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Analysis of protein-protein interactions network based on differentially expressed genes in cerebrospinal fluid for multiple sclerosis
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Nahid Safari-Alighiarloo   , Mostafa Rezaei-Tavirani , Mohammad Taghizadeh , Seyyed Mohammad Tabatabaei , Saeed Namaki |
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Abstract: (4858 Views) |
| Introduction: Multiple sclerosis (MS) is the most common central nervous system (CNS) demyelinating disease. New methods are substantive in order to have a better understanding its pathogenesis and also identifying new therapeutic targets for the disease. The aim of this study was to use network biology approach to identify potential key markers involved in MS pathogenesis.
Materials and Methods: In this study, gene expression profile of cerebrospinal fluid (CSF) samples from 26 newly diagnosed MS patients and 18 controls, which obtained from Array Express Database, were analyzed. Differentially expressed genes (DEG) were integrated with protein-protein interaction (PPI) data to construct PPI sub network. The sub network underwent further topological analysis by Cytoscape software.
Results: Gene expression profile analysis unraveled 3062 differential expressed genes (FDR < 0.05) in CSF of MS patients compared to control in which 1080 genes were up regulated and 1981 genes were down regulated. Integrating of DEGs with PPI data lead to construction the sub network with 1440 nodes and 3500 edges. After topological analysis of the network, five new genes with high centrality measures identified as candidate markers. These markers involved in biological processes such as the regulation of cytoskeletal dynamics, cell cycle and splicesome some. By literature survey, it has been confirmed their potential contributions in MS pathogenesis.
Conclusion: Therefore, network-based analysis could identify new markers which can be further explored as potential therapeutic targets for MS |
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| Keywords: Multiple Sclerosis, Transcriptome, Protein Interaction Maps, Topological Features |
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Full-Text [PDF 767 kb]
(1218 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2016/10/25 | Accepted: 2017/10/28 | Published: 2018/01/1
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