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The construction of common and specific significance subnetworks of Alzheimer's disease from multiple brain regions.

Kong W, Mou X, Zhang N, Zeng W, Li S, Yang Y - Biomed Res Int (2015)

Bottom Line: In this paper, commonly and specifically significant subnetworks were identified from six AD brain regions.The identified common subnetworks showed that inflammation of the brain nerves is one of the critical factors of AD and calcium imbalance may be a link among several causative factors in AD pathogenesis.In addition, the extracted specific subnetworks for each brain region revealed many biologically functional mechanisms to understand AD pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Information Engineering College, Shanghai Maritime University, Shanghai 201306, China.

ABSTRACT
Alzheimer's disease (AD) is a progressively and fatally neurodegenerative disorder and leads to irreversibly cognitive and memorial damage in different brain regions. The identification and analysis of the dysregulated pathways and subnetworks among affected brain regions will provide deep insights for the pathogenetic mechanism of AD. In this paper, commonly and specifically significant subnetworks were identified from six AD brain regions. Protein-protein interaction (PPI) data were integrated to add molecular biological information to construct the functional modules of six AD brain regions by Heinz algorithm. Then, the simulated annealing algorithm based on edge weight is applied to predicting and optimizing the maximal scoring networks for common and specific genes, respectively, which can remove the weak interactions and add the prediction of strong interactions to increase the accuracy of the networks. The identified common subnetworks showed that inflammation of the brain nerves is one of the critical factors of AD and calcium imbalance may be a link among several causative factors in AD pathogenesis. In addition, the extracted specific subnetworks for each brain region revealed many biologically functional mechanisms to understand AD pathogenesis.

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Related in: MedlinePlus

Specific subnetwork of HIP.
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Related In: Results  -  Collection


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fig4: Specific subnetwork of HIP.

Mentions: Figure 1 revealed that many significant genes were specially expressed in different brain regions. It suggested that some specific dysregulated pathways and subnetworks among them will provide deep insights into the pathogenetic mechanism of AD. By getting rid of the common genes overlapped in different brain regions, the maximal scoring function and the simulated annealing method were used again to construct the specific functional subnetwork by the specifically differential significant genes for each brain region including HIP, EC, PC, MTG, and SFG. Therefore, the sizes of the constructed specific subnetworks are much smaller. Since there were not enough significant genes that can be discovered to construct any functional subnetwork, the result of primary visual cortex (VCX) was absence. Figures 4–8 showed the specific functional subnetworks in HIP, EC, PC, MTG, and SFG, respectively. In Figures 4–8, red circles represented the genes upregulated in this brain region for AD samples, blue circles denoted the genes downregulated, and grey ones denoted that this gene had no great changes compared with normal samples in this brain area.


The construction of common and specific significance subnetworks of Alzheimer's disease from multiple brain regions.

Kong W, Mou X, Zhang N, Zeng W, Li S, Yang Y - Biomed Res Int (2015)

Specific subnetwork of HIP.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4383160&req=5

fig4: Specific subnetwork of HIP.
Mentions: Figure 1 revealed that many significant genes were specially expressed in different brain regions. It suggested that some specific dysregulated pathways and subnetworks among them will provide deep insights into the pathogenetic mechanism of AD. By getting rid of the common genes overlapped in different brain regions, the maximal scoring function and the simulated annealing method were used again to construct the specific functional subnetwork by the specifically differential significant genes for each brain region including HIP, EC, PC, MTG, and SFG. Therefore, the sizes of the constructed specific subnetworks are much smaller. Since there were not enough significant genes that can be discovered to construct any functional subnetwork, the result of primary visual cortex (VCX) was absence. Figures 4–8 showed the specific functional subnetworks in HIP, EC, PC, MTG, and SFG, respectively. In Figures 4–8, red circles represented the genes upregulated in this brain region for AD samples, blue circles denoted the genes downregulated, and grey ones denoted that this gene had no great changes compared with normal samples in this brain area.

Bottom Line: In this paper, commonly and specifically significant subnetworks were identified from six AD brain regions.The identified common subnetworks showed that inflammation of the brain nerves is one of the critical factors of AD and calcium imbalance may be a link among several causative factors in AD pathogenesis.In addition, the extracted specific subnetworks for each brain region revealed many biologically functional mechanisms to understand AD pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Information Engineering College, Shanghai Maritime University, Shanghai 201306, China.

ABSTRACT
Alzheimer's disease (AD) is a progressively and fatally neurodegenerative disorder and leads to irreversibly cognitive and memorial damage in different brain regions. The identification and analysis of the dysregulated pathways and subnetworks among affected brain regions will provide deep insights for the pathogenetic mechanism of AD. In this paper, commonly and specifically significant subnetworks were identified from six AD brain regions. Protein-protein interaction (PPI) data were integrated to add molecular biological information to construct the functional modules of six AD brain regions by Heinz algorithm. Then, the simulated annealing algorithm based on edge weight is applied to predicting and optimizing the maximal scoring networks for common and specific genes, respectively, which can remove the weak interactions and add the prediction of strong interactions to increase the accuracy of the networks. The identified common subnetworks showed that inflammation of the brain nerves is one of the critical factors of AD and calcium imbalance may be a link among several causative factors in AD pathogenesis. In addition, the extracted specific subnetworks for each brain region revealed many biologically functional mechanisms to understand AD pathogenesis.

Show MeSH
Related in: MedlinePlus