Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry

Abstract

Concern over per- and polyfluoroalkyl substances (PFAS) has increased as more is learned about their environmental presence, persistence, and bioaccumulative potential. The limited monitoring, toxicokinetic (TK), and toxicologic data available are inadequate to inform risk across this diverse domain. Here, 73 PFAS were selected for in vitro TK evaluation to expand knowledge across lesser-studied PFAS alcohols, amides, and acrylates. Targeted methods developed using gas chromatography–tandem mass spectrometry (GC-MS/MS) were used to measure human plasma protein binding and hepatocyte clearance. Forty-three PFAS were successfully evaluated in plasma, with fraction unbound (fup) values ranging from 0.004 to 1. With a median fup of 0.09 (i.e., 91% bound), these PFAS are highly bound but exhibit 10-fold lower binding than legacy perfluoroalkyl acids recently evaluated. Thirty PFAS evaluated in the hepatocyte clearance assay showed abiotic loss, with many exceeding 60% loss within 60 min. Metabolic clearance was noted for 11 of the 13 that were successfully evaluated, with rates up to 49.9 μL/(min × million cells). The chemical transformation simulator revealed potential (bio)transformation products to consider. This effort provides critical information to evaluate PFAS for which volatility, metabolism, and other routes of transformation are likely to modulate their environmental fates.

A Comparison of In Vitro Points of Departure with Human Blood Levels for Per- and Polyfluoroalkyl Substances (PFAS)

“…The steady-state blood-to-plasma concentration ratio is predicted with a calibrated version of the Schmitt 2008 algorithm using the function httk::get_rblood2plasma() [ 34 , 35 ]. Chemical-specific in vitro plasma protein binding was recently measured and reported for ~120 PFAS compounds [ 36 , 37 , 38 ]. Httk includes in vivo measured blood:plasma ratios for four PFAS; for these chemicals, the in vivo values were used in place of the in vitro-derived predictions [ 39 ].…”

Risk-based prioritization of PFAS using phenotypic and transcriptomic data from human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes

“…This conversion used either human steady-state plasma concentrations (Css) from the httk R package (Pearce et al, 2017); or the predicted fraction unbound data from recent publications (Kreutz et al, 2023;Smeltz et al, 2023). See Css and exposure values for 18 PFAS that had available data from either source in Tab.…”

“…Second, exposure values used in our study were based on in silico predictions rather than empirical data. Third, multiple data sources that we used to inform IVIVE have limitations with respect to the uncertainties in chemical-specific kinetic information for PFAS (Kreutz et al, 2023;Smeltz et al, 2023). Collectively, the uncertainty in BER estimates for PFAS is considerable and more confident toxicokinetic data is needed for these substances.…”

“…Additional data, including that from in vitro studies, may provide a biological dimension for informing class-based approaches for read-across and/or within-group prioritization for additional testing. Indeed, toxicity and toxicokinetic data are being generated using in vitro testing and computational methodologies to inform PFAS hazard characterization (US EPA, 2019; Patlewicz et al, 2019Patlewicz et al, , 2022Kreutz et al, 2023;Dawson et al, 2023;Carstens et al, 2023). In addition, gene expression data offer a comprehensive understanding of chemical-induced bioactivity, delivering not only mechanistic insights but also dose-response information (Reardon et al, 2023;Johnson et al, 2022).…”