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运用综合生物信息学分析鉴定糖尿病肾病中的新型关键基因和潜在候选小分子药物

Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis.

作者信息

Li Bin, Ye Siyang, Fan Yuting, Lin Yi, Li Suchun, Peng Huajing, Diao Hui, Chen Wei

机构信息

Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

NHC Key Laboratory of Clinical Nephrology (Sun Yat-sen University) and Guangdong Provincial Key Laboratory of Nephrology, Guangzhou, China.

出版信息

Front Genet. 2022 Aug 12;13:934555. doi: 10.3389/fgene.2022.934555. eCollection 2022.

DOI:10.3389/fgene.2022.934555
PMID:36035169
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9411649/
Abstract

The currently established diagnostic and prognostic tools for diabetic kidney disease (DKD) have limitations, which demands the necessity to find new genes and pathways associated with diagnosis and treatment. Our study aims to reveal the gene expression alteration and discover critical genes involved in the development of DKD, thus providing novel diagnostic molecular markers and therapeutic targets. The differences of infiltrating immune cells within kidney were compared between healthy living donors and DKD patients. Besides, differentially expressed genes (DEGs) within kidney from healthy living donor, early stage DKD and advanced stage DKD samples were detected. Furthermore, the weighted co-expressed network (WGCNA) and protein-protein interaction (PPI) network were constructed, followed by recognition of core hub genes and module analysis. Receiver operating characteristic (ROC) curve analysis was implemented to determine the diagnostic value of hub genes, correlation analysis was employed to explore the association between hub genes and infiltrating immune cells, and certain hub genes was validated by quantitative real-time PCR and immunohistochemistry staining in cultured tubule cells and diabetic mice kidney. Finally, the candidate small molecules as potential drugs to treat DKD were anticipated through utilizing virtual screening and molecular docking investigation. Our study revealed significantly higher proportion of infiltrating immune cells within kidney from DKD patients via probing the immune landscape by single-cell transcriptomics. Besides, 126 commonly shared DEGs identified among three group samples were enriched in immune biological process. In addition, the ROC curve analysis demonstrated the strong diagnostic accuracy of recognized hub genes (, , , , and ) from PPI network. Correlation analysis further confirmed the positive association between these hub genes with infiltrating natural killer cells. More importantly, the mRNA transcripts and protein abundance of YAP1 were significantly higher in high glucose-treated renal tubule cells and diabetic mice kidney, and the small molecules exhibiting the best binding affinities with YAP1 were predicted and acquired. Our findings for the first time indicate that , , , , and might be potential novel biomarkers and therapeutic targets for DKD, providing insights into the molecular mechanisms underlying the pathogenesis of DKD.

摘要

目前已确立的糖尿病肾病(DKD)诊断和预后工具存在局限性,这就需要寻找与诊断和治疗相关的新基因和途径。我们的研究旨在揭示基因表达变化,发现参与DKD发生发展的关键基因,从而提供新的诊断分子标志物和治疗靶点。比较了健康活体供者和DKD患者肾脏中浸润免疫细胞的差异。此外,检测了健康活体供者、DKD早期和晚期样本肾脏中的差异表达基因(DEG)。此外,构建了加权共表达网络(WGCNA)和蛋白质-蛋白质相互作用(PPI)网络,随后识别核心枢纽基因并进行模块分析。采用受试者工作特征(ROC)曲线分析来确定枢纽基因的诊断价值,采用相关性分析来探索枢纽基因与浸润免疫细胞之间的关联,并通过定量实时PCR和免疫组织化学染色在培养的肾小管细胞和糖尿病小鼠肾脏中验证某些枢纽基因。最后,通过虚拟筛选和分子对接研究预测了作为治疗DKD潜在药物的候选小分子。我们的研究通过单细胞转录组学探究免疫图谱,发现DKD患者肾脏中浸润免疫细胞的比例显著更高。此外,在三组样本中鉴定出的126个共同的DEG在免疫生物学过程中富集。此外,ROC曲线分析表明从PPI网络识别出的枢纽基因(、、、、和)具有很强的诊断准确性。相关性分析进一步证实了这些枢纽基因与浸润性自然杀伤细胞之间的正相关。更重要的是,YAP1的mRNA转录本和蛋白质丰度在高糖处理的肾小管细胞和糖尿病小鼠肾脏中显著更高,并预测并获得了与YAP1表现出最佳结合亲和力的小分子。我们的研究首次表明,、、、、和可能是DKD潜在的新型生物标志物和治疗靶点,为DKD发病机制的分子机制提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68fb/9411649/49129c178d48/fgene-13-934555-g008.jpg
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