Integration of Toxicogenomics and Physiologically Based Pharmacokinetic Modeling in Human Health Risk Assessment of Perfluorooctane Sulfonate

Toxicogenomics and
physiologically based pharmacokinetic (PBPK)
models are useful approaches in chemical risk assessment, but the
methodology to incorporate toxicogenomic data into a PBPK model to
inform risk assessment remains to be developed. This study aimed to
develop a probabilistic human health risk assessment approach by integrating
toxicogenomic dose–response data and PBPK modeling using perfluorooctane
sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic
data, we identified the differentially expressed genes (DEGs) at each
exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes
and disease ontology enrichment analyses were conducted on the DEGs
to identify significantly enriched pathways and diseases. The dose–response
data of DEGs were analyzed using the Bayesian benchmark dose (BMD)
method. Using a previously published PBPK model, the gene BMDs were
converted to human equivalent doses (HEDs), which were summarized
to pathway and disease HEDs and then extrapolated to reference doses
(RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data.
The results suggested that the median RfDs at different exposure paradigms
were similar to the 2016 U.S. Environmental Protection Agency’s
recommended RfD, while the RfDs for the most sensitive pathways and
diseases were closer to the recent European Food Safety Authority’s
guidance values. In conclusion, genomic dose–response data
and PBPK modeling can be integrated to become a useful alternative
approach in risk assessment of environmental chemicals. This approach
considers multiple endpoints, provides toxicity mechanistic insights,
and does not rely on apical toxicity endpoints.