Integration of a physiologically-based pharmacokinetic model with a whole-body, organ-resolved genome-scale model for characterization of ethanol and acetaldehyde metabolism

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.

A physiologically-based digital twin for alcohol consumption – predicting real-life drinking responses and long-term plasma PEth

“…Unlike previous models, our model has integrated gastric emptying dynamics to account for the influence of the caloric content, drink volume, and meal effect on gastric emptying (42,(64)(65)(66). While newer models have been developed to include dynamics of the stomach, they are limited to only considering alcoholic drinks (43,45) and not the consumption of drinks paired with food. This makes them less usable when describing a real-life setting, where alcoholic drinks are often mixed with food and non-alcoholic drinks.…”

“…Because the Widmark equation does not describe gastric emptying, it can neither describe the slowing effect of beverage caloric content on gastric emptying (28)(29)(30)(31)(32), nor the ingestion of meals which greatly reduces the BAC following consumption of alcohol (33)(34)(35)(36)(37). There are other more advanced models that describe either (i) the gastric emptying (38)(39)(40), (ii) detailed BAC profiles of varying detail (41)(42)(43)(44)(45), or (iii) the PEth dynamics (46). However, to our knowledge, there does not exist a mathematical model that can describe all these aspects in a single model.…”

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

“…Neurotoxic risk assessment using PBPK models to determine the acute effects of ethanol in rats is also covered in the literature [ 112 ]. Specific enzyme polymorphisms in acetaldehyde dehydrogenase (ALDH) [ 113 ], alcohol dehydrogenase (ALD) [ 113 , 114 , 115 , 116 , 117 ], and CYP2E1 [ 118 , 119 ] have also been addressed for ethanol metabolism to simulate individual genomics, population simulations, and interindividual, and interracial variability. Although interracial variability is not defined in the Loizou et al 2004 article, interpopulation may be a more appropriate term.…”

“…Although interracial variability is not defined in the Loizou et al 2004 article, interpopulation may be a more appropriate term. [ 113 , 114 , 116 , 117 , 118 , 119 , 120 ]. Accounting for variations in the PBPK model allows for more accurate prediction of PK outcomes within a population or for an individual if their specific genetic profile is known or postulated.…”

Gut microbiota dysbiosis: The potential mechanisms by which alcohol disrupts gut and brain functions

“…Acetaldehyde is the major metabolite of alcohol and is generally considered a mediator of adverse reactions to alcohol and plays a significant role in the rewarding, motivating, and addictive properties of alcohol (Chen et al, 2021;Jin et al, 2021). The negative effects of AUD are mainly mediated by acetaldehyde, such as facial flushing, nausea, vomiting, and chest tightness (Zhu et al, 2021). After alcohol intake, the blood acetaldehyde concentration increases significantly, which is greatly affected by the ALDH allele and correlated with the dose of alcohol consumption (Chen et al, 2021).…”