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Open Access Highly Accessed Research article

A computational analysis of protein-protein interaction networks in neurodegenerative diseases

Joaquín Goñi12, Francisco J Esteban3, Nieves Vélez de Mendizábal14, Jorge Sepulcre1, Sergio Ardanza-Trevijano2, Ion Agirrezabal1 and Pablo Villoslada1*

Author Affiliations

1 Neuroimmunology laboratory, Department of Neuroscience, Center for Applied Medical Research, University of Navarra, Spain

2 Department of Physics and Applied Mathematics, University of Navarra, Spain

3 Systems Biology Unit, Department of Experimental Biology, University of Jaen, Spain

4 Department of Computational Sciences and Artificial Intelligence, University of the Basque Country, San Sebastian, Spain

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BMC Systems Biology 2008, 2:52  doi:10.1186/1752-0509-2-52

Published: 20 June 2008

Abstract

Background

Recent developments have meant that network theory is making an important contribution to the topological study of biological networks, such as protein-protein interaction (PPI) networks. The identification of differentially expressed genes in DNA array experiments is a source of information regarding the molecular pathways involved in disease. Thus, considering PPI analysis and gene expression studies together may provide a better understanding of multifactorial neurodegenerative diseases such as Multiple Sclerosis (MS) and Alzheimer disease (AD). The aim of this study was to assess whether the parameters of degree and betweenness, two fundamental measures in network theory, are properties that differentiate between implicated (seed-proteins) and non-implicated nodes (neighbors) in MS and AD. We used experimentally validated PPI information to obtain the neighbors for each seed group and we studied these parameters in four networks: MS-blood network; MS-brain network; AD-blood network; and AD-brain network.

Results

Specific features of seed-proteins were revealed, whereby they displayed a lower average degree in both diseases and tissues, and a higher betweenness in AD-brain and MS-blood networks. Additionally, the heterogeneity of the processes involved indicate that these findings are not pathway specific but rather that they are spread over different pathways.

Conclusion

Our findings show differential centrality properties of proteins whose gene expression is impaired in neurodegenerative diseases.