20 research outputs found

    PON1 status does not influence cholinesterase activity in Egyptian agricultural workers exposed to chlorpyrifos.

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    Animal studies have shown that paraoxonase 1 (PON1) genotype can influence susceptibility to the organophosphorus pesticide chlorpyrifos (CPF). However, Monte Carlo analysis suggests that PON1 genotype may not affect CPF-related toxicity at low exposure conditions in humans. The current study sought to determine the influence of PON1 genotype on the activity of blood cholinesterase as well as the effect of CPF exposure on serum PON1 in workers occupationally exposed to CPF. Saliva, blood and urine were collected from agricultural workers (n=120) from Egypt's Menoufia Governorate to determine PON1 genotype, blood cholinesterase activity, serum PON1 activity towards chlorpyrifos-oxon (CPOase) and paraoxon (POase), and urinary levels of the CPF metabolite 3,5,6-trichloro-2-pyridinol (TCPy). The PON1 55 (P≤0.05) but not the PON1 192 genotype had a significant effect on CPOase activity. However, both the PON1 55 (P≤0.05) and PON1 192 (P≤0.001) genotypes had a significant effect on POase activity. Workers had significantly inhibited AChE and BuChE after CPF application; however, neither CPOase activity nor POase activity was associated with ChE depression when adjusted for CPF exposure (as determined by urinary TCPy levels) and stratified by PON1 genotype. CPOase and POase activity were also generally unaffected by CPF exposure although there were alterations in activity within specific genotype groups. Together, these results suggest that workers retained the capacity to detoxify chlorpyrifos-oxon under the exposure conditions experienced by this study population regardless of PON1 genotype and activity and that effects of CPF exposure on PON1 activity are minimal

    Metabolism of profenofos to 4-bromo-2-chlorophenol, a specific and sensitive exposure biomarker.

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    Profenofos is a direct acting phosphorothioate organophosphorus (OP) pesticide capable of inhibiting β-esterases such as acetylcholinesterase, butyrylcholinesterase, and carboxylesterase. Profenofos is known to be detoxified to the biologically inactive metabolite, 4-bromo-2-chlorophenol (BCP); however, limited data are available regarding the use of urinary BCP as an exposure biomarker in humans. A pilot study conducted in Egyptian agriculture workers, demonstrated that urinary BCP levels prior to application (3.3-30.0 μg/g creatinine) were elevated to 34.5-3,566 μg/g creatinine during the time workers were applying profenofos to cotton fields. Subsequently, the in vitro enzymatic formation of BCP was examined using pooled human liver microsomes and recombinant human cytochrome P-450s (CYPs) incubated with profenofos. Of the nine human CYPs studied, only CYPs 3A4, 2B6, and 2C19 were able to metabolize profenofos to BCP. Kinetic studies indicated that CYP 2C19 has the lowest Km, 0.516 μM followed by 2B6 (Km=1.02 μM) and 3A4 (Km=18.9μM). The Vmax for BCP formation was 47.9, 25.1, and 19.2 nmol/min/nmol CYP for CYP2B6, 2C19, and 3A4, respectively. Intrinsic clearance (Vmax/Km) values of 48.8, 46.9, and 1.02 ml/min/nmol CYP 2C19, 2B6, and 3A4, respectively, indicate that CYP2C19 and CYP2B6 are primarily responsible for the detoxification of profenofos. These findings support the use of urinary BCP as a biomarker of exposure to profenofos in humans and suggest polymorphisms in CYP 2C19 and CYP 2B6 as potential biomarkers of susceptibility

    Toxicogenomic analysis of exposure to TCDD, PCB126 and PCB153: identification of genomic biomarkers of exposure to AhR ligands

