Deng Wenjia, Cui Lingang, Li Teng, Meng Qingjun, Sun Taotao, Yuan Penghui
Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
Sex Med. 2025 Jan 9;12(6):qfae090. doi: 10.1093/sexmed/qfae090. eCollection 2024 Dec.
Diabetic erectile dysfunction (DMED) has a high incidence and is poorly treated.
This study investigates fibrosis's genetic profiling and explores potential mechanisms for DMED.
The DMED model was constructed in rats using streptozotocin. Erectile function was quantified using cavernous nerve electrostimulation. Fibrosis was evaluated using Masson's staining. RNA-seq was employed to analyze differentially expressed genes and fibrosis-related genes (FRGs) were acquired. Function enrichment analyses were performed, and genetic interaction was analyzed. Hub FRGs were screened using machine learning algorithms and Cytoscape tools and validated in Gene Expression Omnibus databases. Moreover, biological roles and subpopulation distribution of hub FRGs were determined.
Fibrosis-related genetic functions may play a vital role in DMED.
Based on comprehensive analysis, 45 differentially expressed FRGs were identified. These genes participate in regulating smooth muscle cell proliferation, vasoconstriction, and collagen-associated activities. Final analyses identified and validated a core gene signature comprising TIMP1, BMP7, and POSTN. They were closely associated with diabetic complications-related signaling pathways and extracellular matrix-receptor interaction.
The identified fibrosis-related gene signature may serve as the novel biomarkers for treating DMED.
The study is the first to investigate the genetic profiles behind fibrosis and DMED using comprehensive approaches. However, the validation is not adequate and more animal experiments are needed.
The gene profiling and biological functions of FRGs in DMED were identified. These results broaden the understanding of fibrosis in DMED.
糖尿病性勃起功能障碍（DMED）发病率高且治疗效果不佳。
本研究调查纤维化的基因谱，并探索DMED的潜在机制。
使用链脲佐菌素在大鼠中构建DMED模型。通过海绵体神经电刺激对勃起功能进行量化。使用Masson染色评估纤维化。采用RNA测序分析差异表达基因，并获取纤维化相关基因（FRGs）。进行功能富集分析，并分析基因相互作用。使用机器学习算法和Cytoscape工具筛选枢纽FRGs，并在基因表达综合数据库中进行验证。此外，确定枢纽FRGs的生物学作用和亚群分布。
纤维化相关基因功能可能在DMED中起关键作用。
基于综合分析，鉴定出45个差异表达的FRGs。这些基因参与调节平滑肌细胞增殖、血管收缩和胶原相关活动。最终分析鉴定并验证了一个由TIMP1、BMP7和POSTN组成的核心基因特征。它们与糖尿病并发症相关信号通路和细胞外基质-受体相互作用密切相关。
鉴定出的纤维化相关基因特征可作为治疗DMED的新型生物标志物。
本研究首次采用综合方法研究纤维化和DMED背后的基因谱。然而，验证不够充分，需要更多动物实验。
确定了DMED中FRGs的基因谱和生物学功能。这些结果拓宽了对DMED中纤维化的认识。
