Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis.
Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis.
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DOI：
10.1186/ar4559
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发表时间：
2014-05-08
影响因子：
4.9
通讯作者：
Donn RP
中科院分区：
文献类型：
--
作者：
Stevens A;Meyer S;Hanson D;Clayton P;Donn RP
我们的目标是利用网络分析来确定在少关节和类风湿因子阴性(RF-VE)多关节幼年特发性关节炎(JIA)的发病机制中最具潜在功能相关性的蛋白质簇。利用JA基因关联数据构建了BioGRID 3.2.99的互作组网络模型。这个蛋白的前10%：JIA蛋白相互作用组被用来产生最小的基本网络(MEN)。使用Reactome FI Cytoscape 2.83插件和疾病协会蛋白质-蛋白质链接评估器(DAPPLE)算法来评估男性体内生物通路的功能并对蛋白质进行统计排序。JIA基因表达数据与MCODE获得的MAN和功能重要蛋白质簇整合在一起。从348个JIA相关基因中构建了一个由2,479个蛋白质组成的JIA互作组。MAN代表了该网络功能上最相关的组成部分，由七个具有不同功能特征的集群组成。来自外周血单个核细胞(PBMC)、中性粒细胞和滑液单核细胞的四个基因表达数据集被映射到男性身上，并确定了一系列功能意义丰富的基因。这一分析揭示了对于少关节JIA具有最大潜在功能重要性的基因PTPN2和STAT1以及对于RF-VE多关节JIA具有最大潜在功能重要性的基因KSR1。少关节JIA和RF-VE多关节JIA分别获得23个和14个相关蛋白质簇。这是第一份将网络生物学应用于JIA的报告，整合了遗传关联发现和基因表达数据，优先考虑蛋白质簇进行功能验证，并确定了有针对性的药物干预的新途径。
Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA). JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE. A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively. This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention.