Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease

动态微分网络和模块推断与阿尔茨海默病进展相关的异常基因

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Abstract

In order to understand the pathogenic factors that initiate the processes of Alzheimer's disease (AD), a method of inference of multiple differential modules (iMDM) to conduct analysis was performed on the gene expression profile of AD. A total of 11,089 genes and 588,391 interactions were gained based on the gene expression profile and protein-protein interaction network. Subsequently, three differential co-expression networks (DCNs) were constructed with the same nodes but different interactions, and eight multiple differential modules (M-DMs) were identified. Furthermore, by performing Module Connectivity Dynamic Score to quantify the change in the connectivity of component modules, two M-DMs were identified: Module 1 (P=0.0419) and 2 (P=0.0419; adjusted, P≤0.05). Finally, hub genes of MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 were gained via topological analysis conducted on the 2 M-DMs. In conclusion, the method of iMDM was suitable for conducting analysis on AD. By applying iMDM, 2 M-DMs were successfully identified and the MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 genes were predicted to be important during the occurrence and development of AD.

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