Unraveling Human Hepatocellular Responses to PFAS and Aqueous Film-Forming Foams (AFFFs) for Molecular Hazard Prioritization and In Vivo Translation

Abstract

Aqueous film-forming foams (AFFFs) are complex product mixtures that often contain per- and polyfluorinated alkyl substances (PFAS) to enhance fire suppression and protect firefighters. However, PFAS have been associated with a range of adverse health effects (e.g., liver and thyroid disease and cancer), and innovative approach methods to better understand their toxicity potential and identify safer alternatives are needed. In this study, we investigated a set of 30 substances (e.g., AFFF, PFAS, and clinical drugs) using differentiated cultures of human hepatocytes (HepaRG, 2D), high-throughput transcriptomics, deep learning of cell morphology images, and liver enzyme leakage assays with benchmark dose analysis to (1) predict the potency ranges for human liver injury, (2) delineate gene- and pathway-level transcriptomic points-of-departure for molecular hazard characterization and prioritization, (3) characterize human hepatocellular response similarities to inform regulatory read-across efforts, and (4) introduce an innovative approach to translate mechanistic hepatocellular response data to predict the potency ranges for PFAS-induced hepatomegaly in vivo. Collectively, these data fill important mechanistic knowledge gaps with PFAS/AFFF and represent a scalable platform to address the thousands of PFAS in commerce for greener chemistries and next-generation risk assessments.

Keywords: AFFF; CAR; PFAS; PPARα; VDR; biological-response similarity; environmental health; hepatomegaly; human liver injury; prioritization; transcriptomic response pathways; translation.

Figure 1

Accumulation plot summarizing the potency-ordered distribution of transcriptomic benchmark concentrations (BMCs) versus their respective BMC rank orders (i.e., independent experiments Run1 and Run2) with tabulated BMC totals. Red line portrays the statistically defined liver injury threshold at the 105^th potency-ordered BMC (i.e., BMC105) to estimate potency ranges for human liver injury, as described in Materials and Methods. A suppositional average constituent molecular weight of 300 Da was used for 7 AFFF-related products to enable relative comparisons, as described in Materials and Methods.

Figure 2

Accumulation plots for experimental Run1 highlighting PPARα pathway potencies (median gene in pathway) using Wikipathway (MSigDB7.2) gene sets. Comparable responses were observed in experimental Run2 (Supporting Information).

Figure 3

Venn diagram comparing the intersecting gene- and pathway-level transcriptomic response similarities for 5 MIL-SPEC-qualified AFFFs in human hepatocytes across 2 independent experiments.

Figure 4

Venn diagram comparing the overlap of identified transcriptomic BMCs for PFOS, PFHxS, and 6,2-FTS at the gene- and pathway-level by their consensus (intersecting) responses across 2 independent experiments.

Figure 5

Constellation plot of hierarchical clustering of rank order scores for the top 100 most potent BMCs and top 100 BMCs with highest maximum fold-change gene-level BMCs, as described in Materials and Methods.

Figure 6

Comparison of in vivo plasma concentrations at the liver weight LOEL (violet triangles) from National Toxicology Program 28 day studies to in vitro human hepatocyte transcriptomic pathway potencies (nominal) with established causal associations to liver weight change. Here, red circles indicate mean in vitro CAR BMC_Median values with solid red lines reflecting the 2-fold potency range, dotted red lines reflecting the 3-fold potency range, and vertical line markers reflecting the statistically derived BMCL and BMCU boundary values for the CAR and PPARα pathways over independent experiments (summarized BMC ranges for each experiment provided in Table S13).