Competing Mechanistic Hypotheses of Acetaminophen-Induced Hepatotoxicity Challenged by Virtual Experiments

Abstract

Acetaminophen-induced liver injury in mice is a model for drug-induced liver injury in humans. A precondition for improved strategies to disrupt and/or reverse the damage is a credible explanatory mechanism for how toxicity phenomena emerge and converge to cause hepatic necrosis. The Target Phenomenon in mice is that necrosis begins adjacent to the lobule’s central vein (CV) and progresses outward. An explanatory mechanism remains elusive. Evidence supports that location dependent differences in NAPQI (the reactive metabolite) formation within hepatic lobules (NAPQI zonation) are necessary and sufficient prerequisites to account for that phenomenon. We call that the NZ-mechanism hypothesis. Challenging that hypothesis in mice is infeasible because 1) influential variables cannot be controlled, and 2) it would require sequential intracellular measurements at different lobular locations within the same mouse. Virtual hepatocytes use independently configured periportal-to-CV gradients to exhibit lobule-location dependent behaviors. Employing NZ-mechanism achieved quantitative validation targets for acetaminophen clearance and metabolism but failed to achieve the Target Phenomenon. We posited that, in order to do so, at least one additional feature must exhibit zonation by decreasing in the CV direction. We instantiated and explored two alternatives: 1) a glutathione depletion threshold diminishes in the CV direction; and 2) ability to repair mitochondrial damage diminishes in the CV direction. Inclusion of one or the other feature into NZ-mechanism failed to achieve the Target Phenomenon. However, inclusion of both features enabled successfully achieving the Target Phenomenon. The merged mechanism provides a multilevel, multiscale causal explanation of key temporal features of acetaminophen hepatotoxicity in mice. We discovered that variants of the merged mechanism provide plausible quantitative explanations for the considerable variation in 24-hour necrosis scores among 37 genetically diverse mouse strains following a single toxic acetaminophen dose.

A Model Mechanism Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

“…Our virtual mouse is engineered to have software components that are concrete and strongly analogous to counterpart mouse components, but only to the extent needed to achieve prespecified by Targeted Attributes [Smith et al, 2016]. To stress that analogies-although numerous, qualitative, and quantitative-are limited, we refer to the virtual mouse as Mouse Analog.…”

“…It is engineered to be quantitatively and qualitatively biomimetic during execution and is strongly analogous to actual livers across several anatomical, hepatic zonation, and cell biology characteristics. Having already achieved several qualitative and quantitative Target Attributes [Smith et al, 2016, Smith et al, 2014, Yan et al, 2008a, Yan et al, 2008b, Park et al, 2009, Park et al, 2010, Liver composition is now stable and robust. In this work, a Target Attribute is a characteristic trait of the liver and APAP metabolism, disposition, and toxicity to which a prespecified Similarity Criterion is assigned.…”

“…4) It is straightforward to "isolate" all virtual hepatocytes from the liver, without altering intra-hepatocyte mechanisms; and then reorganize them to simulate a 2D hepatocyte culture to study responses to virtual counterparts of xenobiotics. We recently reported using experiments on virtual mice to discover model mechanisms that together provide plausible causal explanations for major temporal characteristics of acetaminophen (APAP) hepatotoxicity in mice [Smith et al, 2016]. Those virtual mice meet the first three requisites.…”

Mechanistic Systems Modeling to Improve Understanding and Prediction of Cardiotoxicity Caused by Targeted Cancer Therapeutics

“…Using the mechanistic DILIsym R model, a testable hypothesis was generated in which the amount of reactive metabolite produced from each isomer was identified as an important contributor to the observed species differences, and this prediction was confirmed experimentally in a later study (Kyriakides et al, 2016). In addition to the consortium that has developed the DILIsym R package, other groups have gained important insight into DILI through mathematical modeling (Smith et al, 2016;Blais et al, 2017;Thiel et al, 2017).…”

“…The simulations can uncover the reasons for counterintuitive results, such as drugs that block K v 11.1 but are nonetheless safe Lancaster and Sobie, 2016;Li et al, 2017), or drugs that only cause hepatotoxicity in some species (Kyriakides et al, 2016;Smith et al, 2016;Blais et al, 2017;Thiel et al, 2017;Woodhead et al, 2017). The simulations can also suggest the prioritization of experiments that are most likely to provide additional insight.…”