Point Road, Groton, CT, 06340, USA
| | - Tatyana Doktorova
- Douglas Connect GmbH, Technology Park Basel, Hochbergerstrasse 60C, CH-4057, Basel / Basel-Stadt, Switzerland
| | - David Faulkner
- Lawrence Berkeley National Laboratory, One Cyclotron Road, MS 70A-1161A, Berkeley, CA, 947020, USA
| | - Kevin A Ford
- Global Blood Therapeutics, 171 Oyster Point Boulevard, South San Francisco, CA, 94080, USA
| | - Marie C Fortin
- Jazz Pharmaceuticals, Inc., 200 Princeton South Corporate Center, Suite 180, Ewing, NJ, 08628, USA; Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, 170 Frelinghuysen Rd, Piscataway, NJ, 08855, USA
| | | | | | - Nichola Gellatly
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), Gibbs Building, 215 Euston Road, London, NW1 2BE, UK
| | - Helga Gerets
- UCB BioPharma SPRL, Chemin du Foriest, B-1420, Braine-l'Alleud, Belgium
| | | | - Susanne Glowienke
- Novartis Pharma AG, Pre-Clinical Safety, Werk Klybeck, CH, 4057, Basel, Switzerland
| | - Jacky Van Gompel
- Janssen Pharmaceutical Companies of Johnson & Johnson, 2340, Beerse, Belgium
| | - James S Harvey
- GlaxoSmithKline Pre-Clinical Development, Park Road, Ware, Hertfordshire, SG12 0DP, UK
| | - Jedd Hillegass
- Bristol-Myers Squibb, Drug Safety Evaluation, 1 Squibb Dr, New Brunswick, NJ, 08903, USA
| | - Masamitsu Honma
- Division of Genetics and Mutagenesis, National Institute of Health Sciences, Kanagawa, 210-9501, Japan
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Research Triangle Park, NC, 27709, USA
| | - Chia-Wen Hsu
- FDA Center for Drug Evaluation and Research, Silver Spring, MD, USA
| | | | | | - Robert Jolly
- Toxicology Division, Eli Lilly and Company, Indianapolis, IN, USA
| | - David Jones
- Medicines and Healthcare Products Regulatory Agency, 10 South Colonnade, Canary Wharf, London, E14 4PU, UK
| | - Ray Kemper
- Vertex Pharmaceuticals Inc., Predictive and Investigative Safety Assessment, 50 Northern Ave, Boston, MA, USA
| | - Michelle O Kenyon
- Pfizer Global Research & Development, 558 Eastern Point Road, Groton, CT, 06340, USA
| | - Naomi L Kruhlak
- FDA Center for Drug Evaluation and Research, Silver Spring, MD, USA
| | - Sunil A Kulkarni
- Existing Substances Risk Assessment Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada
| | - Klaus Kümmerer
- Institute for Sustainable and Environmental Chemistry, Leuphana University Lüneburg, Scharnhorststraße 1/C13.311b, 21335, Lüneburg, Germany
| | - Penny Leavitt
- Bristol-Myers Squibb, Drug Safety Evaluation, 1 Squibb Dr, New Brunswick, NJ, 08903, USA
| | - Scott Masten
- The National Institute of Environmental Health Sciences, Division of the National Toxicology Program, Research Triangle Park, NC, 27709, USA
| | - Scott Miller
- Leadscope, Inc, 1393 Dublin Rd, Columbus, OH, 43215, USA
| | | | - Wolfgang Muster
- Roche Pharmaceutical Research & Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | | | | | - Mark Powley
- Merck Research Laboratories, West Point, PA, 19486, USA
| | | | | | | | | | - Ronald D Snyder
- RDS Consulting Services, 2936 Wooded Vista Ct, Mason, OH, 45040, USA
| | | | | | | | | | | | | | | | - Brian A Wall
- Colgate-Palmolive Company, Piscataway, NJ, 08854, USA
| | - Pete Watts
- Bibra, Cantium House, Railway Approach, Wallington, Surrey, SM6 0DZ, UK
| | - Angela T White
- GlaxoSmithKline Pre-Clinical Development, Park Road, Ware, Hertfordshire, SG12 0DP, UK
| | - Joerg Wichard
- Bayer AG, Pharmaceuticals Division, Investigational Toxicology, Muellerstr. 178, D-13353, Berlin, Germany
| | - Kristine L Witt
- The National Institute of Environmental Health Sciences, Division of the National Toxicology Program, Research Triangle Park, NC, 27709, USA
| | - Adam Woolley
- ForthTox Limited, PO Box 13550, Linlithgow, EH49 7YU, UK
| | - David Woolley
- ForthTox Limited, PO Box 13550, Linlithgow, EH49 7YU, UK
| | - Craig Zwickl
