目的

利用生物信息学，筛选原发性痛风性关节炎（PGA）与高尿酸血症（HUA）的关键基因及探索相关通路。

方法

从GeneCards、OMIM、DisGeNET 3个数据库中检索PGA与HUA的疾病基因靶点，分别对所得的靶点进行总结、筛选和去重，分别获得两组疾病最终基因靶点。然后取交集处理，将共同的基因靶点导入STRING数据库构建蛋白互作（PPI）网络图中，下载 tsv格式的PPI网络，并导入Cytoscape 3.8.0软件，通过CytoHubba插件，按度中心度、接近中心度、介数中心度大于中值的条件，筛选出度中心度排在前27个的目标靶基因。利用 DAVID数据库对PGA和HUA两种疾病的共同靶基因进行GO富集分析和KEGG富集分析。

结果

筛选出PGA相关基因389个、HUA相关基因 802个，两组疾病基因交集后获得共同靶基因150个，利用PPI网络图和CytoHubba的分析结果，确定了IL-6、RELA、APP、TNF、INS、IL-1β、CXCL8、MAPK1、TLR4等为PGA与HUA的共同关键靶基因，GO富集分析显示其主要与炎症反应、免疫反应等生物过程相关，KEGG信号通路分析包括NOD样受体信号通路、Toll样受体信号通路、核因子κB信号通路、HIF-1信号通路、肿瘤坏死因子信号通路等。

结论

通过PGA与HUA的共同关键基因和涉及的信号通路，为了解两种疾病相关性，以及后续相关研究提供了一定的理论基础。

Objective

To identify shared key genes and pathways linking primary gouty arthritis(PGA) and hyperuricemia (HUA) through bioinformatics approaches.

Methods

Disease-associated gene targets of PGA and HUA were retrieved from GeneCards, OMIM and DisGeNET databases. After deduplication and filtration, the final gene targets for two groups of diseases were obtained. Then take the intersection and import the common gene targets into the STRING database to construct a protein-protein interaction (PPI) network diagram. Download the tsv format PPI network and import it into Cytoscape 3.8.0.Hub genes were prioritized using CytoHubba plugin with topological criteria: degree/closeness/betweenness centrality above median values, yielding top 27 hub genes. Perform GO enrichment analysis and KEGG enrichment analysis on common target genes of PGA and HUA using the DAVID database.

Results

389 genes from PGA and 802 genes from HUA were selected, 150 common target genes, according to the PPI network diagram, IL-6, RELA, APP, TNF, INS, IL-1β, CXCL8, MAPK1, and TLR4 are the common key target genes of PGA and HUA, GO enrichment showed that it was mainly related to inflammatory response, immune response, etc., KEGG signaling includes NOD-like receptor signaling, Toll-like receptor signaling, nuclear factor-kappa B signaling, HIF-1 signaling and tumor necrosis factor signaling.

Conclusion

The common key genes and signaling pathways involved in PGA and HUA provide a theoretical basis for understanding the correlation between the two diseases and subsequent related research.