Physiologically based pharmacokinetic (PBPK) modeling of perfluorohexane sulfonate (PFHxS) in humans

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Highlights

  • Serum and urine PFHxS data were used for model calibration and evaluation.

  • Gender specific renal resorption parameter values were calibrated.

  • Calendar year and age-specific PFHxS exposure descriptors were calibrated.

  • Exposure times to an internal target serum concentration of 5 ng/ml were estimated.

Abstract

Per- and polyfluoroalkyl substances (PFAS) are persistent, man-made compounds prevalent in the environment and consistently identified in human biomonitoring samples. In particular, perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS) have been identified at U.S. Air Force installations. The study of human toxicokinetics and physiologically based pharmacokinetic (PBPK) modeling of PFHxS has been less robust and has been limited in scope and application as compared to PFOS and PFOA. The primary goal of the current effort was to develop a PBPK model describing PFHxS disposition in humans that can be applied to retrospective, current, and future human health risk assessment of PFHxS. An existing model developed for PFOS and PFOA was modified and key parameter values for exposure and toxicokinetics were calibrated for PFHxS prediction based on human biomonitoring data, particularly general population serum levels from the U.S. Centers for Disease Prevention and Control (CDC) National Health and Nutrition Examination Survey (NHANES). Agreement between the model and the calibration and evaluation data was excellent and recapitulated observed trends across sex, age, and calendar years. Confidence in the model is greatest for application to adults in the 2000–2018 time frame and for shorter-term future projections.

Introduction

Per- and polyfluoroalkyl substances (PFAS) are persistent, man-made compounds prevalent in the environment and consistently identified in human biomonitoring samples (CDC, 2021, East et al., 2021). In particular, perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS) have been identified at U.S. Air Force installations. As reported by East et al. (2021), “We applied a data science approach to characterize and prioritize PFAS and PFAS mixtures from a large dataset of PFAS measurements in surface waters associated with US Air Force Installations with a history of the use of aqueous film-forming foams (AFFFs). Several iterations of stakeholder feedback culminated in a few main points [ …. ] First, perfluorooctane sulfonate (PFOS) was often a dominant PFAS in a given surface water sample, frequently followed by perfluorohexane sulfonate (PFHxS). Second, a 4-chemical mixture generally accounted for >80% of the sum of all routinely reported PFAS in a sample, and the most representative 4-chemical mixture was composed of PFOS, PFHxS, perfluorohexanoic acid (PFHxA), and perfluorooctanoic acid (PFOA).”

Associations between PFHxS plasma/serum levels and health effect biomarkers have been noted in cross-sectional studies of the general population. Endpoints identified in these studies as associated with serum PFHxS level included increased androgens (a risk factor for cardiometabolic diseases) in overweight/obese postmenopausal women (Wang et al., 2021), altered thyroid function (free T4 levels) in nonsmokers (van Gerwen et al., 2020), and increased inflammatory and oxidative stress markers (increased lymphocyte counts and increased serum iron, albumin, and total bilirubin) (Omoike et al., 2020). However, associations may be manifestations of reverse causality (Andersen et al., 2021). For example, changes in renal function (Jain and Ducatman, 2019) may produce changes in plasma PFAS concentration, rather than the other way around. Furthermore, in these cross-sectional studies, attribution of causality to PFHxS may be spurious due to potential correlation with exposure to other chemicals (especially other PFAS) or potency overestimated due to co-exposure to other chemical classes with potential to contribute to the same observed effect.

The toxicokinetics of PFOS and PFOA have been extensively studied and modeled in support of human health risk assessment (e.g., Loccisano et al., 2011; Worley et al., 2017; Chou and Lin 2019, 2020; Ruark et al., 2017; Deepika et al., 2021). The model structures are very similar, consisting of a plasma compartment and distribution of unbound compound via plasma flow into several tissue compartments. The chemical was assumed to be cleared by way of renal filtration of unbound compound, with potential reuptake into the kidney mediated via organic anion transporting peptides (OATPs) (Han et al., 2012). The earlier model of Andersen et al. (2021) also incorporated the element of saturable reuptake, but was a simpler model with fewer compartments.

