Environmental exposures often occur in complex mixtures and at low concentrations. Generalized concentration addition (GCA) is a method used to estimate the joint effect of receptor ligands that vary in efficacy. GCA models have been successfully applied to mixtures of aryl hydrocarbon receptor (AhR) and peroxisome proliferator-activated receptor gamma (PPARγ) ligands, each of which can be modeled as a receptor with a single binding site. Here, we evaluated whether GCA could be applied to homodimer nuclear receptors, which have two binding sites, to predict the combined effect of full glucocorticoid receptor (GR) agonists with partial agonists. We measured transcriptional activation of GR using a cell-based bioassay. Individual concentration-response curves for dexamethasone (full agonist), prednisolone (full agonist), and medroxyprogesterone 17-acetate (partial agonist) were generated and applied in three additivity models, GCA, effect summation (ES), and relative potency factor (RPF), to generate response surfaces. GCA and RPF yielded adequate predictions of the experimental data for two full agonists. However, GCA fit experimental data significantly better than ES and RPF for all other binary mixtures. This work extends the application of GCA to homodimer nuclear receptors and improves prediction accuracy of mixture effects of GR agonists.

环境暴露通常以复杂的混合物和低浓度发生。广义浓度加法 (GCA) 是一种用于估计功效不同的受体配体的联合效应的方法。GCA 模型已成功应用于芳烃受体 (AhR) 和过氧化物酶体增殖物激活受体 γ (PPARγ) 配体的混合物，每种配体都可以模拟为具有单个结合位点的受体。在这里，我们评估了 GCA 是否可以应用于具有两个结合位点的同型二聚体核受体，以预测全糖皮质激素受体 (GR) 激动剂与部分激动剂的联合作用。我们使用基于细胞的生物测定法测量了 GR 的转录激活。地塞米松（完全激动剂）、泼尼松龙（完全激动剂）、和 17-醋酸甲羟孕酮（部分激动剂）被生成并应用于三个可加性模型、GCA、效应总和 (ES) 和相对效力因子 (RPF)，以生成响应面。GCA 和 RPF 对两种完全激动剂的实验数据产生了足够的预测。然而，对于所有其他二元混合物，GCA 比 ES 和 RPF 更适合实验数据。这项工作将 GCA 的应用扩展到同二聚体核受体，并提高了 GR 激动剂混合效应的预测准确性。对于所有其他二元混合物，GCA 拟合实验数据明显优于 ES 和 RPF。这项工作将 GCA 的应用扩展到同二聚体核受体，并提高了 GR 激动剂混合效应的预测准确性。对于所有其他二元混合物，GCA 拟合实验数据明显优于 ES 和 RPF。这项工作将 GCA 的应用扩展到同二聚体核受体，并提高了 GR 激动剂混合效应的预测准确性。