ArticleJournal of lipid research2012
A physiologically based in silico kinetic model predicting plasma cholesterol concentrations in humans.
Article in Journal of lipid research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 35 citations in OpenAlex.
- Credibility assessment of a mechanistic model of atherosclerosis to predict cardiovascular outcomes under lipid-lowering therapy.NPJ digital medicine · 2025Article
- Exploring dynamic metabolomics data with multiway data analysis: a simulation study.BMC bioinformatics · 2022Article
- A mathematical model of in vitro hepatocellular cholesterol and lipoprotein metabolism for hyperlipidemia therapy.PloS one · 2022Article
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- Exploring the Bacterial Impact on Cholesterol Cycle: A Numerical Study.Frontiers in microbiology · 2020Article
- The Virtual Anemia Trial: An Assessment of Model-Based In Silico Clinical Trials of Anemia Treatment Algorithms in Patients With Hemodialysis.CPT: pharmacometrics & systems pharmacology · 2018Article
- A Quantitative Systems Pharmacology Platform to Investigate the Impact of Alirocumab and Cholesterol-Lowering Therapies on Lipid Profiles and Plaque Characteristics.Gene regulation and systems biology · 2017Article
- Linear-In-Flux-Expressions Methodology: Toward a Robust Mathematical Framework for Quantitative Systems Pharmacology Simulators.Gene regulation and systems biology · 2017Review
- Efficient Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models.CPT: pharmacometrics & systems pharmacology · 2016Article
- Evaluation of HDL-modulating interventions for cardiovascular risk reduction using a systems pharmacology approach.Journal of lipid research · 2016Article
- Article
- Computationally Modeling Lipid Metabolism and Aging: A Mini-review.Computational and structural biotechnology journal · 2015Review
- Predicting individual responses to pravastatin using a physiologically based kinetic model for plasma cholesterol concentrations.Journal of pharmacokinetics and pharmacodynamics · 2014Article
- An in-silico model of lipoprotein metabolism and kinetics for the evaluation of targets and biomarkers in the reverse cholesterol transport pathway.PLoS computational biology · 2014Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increased plasma cholesterol concentration is associated with increased risk of cardiovascular disease. This study describes the development, validation, and analysis of a physiologically based kinetic (PBK) model for the prediction of plasma cholesterol concentrations in humans. This model was directly adapted from a PBK model for mice by incorporation of the reaction catalyzed by cholesterol ester transfer protein and contained 21 biochemical reactions and eight different cholesterol pools. The model was calibrated using published data for humans and validated by comparing model predictions on plasma cholesterol levels of subjects with 10 different genetic mutations (including familial hypercholesterolemia and Smith-Lemli-Opitz syndrome) with experimental data. Average model predictions on total cholesterol were accurate within 36% of the experimental data, which was within the experimental margin. Sensitivity analysis of the model indicated that the HDL cholesterol (HDL-C) concentration was mainly dependent on hepatic transport of cholesterol to HDL, cholesterol ester transfer from HDL to non-HDL, and hepatic uptake of cholesterol from non-HDL-C. Thus, the presented PBK model is a valid tool to predict the effect of genetic mutations on cholesterol concentrations, opening the way for future studies on the effect of different drugs on cholesterol levels in various subpopulations in silico.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.