Integrating high-throughput phenotypic profiling and transcriptomic analyses to predict the hepatosteatosis effects induced by per- and polyfluoroalkyl substances

Abstract

Per- and polyfluoroalkyl substances (PFAS) is a large compound class (n > 12,000) that is extensively present in food, drinking water, and aquatic environments. Reduced serum triglycerides and hepatosteatosis appear to be the common phenotypes for different PFAS chemicals. However, the hepatosteatosis potential of most PFAS chemicals remains largely unknown. This study aims to investigate PFAS-induced hepatosteatosis using in vitro high-throughput phenotype profiling (HTPP) and high-throughput transcriptomic (HTTr) data. We quantified the in vitro hepatosteatosis effects and mitochondrial damage using high-content imaging, curated the transcriptomic data from the Gene Expression Omnibus (GEO) database, and then calculated the point of departure (POD) values for HTPP phenotypes or HTTr transcripts, using the Bayesian benchmark dose modeling approach. Our results indicated that PFAS compounds with fully saturated C-F bonds, sulfur- and nitrogen-containing functional groups, and a fluorinated carbon chain length greater than 8 have the potential to produce biological effects consistent with hepatosteatosis. PFAS primarily induced hepatosteatosis via disturbance in lipid transport and storage. The potency rankings of PFAS compounds are highly concordant among in vitro HTPP, HTTr, and in vivo hepatosteatosis phenotypes (ρ = 0.60-0.73). In conclusion, integrating the information from in vitro HTPP and HTTr analyses can accurately project in vivo hepatosteatosis effects induced by PFAS compounds.

Keywords: Hepatosteatosis; Hepatotoxicity; High-content imaging; High-throughput transcriptomics (HTTr); Per-and poly-fluoroalkyl substances.