DR 患者和健康对照的 RNA 数据测序 （2）

我们收集了 10 例 DR 个体和 10 例正常对照 （NCs） 的全血样本用于转录组测序。在对测序数据进行质量控制和预处理后，进行差异表达分析以鉴定 DR 组和 NC 组之间的差异表达基因 （DEG）。然后通过将这些 DEGs 与通过加权基因共表达网络分析鉴定的关键模块基因相交来选择候选基因。这些候选基因进行孟德尔随机化 （MR） 分析，然后进行最小绝对收缩和选择运算符分析以查明关键基因。采用受试者工作特征曲线分析评价这些关键基因的诊断效用，并检查其表达水平。进行了其他分析，包括列线图构建、基因集富集分析、药物预测和分子对接，以研究关键基因的功能和分子机制。

We collected whole blood samples from 10 individuals with Diabetic Retinopathy (DR) and 10 normal controls (NCs) for transcriptome sequencing. After quality control and preprocessing of the sequencing data, differential expression analysis was performed to identify differentially expressed genes (DEGs) between the DR and NC groups. Candidate genes were then selected by intersecting these DEGs with key module genes identified via Weighted Gene Co-expression Network Analysis (WGCNA). These candidate genes were subjected to Mendelian Randomization (MR) analysis, followed by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis to screen out key genes. Receiver Operating Characteristic (ROC) curve analysis was employed to evaluate the diagnostic utility of these key genes, and their expression levels were examined. Additional analyses including nomogram construction, Gene Set Enrichment Analysis (GSEA), drug prediction, and molecular docking were conducted to investigate the functions and molecular mechanisms of the key genes.