Dataset Information

Proctor2013 - Effect of Aβ immunisation in Alzheimer's disease (stochastic version)

ABSTRACT: Proctor2013 - Effect of Aβ immunisation in Alzheimer's disease (stochastic version) Extension of a previously published stochastic model (designed to examine some of the key pathways involved in the aggregation of amyloid-beta (A β) and the micro-tubular binding protein tau ( BIOMD0000000286, BIOMD0000000462)) to include the main processes involved in passive and active immunisation against A β and then to demonstrate the effects of this intervention on soluble A β. This is the stochastic version of the model, the deterministic version is BIOMD0000000488. This model is described in the article: Investigating interventions in Alzheimer's disease with computer simulation models. Proctor CJ, Boche D, Gray DA, Nicoll JA. PLoS ONE 2013; 8(9): e73631 Abstract: Progress in the development of therapeutic interventions to treat or slow the progression of Alzheimer's disease has been hampered by lack of efficacy and unforeseen side effects in human clinical trials. This setback highlights the need for new approaches for pre-clinical testing of possible interventions. Systems modelling is becoming increasingly recognised as a valuable tool for investigating molecular and cellular mechanisms involved in ageing and age-related diseases. However, there is still a lack of awareness of modelling approaches in many areas of biomedical research. We previously developed a stochastic computer model to examine some of the key pathways involved in the aggregation of amyloid-beta (Aβ) and the micro-tubular binding protein tau. Here we show how we extended this model to include the main processes involved in passive and active immunisation against Aβ and then demonstrate the effects of this intervention on soluble Aβ, plaques, phosphorylated tau and tangles. The model predicts that immunisation leads to clearance of plaques but only results in small reductions in levels of soluble Aβ, phosphorylated tau and tangles. The behaviour of this model is supported by neuropathological observations in Alzheimer patients immunised against Aβ. Since, soluble Aβ, phosphorylated tau and tangles more closely correlate with cognitive decline than plaques, our model suggests that immunotherapy against Aβ may not be effective unless it is performed very early in the disease process or combined with other therapies. This model is hosted on BioModels Database and identified by: BIOMD0000000634. 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: Carole Proctor

PROVIDER: BIOMD0000000634 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000000634?filename=BIOMD0000000634-biopax2.owl	Owl
	BIOMD0000000634?filename=BIOMD0000000634-biopax3.owl	Owl
	BIOMD0000000634?filename=BIOMD0000000634.m	Other
	BIOMD0000000634?filename=BIOMD0000000634.png	Other
	BIOMD0000000634?filename=BIOMD0000000634.sci	Other

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Publications

Investigating interventions in Alzheimer's disease with computer simulation models.

Proctor Carole J CJ Boche Delphine D Gray Douglas A DA Nicoll James A R JA

PloS one 20130916 9

Progress in the development of therapeutic interventions to treat or slow the progression of Alzheimer's disease has been hampered by lack of efficacy and unforeseen side effects in human clinical trials. This setback highlights the need for new approaches for pre-clinical testing of possible interventions. Systems modelling is becoming increasingly recognised as a valuable tool for investigating molecular and cellular mechanisms involved in ageing and age-related diseases. However, there is sti ...[more]

