加权基因共表达网络分析结合机器学习筛选糖尿病心肌病中与Th17细胞相关的核心基因-现代医学

加权基因共表达网络分析结合机器学习筛选糖尿病心肌病中与Th17细胞相关的核心基因

单位：1. 佳木斯大学临床医学院, 黑龙江佳木斯 154000;
2. 佳木斯大学附属第一医院心内科, 黑龙江佳木斯 154000

关键词：糖尿病心肌病|辅助性T细胞17|加权基因共表达网络分析|机器学习|核心基因

分类号：R542.2;R587.2

出版年·卷·期（页码）：2025·53·第四期（546-558）

摘要：

目的： 探讨免疫细胞相关基因在糖尿病心肌病(DCM)中的作用，并探讨其潜在机制。方法： 采用单样本基因集富集分析探讨样本的免疫浸润情况。通过加权基因共表达网络分析(WGCNA)挖掘与免疫浸润相关的基因。通过富集分析，分析这些基因的功能。基因间的相互作用在蛋白-蛋白相互作用网络中可视化，通过Cytoscape软件鉴定核心基因。通过机器学习筛选核心基因，生成受试者工作特征(ROC)曲线来评估核心基因在DCM诊断中的表现。采用实时荧光定量逆转录聚合酶链反应(qRT-PCR)和Western blot检测核心基因在大鼠心肌组织中的表达。结果： DCM组样本中辅助性T细胞17(Th17)细胞浸润分数显著增加。差异表达分析和WGCNA鉴定出28个与Th17细胞浸润相关的差异基因，这些基因与代谢相关。使用LASSO回归、随机森林模型等算法从28个差异基因中鉴定出核心基因。此外，ROC曲线分析显示，核心基因具有极佳的区分DCM的能力。最后，体内实验表明，qRT-PCR和Western blot的结果与测序结果一致。结论： WGCNA联合机器学习筛选出DCM中与Th17细胞相关的核心基因为2，4-二烯酰辅酶a还原酶1(Decr1)和线粒体3-羟基-3-甲基戊二酰辅酶A合成酶2(Hmgcs2)，在DCM中表达量均显著高于正常。

Objective: To investigate the role of immune cell-related genes in diabetic cardiomyopathy(DCM) and their mechanistic underpinnings. Methods: Immune infiltration profiles were analyzed via single-sample gene set enrichment analysis(ssGSEA). Weighted gene co-expression network analysis(WGCNA) identified immune-associated gene modules. Functional enrichment analyses(GO/KEGG) elucidated biological pathways, while protein-protein interaction(PPI) networks(STRING/Cytoscape) revealed core genes. Machine learning(LASSO/random forest) screened core diagnostic biomarkers, validated by receiver operating characteristic(ROC) curves. Expression levels of core genes were experimentally confirmed in rat DCM myocardial tissues using qRT-PCR and Western blot. Results: The DCM group exhibited significantly elevated T helper cell 17(Th17)cell infiltration scores. Differential expression analysis combined with WGCNA identified 28 Th17-associated genes enriched in metabolic pathways. Machine learning algorithms(LASSO/random forest) screened core genes from this cohort, validated by ROC curves demonstrating robust DCM diagnostic capacity. Experimental validation via qRT-PCR and Western blot confirmed consistent expression patterns between sequencing data and myocardial tissues in vivo. Conclusion: Integrated WGCNA and machine learning revealed two Th17-associated core genes in DCM: Decr1(2,4-dienoyl-CoA reductase 1) and Hmgcs2(mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase 2), both showing significantly upregulated expression compared to controls.

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