期刊论文详细信息
Molecules
A Sub-Pathway Based Method to Identify Candidate Agents for Ankylosing Spondylitis
Kai Chen1  Yingchuan Zhao1  Yu Chen2  Chuanfeng Wang2  Ziqiang Chen2  Yushu Bai2  Xiaodong Zhu2 
[1] id="af1-molecules-17-12460">Department of Orthopedics, Changhai Hospital, Shanghai 200433, Chi
关键词: Ankylosing Spondylitis;    bioinformatics;    connectivity map;    drug discovery;   
DOI  :  10.3390/molecules171012460
来源: mdpi
PDF
【 摘 要 】

The need for new therapeutics for Ankylosing Spondylitis (AS) is highlighted by the general lack of efficacy for most agents currently available for this disease. Many recent studies have detailed molecular pathways in AS, and several molecule-targeting agents are undergoing evaluation. We aimed to explore the mechanism of AS and identify biologically active small molecules capable of targeting the sub-pathways which were disregulated in the development of AS. By using the GSE25101 microarray data accessible from the Gene Expression Omnibus database, we first identified the differentially expressed genes (DEGs) between AS samples and healthy controls, followed by the sub-pathway enrichment analysis of the DEGs. In addition, we propose the use of an approach based on targeting sub-pathways to identify potential agents for AS. A total of 3,280 genes were identified as being significantly different between patients and controls with p-values < 0.1. Our study showed that neurotrophic signaling pathway and some immune-associated pathways may be involved in the development of AS. Besides, our bioinformatics analysis revealed a total of 15 small molecules which may play a role in perturbing the development of AS. Our study proposes the use of an approach based on targeting sub-pathways to identify potential agents for AS. Candidate agents identified by our approach may provide the groundwork for a combination therapy approach for AS.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.

【 预 览 】
附件列表
Files Size Format View
RO202003190041150ZK.pdf 218KB PDF download
  文献评价指标  
  下载次数:6次 浏览次数:10次