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不同可溶性免疫检查点特征可用于表征 COVID-19 严重程度、死亡率和 SARS-CoV-2 变异感染。

Distinct soluble immune checkpoint profiles characterize COVID-19 severity, mortality and SARS-CoV-2 variant infections.

机构信息

Department of Infectious Diseases (Internal Medicine II), Faculty of Medicine, Grigore T. Popa University of Medicine and Pharmacy, Iasi, Romania.

St. Parascheva Clinical Hospital for Infectious Diseases, Iasi, Romania.

出版信息

Front Immunol. 2024 Sep 23;15:1464480. doi: 10.3389/fimmu.2024.1464480. eCollection 2024.

Abstract

INTRODUCTION

Over the past four years, the COVID-19 pandemic has posed serious global health challenges. The severe form of disease and death resulted from the failure of immune regulatory mechanisms, closely highlighted by the dual proinflammatory cytokine and soluble immune checkpoint (sICP) storm. Identifying the individual factors impacting on disease severity, evolution and outcome, as well as any additional interconnections, have become of high scientific interest.

METHODS

In this study, we evaluated a novel panel composed of ten sICPs for the predictive values of COVID-19 disease severity, mortality and Delta vs. Omicron variant infections in relation to hyperinflammatory biomarkers. The serum levels of sICPs from confirmed SARS-CoV-2 infected patients at hospital admission were determined by Luminex, and artificial neural network analysis was applied for defining the distinct patterns of molecular associations with each form of disease: mild, moderate, and severe.

RESULTS

Notably, distinct sICP profiles characterized various stages of disease and Delta infections: while sCD40 played a central role in all defined diagrams, the differences emerged from the distribution levels of four molecules recently found and relatively less investigated (sCD30, s4-1BB, sTIM-1, sB7-H3), and their associations with various hematological and biochemical inflammatory biomarkers. The artificial neural network analysis revealed the prominent role of serum sTIM-1 and Galectin-9 levels at hospital admission in discriminating between survivors and non-survivors, as well as the role of specific anti-interleukin therapy (Tocilizumab, Anakinra) in improving survival for patients with initially high sTIM-1 levels. Furthermore, strong associations between sCD40 and Galectin-9 with suPAR defined the Omicron variant infections, while the positive match of sCD40 with sTREM-1 serum levels characterized the Delta-infected patients.

CONCLUSIONS

Of importance, this study provides a comprehensive analysis of circulatory immune factors governing the COVID-19 pathology, and identifies key roles of sCD40, sTIM-1, and Galectin-9 in predicting mortality.

摘要

简介

在过去的四年中,COVID-19 大流行对全球健康构成了严重挑战。疾病的严重形式和死亡是由于免疫调节机制失效所致,这一点被双重促炎细胞因子和可溶性免疫检查点(sICP)风暴密切强调。确定影响疾病严重程度、演变和结局的个体因素,以及任何额外的相互关系,已成为高度科学关注的问题。

方法

在这项研究中,我们评估了一个由十个 sICP 组成的新面板,用于预测 COVID-19 疾病严重程度、死亡率以及与过度炎症生物标志物相关的 Delta 与 Omicron 变体感染。通过 Luminex 测定入院时确诊 SARS-CoV-2 感染患者的 sICP 血清水平,并应用人工神经网络分析定义每种疾病形式(轻度、中度和重度)的分子关联的不同模式。

结果

值得注意的是,不同的 sICP 谱特征描述了疾病和 Delta 感染的各个阶段:虽然 sCD40 在所有定义的图表中起着核心作用,但差异来自于最近发现和相对较少研究的四种分子(sCD30、s4-1BB、sTIM-1、sB7-H3)的分布水平,以及它们与各种血液学和生化炎症生物标志物的关联。人工神经网络分析显示,入院时血清 sTIM-1 和半乳糖凝集素-9 水平在区分幸存者和非幸存者方面具有突出作用,以及特定抗白细胞介素治疗(托珠单抗、阿那白滞素)在改善初始 sTIM-1 水平较高的患者的生存率方面的作用。此外,sCD40 与 Galectin-9 与 suPAR 之间的强烈关联定义了 Omicron 变体感染,而 sCD40 与 sTREM-1 血清水平的阳性匹配则特征化了 Delta 感染患者。

结论

重要的是,本研究提供了对控制 COVID-19 病理学的循环免疫因素的全面分析,并确定了 sCD40、sTIM-1 和 Galectin-9 在预测死亡率方面的关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8403/11456479/cb7b2a0c269a/fimmu-15-1464480-g001.jpg

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