Advertisement

Archives of Toxicology

, Volume 91, Issue 9, pp 3039–3049 | Cite as

A review of drug-induced liver injury databases

  • Guangwen Luo
  • Yiting Shen
  • Lizhu Yang
  • Aiping LuEmail author
  • Zheng XiangEmail author
Review Article

Abstract

Drug-induced liver injuries have been a major focus of current research in drug development, and are also one of the major reasons for the failure and withdrawal of drugs in development. Drug-induced liver injuries have been systematically recorded in many public databases, which have become valuable resources in this field. In this study, we provide an overview of these databases, including the liver injury-specific databases LiverTox, LTKB, Open TG-GATEs, LTMap and Hepatox, and the general databases, T3DB, DrugBank, DITOP, DART, CTD and HSDB. The features and limitations of these databases are summarized and discussed in detail. Apart from their powerful functions, we believe that these databases can be improved in several ways: by providing the data about the molecular targets involved in liver toxicity, by incorporating information regarding liver injuries caused by drug interactions, and by regularly updating the data.

Keywords

Review Databases Drug-induced liver injury Hepatotoxicity Liver toxicity 

Notes

Acknowledgements

We would like to thank Dr. Hongdong Li for his useful discussions, comments and suggestions throughout this entire work. The authors acknowledge financial support from the Nature Foundation Committee of China (No. 31300819).

