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A mathematical model of in vitro hepatocellular cholesterol and lipoprotein metabolism for hyperlipidemia therapy.

ABSTRACT: Cardiovascular diseases associated with high cholesterol (hypercholesterolemia) and low-density lipoproteins (LDL) levels are significant contributors to total mortality in developing and developed countries. Mathematical modeling of LDL metabolism is an important step in the development of drugs for hypercholesterolemia. The aim of this work was to develop and to analyze an integrated mathematical model of cholesterol metabolism in liver cells and its interaction with two types of drugs, statins and PCSK9 inhibitors. The model consisted of 21 ordinary differential equations (ODE) describing cholesterol biosynthesis and lipoprotein endocytosis in liver cells in vitro. The model was tested for its ability to mimic known biochemical effects of familial hypercholesterolemia, statin therapy, and PCSK9 inhibitors. The model qualitatively reproduced the well-known biology of cholesterol regulation, which confirms its potential for minimizing cellular research in initial testing of new drugs for cardiology.

SUBMITTER: Efremov Y

PROVIDER: S-EPMC9165868 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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A mathematical model of in vitro hepatocellular cholesterol and lipoprotein metabolism for hyperlipidemia therapy.

Efremov Yuri Y Ermolaeva Anastasia A Vladimirov Georgiy G Gordleeva Susanna S Svistunov Andrey A Zaikin Alexey A Timashev Peter P

PloS one 20220603 6

Cardiovascular diseases associated with high cholesterol (hypercholesterolemia) and low-density lipoproteins (LDL) levels are significant contributors to total mortality in developing and developed countries. Mathematical modeling of LDL metabolism is an important step in the development of drugs for hypercholesterolemia. The aim of this work was to develop and to analyze an integrated mathematical model of cholesterol metabolism in liver cells and its interaction with two types of drugs, statin ...[more]

PMID: 35657919

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Project description:BackgroundGlobal demographic changes have stimulated marked interest in the process of aging. There has been, and will continue to be, an unrelenting rise in the number of the oldest old ( >85 years of age). Together with an ageing population there comes an increase in the prevalence of age related disease. Of the diseases of ageing, cardiovascular disease (CVD) has by far the highest prevalence. It is regarded that a finely tuned lipid profile may help to prevent CVD as there is a long established relationship between alterations to lipid metabolism and CVD risk. In fact elevated plasma cholesterol, particularly Low Density Lipoprotein Cholesterol (LDL-C) has consistently stood out as a risk factor for having a cardiovascular event. Moreover it is widely acknowledged that LDL-C may rise with age in both sexes in a wide variety of groups. The aim of this work was to use a whole-body mathematical model to investigate why LDL-C rises with age, and to test the hypothesis that mechanistic changes to cholesterol absorption and LDL-C removal from the plasma are responsible for the rise. The whole-body mechanistic nature of the model differs from previous models of cholesterol metabolism which have either focused on intracellular cholesterol homeostasis or have concentrated on an isolated area of lipoprotein dynamics. The model integrates both current and previously published data relating to molecular biology, physiology, ageing and nutrition in an integrated fashion.ResultsThe model was used to test the hypothesis that alterations to the rate of cholesterol absorption and changes to the rate of removal of LDL-C from the plasma are integral to understanding why LDL-C rises with age. The model demonstrates that increasing the rate of intestinal cholesterol absorption from 50% to 80% by age 65 years can result in an increase of LDL-C by as much as 34 mg/dL in a hypothetical male subject. The model also shows that decreasing the rate of hepatic clearance of LDL-C gradually to 50% by age 65 years can result in an increase of LDL-C by as much as 116 mg/dL.ConclusionsOur model clearly demonstrates that of the two putative mechanisms that have been implicated in the dysregulation of cholesterol metabolism with age, alterations to the removal rate of plasma LDL-C has the most significant impact on cholesterol metabolism and small changes to the number of hepatic LDL receptors can result in a significant rise in LDL-C. This first whole-body systems based model of cholesterol balance could potentially be used as a tool to further improve our understanding of whole-body cholesterol metabolism and its dysregulation with age. Furthermore, given further fine tuning the model may help to investigate potential dietary and lifestyle regimes that have the potential to mitigate the effects aging has on cholesterol metabolism.

