中国组织工程研究

中国组织工程研究 ›› 2026, Vol. 30 ›› Issue (22): 5694-5706.doi: 10.12307/2026.171

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糖尿病足溃疡生物标志物：单细胞转录组生物信息学分析和实验验证

杨文燕1，2，王华雨1，杨丽科1，庞  雪3，王玉涛1，4   

  1. 1山东中医药大学第一临床医学院，山东省济南市   250355；2河北省沧州中西医结合医院疮疡脉管病科，河北省沧州市   061000；3山东第一医科大学第一附属医院肛肠科，山东省济南市   250014；4中国中医科学院广安门医院济南医院(济南市中医医院)周围血管病科，山东省济南市   250012
  • 收稿日期:2025-06-26 接受日期:2025-10-11 出版日期:2026-08-08 发布日期:2025-12-26
  • 通讯作者: 王玉涛，副主任医师，硕士生导师，山东中医药大学第一临床医学院，山东省济南市 250355；中国中医科学院广安门医院济南医院(济南市中医医院)周围血管病科，山东省济南市 250012
  • 作者简介:杨文燕，女，1993年生，山东中医药大学第一临床医学院在读硕士，河北省沧州中西医结合医院疮疡脉管病科主治医师，主要从事疮疡脉管疾病诊疗工作。
  • 基金资助:
    国家自然科学基金青年基金项目(82104860)，项目负责人：王玉涛；山东省中医药科技发展计划(2019-0559)，项目负责人：王玉涛；济南市卫生健康委员会科技计划项目(2019-1-23)，项目负责人：王玉涛；张红星全国名老中医药专家传承工作室建设项目(国中医药人教函〔2022〕75号)，项目负责人：王玉涛；山东省卫健医疗管理研究中心科研项目(20240430-044)，项目负责人：庞雪；济南市医疗卫生行业高层次人才专项经费资助(202412)，项目负责人：王玉涛

Biomarkers for diabetic foot ulcers: single-cell transcriptomics bioinformatics analysis and experimental validation

Yang Wenyan1, 2, Wang Huayu1, Yang Like1, Pang Xue3, Wang Yutao1, 4   

  1. 1First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; 2Department of Ulcer and Vascular Diseases, Cangzhou Hospital of Integrated TCM-WM·HEBEI, Cangzhou 061000, Hebei Province, China; 3Department of Proctology, First Affiliated Hospital of Shandong First Medical University, Jinan 250014, Shandong Province, China; 4Department of Peripheral Vascular Diseases, Guang'anmen Hospital Jinan Hospital (Jinan Municipal Hospital of Traditional Chinese Medicine), China Academy of Chinese Medical Sciences, Jinan 250012, Shandong Province, China 
  • Received:2025-06-26 Accepted:2025-10-11 Online:2026-08-08 Published:2025-12-26
  • Contact: Wang Yutao, Associate chief physician, Master’s supervisor, First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; Department of Peripheral Vascular Diseases, Guang'anmen Hospital Jinan Hospital (Jinan Municipal Hospital of Traditional Chinese Medicine), China Academy of Chinese Medical Sciences, Jinan 250012, Shandong Province, China
  • About author:Yang Wenyan, MS candidate, First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; Department of Ulcer and Vascular Diseases, Cangzhou Hospital of Integrated TCM-WM·HEBEI, Cangzhou 061000, Hebei Province, China
  • Supported by:
    The Young Scientists Fund of the National Natural Science Foundation of China, No. 82104860 (to WYT); Traditional Chinese Medicine Science and Technology Development Program of Shandong Province, China, No. 2019-0559 (to WYT); Health Commission Science and Technology Program Project of Jinan, China, No. 2019-1-23 (to WYT); Zhang Hongxing National Famous Traditional Chinese Medicine Experts Inheritance Studio Construction Project, No. [2022] 75 (to WYT); Shandong Provincial Health and Medical Management Research Center Scientific Research Project of Shandong Province,China, No. 20240430-044 (to PX); Health and Medical Industry High-Level Talent Special Fund Support of Jinan, China, No. 202412 (to WYT)

