Song Yongfei, Wang Xiaofei, Tong Dongdong, Huang Xiaoyan, Jin Xiaojun, Zhang Chuanjing, Liu Jianhui, Guo Bo, Huang Chen, Lian Jiangfang
Ningbo Institute of Innovation for Combined Medicine and Engineering, Ningbo Medical Center Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China.
Department of Cardiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, Ningbo, Zhejiang, China.
Cardiol Res Pract. 2025 Apr 7;2025:2349610. doi: 10.1155/crp/2349610. eCollection 2025.
The present study aims to elucidate the significance of immune cell infiltration in Coronavirus disease 2019 (COVID-19) myocarditis and identify potential diagnostic markers for this condition. Myocarditis, an inflammatory cardiac disease, primarily results from viral infections. Although the association between COVID-19 and myocarditis is well-established, the specific mechanism(s) underlying this relationship remain incompletely understood. The GSE53607 and GSE35182 datasets were obtained from the GEO database, which contains samples from a mouse model for viral myocarditis. Differentially expressed genes (DEGs) and candidate biomarkers were selected using the LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analysis. Subsequently, the diagnostic potential of these biomarkers was evaluated by calculating the area under the receiver operating characteristic curve (AUC). Further validation of the biomarkers was conducted using the GSE183850 dataset, which consists of samples from patients with COVID-19 myocarditis. In addition, CIBERSORT analysis was employed to estimate the compositional patterns of 22 types of immune cell fractions in merged cohorts. Thirty genes were identified, with a significant proportion of the DEGs being associated with carbohydrate binding, endopeptidase activity, and pathogenic organisms such as and coronavirus disease. Importantly, gene sets related to the IL6-JAK-STAT3 signaling pathways, inflammatory response, and interferon response exhibited differential activation in viral myocarditis compared to the control group. In addition, in the context of COVID-19 myocarditis patients from the GSE183850 dataset, B2M and C3 were established as diagnostic markers that were subsequently validated (AUC = 0.978 and AUC = 0.956, respectively). Furthermore, analysis of immune cell infiltration revealed correlations between B2M and C3 expression levels and the activation of NK cells, dendritic cells, T cells CD4 memory resting, as well as eosinophils. B2M and C3 have been identified as potential biomarkers for viral myocarditis, providing valuable insights for future investigations into the pathogenesis of COVID-19-associated myocarditis.
本研究旨在阐明免疫细胞浸润在2019冠状病毒病（COVID-19）心肌炎中的意义，并确定该病症的潜在诊断标志物。心肌炎是一种炎症性心脏病，主要由病毒感染引起。虽然COVID-19与心肌炎之间的关联已得到充分证实，但这种关系背后的具体机制仍未完全了解。从基因表达综合数据库（GEO）数据库中获取了GSE53607和GSE35182数据集，该数据库包含来自病毒性心肌炎小鼠模型的样本。使用套索回归模型和支持向量机递归特征消除（SVM-RFE）分析选择差异表达基因（DEG）和候选生物标志物。随后，通过计算受试者工作特征曲线（AUC）下的面积来评估这些生物标志物的诊断潜力。使用由COVID-19心肌炎患者样本组成的GSE183850数据集对生物标志物进行进一步验证。此外，采用CIBERSORT分析来估计合并队列中22种免疫细胞组分的组成模式。鉴定出30个基因，其中很大一部分DEG与碳水化合物结合、内肽酶活性以及诸如冠状病毒病等病原体相关。重要的是，与白细胞介素6- Janus激酶-信号转导和转录激活因子3（IL6-JAK-STAT3）信号通路、炎症反应和干扰素反应相关的基因集在病毒性心肌炎中与对照组相比表现出不同的激活。此外，在来自GSE183850数据集的COVID-19心肌炎患者中，β2微球蛋白（B2M）和补体C3（C3）被确立为诊断标志物，随后得到验证（AUC分别为0.978和0.956）。此外，免疫细胞浸润分析揭示了B2M和C3表达水平与自然杀伤（NK）细胞、树突状细胞、静息CD4记忆T细胞以及嗜酸性粒细胞的激活之间的相关性。B2M和C3已被确定为病毒性心肌炎的潜在生物标志物，为未来对COVID-19相关心肌炎发病机制的研究提供了有价值的见解。
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