PDF(Pubmed)
Abstract：
Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein-protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD.
摘要：
如果不及时进行干预，慢性肾脏病（CKD）不可避免地会发展为终末期肾病。然而,单纯依靠肾功能变化预测CKD进展存在局限性.需要能够早期预测CKD进展的具有高灵敏度和特异性的生物标志物。我们使用在线基因表达Omnibus微阵列数据集GSE45980来鉴定进行性和稳定性CKD患者的差异表达基因(DEGs)。然后，我们对DEGs进行了功能富集和蛋白质-蛋白质相互作用网络分析，并确定了关键基因。最后,使用GSE60860数据集验证了关键基因的表达模式，并进行了受试者工作特征曲线分析，以阐明其对进行性CKD的预测能力。最终,我们通过实时PCR和蛋白质印迹分析验证了这些hub基因在体外肾间质纤维化模型中的表达谱.差异表达分析鉴定了50个上调基因和47个下调基因。功能富集分析结果表明,上调的DEGs主要富集在免疫应答中,炎症反应，和NF-κB信号通路，而下调的DEGs主要与血管生成和细胞外环境有关。蛋白质-蛋白质相互作用网络和关键基因分析确定CCR7是最重要的基因。CCR7主要在免疫应答中起作用,和它唯一的受体，CCL19和CCL21也被确定为DEG。CCR7，CCL19和CCL21的受试者工作特征曲线分析发现，CCR7和CCL19具有良好的疾病预测能力。CCR7可能是预测CKD进展的稳定生物标志物。CCR7-CCL19/CCL21轴可能是终末期肾病的治疗靶点。然而,需要进一步的实验来探索这些基因与CKD之间的关系。
