目的：探讨糖尿病肾病(DN)与糖尿病视网膜病变(DR)之间的遗传关联及潜在因果关系，结合差异基因表达分析和孟德尔随机化(MR)方法，揭示二者的共同分子机制。

方法：整合来自Gene Expression Omnibus(GEO)数据库的DN和DR转录组数据进行差异基因表达分析(DEGs)。选取符合显著性标准(log2FC>1，P<0.05)的差异基因，并通过GO和KEGG通路富集分析探讨二者共同的生物学通路。结合DN和DR的全基因组关联研究(GWAS)统计数据，采用双样本MR分析方法探讨DN和DR之间的因果关系，以DN作为暴露因素，DR作为结局变量，主要通过逆方差加权(IVW)法计算因果效应，并进行敏感性分析验证结果的稳健性。

结果：MR分析结果显示，DN显著增加DR的风险。IVW方法估算，非增殖性DR(NPDR)的比值比(OR)为3.23(95%CI：2.12-4.95，P<0.001)，增殖性DR(PDR)的OR为1.10(95%CI：1.06-1.15，P<0.001)。此外，差异基因分析鉴定出多个关键基因(如FN1、COL1A2、THBS2)。FN1和COL1A2在细胞外基质重塑和纤维化过程中发挥重要作用，导致糖尿病并发症中血管通透性改变及微血管损伤。THBS2与新生血管形成和血管稳态调控密切相关，提示其在DR中的潜在作用。通过KEGG通路富集分析，这些差异基因主要富集于糖基化终末产物(AGEs)-RAGE信号通路、细胞外基质降解、氧化应激反应等通路，这些通路与糖尿病肾病和DR的病理特征密切相关。

结论：本研究通过MR分析和差异基因表达分析揭示了DN与DR之间的遗传关联。差异基因表达分析和通路富集分析，揭示了这两种疾病在细胞外基质重塑、炎症反应及新生血管形成等生物学通路中的共同机制，可能成为未来治疗糖尿病并发症的新靶点，为早期诊断和靶向治疗提供了理论依据。

METHODS: Transcriptomic data of DN and DR were obtained from the Gene Expression Omnibus(GEO)database and analyzed for differentially expressed genes(DEGs). Genes meeting the significance threshold(log2FC>1, P<0.05)were identified, followed by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to explore shared biological pathways. Using genome-wide association study(GWAS)summary statistics for DN and DR, two-sample MR analysis was performed, with DN as the exposure and DR as the outcome. The causal effect was primarily estimated with the inverse-variance weighted(IVW)method, and sensitivity analyses were conducted to assess robustness.

RESULTS: MR analysis revealed that DN significantly increased the risk of DR. IVW estimates indicated that the odds ratio(OR)for non-proliferative DR(NPDR)was 3.23(95% CI: 2.12-4.95, P<0.001), and the OR for proliferative DR(PDR)was 1.10(95% CI: 1.06-1.15, P<0.001). DEG analysis identified several key genes, including FN1, COL1A2, and THBS2. FN1 and COL1A2 are involved in extracellular matrix remodeling and fibrosis, contributing to vascular permeability alterations and microvascular damage in diabetic complications. THBS2 is closely associated with angiogenesis and vascular homeostasis, suggesting its potential role in DR. KEGG enrichment analysis showed that these DEGs were mainly enriched in advanced glycation end products(AGEs)-RAGE signaling, extracellular matrix degradation, and oxidative stress pathways, all of which are highly relevant to the pathogenesis of DN and DR.

CONCLUSION: This study demonstrates the genetic association between DN and DR using MR and DEGs analyses. The shared mechanisms, particularly involving extracellular matrix remodeling, inflammatory response, and angiogenesis, may serve as novel therapeutic targets and provide a theoretical basis for the early diagnosis and targeted treatment of diabetic complications.