Dataset Information

Ehrenstein2000 - Positive-Feedback model for the loss of acetylcholine in Alzheimer's disease

ABSTRACT: Ehrenstein2000 - Positive-Feedback model for the loss of acetylcholine in Alzheimer's disease Curated model derived from BIOMD0000000553 This model is described in the article: A positive-feedback model for the loss of acetylcholine in Alzheimer's disease. Ehrenstein G, Galdzicki Z, Lange GD. Ann. N. Y. Acad. Sci. 2000; 899: 283-291 Abstract: We describe a two-component positive-feedback system that could account for the large reduction of acetylcholine that is characteristic of patients with Alzheimer's disease (AD). One component is beta-amyloid-induced apoptosis of cholinergic cells, leading to a decrease in acetylcholine. The other component is an increase in the concentration of beta-amyloid in response to a decrease in acetylcholine. We describe each mechanism with a differential equation, and then solve the two equations numerically. The solution provides a description of the time course of the reduction of acetylcholine in AD patients that is consistent with epidemiological data. This model may also provide an explanation for the significant, but lesser, decrease of other neurotransmitters that is characteristic of AD. This model is hosted on BioModels Database and identified by: BIOMD0000000552. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

DISEASE(S): Alzheimer's Disease

SUBMITTER: Audald Lloret i Villas

PROVIDER: BIOMD0000000552 | BioModels | 2014-10-20

REPOSITORIES: BioModels

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Publications

A positive-feedback model for the loss of acetylcholine in Alzheimer's disease.

Ehrenstein G G Galdzicki Z Z Lange G D GD

Annals of the New York Academy of Sciences 20000101

We describe a two-component positive-feedback system that could account for the large reduction of acetylcholine that is characteristic of patients with Alzheimer's disease (AD). One component is beta-amyloid-induced apoptosis of cholinergic cells, leading to a decrease in acetylcholine. The other component is an increase in the concentration of beta-amyloid in response to a decrease in acetylcholine. We describe each mechanism with a differential equation, and then solve the two equations numer ...[more]

