Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease
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- Published online on: August 8, 2017 https://doi.org/10.3892/etm.2017.4905
- Pages: 2969-2975
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Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
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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.
