Genomic indicators in the blood predict drug-induced liver injury

Abstract

Genomic biomarkers for the detection of drug-induced liver injury (DILI) from blood are urgently needed for monitoring drug safety. We used a unique data set as part of the Food and Drug Administration led MicroArray Quality Control Phase-II (MAQC-II) project consisting of gene expression data from the two tissues (blood and liver) to test cross-tissue predictability of genomic indicators to a form of chemically-induced liver injury. We then use the genomic indicators from the blood as biomarkers for prediction of acetaminophen-induced liver injury and show that the cross tissue predictability of a response to the pharmaceutical agent (accuracy as high as 92.1%) is better than, or at least comparable to, that of non-therapeutic compounds. We provide a database of gene expression for the highly informative predictors which brings biological context to the possible mechanisms involved in DILI. Pathway-based predictors were associated with inflammation, angiogenesis, Toll-like receptor signaling, apoptosis and mitochondrial damage. The results demonstrate for the first time and support the hypothesis that genomic indicators in the blood can serve as potential diagnostic biomarkers predictive of DILI.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

“…The companion MAQC-II papers published elsewhere give more in-depth analyses of specific issues such as the clinical benefits of genomic classifiers (unpublished data), the impact of different modeling factors on prediction performance 45 , the objective assessment of microarray cross-platform prediction 46 , cross-tissue prediction 47 , one-color versus two-color prediction comparison 48 , functional analysis of gene signatures 36 and recommendation of a simple yet robust data analysis protocol based on the KNN 32 . For example, we systematically compared the classification performance resulting from one- and two-color gene-expression profiles of 478 neuroblastoma samples and found that analyses based on either platform yielded similar classification performance 48 .…”

Gamma‐Glutamylcysteine Ethyl Ester Protects against Cyclophosphamide‐Induced Liver Injury and Hematologic Alterations via Upregulation of PPARγ and Attenuation of Oxidative Stress, Inflammation, and Apoptosis

“…The resultant mitochondrial membrane permeabilization leads to the release of cytochrome C and activation of procaspase-9. These events activate executioner caspase-3 resulting in apoptotic cell death [56, 57]. Here, CP-induced rats showed significant increase in expression of the apoptotic markers caspase-3 and BAX.…”

Biomarker Classifiers for Identifying Susceptible Subpopulations for Treatment Decisions

“…The difference and inter-relationship between the two biomarkers have rarely been addressed from the statistical modeling and methodology aspects. Many preclinical and clinical drug safety studies were primarily designed to identify markers that can indicate toxicity from drug treatment [9][10][11][12][13][14][15][16][17][18]. These markers were generally found by comparing treated and untreated subjects.…”