Lin Jiaqiong, Lin Yan, Li Xiaoyong, He Fei, Gao Qinyuan, Wang Yuanjun, Huang Zena, Xiong Fu
Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, People's Republic of China.
Dongguan Maternal and Child Health Care Hospital, Postdoctoral Innovation Practice Base of Southern Medical University, Dongguan, People's Republic of China.
J Inflamm Res. 2024 Jul 24;17:4975-4991. doi: 10.2147/JIR.S446752. eCollection 2024.
Diabetic kidney disease (DKD) is an intricate complication of diabetes with limited treatment options. Anoikis, a programmed cell death activated by loss of cell anchorage to the extracellular matrix, participated in various physiological and pathological processes. Our study aimed to elucidate the role of anoikis-related genes in DKD pathogenesis.
Differentially expressed genes (DEGs) associated with anoikis in DKD were identified. Weighted gene co-expression network analysis (WGCNA) was conducted to identify DKD-correlated modules and assess their functional implications. A diagnostic model for DKD was developed using LASSO regression and Gene set variation analysis (GSVA) was performed for enrichment analysis. Experimental validation was employed to validate the significance of selected genes in the progression of DKD.
We identified 10 anoikis-related DEGs involved in key signaling pathways impacting DKD progression. WGCNA highlighted the yellow module's significant enrichment in immune response and regulatory pathways. Correlation analysis further revealed the association between immune infiltration and anoikis-related DEGs. Our LASSO regression-based diagnostic model demonstrated a well-predictive efficacy with seven identified genes. GSVA indicated that gene function in the high-risk group was primarily associated with immune regulation. Further experimental validation using diabetic mouse models and data analysis in the single-cell dataset confirmed the significance of PYCARD and SFN in DKD progression. High glucose stimulation in RAW264.7 and TCMK-1 cells showed significantly increased expression levels of both Pycard and Sfn. Co-expression analysis demonstrated distinct functions of PYCARD and SFN, with KEGG pathway analysis showing significant enrichment in immune regulation and cell proliferation pathway.
In conclusion, our study provides valuable insights into the molecular mechanisms involved in DKD pathogenesis, specifically highlighting the role of anoikis-related genes in modulating immune infiltration. These findings suggest that targeting these genes may hold promise for future diagnostic and therapeutic approaches in DKD management.
糖尿病肾病(DKD)是糖尿病一种复杂的并发症,治疗选择有限。失巢凋亡是一种由细胞与细胞外基质失去锚定作用而激活的程序性细胞死亡,参与各种生理和病理过程。我们的研究旨在阐明失巢凋亡相关基因在DKD发病机制中的作用。
鉴定与DKD中失巢凋亡相关的差异表达基因(DEGs)。进行加权基因共表达网络分析(WGCNA)以识别与DKD相关的模块并评估其功能意义。使用LASSO回归开发DKD的诊断模型,并进行基因集变异分析(GSVA)以进行富集分析。采用实验验证来验证所选基因在DKD进展中的意义。
我们鉴定出10个与失巢凋亡相关的DEGs,它们参与影响DKD进展的关键信号通路。WGCNA突出显示黄色模块在免疫反应和调节通路中显著富集。相关性分析进一步揭示了免疫浸润与失巢凋亡相关DEGs之间的关联。我们基于LASSO回归的诊断模型显示,7个已鉴定基因具有良好的预测效能。GSVA表明高危组中的基因功能主要与免疫调节相关。使用糖尿病小鼠模型进行的进一步实验验证以及单细胞数据集中的数据分析证实了PYCARD和SFN在DKD进展中的意义。RAW264.7和TCMK-1细胞中的高糖刺激显示Pycard和Sfn的表达水平均显著升高。共表达分析显示PYCARD和SFN具有不同功能,KEGG通路分析显示在免疫调节和细胞增殖通路中显著富集。
总之,我们的研究为DKD发病机制所涉及的分子机制提供了有价值的见解,特别强调了失巢凋亡相关基因在调节免疫浸润中的作用。这些发现表明,针对这些基因可能为DKD管理的未来诊断和治疗方法带来希望。