Network Analysis Of Pathogenesis Of Alzheimer’s Disease Based On Transcriptome And Genetics Data

Alzheimer’s Disease(AD) is the most common neurodegenerative disease, affecting more than30million patients worldwide. The typical symptom of AD is gradual loss of memory and decrease in cognitive function. Currently, there is no available approach to cure AD. The two typical pathological hallmark of AD is extracellular deposition of amyloid plaques and intracellular neurofibrillary tangles. The pathogenesis of AD is not very clear. There are some hypothesis relating to AD. The most famous of one is the amyloid cascade hypothesis, which indicates that Aβ-induced neurotoxicity caused the apoptosis of neuron. The research on pathogenesis of AD has played a important role on precautions against AD and therapy of AD. Genetic association study based on case-control and transcriptome based on microarray have been applied to pathogenesis of AD. Now, network analysis is a important method of systems biology, which has been used to data related to genome and transcriptome of AD is helpful to explore the pathogenesis of AD. In the first part of the thesis, we develop a tool used to construct and analyze network by building background database through collecting various protein or gene interactions data, implementing the procedure of constructing and analyzing network using script language PHP and implementing web client by HTML and Javascript language. In the second part of thesis, we apply our tool constructed in the first part to analyze transcriptome and genome of AD. The results coincide with several hypothesis about AD, implying our tool is effective.