{"title":"Asbestos exposure, lung fiber burden, and mesothelioma rates: Mechanistic modelling for risk assessment","authors":"Andrey A. Korchevskiy , Ann G. Wylie","doi":"10.1016/j.comtox.2022.100249","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Relationships among asbestos exposure, lung burden, and mesothelioma risks have been previously evaluated, but it would be useful to validate published epidemiological observations with a mathematical model describing deposition and elimination of various mineral types of fibers.</p></div><div><h3>Objective</h3><p>(a) To develop a mechanistical model demonstrating uptake and removal of fibers from human lungs, (b) To test the model on the results of a British case-control study, (c) To quantify the updated values for elimination coefficient of various mineral types of asbestos fibers.</p></div><div><h3>Methods</h3><p>A mechanistic model utilizing the first-order kinetic relationship is proposed that relates levels of exposure to mineral fibers, elimination coefficients, and lung burden at certain points of time. The behaviour of the model was explored for different exposure scenarios. Elimination coefficients for various mineral types were estimated based on the observed proportion of asbestos minerals in exposure vs observed lung burden.</p></div><div><h3>Results</h3><p><span><span>Based on the proposed model, the average elimination coefficient was estimated for crocidolite as 0.099 vs average published value of 0.092, for amosite as 0.169 vs 0.19, and for </span>chrysotile as 6.45 vs average published value of 6.36 (years</span><sup>−1</sup>). Lung burden level was demonstrated to change linearly with exposure intensity, and supra-linearly with exposure duration. The simulation of three separate exposure events during three decades showed that lung burden level prevailingly depends on the most recent event (R = 0.967, p < 0.05) and only weakly correlates with the most remote event (R = 0.032, p < 0.05).</p></div><div><h3>Conclusion</h3><p>In spite of potential limitations, mechanistical modelling of asbestos exposure can serve as an effective tool for risk assessment purposes.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111322000378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 2
Abstract
Context
Relationships among asbestos exposure, lung burden, and mesothelioma risks have been previously evaluated, but it would be useful to validate published epidemiological observations with a mathematical model describing deposition and elimination of various mineral types of fibers.
Objective
(a) To develop a mechanistical model demonstrating uptake and removal of fibers from human lungs, (b) To test the model on the results of a British case-control study, (c) To quantify the updated values for elimination coefficient of various mineral types of asbestos fibers.
Methods
A mechanistic model utilizing the first-order kinetic relationship is proposed that relates levels of exposure to mineral fibers, elimination coefficients, and lung burden at certain points of time. The behaviour of the model was explored for different exposure scenarios. Elimination coefficients for various mineral types were estimated based on the observed proportion of asbestos minerals in exposure vs observed lung burden.
Results
Based on the proposed model, the average elimination coefficient was estimated for crocidolite as 0.099 vs average published value of 0.092, for amosite as 0.169 vs 0.19, and for chrysotile as 6.45 vs average published value of 6.36 (years−1). Lung burden level was demonstrated to change linearly with exposure intensity, and supra-linearly with exposure duration. The simulation of three separate exposure events during three decades showed that lung burden level prevailingly depends on the most recent event (R = 0.967, p < 0.05) and only weakly correlates with the most remote event (R = 0.032, p < 0.05).
Conclusion
In spite of potential limitations, mechanistical modelling of asbestos exposure can serve as an effective tool for risk assessment purposes.
石棉暴露、肺负荷和间皮瘤风险之间的关系先前已被评估过，但用描述各种矿物纤维沉积和消除的数学模型来验证已发表的流行病学观察结果将是有用的。目的(a)建立一个机械模型来证明纤维从人体肺部吸收和去除，(b)在英国病例对照研究的结果上测试该模型。(c)量化各种矿物类型石棉纤维消除系数的最新数值。方法利用一级动力学关系建立了矿物纤维暴露水平、消除系数和特定时间点肺负荷之间的机制模型。研究了该模型在不同暴露情景下的行为。各种矿物类型的消除系数是根据观察到的暴露中石棉矿物的比例与观察到的肺负担来估计的。基于所提出的模型，估计青橄榄石的平均消除系数为0.099，平均公布值为0.092，阿莫石的平均消除系数为0.169，平均公布值为0.19，温石棉的平均消除系数为6.45，平均公布值为6.36(年)。肺负荷水平与暴露强度呈线性变化，与暴露时间呈超线性变化。对三十年中三个独立暴露事件的模拟表明，肺负荷水平主要取决于最近的事件(R = 0.967, p <0.05)，且仅与最远的事件呈弱相关(R = 0.032, p <0.05)。结论尽管存在潜在的局限性，但石棉暴露力学模型可以作为风险评估的有效工具。
期刊介绍：
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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