Testing for departures from additivity in mixtures of perfluoroalkyl acids (PFAAs)

Abstract

This study is a follow-up to a paper by Carr et al. that determined a design structure to optimally test for departures from additivity in a fixed ratio mixture of four perfluoroalkyl acids (PFAAs) using an in vitro transiently-transfected COS-1 PPARα reporter model with a mixing ratio that is based on average serum levels in NHANES subjects. Availability of information regarding potential for additivity of PFAAs in mixtures is critically important for risk assessors who are concerned with the ability of the compounds to affect human health and impact ecological systems. It is clear that exposures are not to single compounds, but to mixtures of the PFAAs. This paper presents the results from the data collected using the design from Carr et al. along with subsequent analyses that were performed to classify the relationships among mixtures of PFAAs. A non-linear logistic additivity model was employed to predict relative luciferase units (RLU), an indicator of PPARα activation. The results indicated a less than additive relationship among the four PFAAs. To determine if the possible "antagonism" is from the competition among or between carboxylates and sulfonates, four different binary mixtures were also studied. There was a less than additive relationship in all four binary mixtures. These findings are generally similar to two other reports of interfering interactions between PFAAs in mixtures. The most conservative interpretation for our data would be an assumption of additivity (and lack of a greater than additive interaction), with a potential for antagonistic interactions.

Fig. 1

Single chemical model fit from additivity model.

Fig. 2

Mixture model fit under additivity assumption.

Fig. 3

Simultaneous plot of models with and without additivity assumption.

Fig. 4

Binary mixture plots.