Predose blood gene expression profiles might identify the individuals susceptible to carbon tetrachloride-induced hepatotoxicity

Jun Won Yun, Tae Ryong Lee, Chae Wook Kim, Young Ho Park, Jin Ho Chung, Yong Soon Lee, Kyung Sun Kang, Kyung Min Lim

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Although the extent of chemical-induced liver injury differs substantially from individual to individual, it is very hard to identify susceptible population priori to chemical exposure. We report here that the gene expression of the blood samples collected predose might identify the susceptible population without actual exposure to hepatotoxicant. The innate gene expressions in the blood samples collected at predose were compared using wholegenome microarray analysis and semiquantitative PCR with the extent of hepatotoxicity following the treatment of a model hepatotoxicant, carbon tetrachloride (CCl4) posteriori. The expression of 18 genes was found to innately differ in the blood of the susceptible animals from the resistant to CCl4-induced hepatotoxicity. Of these 18 genes, three genes, NADH dehydrogenase subunit 6 (ND6), transient receptor potential cation channel, subfamily C, member 6 (Trpc6), and tetraspanin 12 (Tspan12), were found to be different reproducibly in real-time PCR analysis with independent sets of animals. Of particular note, animals with the low expression level of ND6 and Tspan12 showed significantly higher susceptibility to CCl4-induced hepatotoxicity indeed. This study demonstrated that blood gene expression profiling might identify the susceptible individuals to chemical-induced hepatotoxicity without actual chemical exposure, providing a novel and important methodology for the prevention of drug-induced hepatotoxicity.

Original languageEnglish
Pages (from-to)12-21
Number of pages10
JournalToxicological Sciences
Volume115
Issue number1
DOIs
StatePublished - May 2010

Keywords

  • Blood
  • Carbon tetrachloride
  • Hepatotoxicity
  • Individual variation
  • Microarray analysis

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