New Approach Methods for Hazard Identification: A Case Study with Azole Fungicides Affecting Molecular Targets Associated with the Adverse Outcome Pathway for Cholestasis.
Constanze KnebelRoderich D SüssmuthHelen S HammerAlbert BraeuningPhilip Marx-StoeltingPublished in: Cells (2022)
Triazole fungicides such as propiconazole (Pi) or tebuconazole (Te) show hepatotoxicity in vivo, e.g., hypertrophy and vacuolization of liver cells following interaction with nuclear receptors such as PXR (pregnane-X-receptor) and CAR (constitutive androstane receptor). Accordingly, azoles affect gene expression associated with these adverse outcomes in vivo but also in human liver cells in vitro. Additionally, genes indicative of liver cholestasis are affected in vivo and in vitro. We therefore analyzed the capability of Pi and Te to cause cholestasis in an adverse outcome pathway (AOP)-driven approach in hepatic cells of human origin in vitro, considering also previous in vivo studies. Bile salt export pump (BSEP) activity assays confirmed that both azoles are weak inhibitors of BSEP. They alternate the expression of various cholestasis-associated target genes and proteins as well as the mitochondrial membrane function. Published in vivo data, however, demonstrate that neither Pi nor Te cause cholestasis in rodent bioassays. This discrepancy can be explained by the in vivo concentrations of both azoles being well below their EC50 for BSEP inhibition. From a regulatory perspective, this illustrates that toxicogenomics and human in vitro models are valuable tools to detect the potential of a substance to cause a specific type of toxicity. To come to a sound regulatory conclusion on the in vivo relevance of such a finding, results will have to be considered in a broader context also including toxicokinetics in a weight-of-evidence approach.
Keyphrases
- induced apoptosis
- gene expression
- drug induced
- cell cycle arrest
- oxidative stress
- genome wide
- endoplasmic reticulum stress
- dna methylation
- randomized controlled trial
- signaling pathway
- systematic review
- binding protein
- bioinformatics analysis
- big data
- physical activity
- body mass index
- induced pluripotent stem cells
- electronic health record
- cell proliferation
- weight loss
- artificial intelligence
- pi k akt
- genome wide identification
- single molecule
- deep learning
- case control
- single cell