| Late-onset Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder of the brain and is the most common form of dementia. Advancing age is the major contributing factor for increased susceptibility to Alzheimer's disease and the old are the fastest-growing segment of the United States population. Early diagnosis and treatment of AD can help in relieving some of the debilitating effects of Alzheimer's. Due to its polygenic nature, AD is considered to be caused not by defects in single genes, but rather by variations in a large number of genes and their complex interactions that ultimately contribute to the broad spectrum of disease phenotypes. Conventional biological analyses involve the study of individual components independently of each other, whereas systems biology "recognises the importance of wholeness," where a system cannot be effectively understood by the investigation of its parts in isolation from each other.;In this dissertation, integrative systems biology methods were developed to explore (exploratory analyses) the pathogenesis of AD and generate testable hypotheses. Analyses indicated that integrating multiple phenotypic and gene expression information of samples increased the power of statistical methods while analysing datasets containing few patient samples. Transcriptome analyses showed that there were extensive connections between genes associated with Alzheimer's and cardiovascular diseases/diabetes, at the co-expression and co-regulation levels providing strong supporting evidence to the hypotheses linking cardiovascular diseases, diabetes and AD. Lastly, differential network topology analyses were performed to examine the disease severity in four different AD affected brain regions. Latest results suggest that the middle temporal gyrus shows signs of early AD pathology compared to the entorhinal cortex, hippocampus, and posterior cingulate cortex. From this analysis, it is concluded that methods relating to differential coexpression network topology should be included in the toolkit of techniques employed to study complex diseases, such as Alzheimer's. Through the series of analyses performed in the work presented in this treatise, it was observed that the integration of multiple layers of data using appropriate systems biology methods is an efficient way to study complex diseases. |
