A Computational Analysis of Protein-Protein Interaction Networks in Neurodegenerative Diseases
Goñi Cortés, Joaquín
Esteban Ruiz, Francisco J.
Vélez de Mendizábal, Nieves
Ardanza Trevijano, Sergio
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BMC Systems Biolog 2 : (2008) // Article ID 52
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.