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


CONCLUSIONS
Our findings show differential centrality properties of proteins whose gene expression is impaired in neurodegenerative diseases.
Neuroimmunology laboratory, Department of Neuroscience, Center for Applied Medical Research, University of Navarra, Spain. jgoni@unav.es
Joaquín
J
Goñi
Francisco J
FJ
Esteban
Nieves Vélez
NV
de Mendizábal
Jorge
J
Sepulcre
Sergio
S
Ardanza-Trevijano
Ion
I
Agirrezabal
Pablo
P
Villoslada
D000544:Alzheimer Disease / Q000097:blood / Q000378:metabolism* / Q000473:pathology; D001921:Brain / Q000378:metabolism / Q000473:pathology; D019295:Computational Biology; D003198:Computer Simulation; D005786:Gene Expression Regulation; D008954:Models, Biological; D009103:Multiple Sclerosis / Q000097:blood / Q000378:metabolism* / Q000473:pathology; D011485:Protein Binding