Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Eur Rev Med Pharmacol Sci. 2022 May;26(10):3607-3620. doi: 10.26355/eurrev_202205_28857.
Emerging studies have suggested a strong link between Crohn's disease (CD) and IgA nephropathy (IgAN), but the underlying pathogenesis remains unclear. This led us to explore the common pathogenic genes for the two diseases by originally applying a bioinformatic method.
The CD and IgAN datasets were downloaded from the Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) of the two diseases were identified. GO and KEGG enrichment analyses for the common DEGs were further performed. Then, PPI networks were constructed to identify the hub genes. Afterwards, the receiver operating characteristic (ROC) curves were constructed to assess the diagnostic value of the hub genes. Finally, the immune infiltrations in the samples were analyzed and the correlation of the hub genes with the immune infiltration was studied.
47 common DEGs were identified between CD and IgAN with the threshold of p-value < 0.05 and |log2FC| > 1. The top 5 GO terms and 5 KEGG pathways were displayed, and the top 10 hub genes were selected. The diagnostic value of these hub genes was evaluated by calculating the area under the ROC curves. Among the hub genes, CXCL2 was not only identified as the common hub gene, but also with the highest diagnostic value. Finally, CXCL2 was verified to be crucially correlated with the immune infiltration in the samples of CD and IgAN.
Our study identified critical pathogenic genes commonly responsible for the pathogenesis of CD and IgAN, which provided novel biomarkers and promising therapeutic targets for the two diseases. Further experimental and clinical research are needed to verify our results.
越来越多的研究表明,克罗恩病(CD)与 IgA 肾病(IgAN)之间存在很强的关联,但潜在的发病机制尚不清楚。因此,我们通过最初应用生物信息学方法来探索这两种疾病的共同致病基因。
从基因表达综合数据库(GEO)下载 CD 和 IgAN 数据集。鉴定两种疾病的常见差异表达基因(DEGs)。对共同 DEGs 进行 GO 和 KEGG 富集分析。然后构建 PPI 网络以识别枢纽基因。接下来,构建 ROC 曲线以评估枢纽基因的诊断价值。最后,分析样本中的免疫浸润情况,并研究枢纽基因与免疫浸润的相关性。
以 p 值<0.05 和 |log2FC|>1 为阈值,在 CD 和 IgAN 之间鉴定出 47 个共同 DEG。展示了前 5 个 GO 术语和前 5 个 KEGG 途径,并选择了前 10 个枢纽基因。通过计算 ROC 曲线下的面积来评估这些枢纽基因的诊断价值。在枢纽基因中,CXCL2 不仅被鉴定为共同枢纽基因,而且具有最高的诊断价值。最后,验证了 CXCL2 与 CD 和 IgAN 样本中的免疫浸润密切相关。
本研究确定了共同导致 CD 和 IgAN 发病机制的关键致病基因,为这两种疾病提供了新的生物标志物和有前途的治疗靶点。需要进一步的实验和临床研究来验证我们的结果。