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摘要：


文题释义：
糖尿病足溃疡：指糖尿病患者因下肢远端神经异常和不同程度外周血管病变导致的足部感染、溃疡和(或)深层组织破坏，严重者可以导致截肢和死亡。
生物标志物：指可以标记系统、器官、组织、细胞及亚细胞结构/功能改变或可能发生改变的生化指标，具有非常广泛的用途。生物标志物可用于疾病诊断、判断疾病分期或者用来评价新药或新疗法在目标人群中的安全性及有效性。

背景：感染、肢体缺血和组织细胞激活等因素参与糖尿病足溃疡，但影响糖尿病足溃疡愈合的关键细胞亚群尚不明确，特异性的糖尿病足溃疡生物标志物尚未发掘。基因表达数据库是美国国家生物技术信息中心管理的存储高通量基因表达数据的公开数据库，允许用户免费提交、共享、查询和分析数据。对已经发表的数据进行二次分析，可以节约研究成本，挖掘新的研究靶点和思路。
目的：利用单细胞转录组和常规转录组生物信息学分析、高维加权基因共表达网络分析和加权基因共表达网络分析，筛选糖尿病足溃疡的生物标志物。
方法：下载基因表达数据库中包含糖尿病足溃疡患者未愈合的溃疡组织样本和糖尿病患者足部皮肤样本的单细胞转录组数据集GSE165816，经数据质量控制、降维、差异分析、细胞类型注释和拟时序分析后，筛选贯穿整个糖尿病足溃疡病程的细胞类型，获得差异表达基因，高维加权基因共表达网络分析识别与糖尿病足溃疡高度相关的基因模块；下载包含糖尿病足溃疡患者未愈合的溃疡组织样本和糖尿病患者足部皮肤样本的常规转录组数据集GSE68183、GSE80178，进行差异分析筛选差异表达基因，加权基因共表达网络分析筛选糖尿病足溃疡相关基因模块，将单细胞转录组差异表达基因、常规转录组样本差异表达基因、加权基因共表达网络分析及高维加权基因共表达网络分析筛选的模块基因进行整合，筛选糖尿病足溃疡的生物标志物。下载GSE134431数据集作为验证常规转录组数据集，比较糖尿病足溃疡生物标志物在单细胞转录组和验证常规转录组数据集中的表达水平。复制糖尿病和糖尿病足溃疡大鼠模型，取创面组织，免疫组织化学法和Western blot法检测生物标志物表达水平。
结果与结论：单细胞转录组数据分析结果显示，上皮细胞分化贯穿了糖尿病足溃疡整个病理过程，获得单细胞转录组组间差异表达基因共146个，其中差异表达上调基因59个，差异表达下调基因87个；高维加权基因共表达网络分析识别出与糖尿病足溃疡相关的基因模块19个，包含核心基因476个。常规转录组数据分析共获得913个差异表达基因，其中差异表达上调基因343个，差异表达下调基因570个；加权基因共表达网络分析获得19个糖尿病足溃疡相关基因模块，包含887个基因。筛选出2个糖尿病足溃疡的生物标志物：S100A14和SFN，2个基因在单细胞转录组和常规转录组数据验证集糖尿病足溃疡样本的表达水平均高于糖尿病患者足部皮肤样本。动物实验显示糖尿病足溃疡大鼠创面组织S100A14、SFN表达水平高于糖尿病大鼠背部皮肤组织。结果表明，糖尿病足溃疡病变过程涉及多种细胞类型，其中上皮细胞为糖尿病足溃疡的关键细胞亚群，S100A14和SFN在糖尿病足溃疡样本中表达水平显著增高，是糖尿病足溃疡治疗的潜在靶点。
https://orcid.org/0000-0002-5384-3656 (王玉涛) 


