Citation:

MedlockKakaley, E., M. Cardon, E. Gray, P. Hartig, AND V. Wilson. Generalized concentration addition model predicts glucocorticoid activity bioassay responses to environmentally detected receptor-ligand mixtures. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, , 252-263, (2019). https://doi.org/10.1093/toxsci/kfy290

Impact/Purpose:

We, and others, have detected glucocorticoid receptor (GR) agonist activity in waste and surface waters domestically and around the world. This study describes the characterization of environmentally relevant GR ligands in a cell-based GR activity detection method. Herein, we illustrate the variety of responses obtained from the selected suite of chemicals and the complexities of modeling specific GR agonists in environmental mixtures.

Description:

Attached is a manuscript which includes a broad introduction and reasoning for the study, as well as a detailed study design, results and conclusions. The manuscript was written with the intent of submission to Toxicological Sciences for peer-review and publication. -----(ABSTRACT) The glucocorticoid receptor (GR) is ubiquitously expressed in humans and wildlife species. Many known GR agonists have been detected in waste and surface waters domestically and around the world, but the manner in which a mixture of these environmental compounds act together to 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 and partial agonists, or using a two-chemical matrix design with full and partial agonists. Agonist efficacy varied and potency ranged over several orders of magnitude, 48.09 to 102.5% and 1.278 x 10-10 to 3.93 x 10-8 M, respectfully. Concentration addition (CA) and response addition (RA) mixture models accurately predicted observed equipotent mixture responses of full agonists (r2 = 0.992 and 0.987, respectively), however they overestimated observed maximum efficacies for mixtures containing partial agonists. The generalized concentration addition (GCA) model fell within the 95% confidence interval bands of observed equipotent mixture curves containing partial agonists, providing the best fit of the three models. The GCA model, but not CA and RA model, predictions of non-equipotent 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 in the CV1-hGR bioassay. Elucidating the mechanistic basis of GR activation will benefit the interpretation of environmental mixture sample contents in future water quality monitoring studies.

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