- Transendix LLC, 1407 Moores Manor, Indianapolis, IN, 46229, USA
| | - Glenn J Myatt
- Leadscope, Inc, 1393 Dublin Rd, Columbus, OH, 43215, USA
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80
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Jensen SM, Kluxen FM, Ritz C. A Review of Recent Advances in Benchmark Dose Methodology. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2019; 39:2295-2315. [PMID: 31046141 DOI: 10.1111/risa.13324] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 02/01/2019] [Accepted: 04/03/2019] [Indexed: 06/09/2023]
Abstract
In this review, recent methodological developments for the benchmark dose (BMD) methodology are summarized. Specifically, we introduce the advances for the main steps in BMD derivation: selecting the procedure for defining a BMD from a predefined benchmark response (BMR), setting a BMR, selecting a dose-response model, and estimating the corresponding BMD lower limit (BMDL). Although the last decade has shown major progress in the development of BMD methodology, there is still room for improvement. Remaining challenges are the implementation of new statistical methods in user-friendly software and the lack of consensus about how to derive the BMDL.
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Affiliation(s)
- Signe M Jensen
- Department of Plant and Environmental Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Christian Ritz
- Department of Nutrition, Sports and Exercise, University of Copenhagen, Copenhagen, Denmark
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81
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The use of evidence from high-throughput screening and transcriptomic data in human health risk assessments. Toxicol Appl Pharmacol 2019; 380:114706. [DOI: 10.1016/j.taap.2019.114706] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/31/2019] [Accepted: 08/06/2019] [Indexed: 12/23/2022]
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82
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Kosnik MB, Reif DM. Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases. Toxicol Appl Pharmacol 2019; 379:114674. [PMID: 31323264 PMCID: PMC6708494 DOI: 10.1016/j.taap.2019.114674] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/05/2019] [Accepted: 07/15/2019] [Indexed: 12/18/2022]
Abstract
Traditional methods for chemical risk assessment are too time-consuming and resource-intensive to characterize either the diversity of chemicals to which humans are exposed or how that diversity may manifest in population susceptibility differences. The advent of novel toxicological data sources and their integration with bioinformatic databases affords opportunities for modern approaches that consider gene-environment (GxE) interactions in population risk assessment. Here, we present an approach that systematically links multiple data sources to relate chemical risk values to diseases and gene-disease variants. These data sources include high-throughput screening (HTS) results from Tox21/ToxCast, chemical-disease relationships from the Comparative Toxicogenomics Database (CTD), hazard data from resources like the Integrated Risk Information System, exposure data from the ExpoCast initiative, and gene-variant-disease information from the DisGeNET database. We use these integrated data to identify variants implicated in chemical-disease enrichments and develop a new value that estimates the risk of these associations toward differential population responses. Finally, we use this value to prioritize chemical-disease associations by exploring the genomic distribution of variants implicated in high-risk diseases. We offer this modular approach, termed DisQGOS (Disease Quotient Genetic Overview Score), for relating overall chemical-disease risk to potential for population variable responses, as a complement to methods aiming to modernize aspects of risk assessment.
