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作者

Fang Miao Xixi Li Chenglin Wang Heju Yuan Zhongming Wu

作者单位

NHC Key Laboratory of Hormones and Development，Tianjin Key Laboratory of Metabolic Diseases，Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology，Tianjin Medical University，Tianjin，China；Department of Endocrinology，Shanxi Provincial People’s Hospital，Taiyuan，China；Shanxi Medical University，Taiyuan，China；Department of Endocrinology，Shanxi Provincial People’s Hospital，Taiyuan，China；Department of Endocrinology，Shanxi Provincial People’s Hospital，Taiyuan，China；NHC Key Laboratory of Hormones and Development，Tianjin Key Laboratory of Metabolic Diseases，Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology，Tianjin Medical University，Tianjin，China；Department of Endocrinology，Shandong Provincial Hospital Affiliated to Shandong First Medical University，Jinan，China

刊名

转化医学年鉴

年份

2023

卷号

第11卷

期号

第2期

页码

89

关键词

Diabetic foot ulcer (DFU) bioinformatics differentially expressed genes (DEGs) biomarker

摘要

Background Molecular changes are closely related to the pathogenesis and healing process of diabetic foot ulcers , and are crucial for the early prediction and intervention of DFU. Methods Bioinformatics analysis was performed in this study to identify the key differentially expressed genes in DFU, analyze their functions and function modes, and conduct preliminary experimental verification to determine the potential pivotal genes in the pathogenesis of DFU. Two datasets, GSE68183 and GSE80178,...更多

Background Molecular changes are closely related to the pathogenesis and healing process of diabetic foot ulcers , and are crucial for the early prediction and intervention of DFU. Methods Bioinformatics analysis was performed in this study to identify the key differentially expressed genes in DFU, analyze their functions and function modes, and conduct preliminary experimental verification to determine the potential pivotal genes in the pathogenesis of DFU. Two datasets, GSE68183 and GSE80178, were obtained from the Gene Expression Omnibus . DEGs were obtained using GEO2R. Six co-expressed DEGs were obtained by R language analysis. The co-DEGs were constructed by using STRING and Cytoscape 3.7.2 to construct a protein-protein interaction network, and two hub genes, NHLRC3 and BNIP3, were identified. The BNIP3 gene was selected for further analysis. Co-DEGs were used for Gene Ontology function analysis using the WebGestalt database, and BNIP3-related biological processes focused on mitochondrial protein decomposition. GO function analysis of the BNIP3 gene and its interacting genes was carried out using the cluster profile package and org.hs.eg. db package of the R language and its biological process was enriched in the cell response to external stimuli and autophagy. Results BNIP3 and its interacting genes were retrieved from the Kyoto Encyclopedia of Genes and Genomes database and KEGG pathway enrichment analysis was performed using the WebGestalt database. The results showed that BNIP3 was significantly correlated with mitochondrial autophagy and the FoxO signaling pathway. The miRDB and TargetScan databases were used to identify the relevant microRNAs regulating the BNIP3 gene, and it was found that miRNA-182 may be involved in the targeted regulation of BNIP3. Western blot analysis was performed to determine the abnormal expression of BNIP3. Conclusions Our study found that the BNIP3 gene may be a new biomarker and intervention target for DFU.收起

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