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Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data

Quantitative relationships between carcinogenic potency and mutagenic potency have been previously examined using a benchmark dose (BMD)‐based approach. We extended those analyses by using human exposure data for 48 compounds to calculate carcinogenicity‐derived and genotoxicity‐derived margin of ex...

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Autores principales: Chepelev, Nikolai, Long, Alexandra S., Beal, Marc, Barton‐Maclaren, Tara, Johnson, George, Dearfield, Kerry L., Roberts, Daniel J., van Benthem, Jan, White, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10107494/
https://www.ncbi.nlm.nih.gov/pubmed/36345771
http://dx.doi.org/10.1002/em.22517
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author Chepelev, Nikolai
Long, Alexandra S.
Beal, Marc
Barton‐Maclaren, Tara
Johnson, George
Dearfield, Kerry L.
Roberts, Daniel J.
van Benthem, Jan
White, Paul
author_facet Chepelev, Nikolai
Long, Alexandra S.
Beal, Marc
Barton‐Maclaren, Tara
Johnson, George
Dearfield, Kerry L.
Roberts, Daniel J.
van Benthem, Jan
White, Paul
author_sort Chepelev, Nikolai
collection PubMed
description Quantitative relationships between carcinogenic potency and mutagenic potency have been previously examined using a benchmark dose (BMD)‐based approach. We extended those analyses by using human exposure data for 48 compounds to calculate carcinogenicity‐derived and genotoxicity‐derived margin of exposure values (MOEs) that can be used to prioritize substances for risk management. MOEs for 16 of the 48 compounds were below 10,000, and consequently highlighted for regulatory concern. Of these, 15 were highlighted using genotoxicity‐derived (micronucleus [MN] dose–response data) MOEs. A total of 13 compounds were highlighted using carcinogenicity‐derived MOEs; 12 compounds were overlapping. MOEs were also calculated using transgenic rodent (TGR) mutagenicity data. For 10 of the 12 compounds examined using TGR data, the results similarly revealed that mutagenicity‐derived MOEs yield regulatory decisions that correspond with those based on carcinogenicity‐derived MOEs. The effect of benchmark response (BMR) on MOE determination was also examined. Reinterpretation of the analyses using a BMR of 50% indicated that four out of 15 compounds prioritized using MN‐derived MOEs based on a default BMR of 5% would have been missed. The results indicate that regulatory decisions based on in vivo genotoxicity dose–response data would be consistent with those based on carcinogenicity dose–response data; in some cases, genotoxicity‐based decisions would be more conservative. Going forward, and in the absence of carcinogenicity data, in vivo genotoxicity assays (MN and TGR) can be used to effectively prioritize substances for regulatory action. Routine use of the MOE approach necessitates the availability of reliable human exposure estimates, and consensus regarding appropriate BMRs for genotoxicity endpoints.
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spelling pubmed-101074942023-04-18 Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data Chepelev, Nikolai Long, Alexandra S. Beal, Marc Barton‐Maclaren, Tara Johnson, George Dearfield, Kerry L. Roberts, Daniel J. van Benthem, Jan White, Paul Environ Mol Mutagen Research Articles Quantitative relationships between carcinogenic potency and mutagenic potency have been previously examined using a benchmark dose (BMD)‐based approach. We extended those analyses by using human exposure data for 48 compounds to calculate carcinogenicity‐derived and genotoxicity‐derived margin of exposure values (MOEs) that can be used to prioritize substances for risk management. MOEs for 16 of the 48 compounds were below 10,000, and consequently highlighted for regulatory concern. Of these, 15 were highlighted using genotoxicity‐derived (micronucleus [MN] dose–response data) MOEs. A total of 13 compounds were highlighted using carcinogenicity‐derived MOEs; 12 compounds were overlapping. MOEs were also calculated using transgenic rodent (TGR) mutagenicity data. For 10 of the 12 compounds examined using TGR data, the results similarly revealed that mutagenicity‐derived MOEs yield regulatory decisions that correspond with those based on carcinogenicity‐derived MOEs. The effect of benchmark response (BMR) on MOE determination was also examined. Reinterpretation of the analyses using a BMR of 50% indicated that four out of 15 compounds prioritized using MN‐derived MOEs based on a default BMR of 5% would have been missed. The results indicate that regulatory decisions based on in vivo genotoxicity dose–response data would be consistent with those based on carcinogenicity dose–response data; in some cases, genotoxicity‐based decisions would be more conservative. Going forward, and in the absence of carcinogenicity data, in vivo genotoxicity assays (MN and TGR) can be used to effectively prioritize substances for regulatory action. Routine use of the MOE approach necessitates the availability of reliable human exposure estimates, and consensus regarding appropriate BMRs for genotoxicity endpoints. John Wiley & Sons, Inc. 2023-01-06 2023-01 /pmc/articles/PMC10107494/ /pubmed/36345771 http://dx.doi.org/10.1002/em.22517 Text en © 2022 His Majesty the King in Right of Canada and The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagen Society. Reproduced with the permission of the Minister of Health. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Chepelev, Nikolai
Long, Alexandra S.
Beal, Marc
Barton‐Maclaren, Tara
Johnson, George
Dearfield, Kerry L.
Roberts, Daniel J.
van Benthem, Jan
White, Paul
Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title_full Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title_fullStr Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title_full_unstemmed Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title_short Establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: Margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
title_sort establishing a quantitative framework for regulatory interpretation of genetic toxicity dose–response data: margin of exposure case study of 48 compounds with both in vivo mutagenicity and carcinogenicity dose–response data
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10107494/
https://www.ncbi.nlm.nih.gov/pubmed/36345771
http://dx.doi.org/10.1002/em.22517
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