Project description:BackgroundThe persistently high mortality and morbidity rates of hepatocellular carcinoma (HCC) remain a global concern. Notably, the disruptions in mitochondrial cholesterol metabolism (MCM) play a pivotal role in the progression and development of HCC, underscoring the significance of this metabolic pathway in the disease's etiology. The purpose of this research was to investigate genes associated with MCM and develop a model for predicting the prognostic features of patients with HCC.MethodsMCM-related genes (MCMGs) were identified through The Cancer Genome Atlas (TCGA), The Molecular Signatures Database (MsigDB), and the Mitocarta3.0 databases. Differential gene expression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed using R software to construct a MCM-related model. This model underwent further analysis for somatic mutations, single sample gene set enrichment analysis (ssGSEA), stromal and immune cell estimation, immune checkpoint evaluation, and drug susceptibility prediction to assess the tumor microenvironment (TME) and therapeutic responses. The mRNA expression levels of the genes associated with the model were quantified using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR).ResultsThe model, which included six MCMGs (ACADL, ACLY, TXNRD1, DTYMK, ACAT1, and FLAD1), divided all patients (age ≤65 vs. >65 years, P<0.001; male vs. female, ns) into a high-risk group and a low-risk group. The high-risk group showed a higher mortality rate and lower survival rate with AUC of 0.785, 0.752, 0.756, 0.774 and 0.759 for the 1-, 2-, 3-, 4-, and 5-year respectively. A nomogram based on risk score, stage, T, and M had a better prognostic accuracy, with AUC of 0.808, 0.796, 0.811, 0.824 and 0.795 for the 1-, 2-, 3-, 4-, and 5-year respectively. The high-risk group showed enrichment in cell cycle, cell division, and chromosome processes, and a significantly higher tumor mutation burden (TMB) value compared to the low-risk group. Further immune infiltration analysis indicated a significantly reduction in the abundances of some immune cells (activated CD4 T cells, type 2 helper T cells, and neutrophils) and significantly higher expression levels of some immune checkpoint (CD80, CTLA4, HAVCR2, and TNFRSF4) in the high-risk group. Moreover, the risk score was associated with the response to immune checkpoint inhibitors (ICIs) therapy and efficiencies of multiple chemotherapy drugs.ConclusionsThis study developed a prognostic model based on MCMGs, which can predict the prognosis of liver cancer patients and their response to immunotherapy and chemotherapy. The model may provide new strategies to enhance the prognosis and treatment of HCC.

Project description:BackgroundThe ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) is a novel lipid measure for assessing the risk of cardiovascular disease. Lipid metabolism disorders are reportedly associated with hearing impairment. This study aimed to investigate the potential association between NHHR and hearing.MethodsThe data used in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) cycles of 2005-2010 and 2017-2018, including 4,296 participants aged 6-19 years. The NHHR was calculated from lipid profiles, and hearing was assessed using pure-tone audiometry. Weighted multivariate logistic regression analyses were used to investigate the association between the NHHR and hearing loss. Subgroup and sensitivity analyses were performed to verify the robustness of the results.ResultsUnivariate analysis revealed significant associations between the NHHR and hearing threshold at all categorized frequency (low, speech, or high-frequency) (P < 0.001). Three models were used: an unadjusted model, a model adjusted for age, sex, and race, and a model further adjusted for PIR, BMI, and diabetes. Multiple regression analysis confirmed these associations consistently across all models. When considered as a continuous variable, NHHR had a significant association with enhanced hearing thresholds at all categorized frequencies: low-frequency (β:0.56, 95% CI: 0.36-0.75), speech-frequency (β:0.55, 95% CI: 0.36-0.7), and high-frequency (β:0.55, 95% CI: 0.36-0.74). The adjusted models showed persistent positive correlations after controlling for covariates. The NHHR was consistently positively associated with hearing loss. The NHHR and auditory thresholds showed a general dose-response association across all frequencies.ConclusionsNHHR is a promising biomarker for predicting adolescent hearing threshold shifts and hearing loss. The study highlights the importance of early lipid monitoring and management as strategies to prevent or reduce hearing impairment.

Dataset Information

A mathematical model of in vitro hepatocellular cholesterol and lipoprotein metabolism for hyperlipidemia therapy.

Publications

A mathematical model of in vitro hepatocellular cholesterol and lipoprotein metabolism for hyperlipidemia therapy.

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