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Affiliation(s)
- Marissa B Kosnik
- Toxicology Program, North Carolina State University, Raleigh, NC 27695-7617, United States of America; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7617, United States of America; Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695-7617, United States of America.
| | - David M Reif
- Toxicology Program, North Carolina State University, Raleigh, NC 27695-7617, United States of America; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7617, United States of America; Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695-7617, United States of America; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695-7617, United States of America.
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83
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Hexabromocyclododecane (HBCD): A case study applying tiered testing for human health risk assessment. Food Chem Toxicol 2019; 131:110581. [DOI: 10.1016/j.fct.2019.110581] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 06/11/2019] [Accepted: 06/12/2019] [Indexed: 10/26/2022]
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84
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Addressing systematic inconsistencies between in vitro and in vivo transcriptomic mode of action signatures. Toxicol In Vitro 2019; 58:1-12. [DOI: 10.1016/j.tiv.2019.02.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 01/14/2019] [Accepted: 02/14/2019] [Indexed: 12/26/2022]
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85
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Martínez R, Navarro-Martín L, Luccarelli C, Codina AE, Raldúa D, Barata C, Tauler R, Piña B. Unravelling the mechanisms of PFOS toxicity by combining morphological and transcriptomic analyses in zebrafish embryos. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 674:462-471. [PMID: 31022537 DOI: 10.1016/j.scitotenv.2019.04.200] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 04/12/2019] [Accepted: 04/12/2019] [Indexed: 06/09/2023]
Abstract
Exposure to PFOS (perfluorooctanesulfonate) has been related to toxic effects on lipid metabolism, immunological response, and different endocrine systems. We present here a transcriptomic analysis of zebrafish embryos exposed to different concentrations of PFOS (0.03-1.0 mg/L) from 48 to 120 hpf. No major survival or morphological alterations (swimming bladder inflation, kyphosis, eye separation and size…) were observed below the 1.0 mg/L mark. Conversely, we observed significant increase in transcripts related to lipid transport and metabolism even at the lowest used concentration. In addition, we observed a general decrease on transcripts related to natural immunity and defense again infections, which adds to the recent concerns about PFOS as immunotoxicant, particularly in humans. Derived PoD (Point of Departure) values for transcriptional changes (0.011 mg/L) were about 200-fold lower than the corresponding PoD values for morphometric effects (2.53 mg/L), and close to levels observed in human blood serum or bird eggs. Our data suggest that currently applicable tolerable levels of PFOS in commercial goods should be re-evaluated, taking into account its potential effects on lipid metabolism and the immune system.
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Affiliation(s)
- Rubén Martínez
- IDAEA-CSIC, Jordi Girona, 18, 08034 Barcelona, Spain; Universitat de Barcelona (UB), Barcelona 08007, Spain.
| | | | | | - Anna E Codina
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain; Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.
| | | | - Carlos Barata
- IDAEA-CSIC, Jordi Girona, 18, 08034 Barcelona, Spain.
| | - Romà Tauler
- IDAEA-CSIC, Jordi Girona, 18, 08034 Barcelona, Spain.
| | - Benjamin Piña
- IDAEA-CSIC, Jordi Girona, 18, 08034 Barcelona, Spain.
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86
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Viant MR, Ebbels TMD, Beger RD, Ekman DR, Epps DJT, Kamp H, Leonards PEG, Loizou GD, MacRae JI, van Ravenzwaay B, Rocca-Serra P, Salek RM, Walk T, Weber RJM. Use cases, best practice and reporting standards for metabolomics in regulatory toxicology. Nat Commun 2019; 10:3041. [PMID: 31292445 PMCID: PMC6620295 DOI: 10.1038/s41467-019-10900-y] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 06/07/2019] [Indexed: 12/23/2022] Open
Abstract
Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.
