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

Ming-Liang Zhang; Wei-Xia Li; Xiao-Yan Wang; Hui Zhang; Ya-Li Wu; Liu-Qing Yang; Xiao-Fei Chen; Shu-Qi Zhang; Yu-Long Chen; Ke-Ran Feng; Jin-Fa Tang

doi:10.3389/fchem.2023.1259569

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

Front Chem. 2023 Oct 6:11:1259569. doi: 10.3389/fchem.2023.1259569. eCollection 2023.

Authors

Ming-Liang Zhang^{1

2

3

4}, Wei-Xia Li^{1

2

3

4}, Xiao-Yan Wang^{1

2

3

4}, Hui Zhang^{1

2

3

4}, Ya-Li Wu^{1

2

3

4}, Liu-Qing Yang^{1

2

3

4}, Xiao-Fei Chen^{1

2

3

4}, Shu-Qi Zhang^{1

2

3

4}, Yu-Long Chen⁵, Ke-Ran Feng^{1

2

3

4}, Jin-Fa Tang^{1

2

3

4

5}

Affiliations

¹ The Department of Pharmacy, First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, China.
² Henan Province Engineering Research Center for Clinical Application, Evaluation and Transformation of Traditional Chinese Medicine, Zhengzhou, China.
³ Henan Provincial Key Laboratory for Clinical Pharmacy of Traditional Chinese Medicine, Zhengzhou, China.
⁴ Henan Province Engineering Research Center of Safety Evaluation and Risk Management of Traditional Chinese Medicine, Zhengzhou, China.
⁵ Henan University of Traditional Chinese Medicine, Zhengzhou, China.

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Drug-induced liver injury (DILI) is one of the most common causes of a drug being withdrawn, and identifying the culprit drugs and the host factors at risk of causing DILI has become a current challenge.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.

Keywords: differentially expressed genes; drug-induced liver injury; host characteristics; predict; psoralen.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (Nos. 82173993 and 82004021), the Key Project of Henan Province for Scientific Research of Traditional Chinese Medicine, China (No. 2019ZYBJ08), the Key Scientific Research Projects of Colleges and Universities in Henan Province, China (No. 19A360007), and Science and Technology Innovation Team in Universities of Henan Province (No. 23IRTSTHN026).