PMID: 10863547

Publication: 1/2

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Project description:Ehrenstein1997 - The choline-leakage hypothesis in Alzheimer's disease This model is described in the article: The choline-leakage hypothesis for the loss of acetylcholine in Alzheimer's disease. Ehrenstein G, Galdzicki Z, Lange GD. Biophys. J. 1997 Sep; 73(3): 1276-1280 Abstract: We present a hypothesis for the loss of acetylcholine in Alzheimer's disease that is based on two recent experimental results: that beta-amyloid causes leakage of choline across cell membranes and that decreased production of acetylcholine increases the production of beta-amyloid. According to the hypothesis, an increase in beta-amyloid concentration caused by proteolysis of the amyloid precursor protein results in an increase in the leakage of choline out of cells. This leads to a reduction in intracellular choline concentration and hence a reduction in acetylcholine production. The reduction in acetylcholine production, in turn, causes an increase in the concentration of beta-amyloid. The resultant positive feedback between decreased acetylcholine and increased beta-amyloid accelerates the loss of acetylcholine. We compare the predictions of the choline-leakage hypothesis with a number of experimental observations. We also approximate it with a pair of ordinary differential equations. The solutions of these equations indicate that the loss of acetylcholine is very sensitive to the initial rate of beta-amyloid production. This model is hosted on BioModels Database and identified by: BIOMD0000000553. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Kyrtsos2011 - A systems biology model for Alzheimer's disease (Cholesterol in AD) Encoded non-curated model. Issues: - Confusing HmgCoA differential equation - Confusing d2 and t1 parameters - Lack of initial values for several key species This model is described in the article: Of Mice and Math: A Systems Biology Model for Alzheimer's disease Kyrtsos, Christina Rose UMD Theses and Dissertations Abstract: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the US, affecting over 1 in 8 people over the age of 65. There are several well-known pathological changes in the brains of AD patients, namely: the presence of diffuse beta amyloid plaques derived from the amyloid precursor protein (APP), hyper-phosphorylated tau protein, neuroinflammation and mitochondrial dysfunction. Recent studies have shown that cholesterol levels in both the plasma and the brain may play a role in disease pathogenesis, however, this exact role is not well understood. Additional proteins of interest have also been identified (ApoE, LRP-1, IL-1) as possible contributors to AD pathogenesis. To help understand these roles better, a systems biology mathematical model was developed. Basic principles from graph theory and control analysis were used to study the effect of altered cholesterol, ApoE, LRP and APP on the system as a whole. Negative feedback regulation and the rate of cholesterol transfer between astrocytes and neurons were identified as key modulators in the level of beta amyloid. Experiments were run concurrently to test whether decreasing plasma and brain cholesterol levels with simvastatin altered the expression levels of beta amyloid, ApoE, and LRP-1, to ascertain the edge directions in the network model and to better understand whether statin treatment served as a viable treatment option for AD patients. The work completed herein represents the first attempt to create a systems-level mathematical model to study AD that looks at intercellular interactions, as well as interactions between metabolic and inflammatory pathways. This model is hosted on BioModels Database and identified by: MODEL1504240000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2012 - Amyloid-beta aggregation This model supports the current thinking that levels of dimers are important in initiating the aggregation process. This model is described in the article: Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer's disease: a stochastic modelling approach. Proctor CJ, Pienaar IS, Elson JL, Kirkwood TB Molecular Neurodegeneration. 2012; 7:32 Abstract: BACKGROUND: Alzheimer's disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating the precise molecular underpinnings of AD, a definitive answer is still lacking. In recent years, consensus has grown that dimerisation of the polypeptide amyloid-beta (Aß), particularly Aß₄₂, plays a crucial role in the neuropathology that characterise AD-affected post-mortem brains, including the large-scale accumulation of fibrils, also referred to as senile plaques. This has led to the realistic hope that targeting Aß₄₂ immunotherapeutically could drastically reduce plaque burden in the ageing brain, thus delaying AD onset or symptom progression. Stochastic modelling is a useful tool for increasing understanding of the processes underlying complex systems-affecting disorders such as AD, providing a rapid and inexpensive strategy for testing putative new therapies. In light of the tool's utility, we developed computer simulation models to examine Aß₄₂ turnover and its aggregation in detail and to test the effect of immunization against Aß dimers. RESULTS: Our model demonstrates for the first time that even a slight decrease in the clearance rate of Aß₄₂ monomers is sufficient to increase the chance of dimers forming, which could act as instigators of protofibril and fibril formation, resulting in increased plaque levels. As the process is slow and levels of Aβ are normally low, stochastic effects are important. Our model predicts that reducing the rate of dimerisation leads to a significant reduction in plaque levels and delays onset of plaque formation. The model was used to test the effect of an antibody mediated immunological response. Our results showed that plaque levels were reduced compared to conditions where antibodies are not present. CONCLUSION: Our model supports the current thinking that levels of dimers are important in initiating the aggregation process. Although substantial knowledge exists regarding the process, no therapeutic intervention is on offer that reliably decreases disease burden in AD patients. Computer modelling could serve as one of a number of tools to examine both the validity of reliable biomarkers and aid the discovery of successful intervention strategies. This model is hosted on BioModels Database and identified by: BIOMD0000000462 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:GFAP and vimentin deficiency alters gene expression in astrocytes and microglia in wild-type mice and changes the transcriptional response of reactive glia in mouse model for Alzheimer's disease. Reactive astrocytes with an increased expression of intermediate filament (IF) proteins Glial Fibrillary Acidic Protein (GFAP) and Vimentin (VIM) surround amyloid plaques in Alzheimer's disease (AD). The functional consequences of this upregulation are unclear. To identify molecular pathways coupled to IF regulation in reactive astrocytes, and to study the interaction with microglia, we examined WT and APPswe/PS1dE9 (AD) mice lacking either GFAP, or both VIM and GFAP, and determined the transcriptome of cortical astrocytes and microglia from 15- to 18-month-old mice. Genes involved in lysosomal degradation (including several cathepsins) and in inflammatory response (including Cxcl5, Tlr6, Tnf, Il1b) exhibited a higher AD-induced increase when GFAP, or VIM and GFAP, were absent. The expression of Aqp4 and Gja1 displayed the same pattern. The downregulation of neuronal support genes in astrocytes from AD mice was absent in GFAP/VIM null mice. In contrast, the absence of IFs did not affect the transcriptional alterations induced by AD in microglia, nor was the cortical plaque load altered. Visualizing astrocyte morphology in GFAP-eGFP mice showed no clear structural differences in GFAP/VIM null mice, but did show diminished interaction of astrocyte processes with plaques. Microglial proliferation increased similarly in all AD groups. In conclusion, absence of GFAP, or both GFAP and VIM, alters AD-induced changes in gene expression profile of astrocytes, showing a compensation of the decrease of neuronal support genes and a trend for a slightly higher inflammatory expression profile. However, this has no consequences for the development of plaque load, microglial proliferation, or microglial activation. 2 cell types from 6 conditions: cortical microglia and cortical astrocytes from 15-18 month old APPswe/PS1dE9 mice compared to wildtype littermates. Biological replicates: microglia from APPswe/PS1dE9, N=7, microglia from WT, N=7, astrocytes from APPswe/PS1dE9, N=4, microglia from WT, N=4

Dataset Information

Ehrenstein2000 - Positive-Feedback model for the loss of acetylcholine in Alzheimer's disease

Publications

A positive-feedback model for the loss of acetylcholine in Alzheimer's disease.

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