ArticlePLoS computational biology2016
A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.
- Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review.Frontiers in physiology · 2021Pooled it
- Virtual clinical trials of anti-PD-1 and anti-CTLA-4 immunotherapy in advanced hepatocellular carcinoma using a quantitative systems pharmacology model.Journal for immunotherapy of cancer · 2022Trial
- The anti-obesity and hepatoprotective effects of bacterial cyclodipeptides in a rat obesity model involve aquaporins, inflammatory factors, and GAB1 modulation.Journal of physiology and biochemistry · 2026Article
- Mapping DEHP-induced metabolic dysregulation through multi-omics and systems biology: an adverse outcome pathway network approach.Frontiers in toxicology · 2026Article
- Quantitative systems toxicology approach that integrates PBPK and core hepatic metabolism: a case study with valproic acid.Frontiers in pharmacology · 2026Article
- Quantitative Approaches to Accelerate MASH Drug Discovery and Development.Clinical pharmacology and therapeutics · 2025Review
- Liver biopsies obtained throughout SIV infection reveal evolving interferon stimulated protein expression within distinct monocyte/macrophage subsets.PLoS pathogens · 2025Article
- Impact of Dapagliflozin on Hepatic Lipid Metabolism and a Dynamic Model of Ketone Body Levels.The AAPS journal · 2025Article
- Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research.PLoS computational biology · 2022Article
- Digital twin predicting diet response before and after long-term fasting.PLoS computational biology · 2022Article
- A biologically based model to quantitatively assess the role of the nuclear receptors liver X (LXR), and pregnane X (PXR) on chemically induced hepatic steatosis.Toxicology letters · 2022Article
- Editorial: Computational Modeling for Liver Surgery and Interventions.Frontiers in physiology · 2022Article
- Citrus Flavanone Narirutin, In Vitro and In Silico Mechanistic Antidiabetic Potential.Pharmaceutics · 2021Article
- Article
- Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes.iScience · 2021Article
- A Spatial Model of Hepatic Calcium Signaling and Glucose Metabolism Under Autonomic Control Reveals Functional Consequences of Varying Liver Innervation Patterns Across Species.Frontiers in physiology · 2021Article
- Emergent Properties of the HNF4α-PPARγ Network May Drive Consequent Phenotypic Plasticity in NAFLD.Journal of clinical medicine · 2020Article
- Liver Bioreactor Design Issues of Fluid Flow and Zonation, Fibrosis, and Mechanics: A Computational Perspective.Journal of functional biomaterials · 2020Review
- Computational Modeling of Fructose Metabolism and Development in NAFLD.Frontiers in bioengineering and biotechnology · 2020Article
- Enzymatic and nonenzymatic protein acetylations control glycolysis process in liver diseases.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2019Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In non-alcoholic fatty liver disease (NAFLD), lipid build-up and the resulting damage is known to occur more severely in pericentral cells. Due to the complexity of studying individual regions of the sinusoid, the causes of this zone specificity and its implications on treatment are largely ignored. In this study, a computational model of liver glucose and lipid metabolism is presented which treats the sinusoid as the repeating unit of the liver rather than the single hepatocyte. This allows for inclusion of zonated enzyme expression by splitting the sinusoid into periportal to pericentral compartments. By simulating insulin resistance (IR) and high intake diets leading to the development of steatosis in the model, we identify key differences between periportal and pericentral cells accounting for higher susceptibility to pericentral steatosis. Secondly, variation between individuals is seen in both susceptibility to steatosis and in its development across the sinusoid. Around 25% of obese individuals do not show excess liver fat, whilst 16% of lean individuals develop NAFLD. Furthermore, whilst pericentral cells tend to show higher lipid levels, variation is seen in the predominant location of steatosis from pericentral to pan-sinusoidal or azonal. Sensitivity analysis was used to identify the processes which have the largest effect on both total hepatic triglyceride levels and on the sinusoidal location of steatosis. As is seen in vivo, steatosis occurs when simulating IR in the model, predominantly due to increased uptake, along with an increase in de novo lipogenesis. Additionally, concentrations of glucose intermediates including glycerol-3-phosphate increased when simulating IR due to inhibited glycogen synthesis. Several differences between zones contributed to a higher susceptibility to steatosis in pericentral cells in the model simulations. Firstly, the periportal zonation of both glycogen synthase and the oxidative phosphorylation enzymes meant that the build-up of glucose intermediates was less severe in the periportal hepatocyte compartments. Secondly, the periportal zonation of the enzymes mediating β-oxidation and oxidative phosphorylation resulted in excess fats being metabolised more rapidly in the periportal hepatocyte compartments. Finally, the pericentral expression of de novo lipogenesis contributed to pericentral steatosis when additionally simulating the increase in sterol-regulatory element binding protein 1c (SREBP-1c) seen in NAFLD patients in vivo. The hepatic triglyceride concentration was predicted to be most sensitive to inter-individual variation in the activity of enzymes which, either directly or indirectly, determine the rate of free fatty acid (FFA) oxidation. The concentration was most strongly dependent on the rate constants for β-oxidation and oxidative phosphorylation. It also showed moderate sensitivity to the rate constants for processes which alter the allosteric inhibition of β-oxidation by acetyl-CoA. The predominant sinusoidal location of steatosis meanwhile was most sensitive variations in the zonation of proteins mediating FFA uptake or triglyceride release as very low density lipoproteins (VLDL). Neither the total hepatic concentration nor the location of steatosis showed strong sensitivity to variations in the lipogenic rate constants.
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