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The key candidate genes in tubulointerstitial injury of chronic kidney diseases patients as determined by bioinformatic analysis.
Cell Biochemistry and Function ( IF 2.8 ) Pub Date : 2020-04-27 , DOI: 10.1002/cbf.3545
Wanpeng Wang 1, 2 , Jianxiao Shen 3 , Chaojun Qi 3 , Juan Pu 2 , Haoyu Chen 2 , Zhi Zuo 4
Affiliation  

Pathologic changes such as renal tubular atrophy and interstitial fibrosis are common in chronic kidney disease (CKD), which in turn, leads to loss of renal function. The aims of present study were to screen critical genes with tubulointerstitial lesion in CKD by weighted gene correlation network analysis (WGCNA). Gene expression data including 169 tubulointerstitial samples of CKD and 21 controls downloaded from Gene Expression Omnibus (GEO) database. Totally 294 differentially expressed genes (DEGs) were screened, including 180 upregulated and 114 downregulated genes. Meanwhile, 90 expression data of tubulointerstitial samples combined with clinic information were applied to explore the potential mechanisms of tubulointerstitial lesion. As a consequence, the blue, brown and yellow modules which included the most DEGs compared to the other modules and exhibited strongly association with eGFR, were significantly enriched in several signalling pathways that have been reported involved in pathogenesis of CKD. Furthermore, it was found that the four genes (PLG, ITGB2, CTSS and CCL5) was one of the DEGs which also be identified as hub genes according to Kwithin. Finally, the Nephroseq online tool showed that the tubulointerstitial expression levels of PLG significantly positively correlated with the estimated glomerular filtration rate (eGFR), while ITGB2, CTSS and CCL5 connected negatively to the eGFR of CKD patients. Taken together, WGCNA is an efficient approach to system biology. By this procedure, the present study enhanced the understanding of the transcriptome status of CKD and might shed a light on the further investigation on the mechanisms of renal tubulointerstitial injury in CKD.

中文翻译:

生物信息学分析确定了慢性肾脏疾病患者肾小管间质损伤的关键候选基因。

诸如肾小管萎缩和间质纤维化之类的病理变化在慢性肾脏病(CKD)中很常见,继而导致肾功能丧失。本研究的目的是通过加权基因相关网络分析(WGCNA)筛选CKD中具有肾小管间质病变的关键基因。基因表达数据包括169个CKD肾小管间质样本和21个从Gene Expression Omnibus(GEO)数据库下载的对照。总共筛选了294个差异表达基因(DEG),包括180个上调的基因和114个下调的基因。同时,结合临床资料,结合肾小管间质标本的90个表达数据,探讨了肾小管间质病变的潜在机制。结果,蓝色 与其他模块相比,包含最多DEG且与eGFR密切相关的棕色和黄色模块明显丰富了一些已报道的CKD发病机制的信号通路。此外,还发现这四个基因(PLG,ITGB2,CTSS和CCL5)是DEGs之一,根据Kwithin,它们也被鉴定为中心基因。最后,Nephroseq在线工具显示PLG的肾小管间质表达水平与估计的肾小球滤过率(eGFR)显着正相关,而ITGB2,CTSS和CCL5与CKD患者的eGFR负相关。综上所述,WGCNA是一种有效的系统生物学方法。通过这个程序,
更新日期:2020-04-27
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