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    <p>Abstract</p> <p>Background</p> <p>Two year cancer bioassays conducted by the National Toxicology Program have shown chronic exposure to dioxin-like compounds (DLCs) to lead to the development of both neoplastic and non-neoplastic lesions in the hepatic tissue of female Sprague Dawley rats. Most, if not all, of the hepatotoxic effects induced by DLC's are believed to involve the binding and activation of the transcription factor, the aryl hydrocarbon receptor (AhR). Toxicogenomics was implemented to identify genomic responses that may be contributing to the development of hepatotoxicity in rats.</p> <p>Results</p> <p>Through comparative analysis of time-course microarray data, unique hepatic gene expression signatures were identified for the DLCs, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (100 ng/kg/day) and 3,3',4,4',5-pentachlorobiphenyl (PCB126) (1000 ng/kg/day) and the non-DLC 2,2',4,4',5,5',-hexachlorobiphenyl (PCB153) (1000 μg/kg/day). A common time independent signature of 41 AhR genomic biomarkers was identified which exhibited at least a 2-fold change in expression following subchronic (13-wk) and chronic (52-wk) p.o. exposure to TCDD and PCB126, but not the non DLC, PCB153. Real time qPCR analysis validated that 30 of these genes also exhibited at least a 2-fold change in hepatic expression at 24 hr following a single exposure to TCDD (5 μg/kg, po). Phenotypic anchoring was conducted which identified forty-six genes that were differently expressed both following chronic p.o. exposure to DLCs and in previously reported studies of cholangiocarcinoma or hepatocellular adenoma.</p> <p>Conclusions</p> <p>Together these analyses provide a comprehensive description of the genomic responses which occur in rat hepatic tissue with exposure to AhR ligands and will help to isolate those genomic responses which are contributing to the hepatotoxicity observed with exposure to DLCs. In addition, the time independent gene expression signature of the AhR ligands may assist in identifying other agents with the potential to elicit dioxin-like hepatotoxic responses.</p

    Refine and Strengthen SAR-Based Read-Across by Considering Bioactivation and Modes of Action

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    Structure–activity relationship (SAR)-based read-across is an important and effective method to establish the safety of a data-poor target chemical (structure of interest (SOI)) using hazard data from structurally similar source chemicals (analogues). Many methods use quantitative similarity scores to evaluate the structural similarity for searching and selecting analogues as well as for evaluating analogue suitability. However, studies suggest that read-across based purely on structural similarity cannot accurately predict the toxicity of an SOI. As mechanistic data become available, we gain a greater understanding of the mode of action (MOA), the relationship between structures and metabolism/bioactivation pathways, and the existence of “activity cliffs” in chemical chain length, which can improve the analogue rating process. For this purpose, the current work identifies a series of classes of chemicals where a small change at a key position can result in a significant change in metabolism and bioactivation pathways and may eventually result in significant changes in chemical toxicity that have a big impact on the suitability of analogues for read-across. Additionally, a series of SAR-based read-across case studies are presented, which cover a variety of chemical classes that commonly link to different toxic endpoints. The case study results indicate that SAR-based read-across can be refined and strengthened by considering MOAs or proposed reactive metabolite formation pathways, which can improve the overall accuracy, consistency, transparency, and confidence in evaluating analogue suitability

    Refine and Strengthen SAR-Based Read-Across by Considering Bioactivation and Modes of Action

    No full text
    Structure–activity relationship (SAR)-based read-across is an important and effective method to establish the safety of a data-poor target chemical (structure of interest (SOI)) using hazard data from structurally similar source chemicals (analogues). Many methods use quantitative similarity scores to evaluate the structural similarity for searching and selecting analogues as well as for evaluating analogue suitability. However, studies suggest that read-across based purely on structural similarity cannot accurately predict the toxicity of an SOI. As mechanistic data become available, we gain a greater understanding of the mode of action (MOA), the relationship between structures and metabolism/bioactivation pathways, and the existence of “activity cliffs” in chemical chain length, which can improve the analogue rating process. For this purpose, the current work identifies a series of classes of chemicals where a small change at a key position can result in a significant change in metabolism and bioactivation pathways and may eventually result in significant changes in chemical toxicity that have a big impact on the suitability of analogues for read-across. Additionally, a series of SAR-based read-across case studies are presented, which cover a variety of chemical classes that commonly link to different toxic endpoints. The case study results indicate that SAR-based read-across can be refined and strengthened by considering MOAs or proposed reactive metabolite formation pathways, which can improve the overall accuracy, consistency, transparency, and confidence in evaluating analogue suitability
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