Pathway-based network analyses and candidate genes associated with Kashin-Beck disease

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.