title: Is toxicogenomics a more reliable and sensitive biomarker than conventional indicators from rats to predict drug-induced liver injury in humans?
abstract: Around 40% of drug-induced liver injury (DILI) cases are not detected in preclinical studies using the conventional indicators. It has been hypothesized that genomic biomarkers will be more sensitive than conventional markers in detecting human hepatotoxicity signals in preclinical studies. For example, it has been hypothesized and demonstrated in some cases that (1) genomic biomarkers from the rat liver can discriminate drug candidates that have a greater or lesser potential to cause DILI in susceptible patients despite no conventional indicators of liver toxicity being observed in preclinical studies, and (2) more sensitive biomarkers for early detection of DILI can be derived from a "subtoxic dose" at which the injury in the liver occurs at the molecular but not the phenotypic level. With a public TGx data set derived from short-term in vivo studies using rats, we divided drugs exhibiting human hepatotoxicity into three groups according to whether elevated alanine aminotransferase (ALT) or total bilirubin (TBL) were observed in the treated rats: (A) The elevation was observed in the treated rats, (B) no elevation was observed for all of the treated rats, and (C) no elevation could be observed at a lower dose and shorter duration but occur when a higher or longer treatment was applied. A control group (D) was comprised of drugs known not to cause human hepatotoxicity and for which no rats exhibited elevated ALT or TBL. We developed classifiers for groups A, B, and C against group D and found that the gene signature from scenario A could achieve 83% accuracy for human hepatotoxicity potential of drugs in a leave-one-compound-out cross-validation process, much higher than scenarios B (average 45%) and C (61%). Furthermore, the signature derived from scenario A exhibited relevance to hepatotoxicity in a pathway-based analysis and performed well on two independent public TGx data sets using different chemical treatments and profiled with different microarray platforms. Our study implied that the human hepatotoxicity potential of a drug can be reasonably assessed using TGx analysis of short-term in vivo studies only if it produces significant elevation of ALT or TBL in the treated rats. The study further revealed that the value of "sensitive" biomarkers derived from scenario C was not promising as expected for DILI assessment using the reported TGx design. The study will facilitate further research to understand the role of genomic biomarkers from rats for assessing human hepatotoxicity.
authors: Center of Excellence for Bioinformatics, Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration , 3900 NCTR Road, Jefferson, Arkansas 72079, United States.
authors: Min
authors: M
authors: Zhang
authors: Minjun
authors: M
authors: Chen
authors: Weida
authors: W
authors: Tong
mesh_terms: D000410:Alanine Transaminase / Q000378:metabolism*; D000818:Animals; D001663:Bilirubin / Q000378:metabolism*; D015415:Biomarkers / Q000378:metabolism; D056486:Chemical and Drug Induced Liver Injury / Q000235:genetics* / Q000378:metabolism; D004195:Disease Models, Animal; D015870:Gene Expression; D006801:Humans; D008954:Models, Biological; D051381:Rats; D043922:Toxicogenetics
chemical_list: D015415:Biomarkers; D000410:Alanine Transaminase; D001663:Bilirubin