Zhang Rongqiang, Guo Hao, Yang Xiaoli, Zhang Dandan, Li Baorong, Li Zhaofang, Xiong Yongmin
School of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of National Health Commission of the People's Republic of China, Xi'an.
Shaanxi University of Chinese Medicine, Xianyang, China.
Medicine (Baltimore). 2019 May;98(18):e15498. doi: 10.1097/MD.0000000000015498.
To perform a comprehensive analysis focusing on the biological functions and interactions of Kashin-Beck disease (KBD)-related genes to provide information towards understanding the pathogenesis of KBD.A retrospective, integrated bioinformatics analysis was designed and conducted. First, by reviewing the literature deposited in PubMed, we identified 922 genes genetically associated with KBD. Then, biological function and network analyses were conducted with Cytoscape software. Moreover, KBD specific molecular network analysis was conducted by Cytocluster using the Molecular Complex Detection Algorithm (MCODE).The biological function enrichment analysis suggested that collagen catabolic process, protein activation cascade, cellular response to growth factor stimulus, skeletal system development, and extrinsic apoptosis played important roles in KBD development. The apoptosis pathway, NF-kappa B signaling pathway, and the glutathione metabolism pathway were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway network, suggesting that these pathways may play key roles in KBD occurrence and development. MCODE clusters showed that in top 3 clusters, 54 of KBD-related genes were included in the network and 110 candidate genes were discovered might be potentially related to KBD.The 110 candidate genes discovered in the current study may be related to the development of KBD. The expression changes of apoptosis and oxidative stress-related genes might serve as biomarkers for early diagnosis and treatment of KBD.
为了对大骨节病（KBD）相关基因的生物学功能和相互作用进行全面分析，从而为理解大骨节病的发病机制提供信息。设计并开展了一项回顾性的综合生物信息学分析。首先，通过查阅PubMed上的文献，我们确定了922个与大骨节病有遗传关联的基因。然后，使用Cytoscape软件进行生物学功能和网络分析。此外，通过Cytocluster使用分子复合物检测算法（MCODE）进行大骨节病特异性分子网络分析。生物学功能富集分析表明，胶原蛋白分解代谢过程、蛋白质激活级联反应、细胞对生长因子刺激的反应、骨骼系统发育和外源性细胞凋亡在大骨节病的发展中起重要作用。在京都基因与基因组百科全书（KEGG）通路网络中，细胞凋亡通路、核因子κB信号通路和谷胱甘肽代谢通路显著富集，表明这些通路可能在大骨节病的发生和发展中起关键作用。MCODE聚类显示，在前3个聚类中，54个与大骨节病相关的基因包含在网络中，并且发现了110个可能与大骨节病潜在相关的候选基因。本研究中发现的110个候选基因可能与大骨节病的发展有关。细胞凋亡和氧化应激相关基因的表达变化可能作为大骨节病早期诊断和治疗的生物标志物。