Author contributions

Conceived and designed the review: ZX and AL. Wrote the paper: GL, YS and LY.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Aleo MD, Luo Y, Swiss R, Bonin PD, Potter DM, Will Y (2014) Human drug-induced liver injury severity is highly associated with dual inhibition of liver mitochondrial function and bile salt export pump. Hepatology 60(3):1015–1022. doi: 10.1002/hep.27206 CrossRefPubMedGoogle Scholar
  2. Amberger J, Bocchini CA, Scott AF, Hamosh A (2009) McKusick’s online mendelian inheritance in man (OMIM). Nucleic acids research 37(Database issue):793–796. doi: 10.1093/nar/gkn665 CrossRefGoogle Scholar
  3. Antoine DJ, Jenkins RE, Dear JW et al (2012) Molecular forms of HMGB1 and keratin-18 as mechanistic biomarkers for mode of cell death and prognosis during clinical acetaminophen hepatotoxicity. J Hepatol 56(5):1070–1079. doi: 10.1016/j.jhep.2012.01.017 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Bjornsson ES (2016) Hepatotoxicity by drugs: the most common implicated agents. Int J Mol Sci 17(2):224. doi: 10.3390/ijms17020224 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bjornsson ES, Hoofnagle JH (2016) Categorization of drugs implicated in causing liver injury: critical assessment based on published case reports. Hepatology 63(2):590–603. doi: 10.1002/hep.28323 CrossRefPubMedGoogle Scholar
  6. Chen M, Vijay V, Shi Q, Liu Z, Fang H, Tong W (2011) FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discov Today 16(15–16):697–703. doi: 10.1016/j.drudis.2011.05.007 CrossRefPubMedGoogle Scholar
  7. Chen M, Zhang J, Wang Y et al (2013) The liver toxicity knowledge base: a systems approach to a complex end point. Clin Pharmacol Ther 93(5):409–412. doi: 10.1038/clpt.2013.16 CrossRefPubMedGoogle Scholar
  8. Chen MJ, Suzuki A, Borlak J, Andrade RJ, Lucena MI (2015) Drug-induced liver injury: interactions between drug properties and host factors. J Hepatol 63(2):503–514. doi: 10.1016/j.jhep.2015.04.016 CrossRefPubMedGoogle Scholar
  9. Chen M, Borlak J, Tong W (2016a) A Model to predict severity of drug-induced liver injury in humans. Hepatology 64(3):931–940. doi: 10.1002/hep.28678 CrossRefPubMedGoogle Scholar
  10. Chen M, Suzuki A, Thakkar S, Yu K, Hu C, Tong W (2016b) DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans. Drug Discov Today 21(4):648–653. doi: 10.1016/j.drudis.2016.02.015 CrossRefPubMedGoogle Scholar
  11. Davis AP, Grondin CJ, Lennon-Hopkins K et al (2015) The Comparative Toxicogenomics Database’s 10th year anniversary: update 2015. Nucleic Acids Res 43(Database issue):914–920. doi: 10.1093/nar/gku935 CrossRefGoogle Scholar
  12. Fonger GC, Hakkinen P, Jordan S, Publicker S (2014) The National Library of Medicine’s (NLM) Hazardous Substances Data Bank (HSDB): background, recent enhancements and future plans. Toxicology 325:209–216. doi: 10.1016/j.tox.2014.09.003 CrossRefPubMedGoogle Scholar
  13. Fontana RJ (2014) Pathogenesis of idiosyncratic drug-induced liver injury and clinical perspectives. Gastroenterology 146(4):914–928. doi: 10.1053/j.gastro.2013.12.032 CrossRefPubMedGoogle Scholar
  14. Fontana RJ, Watkins PB, Bonkovsky HL et al (2009) Drug-Induced Liver Injury Network (DILIN) prospective study: rationale, design and conduct. Drug Saf 32(1):55–68. doi: 10.2165/00002018-200932010-00005 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Ganter B, Snyder RD, Halbert DN, Lee MD (2006) Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database. Pharmacogenomics 7(7):1025–1044. doi: 10.2217/14622416.7.7.1025 CrossRefPubMedGoogle Scholar
  16. Gao W, Mizukawa Y, Nakatsu N et al (2010) Mechanism-based biomarker gene sets for glutathione depletion-related hepatotoxicity in rats. Toxicol Appl Pharmacol 247(3):211–221. doi: 10.1016/j.taap.2010.06.015 CrossRefPubMedGoogle Scholar
  17. German P, Greenhouse B, Coates C et al (2007) Hepatotoxicity due to a drug interaction between amodiaquine plus artesunate and efavirenz. Clin Infect Dis 44(6):889–891. doi: 10.1086/511882 CrossRefPubMedGoogle Scholar
  18. Goldkind L, Laine L (2006) A systematic review of NSAIDs withdrawn from the market due to hepatotoxicity: lessons learned from the bromfenac experience. Pharmacoepidemiol Drug Saf 15(4):213–220. doi: 10.1002/pds.1207 CrossRefPubMedGoogle Scholar
  19. Guo YX, Xu XF, Zhang QZ et al (2015) The inhibition of hepatic bile acids transporters Ntcp and Bsep is involved in the pathogenesis of isoniazid/rifampicin-induced hepatotoxicity. Toxicol Mech Methods 25(5):382–387. doi: 10.3109/15376516.2015.1033074 CrossRefPubMedGoogle Scholar
  20. Han D, Shinohara M, Ybanez MD, Saberi B, Kaplowitz N (2010) Signal transduction pathways involved in drug-induced liver injury. Handb Exp Pharmacol 196(196):267–310. doi: 10.1007/978-3-642-00663-0_10 CrossRefGoogle Scholar
  21. Hanafusa H, Morikawa Y, Uehara T et al (2014) Comparative gene and protein expression analyses of a panel of cytokines in acute and chronic drug-induced liver injury in rats. Toxicology 324(10):43–54. doi: 10.1016/j.tox.2014.07.005 CrossRefPubMedGoogle Scholar
