Zhao Jing, Chen Jie, Yang Ting-Hong, Holme Petter
Department of Mathematics, Logistical Engineering University, Chongqing, China.
BMC Syst Biol. 2012;6 Suppl 1(Suppl 1):S4. doi: 10.1186/1752-0509-6-S1-S4. Epub 2012 Jul 16.
Complex chronic diseases are usually not caused by changes in a single causal gene but by an unbalanced regulating network resulting from the dysfunctions of multiple genes or their products. Therefore, network based systems approach can be helpful for the identification of candidate genes related to complex diseases and their relationships. Axial spondyloarthropathy (SpA) is a group of chronic inflammatory joint diseases that mainly affect the spine and the sacroiliac joints. The pathogenesis of SpA remains largely unknown.
In this paper, we conducted a network study of the pathogenesis of SpA. We integrated data related to SpA, from the OMIM database, proteomics and microarray experiments of SpA, to prioritize SpA candidate disease genes in the context of human protein interactome. Based on the top ranked SpA related genes, we constructed a SpA specific PPI network, identified potential pathways associated with SpA, and finally sketched an overview of biological processes involved in the development of SpA.
The protein-protein interaction (PPI) network and pathways reflect the link between the two pathological processes of SpA, i.e., immune mediated inflammation, as well as imbalanced bone modelling caused new boneformation and bone loss. We found that some known disease causative genes, such as TNFand ILs, play pivotal roles in this interaction.
复杂的慢性疾病通常并非由单个致病基因的变化引起,而是由多个基因或其产物功能失调导致的调节网络失衡所致。因此,基于网络的系统方法有助于识别与复杂疾病相关的候选基因及其关系。轴性脊柱关节炎(SpA)是一组主要影响脊柱和骶髂关节的慢性炎症性关节疾病。SpA的发病机制在很大程度上仍然未知。
在本文中,我们对SpA的发病机制进行了网络研究。我们整合了来自OMIM数据库、SpA的蛋白质组学和微阵列实验的与SpA相关的数据,以便在人类蛋白质相互作用组的背景下对SpA候选疾病基因进行优先级排序。基于排名靠前的与SpA相关的基因,我们构建了一个SpA特异性蛋白质-蛋白质相互作用(PPI)网络,确定了与SpA相关的潜在途径,并最终勾勒出了SpA发展过程中涉及的生物学过程的概述。
蛋白质-蛋白质相互作用(PPI)网络和途径反映了SpA的两个病理过程之间的联系,即免疫介导的炎症以及由新骨形成和骨质流失导致的骨建模失衡。我们发现一些已知的疾病致病基因,如TNF和白细胞介素,在这种相互作用中起关键作用。