摘要
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。
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,highdimensional 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.Highdimensional 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.
作者
杨文燕
王华雨
杨丽科
庞雪
王玉涛
Yang Wenyan;Wang Huayu;Yang Like;Pang Xue;Wang Yutao(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;Department of Proctology,First Affiliated Hospital of Shandong First Medical University,Jinan 250014,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)
出处
《中国组织工程研究》
北大核心
2026年第22期5694-5706,共13页
Chinese Journal of Tissue Engineering Research
基金
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
山东大学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
山东大学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。
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
diabetic foot ulcer
single-cell sequencing
weighted gene co-expression network analysis
biomarkers
differentially expressed genes