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Affiliation(s)
- Mark R Viant
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
| | | | | | | | - David J T Epps
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | | | | | | | | | | | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, OX1 3QG, UK
| | - Reza M Salek
- International Agency for Research on Cancer, Lyon, France
| | - Tilmann Walk
- BASF Metabolome Solutions, 10589, Berlin, Germany
| | - Ralf J M Weber
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
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87
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Pagé-Larivière F, Crump D, O'Brien JM. Transcriptomic points-of-departure from short-term exposure studies are protective of chronic effects for fish exposed to estrogenic chemicals. Toxicol Appl Pharmacol 2019; 378:114634. [PMID: 31226361 DOI: 10.1016/j.taap.2019.114634] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 06/03/2019] [Accepted: 06/17/2019] [Indexed: 12/13/2022]
Abstract
Resource limitations often require risk assessors to extrapolate chronic toxicity from acute tests using assessment factors. Transcriptomic dose-response analysis following short-term exposures may provide a more reliable and biologically-based alternative for estimating chronic toxicity. Here, we demonstrate that transcriptomic dose-response analysis in fish following short-term exposure to endocrine disrupting chemicals (EDCs) provides estimates of chronic toxicity that may be used as protective points-of-departure (POD) for risk assessment. The benchmark dose (BMD) method was used on publicly available datasets (n = 5) to determine transcriptomic PODs in fish exposed to three EDCs (bisphenol A, ethinylestradiol, and diethylstilbestrol). To test for potential bias related to data processing, our analysis compared the effect of different normalization, filtering, and BMD-grouping methods on the transcriptomic PODs. The resulting PODs were then compared to the empirically-derived chronic LOEC of each substance. Normalization and filtering methods had limited impact on the final PODs. However, we found that PODs derived from ontology- or pathway-based gene grouping methods were highly variable, whereas PODs from grouping methods that focused on the most responsive genes were more stable and provided POD estimates that were most similar to the chronic LOEC. Overall, 72% of transcriptomic PODs were within 1 order of magnitude of the chronic LOEC, regardless of data analysis method. When our recommended analysis approach was applied, the concordance improved to 100%. These results suggest that toxicogenomic dose-response analysis has the potential to be a protective decision-support tool for compounds with chronic toxicity, such as EDCs.
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Affiliation(s)
| | - Doug Crump
- National Wildlife Research Center, Environment and Climate Change Canada, Ontario, Canada
| | - Jason M O'Brien
- National Wildlife Research Center, Environment and Climate Change Canada, Ontario, Canada.
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88
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Harrill J, Shah I, Setzer RW, Haggard D, Auerbach S, Judson R, Thomas RS. Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions. CURRENT OPINION IN TOXICOLOGY 2019; 15:64-75. [PMID: 31501805 DOI: 10.1016/j.cotox.2019.05.004] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Recently, numerous organizations, including governmental regulatory agencies in the U.S. and abroad, have proposed using data from New Approach Methodologies (NAMs) for augmenting and increasing the pace of chemical assessments. NAMs are broadly defined as any technology, methodology, approach or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. High-throughput transcriptomics (HTTr) is a type of NAM that uses gene expression profiling as an endpoint for rapidly evaluating the effects of large numbers of chemicals on in vitro cell culture systems. As compared to targeted high-throughput screening (HTS) approaches that measure the effect of chemical X on target Y, HTTr is a non-targeted approach that allows researchers to more broadly characterize the integrated response of an intact biological system to chemicals that may affect a specific biological target or many biological targets under a defined set of treatment conditions (time, concentration, etc.). HTTr screening performed in concentration-response mode can provide potency estimates for the concentrations of chemicals that produce perturbations in cellular response pathways. Here, we discuss study design considerations for HTTr concentration-response screening and present a framework for the use of HTTr-based biological pathway-altering concentrations (BPACs) in a screening-level, risk-based chemical prioritization approach. The framework involves concentration-response modeling of HTTr data, mapping gene level responses to biological pathways, determination of BPACs, in vitro-to-in vivo extrapolation (IVIVE) and comparison to human exposure predictions.
