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糖尿病肾病独特的分子机制:对250多个微阵列数据集的生物信息学分析

The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasets.

作者信息

Zhou Le-Ting, Zhang Zhi-Jian, Cao Jing-Yuan, Chen Hanzhi, Zhu Yu-Shan, Wu Xi, Nawabi Abdul Qadir, Liu Xiaobin, Shan Weiwei, Zhang Yue, Zhang Xi-Ran, Xue Jing, Hu Ling, Wang Si-Si, Wang Liang, Sun Zhu-Xing

机构信息

Department of Nephrology, Nanjing Medical University Affiliated Wuxi People's Hospital, Wuxi, Jiangsu, China.

Nephrology Department, Taizhou People's Hospital, Fifth Affiliated Hospital to Nantong University, Taizhou, Jiangsu, China.

出版信息

Clin Kidney J. 2021 Mar 18;14(6):1626-1638. doi: 10.1093/ckj/sfaa190. eCollection 2021 Jun.

Abstract

BACKGROUND/AIMS: Diabetic nephropathy (DN) is one of the main causes of end-stage kidney disease worldwide. Emerging studies have suggested that its pathogenesis is distinct from nondiabetic renal diseases in many aspects. However, it still lacks a comprehensive understanding of the unique molecular mechanism of DN.

METHODS

A total of 255 Affymetrix U133 microarray datasets (Affymetrix, Santa Calra, CA, USA) of human glomerular and tubulointerstitial tissues were collected. The 22 215 Affymetrix identifiers shared by the Human Genome U133 Plus 2.0 and U133A Array were extracted to facilitate dataset pooling. Next, a linear model was constructed and the empirical Bayes method was used to select the differentially expressed genes (DEGs) of each kidney disease. Based on these DEG sets, the unique DEGs of DN were identified and further analyzed using gene ontology and pathway enrichment analysis. Finally, the protein-protein interaction networks (PINs) were constructed and hub genes were selected to further refine the results.

RESULTS

A total of 129 and 1251 unique DEGs were identified in the diabetic glomerulus (upregulated  = 83 and downregulated  = 203) and the diabetic tubulointerstitium (upregulated  = 399 and downregulated  = 874), respectively. Enrichment analysis revealed that the DEGs in the diabetic glomerulus were significantly associated with the extracellular matrix, cell growth, regulation of blood coagulation, cholesterol homeostasis, intrinsic apoptotic signaling pathway and renal filtration cell differentiation. In the diabetic tubulointerstitium, the significantly enriched biological processes and pathways included metabolism, the advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications, the epidermal growth factor receptor (EGFR) signaling pathway, the FoxO signaling pathway, autophagy and ferroptosis. By constructing PINs, several nodes, such as AGR2, CSNK2A1, EGFR and HSPD1, were identified as hub genes, which might play key roles in regulating the development of DN.

CONCLUSIONS

Our study not only reveals the unique molecular mechanism of DN but also provides a valuable resource for biomarker and therapeutic target discovery. Some of our findings are promising and should be explored in future work.

摘要

背景/目的:糖尿病肾病(DN)是全球终末期肾病的主要病因之一。新兴研究表明,其发病机制在许多方面与非糖尿病性肾脏疾病不同。然而,目前仍缺乏对DN独特分子机制的全面了解。

方法

收集了总共255个人类肾小球和肾小管间质组织的Affymetrix U133微阵列数据集(Affymetrix,美国加利福尼亚州圣克拉拉)。提取人类基因组U133 Plus 2.0和U133A阵列共有的22215个Affymetrix标识符,以方便数据集合并。接下来,构建线性模型,并使用经验贝叶斯方法选择每种肾脏疾病的差异表达基因(DEG)。基于这些DEG集,鉴定出DN的独特DEG,并使用基因本体论和通路富集分析进行进一步分析。最后,构建蛋白质-蛋白质相互作用网络(PIN)并选择枢纽基因以进一步完善结果。

结果

在糖尿病肾小球(上调=83,下调=203)和糖尿病肾小管间质(上调=399,下调=874)中分别鉴定出129个和1251个独特的DEG。富集分析显示,糖尿病肾小球中的DEG与细胞外基质、细胞生长、凝血调节、胆固醇稳态、内在凋亡信号通路和肾滤过细胞分化显著相关。在糖尿病肾小管间质中,显著富集的生物学过程和通路包括代谢、糖尿病并发症中的晚期糖基化终产物-晚期糖基化终产物信号通路受体、表皮生长因子受体(EGFR)信号通路、FoxO信号通路、自噬和铁死亡。通过构建PIN,确定了几个节点,如AGR2、CSNK2A1、EGFR和HSPD1作为枢纽基因,它们可能在调节DN的发展中起关键作用。

结论

我们的研究不仅揭示了DN的独特分子机制,还为生物标志物和治疗靶点的发现提供了宝贵资源。我们的一些发现很有前景,应在未来的工作中进行探索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4948/8162860/2565b02fdba6/sfaa190f1.jpg

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