Paired Liver:Plasma PFAS Concentration Ratios from Adolescents in the Teen-LABS Study and Derivation of Empirical and Mass Balance Models to Predict and Explain Liver PFAS Accumulation
Brittney O. Baumert, Fabian C. Fischer, Flemming Nielsen, Philippe Grandjean, Scott M. Bartell, Nikos Stratakis, Douglas I. Walker, Damaskini Valvi, Rohit Kohli, Thomas H. Inge, Justin R. Ryder, Todd Jenkins, Stephanie Sisley, Stavra A. Xanthakos, Sarah Rock, Michele A. La Merrill, David V. Conti, Rob McConnell, Lida Chatzi
Abstract
Animal studies have pointed at the liver as a hotspot for per- and polyfluoroalkyl substances (PFAS) accumulation and toxicity; however, these findings have not been replicated in human populations. We measured concentrations of seven PFAS in matched liver and plasma samples collected at the time of bariatric surgery from 64 adolescents in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study. Liver:plasma concentration ratios were perfectly explained ( r 2 > 0.99) in a multilinear regression (MLR) model based on toxicokinetic (TK) descriptors consisting of binding to tissue constituents and membrane permeabilities. Of the seven matched plasma and liver PFAS concentrations compared in this study, the liver:plasma concentration ratio of perfluoroheptanoic acid (PFHpA) was considerably higher than the liver:plasma concentration ratio of other PFAS congeners. Comparing the MLR model with an equilibrium mass balance model (MBM) suggested that complex kinetic transport processes are driving the unexpectedly high liver:plasma concentration ratio of PFHpA. Intratissue MBM modeling pointed to membrane lipids as the tissue constituents that drive the liver accumulation of long-chain, hydrophobic PFAS, whereas albumin binding of hydrophobic PFAS dominated PFAS distribution in plasma. The liver:plasma concentration data set, empirical MLR model, and mechanistic MBM modeling allow the prediction of liver from plasma concentrations measured in human cohort studies. Our study demonstrates that combining biomonitoring data with mechanistic modeling can identify underlying mechanisms of internal distribution and specific target organ toxicity of PFAS in humans.