Expression Changes in Mitochondrial Genes Affecting Mitochondrial Morphology, Transmembrane Potential, Fragmentation, Amyloidosis, and Neuronal Cell Death Found in Brains of Alzheimer's Disease Patients.

BACKGROUND: Alzheimer's disease (AD) is a neurological disease that has both a genetic and non-genetic origin. Mitochondrial dysfunction is a critical component in the pathogenesis of AD as deficits in oxidative capacity and energy production have been reported. OBJECTIVE: Nuclear-encoded mitochondrial genes were studied in order to understand the effects of mitochondrial expression changes on mitochondrial function in AD brains. These expression data were to be incorporated into a testable mathematical model for AD used to further assess the genes of interest as therapeutic targets for AD. METHODS: RT2-PCR arrays were used to assess expression of 84 genes involved in mitochondrial biogenesis in AD brains. A subset of mitochondrial genes of interest was identified after extensive Ingenuity Pathway Analysis (IPA) (Qiagen). Further filtering of this subset of genes of interest was achieved by individual qPCR analyses. Expression values from this group of genes were included in a mathematical model being developed to identify potential therapeutic targets. RESULTS: Nine genes involved in trafficking proteins to mitochondria, morphology of mitochondria, maintenance of mitochondrial transmembrane potential, fragmentation of mitochondria and mitochondrial dysfunction, amyloidosis, and neuronal cell death were identified as significant to the changes seen. These genes include TP53, SOD2, CDKN2A, MFN2, DNM1L, OPA1, FIS1, BNIP3, and GAPDH. CONCLUSION: Altered mitochondrial gene expression indicates that a subset of nuclear-encoded mitochondrial genes compromise multiple aspects of mitochondrial function in AD brains. A new mathematical modeling system may provide further insights into potential therapeutic targets.

Incorporating Mitochondrial Gene Expression Changes Within a Testable Mathematical Model for Alzheimer's Disease: Stress Response Modulation Predicts Potential Therapeutic Targets.

BACKGROUND: Alzheimer's disease is a specific form of dementia characterized by the aggregation of amyloid-ß plaques and tau tangles. New research has found that the formation of these aggregates occurs after dysregulation of cellular respiration and the production of radical oxygen species. Proteomic data shows that these changes are also related to unique gene expression patterns. OBJECTIVE: This study is designed to incorporate both proteomic and gene expression data into a testable mathematical model for AD. Manipulation of this new model allows the identification of potential therapeutic targets for AD. METHODS: We investigate the impact of these findings on new therapeutic targets via metabolic flux analysis of sirtuin stress response pathways while also highlighting the importance of metabolic enzyme activity in maintaining proper respiratory activity. RESULTS: Our results indicate that protective changes in SIRT1 and AMPK expression are potential avenues for therapeutics. CONCLUSION: Combining our mitochondrial gene expression analyses with available protein data allowed the construction of a new mathematical model for AD that provides a useful approach to test the efficacy of potential AD therapeutic targets.

A mathematical model of insulin resistance in Parkinson's disease.

This paper introduces a mathematical model representing the biochemical interactions between insulin signaling and Parkinson's disease. The model can be used to examine the changes that occur over the course of the disease as well as identify which processes would be the most effective targets for treatment. The model is mathematized using biochemical systems theory (BST). It incorporates a treatment strategy that includes several experimental drugs along with current treatments. In the past, BST models of neurodegeneration have used power law analysis and simulation (PLAS) to model the system. This paper recommends the use of MATLAB instead. MATLAB allows for more flexibility in both the model itself and in data analysis. Previous BST analyses of neurodegeneration began treatment at disease onset. As shown in this model, the outcomes of delayed, realistic treatment and full treatment at disease onset are significantly different. The delayed treatment strategy is an important development in BST modeling of neurodegeneration. It emphasizes the importance of early diagnosis, and allows for a more accurate representation of disease and treatment interactions.

A mathematical model of cell death in multiple sclerosis.

This paper imparts a mathematical model of multiple sclerosis (MS) that was created using Biochemical Systems Theory (BST). This method uses mechanisms and initial values from the literature to create a mathematical model of a disease. The model can then be used to test potential drug therapies and to detect possible trigger points for the disease. The focus of this MS model is mainly the action of reactive oxygen and nitrogen species (RONS), the permeability transition pore (PTP), apoptotic factors, and the eventual cell death in the oligodendrocyte. Several treatment methods were applied based on current therapies; however, one treatment, the prevention of the PTP from opening, is completely experimental and showed positive results based on this model. BST is an effective means of studying MS and can be beneficial in testing new therapy ideas.

In silico evidence for glutathione- and iron-related pathogeneses in Parkinson's disease.

Post-mortem analyses and epidemiological studies strongly indicate metals have a participatory role in neurodegenerative diseases, but whether these roles are pathogenic and not simply subsidiary mechanisms is currently unclear. For Parkinson's disease (PD), iron content in the afflicted brain region, the substantia nigra pars compacta (SNpc), has been consistently reported elevated whereas copper levels have been decreased. Both metals exhibit deleterious functions that occur during the late stages of PD, but mutations involving the regulation of these two metals have not been associated with PD. The pathogenesis of PD is undoubtedly multifaceted and may consist of various etiological factors participating in slow disease ascension. However, the extent to which certain factors may contribute to PD is unclear. To study whether iron and/or copper may facilitate a parkinsonian state, a computational model of neuronal metal regulation was initially developed and then the system was perturbed, corresponding to proposed etiological pathways for PD from the literature, in order to determine which iron- and copper-based pathogeneses would elicit a parkinsonian system. We report that a defective glutathione system and/or inhibited cellular iron efflux have the neurotoxic capacities to initiate a system characteristic of PD; furthermore, these capacities are greatly enhanced with mutated alpha-synuclein proteins.

A pragmatic approach to biochemical systems theory applied to an alpha-synuclein-based model of Parkinson's disease.

This paper presents a detailed systems model of Parkinson's disease (PD), developed utilizing a pragmatic application of biochemical systems theory (BST) intended to assist experimentalists in the study of system behavior. This approach utilizes relative values as a reasonable initial estimate for BST and provides a theoretical means of applying numerical solutions to qualitative and semi-quantitative understandings of cellular pathways and mechanisms. The approach allows for the simulation of human disease through its ability to organize and integrate existing information about metabolic pathways without having a full quantitative description of those pathways, so that hypotheses about individual processes may be tested in a systems environment. Incorporating this method, the PD model describes alpha-synuclein aggregation as mediated by dopamine metabolism, the ubiquitin-proteasome system, and lysosomal degradation, allowing for the examination of dynamic pathway interactions and the evaluation of possible toxic mechanisms in the aggregation process. Four system perturbations: elevated alpha-synuclein aggregation, impaired dopamine packaging, increased neurotoxins, and alpha-synuclein overexpression, were analyzed for correlation to qualitative PD system hypotheses present in the literature, with the model demonstrating a high level of agreement with these hypotheses. Additionally, various PD treatment methods, including levadopa and monoamine oxidase inhibition (MAOI) therapy, were applied to the disease models to examine their effects on the system. Future additions and refinements to the model may further the understanding of the emergent behaviors of the disease, helping in the identification of system sensitivities and possible therapeutic targets.