Tripterygium glycosides tablet (TGT) demonstrates significant therapeutic efficacy in treating various autoimmune diseases. However, its clinical application is substantially limited by drug-induced liver injury, highlighting the need to identify the key toxic drivers and underlying mechanisms. To address this, we aimed to characterize the pharmacokinetic profiles and cellular heterogeneity-related toxic mechanisms of TGT-induced hepatic injury by integrating ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), molecular docking, cell counting kit-8 (CCK-8) assay, an acute liver injury model, and single-cell RNA sequencing with cellular validation. Results showed that triptolide and celastrol, two major toxic components of TGT, were present in defined proportions and exhibited strong binding affinities to known hepatotoxic targets of TGT. Subsequent in vitro experiments confirmed that 0.34 μM celastrol synergistically enhanced the cytotoxicity of 0.01 μM triptolide in AML12 cells. Pharmacokinetic analysis and enzymatic activity assay revealed that celastrol inhibited the metabolic enzyme CYP3A4, thereby reducing triptolide degradation and increasing its hepatic accumulation. Histopathological evaluations verified that the liver injury patterns induced by the triptolide-celastrol combination were consistent with those caused by TGT, confirming their synergistic toxicity. Furthermore, single-cell transcriptomic analysis of TGT-induced acute liver injury in mice and cellular experiments identified that this compound combination activated hepatic stellate cell fibrogenesis, disrupted hepatocyte iron-lipid homeostasis, and triggered oxidative stress-apoptosis cascades in biliary epithelial cells. Collectively, these findings demonstrate that the metabolic interaction and cellular cooperativity between triptolide and celastrol are pivotal drivers of TGT-induced hepatotoxicity, providing crucial insights into the mechanistic basis of TGT-related liver injury and potential strategies for clinical risk mitigation.
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Shen et al. (2026) studied this question.
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