PMID: 24098635

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Project description:Proctor2013 - Effect of Aβ immunisation in Alzheimer's disease (deterministic version) Extension of a previously published stochastic model (designed to examine some of the key pathways involved in the aggregation of amyloid-beta (Aβ) and the micro-tubular binding protein tau ( BIOMD0000000286, BIOMD0000000462)) to include the main processes involved in passive and active immunisation against Aβ and then to demonstrate the effects of this intervention on soluble Aβ. This is the deterministic version of the model, the stochastic version is BIOMD0000000634. This model is described in the article: Investigating interventions in Alzheimer's disease with computer simulation models. Proctor CJ, Boche D, Gray DA, Nicoll JA. PLoS ONE 2013; 8(9): e73631 Abstract: Progress in the development of therapeutic interventions to treat or slow the progression of Alzheimer's disease has been hampered by lack of efficacy and unforeseen side effects in human clinical trials. This setback highlights the need for new approaches for pre-clinical testing of possible interventions. Systems modelling is becoming increasingly recognised as a valuable tool for investigating molecular and cellular mechanisms involved in ageing and age-related diseases. However, there is still a lack of awareness of modelling approaches in many areas of biomedical research. We previously developed a stochastic computer model to examine some of the key pathways involved in the aggregation of amyloid-beta (Aβ) and the micro-tubular binding protein tau. Here we show how we extended this model to include the main processes involved in passive and active immunisation against Aβ and then demonstrate the effects of this intervention on soluble Aβ, plaques, phosphorylated tau and tangles. The model predicts that immunisation leads to clearance of plaques but only results in small reductions in levels of soluble Aβ, phosphorylated tau and tangles. The behaviour of this model is supported by neuropathological observations in Alzheimer patients immunised against Aβ. Since, soluble Aβ, phosphorylated tau and tangles more closely correlate with cognitive decline than plaques, our model suggests that immunotherapy against Aβ may not be effective unless it is performed very early in the disease process or combined with other therapies. This model is hosted on BioModels Database and identified by: BIOMD0000000488. 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:INTRODUCTION Alzheimer’s disease (AD) is an advanced neurodegenerative disorder characterized by progressive impairment in both memory loss and cognitive capacities, which resulting in severe dementia [1]. The pathogenesis of AD is complicated and poorly understood. According to the World Alzheimer Report 2018, it is estimated that AD affects at least 50 million persons throughout the world, and the number of people with AD will double nearly every 20 years [2]. Over the past decade, various theories have been developed for the neuropathological level of AD, but the most popular distinct pathological hallmarks is extracellular accumulation of amyloid beta (Aβ) plaques, as well as the neurofibrillary tangles (NFTs) composed of the hyperphosphorylated tau in the form of in the select brain regions [3]. The other factors including mitochondrial dysfunction, oxidative stress, brain inflammation and neurotransmitter disturbances pathology have been recognized as a contributing factor in the pathogenesis of AD [4]. To date, only symptomatic therapies are available for AD patients. Cholinesterase inhibitors (CIs) are approved for mild to moderate AD patients, and memantine is the only one N-methyl-D-aspartate receptor (NMDAR) antagonist has been approved for moderate to severe AD [5]. NMDAR is a glutamate ionotropic receptor, they display high Ca2+ permeability and voltage-dependent block by Mg2+[6]. In AD patients, NMDARs could be overactivated due to increasing glutamate release from presynaptic neurons. Overactived NMDARs lead first to Ca2+ overload in postsynaptic neurons, followed by desensitization and internalization, resulting in synaptic dysfunction and ultimately cell death [7, 8]. The numerous factors than can influence the levels of endogenous glutamate release in the pathogenesis of AD, deposition of Aβplaques, soluble Aβoligomers, NFTs, mitochondrial dysfunction and oxidative stress have been associated with the higher concentration of glutamate release[9, 10]. Memantine is an uncompetitive, moderate affinity NMDA receptor (NMDAR) antagonist which is used for a further therapeutic option of moderate to severe AD [5]. Its effects have been investigated in a large number of in vitro and in vivo studies, which indicated that memantine can against Aβ-induced glutamate-mediated toxicity, attenuate phosphorylation of tau and reduces level of total precursor protein (APP) in human neuroblastoma SK-N-SH cells [11], and lower Aβ1-42 secretion and plaques in primary cortical neuronal culture cells [9, 12]. Some studies showed that memantine also completely protected against Aβ-induced ROS injure in the primary hippocampal neurons [13]. Studies with transgenic animal models showed that memantine reduced the levels of soluble Aβ1-42, Aβ plaque deposition and lowered the loss of synaptic density in APP/PS1mice [4, 14, 15], and decreased the levels of total tau and hyperphosphorylated tau in 3×Tg-AD mice [3]. Furthermore, memantine altered genes expression in adult rat brain [16], and modulated protein profiles in Down syndrome mice brain [17]. However, no comprehensive study of proteomic characteristics description of 3×Tg-AD transgenic mice under the memantine treatment has been conducted to date as far as we searched. In order to better understand the multiple actions of memantine, we conducted detailed analysis of proteomics and bioinformatics to dissect the molecular mechanisms of memantine for the treatment of AD.