中国组织工程研究杂志出版内容重点：干细胞；骨髓干细胞；造血干细胞；脂肪干细胞；肿瘤干细胞；胚胎干细胞；脐带脐血干细胞；干细胞诱导；干细胞分化；组织工程

关键词: 糖尿病足溃疡, 单细胞测序, 加权基因共表达网络分析, 生物标志物, 差异表达基因

Abstract: BACKGROUND: Factors such as infection, limb ischemia, and histiocyte activation are involved in diabetic foot ulcers, but the key cell subpopulations influencing diabetic foot ulcer healing remain unclear, and specific biomarkers for diabetic foot ulcers have yet to be identified. Gene Expression Omnibus (GEO) is a publicly accessible database managed by the National Center for Biotechnology Information (NCBI) that stores high-throughput gene expression data, allowing users to freely submit, share, query, and analyze data. By conducting secondary analysis on published data, research costs can be minimized and new research avenues and methods can be discovered.
OBJECTIVE: To screen for biomarkers for diabetic foot ulcers using single-cell transcriptomics and conventional transcriptomics bioinformatics analysis, high-dimensional weighted gene co-expression network analysis, and weighted gene co-expression network analysis.
METHODS: The single-cell transcriptomics dataset GSE165816 from the gene expression database was downloaded, including unhealed ulcer tissue samples from diabetic foot ulcer patients and foot skin samples from diabetic patients. After data quality control, dimensionality reduction, differential analysis, cell type annotation, and pseudotime analysis, cell types throughout the entire course of diabetic foot ulcers were identified, differentially expressed genes were obtained, and high-dimensional weighted gene co-expression network analysis was used to identify gene modules highly associated with diabetic foot ulcers. The conventional transcriptomics datasets GSE68183 and GSE80178, including unhealed ulcer tissue samples from diabetic foot ulcer patients and foot skin samples from diabetic patients, were downloaded to screen for differentially expressed genes. Weighted gene co-expression network analysis was used to screen for gene modules associated with diabetic foot ulcers. The differentially expressed genes from single-cell transcriptomics, conventional transcriptomics samples, weighted gene co-expression network analysis, and high-dimensional weighted gene co-expression network analysis were integrated to screen for biomarkers of diabetic foot ulcers. The GSE134431 dataset was downloaded as a validation conventional transcriptomics dataset to compare the expression levels of diabetic foot ulcer biomarkers in single-cell transcriptomics and validation conventional transcriptomics datasets. Wound tissues were obtained from diabetic and diabetic foot ulcer rat models to detect biomarker expression levels using immunohistochemistry and Western blot assays.
RESULTS AND CONCLUSION: Single-cell transcriptomics data analysis revealed that epithelial cell differentiation ran through the entire pathological process of diabetic foot ulcers. A total of 146 differentially expressed genes were identified, including 59 upregulated genes and 87 downregulated genes. High-dimensional weighted gene co-expression network analysis identified 19 gene modules associated with diabetic foot ulcers, containing 476 core genes. Conventional transcriptomics data analysis identified 913 differentially expressed genes, including 343 upregulated genes and 570 downregulated genes; weighted gene co-expression network analysis identified 19 gene modules associated with diabetic foot ulcers, containing 887 genes. Two biomarkers for diabetic foot ulcers were identified: S100A14 and SFN. The expression levels of these two genes were higher in diabetic foot ulcer samples from single-cell transcriptomics and conventional transcriptomics validation datasets compared with diabetic patients' foot skin samples. Animal experiments showed that the expression levels of S100A14 and SFN in wound tissue from diabetic foot ulcer rats were higher than those in back skin tissue from diabetic rats. These findings suggest that epithelial cells play a crucial role in the pathological process of diabetic foot ulcers, with S100A14 and SFN highly expressed in these ulcers, indicating that they could be potential targets for the treatment of diabetic foot ulcer.

Key words: diabetic foot ulcer, single-cell sequencing, weighted gene co-expression network analysis, biomarkers, differentially expressed genes

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