A novel computational solution to the health risk assessment of air pollution via joint toxicity prediction: A case study on selected PAH binary mixtures in particulate matters
A novel computational solution to the health risk assessment of air pollution via joint toxicity prediction: A case study on selected PAH binary mixtures in particulate matters
复制标题
通过联合毒性预测进行空气污染健康风险评估的新型计算解决方案：颗粒物中选定的 PAH 二元混合物的案例研究
DOI：
10.1016/j.ecoenv.2018.12.010
复制
发表时间：
2019-04-15
影响因子：
6.8
通讯作者：
Zhang，Aiqian
中科院分区：
文献类型：
--
作者：
Liu，Xian;Zhang，Huazhou;Zhang，Aiqian
区域性烟霾事件已引起公众高度关注。揭示大气细颗粒物（PM2.5）的代表性成分混合物的健康效应成为当务之急。在这项研究中，一种新的计算解决方案集成化学诱导的基因组残留效应预测在体外基于风险评估，提出了获得典型的化学混合物的颗粒物（PM）的累积健康风险。通过分析相关污染物的基因组相似性和剂量-反应曲线，对化学物质诱导的基因组残留效应进行联合毒性评价。为此，引入了混合物的修正相对效价因子（mRPF），并定义了活化比（RA）值来评价混合物的健康风险。作为一种方法学论证，典型的二元多环芳烃（PAH）混合物的PM，含有苯并[a]芘（BaP）作为一个组成部分的健康风险进行了评估，使用建议的解决方案。结果表明，苯并[a]蒽（BaA）、苯并[B]荧蒽（BbF）和苯并[a]蒽（BaA）对苯并[a]芘（BaP）多环芳烃的联合作用对p53通路具有协同效应，且这种混合物的健康风险比单独的多环芳烃更大。显然，如果将协同效应错误地假设为加和效应，则会低估环境混合物的累积健康风险。据我们所知，这是有史以来第一个研究报告的计算解决方案，以健康风险评估的环境污染viajoint毒性预测。该方法充分利用了开放获取的体外实验数据和文献中的转录组学信息，成功地体现了系统生物学和转化科学的概念。
Regional haze episode has already caused overwhelming public concern. Unraveling the health effects of the representative composition mixtures of atmospheric fine particulate matters (PM2.5) becomes a top priority. In this study, a novel computational solution integrating chemical-induced genomic residual effect prediction within vitro-based risk assessment is proposed to obtain the cumulative health risk of typical chemical mixtures of particulate matters (PM). The joint toxicity of binary mixtures is estimated by analyzing both genomic similarity and dose-response curve of relevant pollutants for the chemical-induced genomic residual effect. Specifically, the modified relative potency factor (mRPF) of mixtures is introduced for this purpose, and the ratio of activation (RA) value is defined to assess the corresponding health risks of the mixtures. As a methodology demonstration, the health risk of typical binary polycyclic aromatic hydrocarbon (PAH) mixtures in PM, containing Benzo[a]pyrene (BaP) as a component, is assessed using the proposed solution. Our results indicate that the combined effect of pairwise PAHs of BaP with Benzo[b]fluoranthene (BbF) and Benz[a]anthracene (BaA) is synergistic on p53 pathway, and that the health risk of the such mixtures increases compared to that of the individual ones. Obviously, the cumulative health risk of environmental mixtures will be underestimated when the synergistic effect is wrongly assumed to be additive. To our knowledge, this is the first study ever report on a computational solution to the health risk assessment of environmental pollutionviajoint toxicity prediction. The novel methodology proposed here makes full use of the open-accessin vitroassay data and transcriptomic information in literatures and provides a successful demonstration of the concept of systems biology and translational science.