基于生物信息学和机器学习方法的糖尿病心肌病巨噬细胞极化相关生物标志物鉴定

IF 5.1 2区医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL

Life sciences Pub Date : 2025-03-01 Epub Date: 2025-02-04 DOI:10.1016/j.lfs.2025.123443

Yi Liu , Juan Zhang , Quancheng Han , Yan Li , Yitao Xue , Xiujuan Liu

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引用次数: 0

摘要

大量研究调查了巨噬细胞在糖尿病性心肌病（DCM）发病机制中的作用；然而，潜在的机制仍不清楚。方法从GEO数据库下载DCM数据集GSE62203。鉴定出DEGs和WGCNA关键模块基因。巨噬细胞极化相关基因从GeneCards数据库中获得。构建GO和KEGG功能富集。LASSO逻辑回归和随机森林两种机器学习技术进一步用于识别中心基因。采用ROC曲线评价诊断效率。单基因GSEA研究其生物学功能。然后，探讨枢纽基因与巨噬细胞通路的关系。预测转录因子（TF）、miRNA和lncRNA。进行单细胞测序分析。最后，利用DCM大鼠模型对枢纽基因进行实验验证。结果通过机器学习方法鉴定出3个中心基因（PGK1、LDHA、EDN1）。所有三个中心基因都被发现与HIF-1信号通路相关。功能富集分析显示HIF-1信号通路和糖酵解/糖异生可能与dcm诱导的巨噬细胞极化有关。枢纽基因的mRNA和蛋白表达水平与生物信息学分析一致。此外，枢纽基因的mRNA表达与CD80和CD86呈正相关。结论pgk1、LDHA和EDN1是DCM中M1巨噬细胞极化的潜在生物标志物。这些基因可能促进DCM中M1巨噬细胞的极化。靶向巨噬细胞极化可能是一种新的治疗DCM的策略。

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Identification of biomarkers associated with macrophage polarization in diabetic cardiomyopathy based on bioinformatics and machine learning approaches

Background

Numerous studies have investigated the role of macrophages in the pathogenesis of diabetic cardiomyopathy (DCM); however, the underlying mechanisms remain unclear.

Methods

The DCM dataset (GSE62203) was downloaded from the GEO database. DEGs and WGCNA key module genes were identified. Macrophage polarization-associated genes were obtained from the GeneCards database. GO and KEGG functional enrichment were constructed. Two machine learning techniques, LASSO logistic regression and random forest, were further used to identify hub genes. The diagnostic efficiency was evaluated using ROC curves. Single-gene GSEA investigated the biological functions. Then, the relationship between hub genes and macrophage pathways was explored. Predicted Transcription factor (TF), miRNA, and lncRNA. Single cell sequencing analysis was performed. Finally, experimental validation of the hub genes using the DCM rat model.

Results

Three hub genes (PGK1, LDHA, EDN1) were identified through machine learning approaches. All three hub genes were found to be associated with the HIF-1 signaling pathway. Functional enrichment analysis revealed that the HIF-1 signaling pathway and Glycolysis/Gluconeogenesis are potentially linked to DCM-induced macrophage polarization. The mRNA and protein expression levels of the hub genes were consistent with the bioinformatics analysis. Furthermore, mRNA expression of the hub genes showed a positive correlation with CD80 and CD86.

Conclusion

PGK1, LDHA, and EDN1 represent potential biomarkers for M1 macrophage polarization in DCM. These genes may facilitate M1 macrophage polarization in DCM. Targeting macrophage polarization could represent a novel therapeutic strategy for DCM.

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来源期刊

Life sciences 医学-药学

CiteScore

12.20

自引率

1.60%

发文量

841

审稿时长

6 months

期刊介绍： Life Sciences is an international journal publishing articles that emphasize the molecular, cellular, and functional basis of therapy. The journal emphasizes the understanding of mechanism that is relevant to all aspects of human disease and translation to patients. All articles are rigorously reviewed. The Journal favors publication of full-length papers where modern scientific technologies are used to explain molecular, cellular and physiological mechanisms. Articles that merely report observations are rarely accepted. Recommendations from the Declaration of Helsinki or NIH guidelines for care and use of laboratory animals must be adhered to. Articles should be written at a level accessible to readers who are non-specialists in the topic of the article themselves, but who are interested in the research. The Journal welcomes reviews on topics of wide interest to investigators in the life sciences. We particularly encourage submission of brief, focused reviews containing high-quality artwork and require the use of mechanistic summary diagrams.