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Affiliation(s)
- Joshua Harrill
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Imran Shah
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - R Woodrow Setzer
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Derik Haggard
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Scott Auerbach
- National Toxicology Program, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC, USA
| | - Richard Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Russell S Thomas
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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89
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Schmitz-Spanke S. Toxicogenomics - What added Value Do These Approaches Provide for Carcinogen Risk Assessment? ENVIRONMENTAL RESEARCH 2019; 173:157-164. [PMID: 30909101 DOI: 10.1016/j.envres.2019.03.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 03/08/2019] [Accepted: 03/10/2019] [Indexed: 06/09/2023]
Abstract
It is still a major challenge to protect humans at workplaces and in the environment. To cope with this task, it is a prerequisite to obtain detailed information on the extent of chemical perturbations of biological pathways, in particular, adaptive vs. adverse effects and the dose-response relationships. This knowledge serves as the basis for the classification of non-carcinogens and carcinogens and for further distinguishing carcinogens in genotoxic (DNA damaging) or non-genotoxic compounds. Basing on quantitative dose-response relationships, points of departures can be derived for chemical risk assessment. In recent years, new methods have shown their capability to support the established rodent models of carcinogenicity testing. In vitro high throughput screening assays assess more comprehensively cell response. In addition, omics technologies were applied to study the mode of action of chemicals whereby the term "toxicogenomics" comprises various technologies such as transcriptomics, epigenomics, or metabolomics. This review aims to summarize the current state of toxicogenomic approaches in risk science and to compare them with established ones. For example, measurement of global transcriptional changes generates meaningful information for toxicological risk assessment such as accurate classification of genotoxic/non-genotoxic carcinogens. Alteration in mRNA expression offers previously unknown insights in the mode of action and enables the definition of key events. Based on these, benchmark doses can be calculated for the transition from an adaptive to an adverse state. In short, this review assesses the potential and challenges of transcriptomics and addresses the impact of other omics technologies on risk assessment in terms of hazard identification and dose-response assessment.
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Affiliation(s)
- Simone Schmitz-Spanke
- Institute and Outpatient Clinic of Occupational, Social and Environmental Medicine, University of Erlangen-Nuremberg, Henkestr. 9-11, 91054, Erlangen, Germany.
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90
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Levorato S, Rietjens IMCM, Carmichael PL, Hepburn PA. Novel approaches to derive points of departure for food chemical risk assessment. Curr Opin Food Sci 2019. [DOI: 10.1016/j.cofs.2019.02.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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91
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Zhang Q, Caudle WM, Pi J, Bhattacharya S, Andersen ME, Kaminski NE, Conolly RB. Embracing Systems Toxicology at Single-Cell Resolution. CURRENT OPINION IN TOXICOLOGY 2019; 16:49-57. [PMID: 31768481 DOI: 10.1016/j.cotox.2019.04.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
As systems biology expands its multi-omic spectrum to increasing resolutions, distinguishing cells based on single-cell profiles becomes feasible. Unlike traditional bulk assays that average cellular responses and blur the distinct identities of responsive cells, single-cell technologies enable sensitive detection of small cellular changes and precise identification of those cells perturbed by toxicants. Among the suite of omic technologies that continue to expand and become affordable, single-cell RNA sequencing (scRNA-seq) is at the cutting edge and leading the way to transform systems toxicology. Single-cell systems toxicology can provide a wealth of information to elucidate cell-specific alterations and response trajectories, detect points-of-departure, map and develop dynamical models of toxicity pathways.
