利用生物信息学和机器学习鉴定及验证糖尿病足溃疡中细胞外基质相关基因CTSH

Identifying and Validating Extracellular Matrix-Related Gene CTSH in Diabetic Foot Ulcer Using Bioinformatics and Machine Learning.

作者信息

Wu Pei-Yu, Yu Yan-Lin, Zhao Wen-Rui, Zhou Bo

机构信息

Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.

Department of VIP, Chongqing General Hospital, Chongqing University, Chongqing, People's Republic of China.

出版信息

J Inflamm Res. 2024 Aug 30;17:5871-5887. doi: 10.2147/JIR.S467507. eCollection 2024.

DOI:10.2147/JIR.S467507

PMID:39228680

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11370762/

Abstract

BACKGROUND

Diabetic foot ulcer (DFU) is a serious clinical problem with high amputation and mortality rates, yet there is a lack of desirable therapy. While the extracellular matrix (ECM) contributes significantly to wound healing, ECM-related biomarker for DFU is still unknown. The study was designed to identify ECM-related biomarker in DFU using bioinformatics and machine learning and validate it in STZ-induced mice models.

METHODS

GSE80178 and GSE134431 microarray datasets were fetched from the GEO database, and differentially expressed genes (DEGs) analysis was performed, respectively. By analyzing DEGs and ECM genes, we identified ECM-related DEGs, and functional enrichment analysis was conducted. Subsequently, three machine learning algorithms (LASSO, RF and SVM-RFE) were applied to filter ECM-related DEGs to identify key ECM-related biomarkers. Next, we conducted immune infiltration analysis, GSEA, and correlation analysis to explore the hub gene underlying mechanism. A lncRNA-miRNA-mRNA and drug regulatory network were constructed. Finally, we validated the key ECM-related biomarker in STZ-induced mice models.

RESULTS

One hundred and forty-five common DEGs in adult DFU between the two datasets were identified. Taking the intersection of 145 common DEGs and 964 ECM genes, we identified 13 ECM-related DEGs. Thirteen ECM-related DEGs were mainly enriched in pathways associated with tissue remodeling, inflammation and defense against infectious agents. Ultimately, CTSH was identified as the key ECM-related biomarker. CTSH was associated with difference immune cells during the occurrence and development of DFU, and it influenced hedgehog, IL-17 and TNF signaling pathway. Additionally, CTSH expression is correlated with many ECM- and immune-related genes. A lncRNA-miRNA-mRNA and drug regulatory network were constructed with 10 lncRNAs, 2 miRNAs, CTSH and 1 drug. Finally, CTSH was validated as a key biomarker for DFU in animal models.

CONCLUSION

Our study found that CTSH can be used for both diagnostic and prognostic purposes and might be a potential therapeutic target.

摘要

背景

糖尿病足溃疡（DFU）是一个严重的临床问题，截肢率和死亡率很高，但目前缺乏理想的治疗方法。虽然细胞外基质（ECM）对伤口愈合有重要作用，但DFU的ECM相关生物标志物仍不清楚。本研究旨在利用生物信息学和机器学习鉴定DFU中与ECM相关的生物标志物，并在链脲佐菌素诱导的小鼠模型中进行验证。

方法

从基因表达综合数据库（GEO数据库）获取GSE80178和GSE134431基因芯片数据集，并分别进行差异表达基因（DEG）分析。通过分析DEG和ECM基因，我们鉴定出与ECM相关的DEG，并进行功能富集分析。随后，应用三种机器学习算法（LASSO、随机森林（RF）和支持向量机递归特征消除法（SVM-RFE））筛选与ECM相关的DEG，以鉴定关键的ECM相关生物标志物。接下来，我们进行免疫浸润分析、基因集富集分析（GSEA）和相关性分析，以探索核心基因的潜在机制。构建lncRNA- miRNA- mRNA和药物调控网络。最后，我们在链脲佐菌素诱导的小鼠模型中验证了关键的ECM相关生物标志物。

结果

在两个数据集中鉴定出成人DFU中的145个常见DEG。取145个常见DEG与964个ECM基因的交集，我们鉴定出13个与ECM相关的DEG。13个与ECM相关的DEG主要富集在与组织重塑、炎症和抗感染相关的通路中。最终，组织蛋白酶H（CTSH）被鉴定为关键的ECM相关生物标志物。CTSH与DFU发生发展过程中的不同免疫细胞有关，它影响刺猬信号通路、白细胞介素-17和肿瘤坏死因子信号通路。此外，CTSH表达与许多ECM和免疫相关基因相关。构建了一个由10个lncRNA、2个miRNA、CTSH和1种药物组成的lncRNA- miRNA- mRNA和药物调控网络。最后，CTSH在动物模型中被验证为DFU的关键生物标志物。