Development of a Liquid Chromatography-Mass Spectrometry-Based In Vitro Assay to Assess Changes in Steroid Hormones Due to Exposure to Per- and Polyfluoroalkyl Substances.

Per- and poly-fluorinated substances (PFASs) are organic pollutants that have been linked to numerous health effects, including diabetes, cancers, and dysregulation of the endocrine system. This study aims to develop a liquid chromatography with tandem mass spectrometry (LC-MS/MS) assay to measure changes in 17 hormones in H295R cell line (a steroid producing adrenocortical cells) upon exposure to PFASs. Due to the challenges in the analysis of steroid hormones using electrospray ionization MS, a chemical derivatization method was employed to achieve 0.07-2 μg/L detection limits in LC-MS/MS. Furthermore, a 10-fold concentration factor through solid-phase extraction (SPE) allows for consistent sub-parts per billion detections. Optimization of the derivatization conditions showed doubly-derivatized products in some hormone analytes, including progesterone, corticosterone, and cortisol, and gave improved ionization efficiency up to 20-fold higher signal than the singly-derivatized product. The use of SPE for sample cleanup to analyze hormones from cellular media using weak anion exchange sorbent yielded 80-100% recovery for the 17 targeted hormones. The method was validated by exposing H295R cells to two known endocrine disruptors, forskolin and prochloraz, which showed expected changes in hormones. An initial exposure of H295R cells with various PFAS standards and their mixtures at 1 μM showed significant increases in progestogens with some PFAS treatments, which include PFBS, PFHxA, PFOS, PFDA, and PFDS. In addition, modest changes in hormone levels were observed in cells treated with other sulfonated or carboxylated headgroup PFASs. This sensitive LC-MS/MS method for hormone analysis in H295R cells will allow for the investigations of the alterations in the hormone production caused by exposure to various environmental insults in cell-based assays and other models.