A gene expression profile-based approach to screen the occurrence and predisposed host characteristics of drug-induced liver injury: a case study of Psoralea corylifolia Linn - Zhang, Ming-Liang; Li, Wei-Xia; Wang, Xiao-Yan; Zhang, Hui; Wu, Ya-Li; Yang, Liu-Qing; Chen, Xiao-Fei; Zhang, Shu-Qi; Chen, Yu-Long; Feng, Ke-Ran; Tang, Jin-Fa (Frontiers in Chemistry, 2023)
Drug-induced liver injury (DILI) is the crucial cause of drug withdrawal, and identifying the culprit drugs and the host factors at risk of DILI has become the current challenge. Recent studies found that immune status plays a considerable role in the development of DILI. In the study, DILI-related differentially expressed genes mediated by immunoinflammatory cytokines were obtained from the Gene Expression Omnibus (GEO) database to predict the occurrence of DILI (named DILI predictive gene set, DILI_PGS), and the predictability of the DILI_PGS was verified by the platforms of Connectivity Map (CMap) and LiverTox. The results obtained DILI_PGS via the GEO database which could predict 81.25% of liver injury drugs. In addition, the Coexpedia platform was used to predict the DILI_PGS-related characteristics of common host diseases and found that DILI_PGS mainly involved immune-related diseases and tumor-related diseases. Then, the animal models of immune stress (IS) and immunosuppression (IP) were selected to simulate the immune status of the above diseases. Meanwhile, psoralen, a main component deriving from Psoralea corylifolia Linn. with definite hepatotoxicity, was selected as an experimental drug with highly similar molecular fingerprints to 3 idiosyncratic hepatotoxic drugs (nefazodone, trovafloxacin, nimesulide) from the same dataset of DILI_PGS. Animal experiment results found single administration of psoralen could significantly induce liver injury in IS mice, while there was no obvious liver function change in IP mice by repeatedly administering the same dose of psoralen, and the potential mechanism of psoralen-induced liver injury in IS mice may be related to regulating the expression of TNF-related pathway. In conclusion, this study constructed the DILI_PGS with high accuracy to predict the occurrence of DILI and preliminarily identified the characteristics of host factors inducing DILI.