Generalized Concentration Addition Model Predicts Glucocorticoid Activity Bioassay Responses to Environmentally Detected Receptor-Ligand Mixtures

Many glucocorticoid receptor (GR) agonists have been detected in waste and surface waters domestically and around the world, but the way a mixture of these environmental compounds may elicit a total glucocorticoid activity response in water samples remains unknown. Therefore, we characterized 19 GR ligands using a CV1 cell line transcriptional activation assay applicable to water quality monitoring. Cells were treated with individual GR ligands, a fixed ratio mixture of full or partial agonists, or a nonequipotent mixture with full and partial agonists. Efficacy varied (48.09%-102.5%) and potency ranged over several orders of magnitude (1.278 x 10(-10) to 3.93 x 10(-8) M). Concentration addition (CA) and response addition (RA) mixtures models accurately predicted equipotent mixture responses of full agonists (r(2) = 0.992 and 0.987, respectively). However, CA and RA models assume mixture compounds produce full agonist-like responses, and therefore they overestimated observed maximal efficacies for mixtures containing partial agonists. The generalized concentration addition (GCA) model mathematically permits < 100% maximal responses, and fell within the 95% confidence interval bands of mixture responses containing partial agonists. The GCA, but not CA and RA, model predictions of nonequipotent mixtures containing both full and partial agonists fell within the same statistical distribution as the observed values, reinforcing the practicality of the GCA model as the best overall model for predicting GR activation. Elucidating the mechanistic basis of GR activation by mixtures of previously detected environmental GR ligands will benefit the interpretation of environmental sample contents in future water quality monitoring studies.