Open AccessCharacterisation of key biomarkers in diabetic ulcers via systems bioinformatics
Author(s) -
Zhang Zhan,
Zhang Ying,
Yang Dan,
Luo Yue,
Luo Ying,
Ru Yi,
Song Jiankun,
Fei Xiaoya,
Chen Yiran,
Li Bin,
Jiang Jingsi,
Kuai Le
Publication year - 2023
Publication title -
international wound journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.867
H-Index - 63
eISSN - 1742-481X
pISSN - 1742-4801
DOI - 10.1111/iwj.13900
Subject(s) - medicine , key (lock) , bioinformatics , computational biology , computer science , biology , computer security
Diabetic ulcers (DUs) are characterised by a high incidence and disability rate. However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co‐expression network analysis was performed on the main data from the Gene Expression Omnibus database. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were adopted to analyse the potential biological function of the most relevant module. Furthermore, we utilised CytoHubba and protein–protein interaction network to identify the hub genes. Finally, the hub genes were validated by animal experiments in diabetic ulcer mice models. The expression of genes from the turquoise module was found to be strongly related to DUs. GO terms, KEGG analysis showed that biological functions are closely related to immune response. The hub genes included IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1, which were higher in wounds of DUs mice than that in normal lesions. Additionally, we also demonstrated that the expression of hub genes was correlated with the immune response using immune checkpoint, immune cell infiltration, and immune scores. These data suggests that IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1 are crucial for DUs.