High-Throughput Transcriptomics for Mechanism-Informed Mixture Risk Assessment of Perfluoroalkyl Substances Using Human Biomonitoring Data.

Shared perturbation of PPAR signaling and lipid metabolism pathways across nine PFAS enables mechanistically informed transcriptomic points of departure.

• Why it matters: Understanding shared toxicological mechanisms among PFAS is crucial due to widespread human exposure and limited toxicological data, to improve mixture risk assessment.
• What they did: Researchers reanalyzed high-throughput transcriptomic datasets from human liver spheroids, integrating benchmark dose modeling and pathway enrichment analysis for nine PFAS, including legacy and short-chain compounds.
• The result: Shared pathway perturbations were identified, with long-chain PFAS showing greater overall effects; derived tPODs were generally consistent with or more conservative than apical PODs, supporting early-tier mixture risk assessment.