Identification of Potential Biomarkers and Immune Cell Signatures in COVID-19 Myocarditis Through Bioinformatic Analysis

通过生物信息学分析鉴定 COVID-19 心肌炎中的潜在生物标志物和免疫细胞特征

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Abstract

Objective: 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. Methods: 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. Results: Thirty genes were identified, with a significant proportion of the DEGs being associated with carbohydrate binding, endopeptidase activity, and pathogenic organisms such as Staphylococcus aureus 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. Conclusion: 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.

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