In contrast, study of human toxicokinetics and physiologically based pharmacokinetic (PBPK) modeling of PFHxS has been less robust and limited in scope and application, and has relied on models with structures similar to those employed for PFOS and PFOA (Fabrega et al., 2015; Kim et al., 2018). With respect to general kinetics of PFHxS in rats, shorter plasma half lives were observed for females as compared to males in at least three separate studies (Sundstrom et al., 2012; Huang et al., 2019, Kim et al., 2016). That finding is consistent with other PFAS (PFOA, in particular) and the difference has often been attributed to differences in abundance of transporters responsible for renal resorption of PFAS by OATPs (Kudo et al., 2002). PFOS and PFHxS demonstrated similar KM values for human Na+/taurocholate cotransporting peptide (a hepatocyte bile acid transporter) when expressed in CHO cells (Zhao et al., 2015). Three human OATPs and 3 rat OATPs also displayed uptake capabilities for PFBS, PFHxS, and PFOS (Zhao et al., 2017). No studies specifically addressing kidney transporter uptake of PFHxS were identified.

A more rigorously evaluated PBPK model for human PFHxS disposition that incorporates historical trends in PFHxS exposure will support human health risk assessment where potential effects of PFHxS are of concern, whether alone or more likely as part of a mixture (East et al., 2021). The primary goal of the current effort was to develop a human PBPK model for PFHxS disposition in adults that can be applied to retrospective, current, and future human health risk assessment of PFHxS in U.S. adults. In addition, the strategies used to develop and evaluate this model have the potential to serve as a template for other human PFAS PBPK models with similar data availability.

Section snippets

Overview

The general workflow toward using PBPK models for human health risk assessment involving PFHxS exposure involved three phases: scoping, model refinement and evaluation, and application. These phases are described in additional detail in the following paragraphs and the Supplementary Material.

Scoping phase

The scoping phase included review of existing human PBPK models for PFHxS and other PFAS, review and analysis of human PFHxS biomonitoring data sets; identification of needed/desirable features for the PBPK

Scoping phase and initial model refinement and evaluation

The key findings of the scoping phase and the initial stages of model refinement and evaluation were reported in detail in the Supplementary Materials (additional text, Figure S-1 and Tables S-1 to S-4). Those findings are briefly summarized here. Two published human PBPK models of PFHxS were identified (Kim et al., 2018; Fàbrega et al., 2015). The model structures were very similar, consisting of a plasma compartment and distribution of unbound compound via plasma flow into several tissue

Conclusions

Confidence in the model is greatest for application to adults in the 2000–2018 time frame and for shorter term future projections. U.S. data for periods prior to the earliest NHANES data were very limited. The 1974 and 1989 data from the Hagerstown area (Olsen et al., 2005, Fig. 2) were chosen for parameterizing changes in historic U.S. exposure (1950–1990) because the 1989 data appeared consistent with ∼1999–2000 NHANES data. The NHANES predictions (2000–2018) have limited sensitivity to the

Disclaimers

This document is published in the interest of scientific and technical information exchange, and its publication does not constitute the Government's approval or disapproval of its ideas or findings. Dr. Sweeney is a contractor working with Air Force Research Laboratory/711th Human Performance Wing and the views expressed in this article are her own and do not necessarily reflect the views of the Air Force, Department of Defense, or her employer, UES, Inc.

Funding statement

This work was funded through the Department of Defense, Office of the Under Secretary of Defense for Research and Engineering, Applied Research for the Advancement of Science and Technology Priorities PE #0602251D8Z.

CRediT authorship contribution statement

Lisa M. Sweeney: Conceptualization, Methodology, Software, Formal analysis, Data curation, Writing – original draft, Visualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The author thanks Ms. Teri Sterner and Dr. Matt Linakis (Air Force Research Laboratory) for assistance with document preparation and helpful comments and discussion. She also thanks Dr. Jim Smith (Navy and Marine Corps Public Health Center) for helpful comments.

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