Hu Bo, Li Xuan, Li Yunfeng, Chai Shengnan, Jin Mei, Zhang Long
Wound Healing Center, Peking University Third Hospital, Beijing, China.
Front Mol Biosci. 2025 Jul 9;12:1593390. doi: 10.3389/fmolb.2025.1593390. eCollection 2025.
Diabetic foot ulcers (DFUs) are chronic complications of diabetes, driven by metabolic dysregulation and impaired wound healing. This study investigates the roles of hypoxia, glycolysis, and lactylation in DFUs and identifies potential diagnostic and therapeutic biomarkers.
Single-cell RNA sequencing (scRNA-seq) was employed to assess cellular diversity, metabolic states, and intercellular communication in DFUs. KEGG/GO enrichment, pseudotime trajectory analysis, and cell-cell communication profiling were conducted to explore metabolic and cellular dynamics. Bulk RNA-seq was integrated for differential expression analysis and biomarker validation. Machine learning methods, including LASSO, Support vector machine, and Random Forest, were applied to identify and validate biomarkers across external datasets.
Metabolic shifts in hypoxia, glycolysis, and lactylation were observed, with keratinocytes displaying the highest metabolic activity. Pseudotime analysis revealed distinct wound-healing phases, while cell-cell communication profiling identified increased signaling among keratinocytes, fibroblasts, and SMCs in high-metabolic states, disrupting key pathways like ECM-receptor interaction and focal adhesion. Machine learning integration of scRNA-seq and bulk RNA-seq identified PKM, GAMT, and EGFR as diagnostic biomarkers strongly linked to metabolic and immune regulation. Functional analyses highlighted their roles in energy metabolism, cellular proliferation, and immune signaling, providing new insights into DFU pathogenesis.
This study reveals metabolic dysregulation and disrupted cellular communication as central to the non-healing DFU microenvironment, with validated biomarkers and pathways offering potential targets for improved diagnosis and treatment.
糖尿病足溃疡（DFUs）是糖尿病的慢性并发症，由代谢失调和伤口愈合受损所致。本研究探讨缺氧、糖酵解和乳酸化在糖尿病足溃疡中的作用，并确定潜在的诊断和治疗生物标志物。
采用单细胞RNA测序（scRNA-seq）评估糖尿病足溃疡中的细胞多样性、代谢状态和细胞间通讯。进行KEGG/GO富集、伪时间轨迹分析和细胞间通讯分析，以探索代谢和细胞动态。整合批量RNA测序进行差异表达分析和生物标志物验证。应用包括LASSO、支持向量机和随机森林在内的机器学习方法，在外部数据集中识别和验证生物标志物。
观察到缺氧、糖酵解和乳酸化中的代谢变化，角质形成细胞表现出最高的代谢活性。伪时间分析揭示了不同的伤口愈合阶段，而细胞间通讯分析确定在高代谢状态下角质形成细胞、成纤维细胞和平滑肌细胞之间的信号传导增加，破坏了细胞外基质受体相互作用和粘着斑等关键途径。scRNA-seq和批量RNA-seq的机器学习整合确定PKM、GAMT和EGFR为与代谢和免疫调节密切相关的诊断生物标志物。功能分析突出了它们在能量代谢、细胞增殖和免疫信号传导中的作用，为糖尿病足溃疡的发病机制提供了新的见解。
本研究揭示代谢失调和细胞通讯中断是糖尿病足溃疡不愈合微环境的核心，经过验证的生物标志物和途径为改善诊断和治疗提供了潜在靶点。
