Exploring potential ion channel targets for rheumatoid arthritis: combination of network analysis and gene expression analysis.

IF 3.2 4区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Sampath Bhuvaneshwari, Krishnamurthy Venkataraman, Kavitha Sankaranarayanan
{"title":"Exploring potential ion channel targets for rheumatoid arthritis: combination of network analysis and gene expression analysis.","authors":"Sampath Bhuvaneshwari, Krishnamurthy Venkataraman, Kavitha Sankaranarayanan","doi":"10.1002/bab.2638","DOIUrl":null,"url":null,"abstract":"<p><p>Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane that leads to the destruction of cartilage and bone. Currently, pharmacological targeting of ion channels is being increasingly recognized as an attractive and feasible strategy for the treatment of RA. The present work employs a network analysis approach to predict the most promising ion channel target for potential RA-treating drugs. A protein-protein interaction map was generated for 343 genes associated with inflammation in RA and ion channel genes using Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. Based on the betweenness centrality and traffic values as key topological parameters, 17 hub nodes were identified, including FOS (9800.85), tumor necrosis factor (3654.60), TGFB1 (3305.75), and VEGFA (3052.88). The backbone network constructed with these 17 hub genes was intensely analyzed to identify the most promising ion channel target using network analyzer. Calcium permeating ion channels, especially store-operated calcium entry channels, and their associated regulatory proteins were found to highly interact with RA inflammatory hub genes. This significant ion channel target for RA identified by theoretical and statistical studies was further validated by a pilot case-control gene expression study. Experimental verification of the above findings in 75 RA cases and 25 controls showed increased ORAI1 expression. Thus, with a combination of network analysis approach and gene expression studies, we have explored potential targets for RA treatment.</p>","PeriodicalId":9274,"journal":{"name":"Biotechnology and applied biochemistry","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biotechnology and applied biochemistry","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1002/bab.2638","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane that leads to the destruction of cartilage and bone. Currently, pharmacological targeting of ion channels is being increasingly recognized as an attractive and feasible strategy for the treatment of RA. The present work employs a network analysis approach to predict the most promising ion channel target for potential RA-treating drugs. A protein-protein interaction map was generated for 343 genes associated with inflammation in RA and ion channel genes using Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. Based on the betweenness centrality and traffic values as key topological parameters, 17 hub nodes were identified, including FOS (9800.85), tumor necrosis factor (3654.60), TGFB1 (3305.75), and VEGFA (3052.88). The backbone network constructed with these 17 hub genes was intensely analyzed to identify the most promising ion channel target using network analyzer. Calcium permeating ion channels, especially store-operated calcium entry channels, and their associated regulatory proteins were found to highly interact with RA inflammatory hub genes. This significant ion channel target for RA identified by theoretical and statistical studies was further validated by a pilot case-control gene expression study. Experimental verification of the above findings in 75 RA cases and 25 controls showed increased ORAI1 expression. Thus, with a combination of network analysis approach and gene expression studies, we have explored potential targets for RA treatment.

探索类风湿性关节炎的潜在离子通道靶点:网络分析与基因表达分析的结合。
类风湿性关节炎(RA)是一种全身性自身免疫性疾病,其特点是滑膜的慢性炎症导致软骨和骨骼的破坏。目前,针对离子通道的药理学治疗正被越来越多的人认为是治疗类风湿性关节炎的一种有吸引力的可行策略。本研究采用了一种网络分析方法来预测治疗RA的潜在药物中最有希望的离子通道靶点。利用检索相互作用基因的搜索工具为343个与RA炎症相关的基因和离子通道基因生成了蛋白质-蛋白质相互作用图谱,并利用Cytoscape将其可视化。根据作为关键拓扑参数的间度中心性和流量值,确定了 17 个中心节点,包括 FOS(9800.85)、肿瘤坏死因子(3654.60)、TGFB1(3305.75)和 VEGFA(3052.88)。利用网络分析器对由这 17 个枢纽基因构建的骨干网络进行了深入分析,以确定最有希望的离子通道靶标。研究发现,钙离子通道,尤其是贮存操作的钙离子通道,及其相关调控蛋白与 RA 炎症枢纽基因高度互作。通过理论和统计研究确定的这一重要的 RA 离子通道靶点在一项病例对照基因表达试验研究中得到了进一步验证。在 75 例 RA 病例和 25 例对照中对上述发现进行了实验验证,结果显示 ORAI1 的表达增加。因此,结合网络分析方法和基因表达研究,我们探索出了治疗 RA 的潜在靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Biotechnology and applied biochemistry
Biotechnology and applied biochemistry 工程技术-生化与分子生物学
CiteScore
6.00
自引率
7.10%
发文量
117
审稿时长
3 months
期刊介绍: Published since 1979, Biotechnology and Applied Biochemistry is dedicated to the rapid publication of high quality, significant research at the interface between life sciences and their technological exploitation. The Editors will consider papers for publication based on their novelty and impact as well as their contribution to the advancement of medical biotechnology and industrial biotechnology, covering cutting-edge research in synthetic biology, systems biology, metabolic engineering, bioengineering, biomaterials, biosensing, and nano-biotechnology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信