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Affiliation(s)
- Qiang Zhang
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - W Michael Caudle
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Jingbo Pi
- Program of Environmental Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Sudin Bhattacharya
- Department of Biomedical Engineering, Department of Pharmacology and Toxicology, Center for Research on Ingredient Safety, Institute for Quantitative Health Science and Engineering, and Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA
| | | | - Norbert E Kaminski
- Departments of Pharmacology and Toxicology and Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA
| | - Rory B Conolly
- Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, United States Environmental Protection Agency, Durham, North Carolina, USA
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92
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Dose-dependence of chemical carcinogenicity: Biological mechanisms for thresholds and implications for risk assessment. Chem Biol Interact 2019; 301:112-127. [DOI: 10.1016/j.cbi.2019.01.025] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 01/11/2019] [Accepted: 01/25/2019] [Indexed: 12/19/2022]
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93
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Klaren WD, Ring C, Harris MA, Thompson CM, Borghoff S, Sipes NS, Hsieh JH, Auerbach SS, Rager JE. Identifying Attributes That Influence In Vitro-to-In Vivo Concordance by Comparing In Vitro Tox21 Bioactivity Versus In Vivo DrugMatrix Transcriptomic Responses Across 130 Chemicals. Toxicol Sci 2019; 167:157-171. [PMID: 30202884 PMCID: PMC6317427 DOI: 10.1093/toxsci/kfy220] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Recent efforts aimed at integrating in vitro high-throughput screening (HTS) data into chemical toxicity assessments are necessitating increased understanding of concordance between chemical-induced responses observed in vitro versus in vivo. This investigation set out to (1) measure concordance between in vitro HTS data and transcriptomic responses observed in vivo, focusing on the liver, and (2) identify attributes that can influence concordance. Signal response profiles from 130 substances were compared between in vitro data produced through Tox21 and liver transcriptomic data through DrugMatrix, collected from rats exposed to a chemical for ≤5 days. A global in vitro-to-in vivo comparative analysis based on pathway-level responses resulted in an overall average percent agreement of 79%, ranging on a per-chemical basis between 41% and 100%. Whereas concordance amongst inactive chemicals was high (89%), concordance amongst chemicals showing in vitro activity was only 13%, suggesting that follow-up in vivo and/or orthogonal in vitro assays would improve interpretations of in vitro activity. Attributes identified to influence concordance included experimental design attributes (eg, cell type), target pathways, and physicochemical properties (eg, logP). The attribute that most consistently increased concordance was dose applicability, evaluated by filtering for experimental doses administered to rats that were within 10-fold of those related to likely bioactivity, derived using Tox21 data and high-throughput toxicokinetic modeling. Together, findings suggest that in vitro screening approaches to predict in vivo toxicity are viable particularly when certain attributes are considered, including whether activity versus inactivity is observed, experimental design, chemical properties, and dose applicability.
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Affiliation(s)
- William D Klaren
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77840
| | | | | | | | | | - Nisha S Sipes
- National Toxicology Program, National Institutes of Health, Research Triangle Park, North Carolina 27709and
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Durham, North Carolina 27709
| | - Scott S Auerbach
- National Toxicology Program, National Institutes of Health, Research Triangle Park, North Carolina 27709and
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94
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Aguilera J, Aguilera‐Gomez M, Barrucci F, Cocconcelli PS, Davies H, Denslow N, Lou Dorne J, Grohmann L, Herman L, Hogstrand C, Kass GEN, Kille P, Kleter G, Nogué F, Plant NJ, Ramon M, Schoonjans R, Waigmann E, Wright MC. EFSA Scientific Colloquium 24 – 'omics in risk assessment: state of the art and next steps. ACTA ACUST UNITED AC 2018. [DOI: 10.2903/sp.efsa.2018.en-1512] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | - Lutz Grohmann
- Federal Office of Consumer Protection and Food Safety
| | | | | | | | | | | | - Fabien Nogué
- French National Institute for Agricultural Research INRA
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95
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Auerbach SS, Paules RS. Genomic dose response: Successes, challenges, and next steps. CURRENT OPINION IN TOXICOLOGY 2018. [DOI: 10.1016/j.cotox.2019.04.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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96
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Zhang Q, Li J, Middleton A, Bhattacharya S, Conolly RB. Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling. Front Public Health 2018; 6:261. [PMID: 30255008 PMCID: PMC6141783 DOI: 10.3389/fpubh.2018.00261] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 08/21/2018] [Indexed: 12/18/2022] Open
Abstract
Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.