  22. Haque T, Sasatomi E, Hayashi PH (2016) Drug-induced liver injury: pattern recognition and future directions. Gut Liver 10(1):27–36. doi: 10.5009/gnl15114 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Hoofnagle JH, Serrano J, Knoben JE, Navarro VJ (2013) LiverTox: a website on drug-induced liver injury. Hepatology 57(3):873–874. doi: 10.1002/hep.26175 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Huang SH, Tung CW, Fulop F, Li JH (2015) Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicines. Food Chem Toxicol Int J Publ Br Ind Biol Res Assoc 78:71–77. doi: 10.1016/j.fct.2015.01.020 CrossRefGoogle Scholar
  25. Hunt CM, Papay JI, Stanulovic V, Regev A (2017) Drug rechallenge following drug-induced liver injury. Hepatology. doi: 10.1002/hep.29152 Google Scholar
  26. Hussein R, El-Halabi M, Ghaith O et al (2011) Severe hepatotoxicity associated with the combination of spiramycin plus metronidazole. Arab J Gastroenterol Off Publ Pan Arab Assoc Gastroenterol 12(1):44–47. doi: 10.1016/j.ajg.2010.11.001 Google Scholar
  27. Igarashi Y, Nakatsu N, Yamashita T et al (2015) Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res 43(Database issue):921–927. doi: 10.1093/nar/gku955 CrossRefGoogle Scholar
  28. Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40(D1):109–114. doi: 10.1093/nar/gkr988 CrossRefGoogle Scholar
  29. Karthivashan G, Arulselvan P, Fakurazi S (2015) Pathways involved in acetaminophen hepatotoxicity with specific targets for inhibition/downregulation. RSC Adv 5(76):62040–62051. doi: 10.1039/c5ra07838e CrossRefGoogle Scholar
  30. Ke Y, Jie Z, Chen M et al (2014) Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study. BMC Bioinformatics 15(17):S6Google Scholar
  31. Kondo C, Minowa Y, Uehara T et al (2009) Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database. Toxicology 265(1–2):15–26. doi: 10.1016/j.tox.2009.09.003 CrossRefPubMedGoogle Scholar
  32. Krauskopf J, Caiment F, Claessen SM et al (2015) Application of high-throughput sequencing to circulating microRNAs reveals novel biomarkers for drug-induced liver injury. Toxicol Sci Off J Soc Toxicol 143(2):268–276. doi: 10.1093/toxsci/kfu232 CrossRefGoogle Scholar
  33. Kresse M, Latta M, Kunstle G et al (2005) Kupffer cell-expressed membrane-bound TNF mediates melphalan hepatotoxicity via activation of both TNF receptors. J Immunol 175(6):4076–4083CrossRefPubMedGoogle Scholar
  34. Law V, Knox C, Djoumbou Y et al (2014) DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res 42(Database issue):1091–1097. doi: 10.1093/nar/gkt1068 CrossRefGoogle Scholar
  35. Lee WM (2013) Drug-induced acute liver failure. Clin Liver Dis 17(4):575–586. doi: 10.1016/j.cld.2013.07.001 CrossRefPubMedGoogle Scholar
  36. Lee SJ, Lee YJ, Park KK (2016) The pathogenesis of drug-induced liver injury. Expert Rev Gastroenterol Hepatol. doi: 10.1080/17474124.2016.1196133 Google Scholar
  37. Li J, Kaneko T, Wang Y, Qin LQ, Wang PY, Sato A (2002) Troglitazone enhances the hepatotoxicity of acetaminophen by inducing CYP3A in rats. Toxicology 176(1–2):91–100. doi: 10.1016/S0300-483x(02)00143-9 CrossRefPubMedGoogle Scholar
  38. Lim Emilia, Pon Allison, Djoumbou Yannick, Knox Craig, Shrivastava Savita, Guo An Chi, Neveu Vanessa, Wishart David S (2010) T3DB: a comprehensively annotated database of common toxins and their targets. Nucleic Acids Res 38(Database issue):781–786CrossRefGoogle Scholar
  39. Liu R, Yu X, Wallqvist A (2015) Data-driven identification of structural alerts for mitigating the risk of drug-induced human liver injuries. J Cheminform 7(1):4. doi: 10.1186/s13321-015-0053-y CrossRefPubMedPubMedCentralGoogle Scholar
  40. Liu L, Tsompana M, Wang Y, Wu D, Zhu L, Zhu R (2016) Connection map for compounds (CMC): a server for combinatorial drug toxicity and efficacy analysis. J Chem Inf Model 56(9):1615–1621. doi: 10.1021/acs.jcim.6b00397 CrossRefPubMedGoogle Scholar
  41. Low Y, Uehara T, Minowa Y et al (2011) Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches. Chem Res Toxicol 24(8):1251–1262. doi: 10.1021/tx200148a CrossRefPubMedPubMedCentralGoogle Scholar
  42. Lu Y, Cederbaum AI (2006) Cisplatin-induced hepatotoxicity is enhanced by elevated expression of cytochrome P450 2E1. Toxicol Sci off J Soc Toxicol 89(2):515–523. doi: 10.1093/toxsci/kfj031 CrossRefGoogle Scholar
  43. Lu RJ, Zhang Y, Tang FL et al (2016) Clinical characteristics of drug-induced liver injury and related risk factors. Exp Ther Med 12(4):2606–2616. doi: 10.3892/etm.2016.3627 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Mao YM (2014) Hepatox: a professional web platform for the study of clinical and translational research on drug-induced liver injury in China. Chin Hepatol 19(8):575–576Google Scholar
