Mathematical model insights into arsenic detoxification.

Sean D Lawley, Molly Cinderella, Megan N Hall, Mary V Gamble, H Frederik Nijhout, Michael C Reed
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引用次数: 20

Abstract

Background: Arsenic in drinking water, a major health hazard to millions of people in South and East Asia and in other parts of the world, is ingested primarily as trivalent inorganic arsenic (iAs), which then undergoes hepatic methylation to methylarsonic acid (MMAs) and a second methylation to dimethylarsinic acid (DMAs). Although MMAs and DMAs are also known to be toxic, DMAs is more easily excreted in the urine and therefore methylation has generally been considered a detoxification pathway. A collaborative modeling project between epidemiologists, biologists, and mathematicians has the purpose of explaining existing data on methylation in human studies in Bangladesh and also testing, by mathematical modeling, effects of nutritional supplements that could increase As methylation.

Methods: We develop a whole body mathematical model of arsenic metabolism including arsenic absorption, storage, methylation, and excretion. The parameters for arsenic methylation in the liver were taken from the biochemical literature. The transport parameters between compartments are largely unknown, so we adjust them so that the model accurately predicts the urine excretion rates of time for the iAs, MMAs, and DMAs in single dose experiments on human subjects.

Results: We test the model by showing that, with no changes in parameters, it predicts accurately the time courses of urinary excretion in mutiple dose experiments conducted on human subjects. Our main purpose is to use the model to study and interpret the data on the effects of folate supplementation on arsenic methylation and excretion in clinical trials in Bangladesh. Folate supplementation of folate-deficient individuals resulted in a 14% decrease in arsenicals in the blood. This is confirmed by the model and the model predicts that arsenicals in the liver will decrease by 19% and arsenicals in other body stores by 26% in these same individuals. In addition, the model predicts that arsenic methyltransferase has been upregulated by a factor of two in this population. Finally, we also show that a modification of the model gives excellent fits to the data on arsenic metabolism in human cultured hepatocytes.

Conclusions: The analysis of the Bangladesh data using the model suggests that folate supplementation may be more effective at reducing whole body arsenic than previously expected. There is almost no data on the upregulation of arsenic methyltransferase in populations chronically exposed to arsenic. Our model predicts upregulation by a factor of two in the Bangladesh population studied. This prediction should be verified since it could have important public health consequences both for treatment strategies and for setting appropriate limits on arsenic in drinking water. Our model has compartments for the binding of arsenicals to proteins inside of cells and we show that these comparments are necessary to obtain good fits to data. Protein-binding of arsenicals should be explored in future biochemical studies.

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数学模型对砷解毒的见解。
背景:饮用水中的砷是南亚和东亚以及世界其他地区数百万人的主要健康危害,主要以三价无机砷(iAs)的形式摄入,然后经肝甲基化生成甲基胂酸(MMAs),再经过第二次甲基化生成二甲基胂酸(DMAs)。虽然已知mma和dma也有毒性,但dma更容易从尿液中排出,因此甲基化通常被认为是一种解毒途径。流行病学家、生物学家和数学家之间的一个合作建模项目的目的是解释孟加拉国人类研究中甲基化的现有数据,并通过数学建模来测试营养补充剂可能增加As甲基化的影响。方法:建立包括砷吸收、储存、甲基化和排泄在内的全身砷代谢数学模型。肝脏中砷甲基化的参数取自生化文献。隔间之间的运输参数在很大程度上是未知的,因此我们调整了它们,以便模型准确地预测人类受试者单剂量实验中iAs, MMAs和DMAs的尿排泄率。结果:我们对该模型进行了测试,结果表明,在参数没有变化的情况下,它可以准确地预测人体多剂量实验中尿排泄的时间过程。我们的主要目的是使用该模型来研究和解释孟加拉国临床试验中叶酸补充对砷甲基化和排泄的影响的数据。叶酸缺乏个体补充叶酸可使血液中的砷含量降低14%。模型证实了这一点,模型预测这些人肝脏中的砷含量将下降19%,其他身体储存处的砷含量将下降26%。此外,该模型预测,砷甲基转移酶在这一人群中被上调了两倍。最后,我们还表明,对模型的修改可以很好地拟合人类培养肝细胞中砷代谢的数据。结论:使用该模型对孟加拉国数据进行的分析表明,叶酸补充剂在减少全身砷方面可能比先前预期的更有效。在长期暴露于砷的人群中,几乎没有关于砷甲基转移酶上调的数据。我们的模型预测,在所研究的孟加拉国人口中,上调幅度为两倍。这一预测应该得到核实,因为它可能对治疗战略和对饮用水中的砷设定适当限制产生重要的公共卫生影响。我们的模型具有用于将砷与细胞内蛋白质结合的隔室,我们表明这些隔室对于获得良好的数据拟合是必要的。在今后的生物化学研究中,应进一步探讨砷的蛋白质结合机制。
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Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
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期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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