Potency Ranking of Per- and Polyfluoroalkyl Substances Using High-Throughput Transcriptomic Analysis of Human Liver Spheroids

Identifying Human Specific Adverse Outcome Pathways of Per- and Polyfluoroalkyl Substances Using Liver-Chimeric Humanized Mice

Background

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants with myriad adverse effects. While perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are the most common contaminants, levels of replacement PFAS, such as perfluoro-2-methyl-3-oxahexanoic acid (GenX), are increasing. In rodents, PFOA, PFOS, and GenX have several adverse effects on the liver, including nonalcoholic fatty liver disease.

Objective

We aimed to determine human-relevant mechanisms of PFAS induced adverse hepatic effects using FRG liver-chimeric humanized mice with livers repopulated with functional human hepatocytes.

Methods

Male humanized mice were treated with 0.067 mg/L of PFOA, 0.145 mg/L of PFOS, or 1 mg/L of GenX in drinking water for 28 days. Liver and serum were collected for pathology and clinical chemistry, respectively. RNA-sequencing coupled with pathway analysis was used to determine molecular mechanisms.

Results

PFOS caused a significant decrease in total serum cholesterol and LDL/VLDL, whereas GenX caused a significant elevation in LDL/VLDL with no change in total cholesterol and HDL. PFOA had no significant changes in serum LDL/VLDL and total cholesterol. All three PFAS induced significant hepatocyte proliferation. RNA-sequencing with alignment to the human genome showed a total of 240, 162, and 619 differentially expressed genes after PFOA, PFOS, and GenX exposure, respectively. Upstream regulator analysis revealed inhibition of NR1D1, a transcriptional repressor important in circadian rhythm, as the major common molecular change in all PFAS treatments. PFAS treated mice had significant nuclear localization of NR1D1. In silico modeling showed PFOA, PFOS, and GenX potentially interact with the DNA-binding domain of NR1D1.

Discussion

These data implicate PFAS in circadian rhythm disruption via inhibition of NR1D1. These studies show that FRG humanized mice are a useful tool for studying the adverse outcome pathways of environmental pollutants on human hepatocytes in situ.

Internal Relative Potency Factors for the Risk Assessment of Mixtures of Per- and Polyfluoroalkyl Substances (PFAS) in Human Biomonitoring

BACKGROUND

In human biomonitoring, blood is often used as a matrix to measure exposure to per- and polyfluoroalkyl substances (PFAS). Because the toxicokinetics of a substance (determining the steady-state blood concentration) may affect the toxic potency, the difference in toxicokinetics among PFAS has to be accounted for when blood concentrations are used in mixture risk assessment.

OBJECTIVES

This research focuses on deriving relative potency factors (RPFs) at the blood serum level. These RPFs can be applied to PFAS concentrations in human blood, thereby facilitating mixture risk assessment with primary input from human biomonitoring studies.

METHODS

Toxicokinetic models are generated for 10 PFAS to estimate the internal exposure in the male rat at the blood serum level over time. By applying dose-response modeling, these internal exposures are used to derive quantitative internal RPFs based on liver effects.

RESULTS

Internal RPFs were successfully obtained for nine PFAS. Perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), perfluorononanoic acid (PFNA), perfluorododecanoic acid (PFDoDA), perfluorooctane sulfonic acid (PFOS), and hexafluoropropylene oxide-dimer acid (HFPO-DA, or GenX) were found to be more potent than perfluorooctanoic acid (PFOA) at the blood serum level in terms of relative liver weight increase, whereas perfluorobutane sulfonic acid (PFBS) and perfluorohexane sulfonic acid (PFHxS) were found to be less potent. The practical implementation of these internal RPFs is illustrated using the National Health and Nutrition Examination Survey (NHANES) biomonitoring data of 2017-2018.

DISCUSSION

It is recommended to assess the health risk resulting from exposure to PFAS as combined, aggregate exposure to the extent feasible. https://doi.org/10.1289/EHP10009.

Predicting the effects of per- and polyfluoroalkyl substance mixtures on peroxisome proliferator-activated receptor alpha activity in vitro

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 α (PPARα). 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 PPARα ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPARα (hPPARα) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 h with two full hPPARα agonists (pemafibrate and GW7647), a full and a partial hPPARα agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPARα 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 hPPARα agonists, only GCA predicted activity for full and partial hPPARα 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 hPPARα 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 hPPARα activity in vitro. Understanding the differences in efficacy with which PFAS activate hPPARα is essential for accurately predicting the effects of PFAS mixtures. As PFAS can activate multiple nuclear receptors, future analyses should examine mixtures effects in intact cells where multiple molecular initiating events contribute to proximate effects and functional changes.