Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China.
Front Endocrinol (Lausanne). 2022 Jul 14;13:836152. doi: 10.3389/fendo.2022.836152. eCollection 2022.
Diabetic foot ulcer (DFU) is a severe complication characterized by low-grade infectious inflammation and probably associated with specific competitive endogenous RNAs (ceRNAs) and infiltrating immune cells. Nonetheless, no reliable biomarkers are used for detecting infectious inflammation in DFU. Therefore, it is essential to explore potential biomarkers for the accurate diagnosis and treatment of DFU.
The gene expression profile was retrieved from Gene Expression Omnibus (GEO) database and divided into two groups, namely, standard samples and DFU samples. To establish the ceRNA networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to analyze differential expression genes (DEGs). The cell type identification was achieved by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to screen-specific immune-infiltrating cells associated with DFU.
A ceRNA network was constructed with 20 differential expression circRNA (DEcircRNAs), 11 differential expression microRNAs (DEmiRNAs), and 9 differential expression mRNAs (DEmRNAs). Functional enrichment analysis demonstrated that DFU was mainly enriched in vascular endothelial growth factor (VEGF) and T-cell receptor signaling. In addition, CIBERSORT estimation indicated that CD8 T cells and Monocytes were significantly related to the expression of IL-6, a DFU-specific infectious inflammation factor.
This study identified that some significant ceRNAs (JUNB, GATA3, hsa-circ-0049271 and hsa-circ-0074559) and infiltrating immune cells (CD8 T cells and monocytes) might be related to DFU infectious inflammation.
糖尿病足溃疡(DFU)是一种严重的并发症,其特征为低度感染性炎症,可能与特定的竞争性内源性 RNA(ceRNA)和浸润免疫细胞有关。然而,目前尚无可靠的生物标志物可用于检测 DFU 的感染性炎症。因此,探索潜在的生物标志物对于 DFU 的准确诊断和治疗至关重要。
从基因表达综合数据库(GEO)中检索基因表达谱,并将其分为两组,即标准样本和 DFU 样本。为了建立 ceRNA 网络,利用基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析对差异表达基因(DEGs)进行分析。通过估计相对 RNA 转录物子集(CIBERSORT)算法进行细胞类型鉴定,以筛选与 DFU 相关的特定免疫浸润细胞。
构建了一个包含 20 个差异表达环状 RNA(DEcircRNAs)、11 个差异表达 microRNA(DEmiRNAs)和 9 个差异表达 mRNA(DEmRNAs)的 ceRNA 网络。功能富集分析表明,DFU 主要富集于血管内皮生长因子(VEGF)和 T 细胞受体信号。此外,CIBERSORT 估计表明 CD8 T 细胞和单核细胞与 DFU 特异性感染性炎症因子 IL-6 的表达显著相关。
本研究鉴定出一些重要的 ceRNA(JUNB、GATA3、hsa-circ-0049271 和 hsa-circ-0074559)和浸润免疫细胞(CD8 T 细胞和单核细胞)可能与 DFU 的感染性炎症有关。