Interindividual variation in response to xenobiotic exposure established in precision-cut human liver slices

Abstract

Large differences in toxicity responses occur within the human population. In this study we evaluate whether interindividual variation in baseline enzyme activity (EA)/gene expression (GE) levels in liver predispose for the variation in toxicity responses by assessing dose-response relationships for several prototypical hepatotoxicants. Baseline levels of cytochrome-P450 (CYP) GE/EA were measured in precision-cut human liver slices. Slices (n=4-5/compound) were exposed to a dose-range of acetaminophen, aflatoxin B1, benzo(α) pyrene or 2-nitrofluorene. Interindividual variation in induced genotoxicity (COMET-assay and CDKN1A/p21 GE) and cytotoxicity (lactate dehydrogenase-leakage), combined with NQO1- and GSTM1-induced GE-responses for oxidative stress and GE-responses of several CYPs was evaluated. The benchmark dose-approach was applied as a tool to model exposure responses on an individual level. Variation in baseline CYP levels, both GE and EA, can explain variation in compound exposure-responses on an individual level. Network analyses enable the definition of key parameters influencing interindividual variation after compound exposure. For 2-nitrofluorene, this analysis suggests involvement of CYP1B1 in the metabolism of this compound, which represents a novel finding. In this study, GSTM1 which is known to be highly polymorphic within the human population, but so far could not be linked to toxicity in acetaminophen-poisoned patients, is suggested to cause interindividual variability in acetaminophen-metabolism, dependent on the individual's gene expression-responses of CYP-enzymes. This study demonstrates that using interindividual variation within network modelling provides a source for the definition of essential and even new parameters involved in compound-related metabolism. This information might enable ways to make more quantitative estimates of human risks.

Keywords: Acetaminophen; Bayesian network; Carcinogens; Interindividual variation; Precision-cut liver slices.