  45. Minowa Y, Kondo C, Uehara T et al (2012) Toxicogenomic multigene biomarker for predicting the future onset of proximal tubular injury in rats. Toxicology 297(1–3):47–56. doi: 10.1016/j.tox.2012.03.014 CrossRefPubMedGoogle Scholar
  46. Okuda T, Norioka M, Shitara Y, Horie T (2010) Multiple mechanisms underlying troglitazone-induced mitochondrial permeability transition. Toxicol Appl Pharmacol 248(3):242–248. doi: 10.1016/j.taap.2010.08.007 CrossRefPubMedGoogle Scholar
  47. Regev A (2014) Drug-induced liver injury and drug development: industry perspective. Semin Liver Dis 34(2):227–239. doi: 10.1055/s-0034-1375962 CrossRefPubMedGoogle Scholar
  48. Rincónvillamizar E, Restrepo G (2014) Rules relating hepatotoxicity with structural attributes of drugs. Toxicol Environ Chem 96(4):594–613CrossRefGoogle Scholar
  49. Seeff LB (2015) Drug-induced liver injury is a major risk for new drugs. Dig Dis 33(4):458–463. doi: 10.1159/000374089 CrossRefPubMedGoogle Scholar
  50. Shah F, Leung L, Barton HA et al (2015) Setting clinical exposure levels of concern for drug-induced liver injury (DILI) using mechanistic in vitro assays. Toxicol Sci off J Soc Toxicol 147(2):500–514. doi: 10.1093/toxsci/kfv152 CrossRefGoogle Scholar
  51. Silva AM, Barbosa IA, Seabra C et al (2016) Involvement of mitochondrial dysfunction in nefazodone-induced hepatotoxicity. Food Chem Toxicol Int J Publ Br Ind Biol Res Assoc 94:148–158. doi: 10.1016/j.fct.2016.06.001 CrossRefGoogle Scholar
  52. Stirnimann G, Kessebohm K, Lauterburg B (2010) Liver injury caused by drugs: an update. Swiss Med Wkly 140:w13080. doi: 10.4414/smw.2010.13080 PubMedGoogle Scholar
  53. Sun W, Sanderson PE, Zheng W (2016) Drug combination therapy increases successful drug repositioning. Drug Discov Today 21(7):1189–1195. doi: 10.1016/j.drudis.2016.05.015 CrossRefPubMedPubMedCentralGoogle Scholar
  54. Teufel A (2015) Bioinformatics and database resources in hepatology. J Hepatol 62(3):712–719. doi: 10.1016/j.jhep.2014.10.036 CrossRefPubMedGoogle Scholar
  55. Uehara T, Minowa Y, Morikawa Y et al (2011) Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database. Toxicol Appl Pharmacol 255(3):297–306. doi: 10.1016/j.taap.2011.07.001 CrossRefPubMedGoogle Scholar
  56. Wang ZY, Chen M, Zhu LL et al (2015) Pharmacokinetic drug interactions with clopidogrel: updated review and risk management in combination therapy. Ther Clin Risk Manag 11:449–467. doi: 10.2147/Tcrm.S80437 PubMedPubMedCentralGoogle Scholar
  57. Wang H, Yin Y, Wang P et al (2016) Current situation and future usage of anticancer drug databases. Apoptosis 21(7):778–794. doi: 10.1007/s10495-016-1250-5 CrossRefPubMedGoogle Scholar
  58. Watkins PB (2015) How to diagnose and exclude drug-induced liver injury. Dig Dis 33(4):472–476. doi: 10.1159/000374091 CrossRefPubMedGoogle Scholar
  59. Wexler P (2001) TOXNET: an evolving web resource for toxicology and environmental health information. Toxicology 157(1–2):3–10CrossRefPubMedGoogle Scholar
  60. Wishart DS, Knox C, Guo AC et al (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37(Database issue):D603–D610. doi: 10.1093/nar/gkn810 CrossRefPubMedGoogle Scholar
  61. Xie JD, Huang Y, Chen DT et al (2015) Fentanyl enhances hepatotoxicity of paclitaxel via inhibition of CYP3A4 and ABCB1 transport activity in mice. PLoS One 10(12):e0143701. doi: 10.1371/journal.pone.0143701 CrossRefPubMedPubMedCentralGoogle Scholar
  62. Xing L, Wu L, Liu Y, Ai N, Lu X, Fan X (2014) LTMap: a web server for assessing the potential liver toxicity by genome-wide transcriptional expression data. J Appl Toxicol JAT 34(7):805–809. doi: 10.1002/jat.2923 CrossRefPubMedGoogle Scholar
  63. Yu K, Geng X, Chen M et al (2014) High daily dose and being a substrate of cytochrome P450 enzymes are two important predictors of drug-induced liver injury. Drug Metab Dispos 42(4):744–750. doi: 10.1124/dmd.113.056267 CrossRefPubMedGoogle Scholar
  64. Zhang JX, Huang WJ, Zeng JH et al (2007) DITOP: drug-induced toxicity related protein database. Bioinformatics 23(13):1710–1712. doi: 10.1093/bioinformatics/btm139 CrossRefPubMedGoogle Scholar
  65. Zhang JD, Berntenis N, Roth A, Ebeling M (2014) Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity. Pharmacogenomics J 14(3):208–216. doi: 10.1038/tpj.2013.39 CrossRefPubMedGoogle Scholar
  66. Zhang C, Cheng F, Li W, Liu G, Lee PW, Tang Y (2016) In silico prediction of drug induced liver toxicity using substructure pattern recognition method. Mol Inform 35(3–4):136–144. doi: 10.1002/minf.201500055 CrossRefPubMedGoogle Scholar
  67. Zhi LJ, Lian YH, Yap CW, Li ZS, Xin C, Chen DYZ (2002) Drug Adverse Reaction Target Database (DART). Drug Saf Int J Med Toxicol Drug Exp 26(10):685–690Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.School of Pharmaceutical SciencesWenzhou Medical UniversityWenzhouPeople’s Republic of China
  2. 2.Institute for Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese MedicineHong Kong Baptist UniversityHong Kong, SARPeople’s Republic of China

Personalised recommendations