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

Andrew K Smith1, Brenden K Petersen2, Glen E P Ropella3

  • 1Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America.

Plos Computational Biology
|December 17, 2016
PubMed

Insights

Acetaminophen-induced liver injury in mice is modeled by a new mechanism combining reactive metabolite formation, glutathione depletion, and mitochondrial repair zonation. This merged mechanism explains necrosis patterns and genetic variations in toxicity.

Area of Science:

  • Toxicology
  • Computational Biology
  • Hepatology

Background:

  • Acetaminophen overdose causes liver injury, a significant clinical problem.
  • Current understanding of acetaminophen-induced liver injury (AILI) mechanisms is incomplete.
  • A key phenomenon in AILI is central vein (CV) necrosis progression, lacking a clear explanation.

Purpose of the Study:

  • To develop and validate a computational mechanism explaining AILI.
  • To investigate the role of NAPQI zonation and other factors in AILI.
  • To account for the spatial and genetic variability of AILI in mice.

Main Methods:

  • Utilized virtual hepatocytes to model lobule-specific acetaminophen metabolism and toxicity.
  • Tested the NAPQI zonation (NZ) mechanism hypothesis.
  • Integrated glutathione depletion and mitochondrial repair zonation into the NZ-mechanism.

Main Results:

  • The NZ-mechanism alone did not replicate the observed CV necrosis pattern.
  • Incorporating either glutathione depletion or mitochondrial repair zonation alone was insufficient.
  • A merged mechanism including both glutathione depletion and mitochondrial repair zonation successfully modeled the Target Phenomenon.
  • The merged mechanism explained variations in necrosis scores across 37 mouse strains.

Conclusions:

  • A combined mechanism of NAPQI zonation, glutathione depletion zonation, and mitochondrial repair zonation is necessary to explain AILI.
  • This multilevel, multiscale model provides a causal explanation for AILI temporal and spatial features.
  • The model offers insights into genetic variations influencing acetaminophen toxicity outcomes.

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