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Additive Mixture Effects of Estrogenic Chemicals in Human Cell-Based Assays Can Be Influenced by Inclusion of Chemicals with Differing Effect Profiles

机译：在人类细胞为基础的分析雌激素类化学的添加剂混合物影响可以影响通过具有不同的影响型材化学品列入

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A growing body of experimental evidence indicates that the in vitro effects of mixtures of estrogenic chemicals can be well predicted from the estrogenicity of their components by the concentration addition (CA) concept. However, some studies have observed small deviations from CA. Factors affecting the presence or observation of deviations could include: the type of chemical tested; number of mixture components; mixture design; and assay choice. We designed mixture experiments that address these factors, using mixtures with high numbers of components, chemicals from diverse chemical groups, assays with different in vitro endpoints and different mixture designs and ratios. Firstly, the effects of mixtures composed of up to 17 estrogenic chemicals were examined using estrogenicity assays with reporter-gene (ERLUX) and cell proliferation (ESCREEN) endpoints. Two mixture designs were used: 1) a ‘balanced’ design with components present in proportion to a common effect concentration (e.g. an EC10) and 2) a ‘non-balanced’ design with components in proportion to potential human tissue concentrations. Secondly, the individual and simultaneous ability of 16 potential modulator chemicals (each with minimal estrogenicity) to influence the assay outcome produced by a reference mixture of estrogenic chemicals was examined. Test chemicals included plasticizers, phthalates, metals, PCBs, phytoestrogens, PAHs, heterocyclic amines, antioxidants, UV filters, musks, PBDEs and parabens. In all the scenarios tested, the CA concept provided a good prediction of mixture effects. Modulation studies revealed that chemicals possessing minimal estrogenicity themselves could reduce (negatively modulate) the effect of a mixture of estrogenic chemicals. Whether the type of modulation we observed occurs in practice most likely depends on the chemical concentrations involved, and better information is required on likely human tissue concentrations of estrogens and of potential modulators. Successful prediction of the effects of diverse chemical combinations might be more likely if chemical profiling included consideration of effect modulation.
机译：越来越多的实验证据表明，可以通过浓度添加（CA）概念从其成分的雌激素性很好地预测雌激素化合物混合物的体外作用。但是，一些研究发现与CA的偏差很小。影响偏差存在或观察到的因素可能包括：测试的化学品类型；混合成分的数量；混合物设计；和分析选择。我们设计了解决这些问题的混合物实验，使用了具有大量成分的混合物，来自不同化学组的化学物质，具有不同体外终点，不同混合物设计和比率的测定方法。首先，使用具有报告基因（ERLUX）和细胞增殖（ESCREEN）终点的雌激素测定法，检查了由多达17种雌激素化学物质组成的混合物的作用。使用了两种混合设计：1）“平衡”设计，其成分与共同效应浓度（例如EC10）成正比； 2）“非平衡”设计，其成分与潜在人体组织浓度成比例。其次，检查了16种潜在调节剂化学物质（每种具有最小的雌激素性）的个体和同时能力，这些能力影响雌激素化学物质参考混合物产生的测定结果。测试化学品包括增塑剂，邻苯二甲酸盐，金属，多氯联苯，植物雌激素，多环芳烃，杂环胺，抗氧化剂，紫外线过滤剂，麝香，多溴二苯醚和对羟基苯甲酸酯。在所有测试的场景中，CA概念可以很好地预测混合效果。调节研究表明，具有最小雌激素作用的化学物质本身可以降低（负调节）雌激素化学物质混合物的作用。我们观察到的调节类型在实践中是否最可能取决于所涉及的化学浓度，并且需要有关可能的人类组织中雌激素和潜在调节剂浓度的更好信息。如果化学分析包括对效应调节的考虑，则更有可能成功预测各种化学组合的作用。

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