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.

ABSTRACT

Drug-induced liver injury (DILI) is one of the most common causes of a drug being withdrawn, and identifying the culprit drugs and the host factors at risk of causing DILI has become a current challenge. Recent studies have found that immune status plays a considerable role in the development of DILI. In this 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 the DILI predictive gene set, DILI_PGS), and the predictability of the DILI_PGS was verified using the Connectivity Map (CMap) and LiverTox platforms. The results obtained DILI_PGS from the GEO database 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 the DILI_PGS mainly involved immune-related diseases and tumor-related diseases. Then, animal models of immune stress (IS) and immunosuppressive (IP) were selected to simulate the immune status of the above diseases. Meanwhile, psoralen, a main component derived from Psoralea corylifolia Linn. with definite hepatotoxicity, was selected as an experimental drug with highly similar molecular fingerprints to three idiosyncratic hepatotoxic drugs (nefazodone, trovafloxacin, and nimesulide) from the same DILI_PGS dataset. The animal experiment results found a 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 the 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.