Predicting the Effects of Per- and Polyfluoroalkyl Substance Mixtures on Peroxisome Proliferator-Activated Receptor Alpha Activity in Vitro

Abstract

Human exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous, with mixtures of PFAS detected in drinking water, food, household dust, and other exposure sources. Animal toxicity studies and human epidemiology indicate that PFAS may act through shared mechanisms including activation of peroxisome proliferator activated receptor (PPAR). However, the effect of PFAS mixtures on human relevant molecular initiating events remains an important data gap in the PFAS literature. Here, we tested the ability of modeling approaches to predict the effect of diverse PPAR ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPAR (hPPAR) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 hours with two full hPPAR agonists (pemafibrate and GW7647), a full and a partial hPPAR agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPAR agonist and a competitive antagonist (pemafibrate and GW6471). Receptor activity was modeled with three additive approaches: effect summation, relative potency factors (RPF), and generalized concentration addition (GCA). While RPF and GCA accurately predicted activity for mixtures of full hPPAR agonists, only GCA predicted activity for full and partial hPPAR agonists and a full agonist and antagonist. We then generated concentration response curves for seven PFAS, which were well-fit with three-parameter Hill functions. The four perfluorinated carboxylic acids (PFCA) tended to act as full hPPAR agonists while the three perfluorinated sulfonic acids (PFSA) tended to act as partial agonists that varied in efficacy between 28-67% of the full agonist, positive control level. GCA and RPF performed equally well at predicting the effects of mixtures with three PFCAs, but only GCA predicted experimental activity with mixtures of PFSAs and a mixture of PFCAs and PFSAs at ratios found in the general population. We conclude that of the three approaches, GCA most accurately models the effect of PFAS mixtures on hPPAR activity in vitro. HighlightsO_LIPerfluorinated carboxylic acids are full human PPAR agonists C_LIO_LIPerfluorinated sulfonic acids are partial human PPAR agonists C_LIO_LIGCA predicts human PPAR activity for mixtures of full and partial agonists C_LIO_LIGCA predicts human PPAR activity for mixtures of agonists and competitive antagonists C_LIO_LIGCA accurately predicts human PPAR activity in response to PFAS mixtures C_LI