Zhang Renlingzi, Di Chong, Gao Hanlu, Zhu Yunlou, Li Congye, Zhu Zhengfang, Wang Qixing, Wang Junjie, Zhou Feng, Wang Sheng
Department of Critical Care Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Front Cardiovasc Med. 2023 Mar 2;10:1018422. doi: 10.3389/fcvm.2023.1018422. eCollection 2023.
Early diagnosis of septic cardiomyopathy is essential to reduce the mortality rate of sepsis. Previous studies indicated that iron metabolism plays a vital role in sepsis-induced cardiomyopathy. Here, we aimed to identify shared iron metabolism-related genes (IMRGs) in the myocardium and blood monocytes of patients with sepsis and to determine their prognostic signature.
First, an applied bioinformatics-based analysis was conducted to identify shared IMRGs differentially expressed in the myocardium and peripheral blood monocytes of patients with sepsis. Second, Cytoscape was used to construct a protein-protein interaction network, and immune infiltration of the septic myocardium was assessed using single-sample gene set enrichment analysis. In addition, a prognostic prediction model for IMRGs was established by Cox regression analysis. Finally, the expression of key mRNAs in the myocardium of mice with sepsis was verified using quantitative polymerase chain reaction analysis.
We screened common differentially expressed genes in septic myocardium and blood monocytes and identified 14 that were related to iron metabolism. We found that , , , and strongly correlated with monocytes and neutrophils, whereas and strongly correlated with macrophages. We then established a prognostic model ( and ) using the common differentially expressed IMRGs. The prognostic model we established was expected to better aid in diagnosing septic cardiomyopathy. Moreover, we verified these genes using datasets and experiments and found a significant difference between the sepsis and control groups.
Common differential expression of IMRGs was identified in blood monocytes and myocardium between sepsis and control groups, among which and might predict prognosis in septic cardiomyopathy. The study may help us deeply understand the molecular mechanisms of iron metabolism and aid in the diagnosis and treatment of septic cardiomyopathy.
脓毒症性心肌病的早期诊断对于降低脓毒症的死亡率至关重要。先前的研究表明,铁代谢在脓毒症诱导的心肌病中起着至关重要的作用。在此,我们旨在识别脓毒症患者心肌和血液单核细胞中与铁代谢相关的共享基因(IMRGs),并确定其预后特征。
首先,进行基于应用生物信息学的分析,以识别脓毒症患者心肌和外周血单核细胞中差异表达的共享IMRGs。其次,使用Cytoscape构建蛋白质-蛋白质相互作用网络,并使用单样本基因集富集分析评估脓毒症心肌的免疫浸润。此外,通过Cox回归分析建立IMRGs的预后预测模型。最后,使用定量聚合酶链反应分析验证脓毒症小鼠心肌中关键mRNA的表达。
我们筛选了脓毒症心肌和血液单核细胞中共同差异表达的基因,并鉴定出14个与铁代谢相关的基因。我们发现, 、 、 和 与单核细胞和中性粒细胞强烈相关,而 和 与巨噬细胞强烈相关。然后,我们使用共同差异表达的IMRGs建立了一个预后模型( 和 )。我们建立的预后模型有望更好地辅助诊断脓毒症性心肌病。此外,我们使用数据集和实验验证了这些基因,发现脓毒症组和对照组之间存在显著差异。
在脓毒症组和对照组的血液单核细胞和心肌中鉴定出IMRGs的共同差异表达,其中 和 可能预测脓毒症性心肌病的预后。该研究可能有助于我们深入了解铁代谢的分子机制,并有助于脓毒症性心肌病的诊断和治疗。