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Affiliation(s)
- Qiang Zhang
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Jin Li
- Unilever, Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, United Kingdom
| | - Alistair Middleton
- Unilever, Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, United Kingdom
| | - Sudin Bhattacharya
- Biomedical Engineering, Michigan State University, East Lansing, MI, United States
| | - Rory B Conolly
- Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, United States Environmental Protection Agency, Durham, NC, United States
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97
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Emerging technologies for food and drug safety. Regul Toxicol Pharmacol 2018; 98:115-128. [PMID: 30048704 DOI: 10.1016/j.yrtph.2018.07.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 07/20/2018] [Indexed: 01/20/2023]
Abstract
Emerging technologies are playing a major role in the generation of new approaches to assess the safety of both foods and drugs. However, the integration of emerging technologies in the regulatory decision-making process requires rigorous assessment and consensus amongst international partners and research communities. To that end, the Global Coalition for Regulatory Science Research (GCRSR) in partnership with the Brazilian Health Surveillance Agency (ANVISA) hosted the seventh Global Summit on Regulatory Science (GSRS17) in Brasilia, Brazil on September 18-20, 2017 to discuss the role of new approaches in regulatory science with a specific emphasis on applications in food and medical product safety. The global regulatory landscape concerning the application of new technologies was assessed in several countries worldwide. Challenges and issues were discussed in the context of developing an international consensus for objective criteria in the development, application and review of emerging technologies. The need for advanced approaches to allow for faster, less expensive and more predictive methodologies was elaborated. In addition, the strengths and weaknesses of each new approach was discussed. And finally, the need for standards and reproducible approaches was reviewed to enhance the application of the emerging technologies to improve food and drug safety. The overarching goal of GSRS17 was to provide a venue where regulators and researchers meet to develop collaborations addressing the most pressing scientific challenges and facilitate the adoption of novel technical innovations to advance the field of regulatory science.
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98
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Metabolomics Discovers Early-Response Metabolic Biomarkers that Can Predict Chronic Reproductive Fitness in Individual Daphnia magna. Metabolites 2018; 8:metabo8030042. [PMID: 30041468 PMCID: PMC6160912 DOI: 10.3390/metabo8030042] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 07/09/2018] [Accepted: 07/18/2018] [Indexed: 12/11/2022] Open
Abstract
Chemical risk assessment remains entrenched in chronic toxicity tests that set safety thresholds based on animal pathology or fitness. Chronic tests are resource expensive and lack mechanistic insight. Discovering a chemical's mode-of-action can in principle provide predictive molecular biomarkers for a toxicity endpoint. Furthermore, since molecular perturbations precede pathology, early-response molecular biomarkers may enable shorter, more resource efficient testing that can predict chronic animal fitness. This study applied untargeted metabolomics to attempt to discover early-response metabolic biomarkers that can predict reproductive fitness of Daphnia magna, an internationally-recognized test species. First, we measured the reproductive toxicities of cadmium, 2,4-dinitrophenol and propranolol to individual Daphnia in 21-day OECD toxicity tests, then measured the metabolic profiles of these animals using mass spectrometry. Multivariate regression successfully discovered putative metabolic biomarkers that strongly predict reproductive impairment by each chemical, and for all chemicals combined. The non-chemical-specific metabolic biomarkers were then applied to metabolite data from Daphnia 24-h acute toxicity tests and correctly predicted that significant decreases in reproductive fitness would occur if these animals were exposed to cadmium, 2,4-dinitrophenol or propranolol for 21 days. While the applicability of these findings is limited to three chemicals, they provide proof-of-principle that early-response metabolic biomarkers of chronic animal fitness can be discovered for regulatory toxicity testing.
