A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.
Mol Med Rep
; 16(3): 3187-3193, 2017 Sep.
Article
em En
| MEDLINE
| ID: mdl-28713940
ABSTRACT
The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where proteinprotein interaction (PPI) network was integrated with pathwaypathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized genegene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparinglycosaminoglycan (HSGAG) degradation, HSGAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Artrite Reumatoide
/
Transdução de Sinais
/
Biologia Computacional
/
Redes Reguladoras de Genes
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Mapas de Interação de Proteínas
Tipo de estudo:
Clinical_trials
Limite:
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article