组织工程与重建外科杂志2025，Vol.21Issue(3)：238-249,12.DOI:10.3969/j.issn.1673-0364.2025.03.005
通过整合生物信息学分析与机器学习揭示糖尿病足溃疡缺氧相关生物标志物
Unveiling hypoxia-related biomarkers for diabetic foot ulcers through integrated bioinformatics analysis and machine learning
摘要
Abstract
Objective Diabetic foot ulcer(DFU)is a severe complication in diabetic patients,where the hypoxic microenvironment plays a critical role in its pathogenesis and delayed healing,though the underlying molecular mechanisms remain unclear.To systematically analyze the regulatory network of hypoxia-related genes in DFU using bioinformatics approaches,identify key biomarkers,and provide insights for targeted therapies.Methods Integrated datasets from GEO and MSigDB hypoxia-related gene sets were utilized.Differential expression analysis(limma,DESeq2),weighted gene co-expression network analysis(WGCNA),and GO/KEGG functional enrichment were performed.Hub genes were screened using three machine learning algorithms(Lasso,SVM-RFE,and random forest),and their diagnostic efficacy was validated.Results A total of 152 differentially expressed genes(DEGs)were identified,including 14 hypoxia-related DEGs(HRDEGs).Enrichment analysis revealed HRDEGs involvement in glucose metabolism,lipid metabolism,and immune cell regulation.Machine learning further pinpointed the hub gene BGN.BGN exhibited significantly lower expression in DFU groups,with area under the ROC curve(AUC)values of 0.833(training set)and 0.931(validation set),indicating high diagnostic accuracy.Single-gene GSEA demonstrated that BGN participates in DFU pathology by regulating tissue repair,inflammatory responses,and extracellular matrix interactions.Conclusion BGN is a key biomarker in the hypoxic microenvironment of DFU and may serve as a potential molecular target for early diagnosis and targeted therapy.This study provides new directions for understanding DFU mechanisms and clinical interventions.关键词
糖尿病足溃疡/缺氧/生物信息学Key words
Diabetic foot ulcer/Hypoxia/Bioinformatics分类
临床医学引用本文复制引用
郭根宇,张楚乔,许尹梅,孟浩,付小兵,姜玉峰..通过整合生物信息学分析与机器学习揭示糖尿病足溃疡缺氧相关生物标志物[J].组织工程与重建外科杂志,2025,21(3):238-249,12.基金项目
中国工程科技发展战略湖南研究院战略研究与咨询(2024WK1006). （2024WK1006）