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99
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Infer the in vivo point of departure with ToxCast in vitro assay data using a robust learning approach. Arch Toxicol 2018; 92:2913-2922. [PMID: 29995190 DOI: 10.1007/s00204-018-2260-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 07/04/2018] [Indexed: 10/28/2022]
Abstract
The development and application of high throughput in vitro assays is an important development for risk assessment in the twenty-first century. However, there are still significant challenges to incorporate in vitro assays into routine toxicity testing practices. In this paper, a robust learning approach was developed to infer the in vivo point of departure (POD) with in vitro assay data from ToxCast and Tox21 projects. Assay data from ToxCast and Tox21 projects were utilized to derive the in vitro PODs for several hundred chemicals. These were combined with in vivo PODs from ToxRefDB regarding the rat and mouse liver to build a high-dimensional robust regression model. This approach separates the chemicals into a majority, well-predicted set; and a minority, outlier set. Salient relationships can then be learned from the data. For both mouse and rat liver PODs, over 93% of chemicals have inferred values from in vitro PODs that are within ± 1 of the in vivo PODs on the log10 scale (the target learning region, or TLR) and R2 of 0.80 (rats) and 0.78 (mice) for these chemicals. This is comparable with extrapolation between related species (mouse and rat), which has 93% chemicals within the TLR and the R2 being 0.78. Chemicals in the outlier set tend to also have more biologically variable characteristics. With the continued accumulation of high throughput data for a wide range of chemicals, predictive modeling can provide a valuable complement for adverse outcome pathway based approach in risk assessment.
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100
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Qutob SS, Chauhan V, Kuo B, Williams A, Yauk CL, McNamee JP, Gollapudi B. The application of transcriptional benchmark dose modeling for deriving thresholds of effects associated with solar-simulated ultraviolet radiation exposure. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2018; 59:502-515. [PMID: 29761935 PMCID: PMC6099464 DOI: 10.1002/em.22196] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Revised: 03/02/2018] [Accepted: 03/16/2018] [Indexed: 06/08/2023]
Abstract
Considerable data has been generated to elucidate the transcriptional response of cells to ultraviolet radiation (UVR) exposure providing a mechanistic understanding of UVR-induced cellular responses. However, using these data to support standards development has been challenging. In this study, we apply benchmark dose (BMD) modeling of transcriptional data to derive thresholds of gene responsiveness following exposure to solar-simulated UVR. Human epidermal keratinocytes were exposed to three doses (10, 20, 150 kJ/m2 ) of solar simulated UVR and assessed for gene expression changes 6 and 24 hr postexposure. The dose-response curves for genes with p-fit values (≥ 0.1) were used to derive BMD values for genes and pathways. Gene BMDs were bi-modally distributed, with a peak at ∼16 kJ/m2 and ∼108 kJ/m2 UVR exposure. Genes/pathways within Mode 1 were involved in cell signaling and DNA damage response, while genes/pathways in the higher Mode 2 were associated with immune response and cancer development. The median value of each Mode coincides with the current human exposure limits for UVR and for the minimal erythemal dose, respectively. Such concordance implies that the use of transcriptional BMD data may represent a promising new approach for deriving thresholds of actinic effects. Environ. Mol. Mutagen. 59:502-515, 2018. © 2018 The Authors Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.
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Affiliation(s)
- Sami S. Qutob
- Consumer and Clinical Radiation Protection BureauHealth CanadaOttawaOntarioK1A 1C1Canada
| | - Vinita Chauhan
- Consumer and Clinical Radiation Protection BureauHealth CanadaOttawaOntarioK1A 1C1Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Health CanadaOttawaOntarioCanada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health CanadaOttawaOntarioCanada
| | - Carole L. Yauk
- Environmental Health Science and Research Bureau, Health CanadaOttawaOntarioCanada
| | - James P. McNamee
- Consumer and Clinical Radiation Protection BureauHealth CanadaOttawaOntarioK1A 1C1Canada
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