糖尿病足溃疡的hub基因及其生物学功能的生物信息学分析

Bioinformatics Analysis of Hub Genes of Diabetic Foot Ulcer and Their Biofunctions

目的通过对转录组测序数据的生物学分析探寻与糖尿病足溃疡发病以及愈合相关的关键(hub)基因及其生物学功能。方法从GEO数据库筛选糖尿病足溃疡的数据集,数据标准化后再分组并进行生物信息学分析。分别对糖尿病足溃疡患者与非糖尿病足溃疡患者,以及糖尿病足溃疡部位创缘皮肤与糖尿病足患者非溃疡部位皮肤转录组测序数据进行组间差异表达基因鉴定、通路富集和蛋白质互作(PPI)分析,通过节点分析找到hub基因,并在测试集中以受试者工作特征(ROC)曲线验证筛选出的hub基因对糖尿病足溃疡的诊断效能。通过两组分析的交集基因再次进行通路富集以及PPI分析,筛选与糖尿病足溃疡创面愈合相关hub基因。最后对相关样本进行GSEA分析寻找全转录组基因在糖尿病足溃疡中可能的作用。结果从糖尿病足溃疡与非糖尿病患者皮肤的测序分析中,得到上调的差异基因620个,下调的差异基因196个。这些基因的功能集中在萜类化合物和聚酮类化合物的代谢、分子和相互作用、磷脂酶D信号通路、丙酸酯代谢、PI3K-Akt信号通路、Toll样受体信号通路、嘧啶代谢、IL-17信号通路、Rap1信号通路等。PPI网络确定了10个hub基因,其中BGN、CCND1在测试集的ROC分析的曲线下面积为0.714、0.712。在糖尿病足溃疡部位创缘皮肤与糖尿病足患者非溃疡部位皮肤的测序分析中筛选出了上调基因4072个,下调基因911个,与糖尿病溃疡的差异基因有交集的基因372个。这些差异基因的功能集中在磷脂酶D信号通路、异种生物降解和能量代谢、谷胱苷酸代谢、嘧啶代谢、ErbB信号通路以及黑色素生成等信号通路。从PPI网络确定了7个hub基因。在GSEA分析中,戊糖和葡萄糖醛酸相互转化、同源重组、烟酸和烟酰胺代谢、神经活性配体受体相互作用、青少年发病的成年型糖尿病、丁酸代谢、赖氨酸降解、泛酸和辅酶A的生物合成、核黄素代谢、类固醇激素生物合成、缬氨酸亮氨酸和异亮氨酸降解等通路在糖尿病足溃疡与非糖尿病足溃疡患者中表现出了较大的表达差异。结论生物信息学结果提示,BGN、CCND1是预测糖尿病足溃疡发生的潜在生物学标志物,CXCL12、TLR4、JAK2、PPARA、UBC、DCN、KDR、ARNTL是糖尿病足溃疡的hub基因,而CXCL8、CXCL12、TXN、SLIT3、KRT14、KIT、NEO1是糖尿病足慢性溃疡愈合相关的hub基因。

Objective To explore the hub genes associated with the pathogenesis and healing of diabetic foot ulcer(DFU)and their biological functions through bioinformatics analysis of transcriptome sequencing data.Methods The transcriptome sequencing datasets of DFU were selected from Gene Expression Omnibus(GEO)database,and the data were regrouped and normalized for bioinformatics analysis.The skin transcriptome sequencing datasets of DFU patients were compared with those of normal controls and the transcriptome sequencing datasets of skin from ulcerous wound edge of DFU patients were compared with those of non-ulcerous skin of DFU patients so that differentially expressed genes were identified,pathway enrichment and protein-to-protein interaction(PPI)analyses were performed,hub genes were found through nodal analysis,and receiver operating characteristic(ROC)curve was applied to a testing dataset to validate the diagnostic efficiency of the hub genes related to DFU.The intersecting genes from the two sets of analyses were again subjected to pathway enrichment and PPI analyses to screen for hub genes associated with DFU wound healing.What’s more,gene set enrichment analysis(GSEA)was carried out on relevant samples to probe for the possible functions and pathway of non-significant genes in DFU.Results A total of 620 up-regulated differentially expressed genes and 196 down-regulated differentially expressed genes were identified in the training dataset which compared DFU patients with non-diabetic patients.The functions of these genes were enriched in the metabolism of terpenoids and polyketides,signaling molecules and interaction,phospholipase D signaling pathway,propanoate metabolism,PI3K-Akt signaling pathway,Toll-like receptor signaling pathway,pyrimidine metabolism,IL-17 signaling pathway,Rap1 signaling pathway,etc.A total of 10 hub genes were identified with the PPI network.Among them,BGN’s value of the area under the curve of ROC analysis was 0.714 and CCND1’s was 0.712.In the sequencing analysis of ulcerous wound edge of DFU patients and non-ulcerous skin of DFU patients,4072 up-regulated genes and 911 downregulated genes were identified,of which,372 genes were also detected in the differentially expressed genes of DFU.The functions of these differentially expressed genes were enriched in phospholipase D signaling pathway,xenobiotics biodegradation and energy metabolism,glutathione metabolism,pyrimidine metabolism,ErbB signaling pathway,melanin production,etc.A total of 7 hub genes were identified from PPI network.In GSEA analysis,pathways including pentose and glucuronate interconversions and homologous recombination,nicotinate and nicotinamide metabolism,neuroactive ligand receptor interaction,maturity-onset diabetes of the young,butanoate metabolism,lysine degradation,pantothenate and coenzyme A biosynthesis,riboflavin metabolism,steroid hormone biosynthesis,and valine,leucine and isoleucine degradation showed significant expression differences between DFU patients and normal controls.Conclusion Bioinformatics analysis results suggest that BGN and CCND1 are potential biomarkers for predicting DFU;CXCL12,TLR4,JAK2,PPARA,UBC,DCN,KDR,and ARNTL are the hub genes of DFU,while CXCL8,CXCL12,TXN,SLIT3,KRT14,KIT,and NEO1 are the hub genes related to wound healing of DFU.