Table_1_Identification and validation of a novel glycolysis-related ceRNA network for sepsis-induced cardiomyopathy.XLSX

PurposeSepsis-induced cardiomyopathy (SIC) is a major life-threatening condition in critically infected patients. Early diagnosis and intervention are important to improve patient prognosis. Recognizing the pivotal involvement of the glycolytic pathway in SIC, this study aims to establish a glycolysis-related ceRNA network and explore novel diagnostic avenues.
Materials and methodsSIC-related datasets were carefully filtered from the GEO database. CytoHubba was used to identify differentially expressed genes (DEGs) associated with glycolysis. A predictive method was then used to construct an lncRNA-miRNA-mRNA network. Dual-luciferase reporter assays validated gene interactions, and the specificity of this ceRNA network was confirmed in peripheral blood mononuclear cells (PBMCs) from SIC patients. Logistic analysis was used to examine the correlation between the ceRNA network and SIC. Diagnostic potential was assessed using receiver operating characteristic (ROC) curves, and correlation analysis investigated any associations between gene expression and clinical indicators.
ResultsIER3 was identified as glycolysis-related DEG in SIC, and a ceRNA network (SNHG17/miR-214-3p/IER3) was established by prediction. Dual luciferase reporter gene assay confirmed the presence of mutual binding between IER3, miR-214-3p and SNHG17. RT-qPCR verified the specific expression of this ceRNA network in SIC patients. Multivariate logistic analysis established the correlation between the ceRNA network and SIC. ROC analysis demonstrated its high diagnostic specificity (AUC > 0.8). Correlation analysis revealed a negative association between IER3 expression and oxygenation index in SIC patients (p < 0.05). Furthermore, miR-214-3p expression showed a negative correlation with NT-proBNP (p < 0.05).
ConclusionIn this study, we identified and validated a ceRNA network associated with glycolysis in SIC: SNHG17/miR-214-3p/IER3. This ceRNA network may play a critical role in the onset and development of SIC. This finding is important to further our understanding of the pathophysiological mechanisms underlying SIC and to explore potential diagnostic and therapeutic targets for SIC.

研究目的
脓毒症诱导型心肌病（Sepsis-induced cardiomyopathy, SIC）是重症感染患者中一类致死性严重疾病。早期诊断与干预对改善患者预后具有重要意义。鉴于糖酵解通路在SIC的发病机制中发挥关键调控作用，本研究旨在构建糖酵解相关的内源竞争RNA（competitive endogenous RNA, ceRNA）调控网络，并探索全新的诊断策略。

材料与方法
从基因表达综合数据库（Gene Expression Omnibus, GEO）中严格筛选SIC相关数据集。使用CytoHubba工具筛选与糖酵解通路相关的差异表达基因（differentially expressed genes, DEGs）。随后通过生物信息学预测方法构建长链非编码RNA（long non-coding RNA, lncRNA）-微小RNA（microRNA, miRNA）-信使RNA（messenger RNA, mRNA）调控网络。采用双荧光素酶报告基因实验验证基因间的相互作用，并在SIC患者的外周血单个核细胞（peripheral blood mononuclear cells, PBMCs）中验证该ceRNA网络的特异性。通过逻辑回归分析探究该ceRNA网络与SIC的相关性。采用受试者工作特征（receiver operating characteristic, ROC）曲线评估其诊断潜力，并通过相关性分析探究基因表达与临床指标之间的关联。

研究结果
本研究证实IER3（Immediate Early Response Factor 3）是SIC中与糖酵解通路相关的DEG，并通过预测构建得到SNHG17/miR-214-3p/IER3 ceRNA调控网络。双荧光素酶报告基因实验验证了IER3、miR-214-3p与SNHG17三者之间存在相互结合作用。采用实时定量聚合酶链反应（real-time quantitative polymerase chain reaction, RT-qPCR）验证了该ceRNA网络在SIC患者中的特异性表达。多变量逻辑回归分析证实了该ceRNA网络与SIC之间存在显著相关性。ROC曲线分析显示其具有较高的诊断特异性（曲线下面积AUC>0.8）。相关性分析显示，SIC患者中IER3的表达水平与氧合指数呈负相关（p<0.05）。此外，miR-214-3p的表达水平与N末端B型利钠肽原（N-terminal pro B-type natriuretic peptide, NT-proBNP）呈负相关（p<0.05）。

结论
本研究鉴定并验证了SIC中与糖酵解通路相关的ceRNA调控网络：SNHG17/miR-214-3p/IER3。该ceRNA网络可能在SIC的发生与发展过程中发挥关键调控作用。本研究结果有助于进一步阐明SIC的病理生理机制，并为探索SIC潜在的诊断与治疗靶点提供科学依据。