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|A computational analysis of protein-protein interaction networks in neurodegenerative diseases|
|Authors: ||Goñi, J. (Joaquín)|
Esteban, F.J. (F. J.)
Velez, N. (Nieves)
Sepulcre, J. (Jorge)
Ardanza-Trevijano, S. (Sergio)
Agirrezabal, I. (Ion)
Villoslada, P. (Pablo)
|Issue Date: ||Jun-2008|
|Citation: ||BMC System Biology|
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.
|Permanent link: ||http://hdl.handle.net/10171/6182|
|Appears in Collections:||DA - Ciencias - Física - Artículos de Revista|
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