HMOX1 as a therapeutic target associated with diabetic foot ulcers based on single-cell analysis and machine learning

基于单细胞分析和机器学习的 HMOX1 作为糖尿病足溃疡相关治疗靶点

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作者:Yiqi Chen, Yixin Zhang, Ming Jiang, Hong Ma, Yuhui Cai

Abstract

Diabetic foot ulcers (DFUs) are a serious chronic complication of diabetes mellitus and a leading cause of disability and death in diabetic patients. However, current treatments remain unsatisfactory. Although macrophages are associated with DFU, their exact role in this disease remains uncertain. This study sought to detect macrophage-related genes in DFU and identify possible therapeutic targets. Single-cell datasets (GSE223964) and RNA-seq datasets (GSM68183, GSE80178, GSE134431 and GSE147890) associated with DFU were retrieved from the gene expression omnibus (GEO) database for this study. Analysis of the provided single-cell data revealed the distribution of macrophage subpopulations in the DFU. Four independent RNA-seq datasets were merged into a single DFU cohort and further analysed using bioinformatics. This included differential expression (DEG) analysis, multiple machine learning algorithms to identify biomarkers and enrichment analysis. Finally, key results were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western bolt. Finally, the findings were validated using RT-qPCR and western blot. We obtained 802 macrophage-related genes in single-cell analysis. Differential expression analysis yielded 743 DEGs. Thirty-seven macrophage-associated DEGs were identified by cross-analysis of marker genes with macrophage-associated DEGs. Thirty-seven intersections were screened and cross-analysed using four machine learning algorithms. Finally, HMOX1 was identified as a potentially valuable biomarker. HMOX1 was significantly associated with biological pathways such as the insulin signalling pathway. The results showed that HMOX1 was significantly overexpressed in DFU samples. In conclusion, the analytical results of this study identified HMOX1 as a potentially valuable biomarker associated with macrophages in DFU. The results of our analysis improve our understanding of the mechanism of macrophage action in this disease and may be useful in developing targeted therapies for DFU.

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