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Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol

Currently, there is a lack of knowledge about the effects of co-exposures of cannabis, contaminated with pesticides like chlorpyrifos (CPF) and the toxic metabolite CPF-oxon (CPFO). CPF/CPFO residues, and (Δ9)Tetrahydrocannabinol ((Δ9)THC), the main component in cannabis, are known to disrupt the en...

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Autores principales: Silva, Marilyn, Kwok, Ryan Kin-Hin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860916/
https://www.ncbi.nlm.nih.gov/pubmed/35243363
http://dx.doi.org/10.1016/j.crtox.2022.100064
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author Silva, Marilyn
Kwok, Ryan Kin-Hin
author_facet Silva, Marilyn
Kwok, Ryan Kin-Hin
author_sort Silva, Marilyn
collection PubMed
description Currently, there is a lack of knowledge about the effects of co-exposures of cannabis, contaminated with pesticides like chlorpyrifos (CPF) and the toxic metabolite CPF-oxon (CPFO). CPF/CPFO residues, and (Δ9)Tetrahydrocannabinol ((Δ9)THC), the main component in cannabis, are known to disrupt the endocannabinoid system (eCBS) resulting in neurodevelopmental defects. Although there are in vivo data characterizing CPF/CPFO and (Δ9)THC, there are mechanistic data gaps and deficiencies. In this study, an investigation of open access CompTox tools and ToxCast/Tox21 data was performed to determine targets relating to the modes of action (MOA) for these compounds and, given the available biological targets, predict points of departure (POD). The main findings were as follows: 1) In vivo PODs for each chemical were from open literature, 2) Concordance between ToxCast/Tox21 assay targets and known targets in the metabolic and eCBS pathways was evaluated, 3) Human Equivalent Administered Dose (EAD(Human)) PODs showed the High throughput toxicokinetic (HTTK) 3 compartment model (3COMP) was more predictive of in vivo PODs than the PBTK model for CPF, CPFO and (Δ9)THC, 4) Age-adjusted 3COMP HTTK-Pop EAD(Human), with CPF and CPFO ToxCast/Tox21 AC(50) values as inputs were predictive for ages 0–4 when but not (Δ9)THC compared to in vivo PODs. 5) Age-related refinements for CPF/CPFO were primarily from ToxCast/Tox21 active hit-calls for nuclear receptors, CYP2B6 and AChE inhibition (CPFO only) associated with the metabolic pathway. Only one assay target (arylhydrocarbon hydroxylase receptor) was common between CPF/CPFO and (Δ9)THC. While computational refinements may select some sensitive events involved in the metabolic pathways; this is highly dependent on the cytotoxicity limits, availability of metabolic activity in the ToxCast/Tox21 assays and reliability of assay performance. Some uncertainties and data gaps for (Δ9)THC might be addressed with assays specific to the eCBS. For CPF, assays with appropriate metabolic activation could better represent the toxic pathway.
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spelling pubmed-88609162022-03-02 Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol Silva, Marilyn Kwok, Ryan Kin-Hin Curr Res Toxicol Article Currently, there is a lack of knowledge about the effects of co-exposures of cannabis, contaminated with pesticides like chlorpyrifos (CPF) and the toxic metabolite CPF-oxon (CPFO). CPF/CPFO residues, and (Δ9)Tetrahydrocannabinol ((Δ9)THC), the main component in cannabis, are known to disrupt the endocannabinoid system (eCBS) resulting in neurodevelopmental defects. Although there are in vivo data characterizing CPF/CPFO and (Δ9)THC, there are mechanistic data gaps and deficiencies. In this study, an investigation of open access CompTox tools and ToxCast/Tox21 data was performed to determine targets relating to the modes of action (MOA) for these compounds and, given the available biological targets, predict points of departure (POD). The main findings were as follows: 1) In vivo PODs for each chemical were from open literature, 2) Concordance between ToxCast/Tox21 assay targets and known targets in the metabolic and eCBS pathways was evaluated, 3) Human Equivalent Administered Dose (EAD(Human)) PODs showed the High throughput toxicokinetic (HTTK) 3 compartment model (3COMP) was more predictive of in vivo PODs than the PBTK model for CPF, CPFO and (Δ9)THC, 4) Age-adjusted 3COMP HTTK-Pop EAD(Human), with CPF and CPFO ToxCast/Tox21 AC(50) values as inputs were predictive for ages 0–4 when but not (Δ9)THC compared to in vivo PODs. 5) Age-related refinements for CPF/CPFO were primarily from ToxCast/Tox21 active hit-calls for nuclear receptors, CYP2B6 and AChE inhibition (CPFO only) associated with the metabolic pathway. Only one assay target (arylhydrocarbon hydroxylase receptor) was common between CPF/CPFO and (Δ9)THC. While computational refinements may select some sensitive events involved in the metabolic pathways; this is highly dependent on the cytotoxicity limits, availability of metabolic activity in the ToxCast/Tox21 assays and reliability of assay performance. Some uncertainties and data gaps for (Δ9)THC might be addressed with assays specific to the eCBS. For CPF, assays with appropriate metabolic activation could better represent the toxic pathway. Elsevier 2022-02-07 /pmc/articles/PMC8860916/ /pubmed/35243363 http://dx.doi.org/10.1016/j.crtox.2022.100064 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Silva, Marilyn
Kwok, Ryan Kin-Hin
Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title_full Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title_fullStr Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title_full_unstemmed Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title_short Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and (Δ9)Tetrahydrocannabinol
title_sort use of computational toxicology tools to predict in vivo endpoints associated with mode of action and the endocannabinoid system: a case study with chlorpyrifos, chlorpyrifos-oxon and (δ9)tetrahydrocannabinol
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860916/
https://www.ncbi.nlm.nih.gov/pubmed/35243363
http://dx.doi.org/10.1016/j.crtox.2022.100064
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