ArticlePLoS computational biology2021
Integration of a physiologically-based pharmacokinetic model with a whole-body, organ-resolved genome-scale model for characterization of ethanol and acetaldehyde metabolism.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Personalized whole-body modeling links gut microbiota to metabolic perturbations in Alzheimer's disease.Gut microbes · 2026Article
- Self-assembled structures as a material basis for indirect pharmacology in Traditional Chinese Medicine.Chinese medicine · 2026Review
- Metabolic modeling links gut microbiota to metabolic markers of Parkinson's disease.Gut microbes · 2025Article
- Expression of Aldehyde Dehydrogenase 1A1 in Relapse-Associated Cells in Acute Myeloid Leukemia.Cells · 2025Review
- A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth.NPJ digital medicine · 2024Article
- Review
- Protective Effects of Several Common Amino Acids, Vitamins, Organic Acids, Flavonoids and Phenolic Acids against Hepatocyte Damage Caused by Alcohol.Foods (Basel, Switzerland) · 2022Article
- Gut microbiota dysbiosis: The potential mechanisms by which alcohol disrupts gut and brain functions.Frontiers in microbiology · 2022Review
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Ethanol is one of the most widely used recreational substances in the world and due to its ubiquitous use, ethanol abuse has been the cause of over 3.3 million deaths each year. In addition to its effects, ethanol's primary metabolite, acetaldehyde, is a carcinogen that can cause symptoms of facial flushing, headaches, and nausea. How strongly ethanol or acetaldehyde affects an individual depends highly on the genetic polymorphisms of certain genes. In particular, the genetic polymorphisms of mitochondrial aldehyde dehydrogenase, ALDH2, play a large role in the metabolism of acetaldehyde. Thus, it is important to characterize how genetic variations can lead to different exposures and responses to ethanol and acetaldehyde. While the pharmacokinetics of ethanol metabolism through alcohol dehydrogenase have been thoroughly explored in previous studies, in this paper, we combined a base physiologically-based pharmacokinetic (PBPK) model with a whole-body genome-scale model (WBM) to gain further insight into the effect of other less explored processes and genetic variations on ethanol metabolism. This combined model was fit to clinical data and used to show the effect of alcohol concentrations, organ damage, ALDH2 enzyme polymorphisms, and ALDH2-inhibiting drug disulfiram on ethanol and acetaldehyde exposure. Through estimating the reaction rates of auxiliary processes with dynamic Flux Balance Analysis, The PBPK-WBM was able to navigate around a lack of kinetic constants traditionally associated with PK modelling and demonstrate the compensatory effects of the body in response to decreased liver enzyme expression. Additionally, the model demonstrated that acetaldehyde exposure increased with higher dosages of disulfiram and decreased ALDH2 efficiency, and that moderate consumption rates of ethanol could lead to unexpected accumulations in acetaldehyde. This modelling framework combines the comprehensive steady-state analyses from genome-scale models with the dynamics of traditional PK models to create a highly personalized form of PBPK modelling that can push the boundaries of precision medicine.
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