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

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.