Liang Yingchao, Liang Zhiyi, Huang Jinxian, Jia Mingjie, Liu Deliang, Zhang Pengxiang, Fang Zebin, Hu Xinyu, Li Huilin
Graduate School of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Front Med (Lausanne). 2023 Jun 19;10:1158166. doi: 10.3389/fmed.2023.1158166. eCollection 2023.
Aging and immune infiltration have essential role in the physiopathological mechanisms of diabetic nephropathy (DN), but their relationship has not been systematically elucidated. We identified aging-related characteristic genes in DN and explored their immune landscape.
Four datasets from the Gene Expression Omnibus (GEO) database were screened for exploration and validation. Functional and pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Characteristic genes were obtained using a combination of Random Forest (RF) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm. We evaluated and validated the diagnostic performance of the characteristic genes using receiver operating characteristic (ROC) curve, and the expression pattern of the characteristic genes was evaluated and validated. Single-Sample Gene Set Enrichment Analysis (ssGSEA) was adopted to assess immune cell infiltration in samples. Based on the TarBase database and the JASPAR repository, potential microRNAs and transcription factors were predicted to further elucidate the molecular regulatory mechanisms of the characteristic genes.
A total of 14 differentially expressed genes related to aging were obtained, of which 10 were up-regulated and 4 were down-regulated. Models were constructed by the RF and SVM-RFE algorithms, contracted to three signature genes: EGF-containing fibulin-like extracellular matrix (EFEMP1), Growth hormone receptor (GHR), and Vascular endothelial growth factor A (VEGFA). The three genes showed good efficacy in three tested cohorts and consistent expression patterns in the glomerular test cohorts. Most immune cells were more infiltrated in the DN samples compared to the controls, and there was a negative correlation between the characteristic genes and most immune cell infiltration. 24 microRNAs were involved in the transcriptional regulation of multiple genes simultaneously, and Endothelial transcription factor GATA-2 (GATA2) had a potential regulatory effect on both GHR and VEGFA.
We identified a novel aging-related signature allowing assessment of diagnosis for DN patients, and further can be used to predict immune infiltration sensitivity.
衰老和免疫浸润在糖尿病肾病（DN）的生理病理机制中起重要作用，但其关系尚未得到系统阐明。我们鉴定了DN中与衰老相关的特征基因，并探索了它们的免疫格局。
从基因表达综合数据库（GEO）中筛选出四个数据集进行探索和验证。使用基因集富集分析（GSEA）进行功能和通路分析。使用随机森林（RF）和支持向量机递归特征消除（SVM-RFE）算法相结合的方法获得特征基因。我们使用受试者工作特征（ROC）曲线评估并验证了特征基因的诊断性能，并评估和验证了特征基因的表达模式。采用单样本基因集富集分析（ssGSEA）评估样本中的免疫细胞浸润情况。基于TarBase数据库和JASPAR储存库，预测潜在的微小RNA和转录因子，以进一步阐明特征基因的分子调控机制。
共获得14个与衰老相关的差异表达基因，其中10个上调，4个下调。通过RF和SVM-RFE算法构建模型，将其缩减为三个特征基因：含表皮生长因子的纤连蛋白样细胞外基质（EFEMP1）、生长激素受体（GHR）和血管内皮生长因子A（VEGFA）。这三个基因在三个测试队列中显示出良好的效果，在肾小球测试队列中表达模式一致。与对照组相比，大多数免疫细胞在DN样本中的浸润更多，且特征基因与大多数免疫细胞浸润之间存在负相关。24个微小RNA同时参与多个基因的转录调控，内皮转录因子GATA-2（GATA2）对GHR和VEGFA均有潜在调控作用。
我们鉴定了一种新的与衰老相关的特征，可用于评估DN患者的诊断，并且进一步可用于预测免疫浸润敏感性。
