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入院时循环免疫细胞和可溶性介质的综合分析揭示了 COVID19 的特定特征,可用于预测临床结局。

Integrated analysis of circulating immune cellular and soluble mediators reveals specific COVID19 signatures at hospital admission with utility for prediction of clinical outcomes.

机构信息

Fundación Instituto de Investigación Sanitaria Aragón (IIS-Aragón), Biomedical Research Centre of Aragon (CIBA), 50009 Zaragoza, Spain.

Centro de Investigación Biomédica en Red (CIBER) de Enfermedades Infecciosas, 50018 Madrid, Spain.

出版信息

Theranostics. 2022 Jan 1;12(1):290-306. doi: 10.7150/thno.63463. eCollection 2022.

Abstract

Coronavirus disease 2019 (COVID19), caused by SARS-CoV-2, is a complex disease, with a variety of clinical manifestations ranging from asymptomatic infection or mild cold-like symptoms to more severe cases requiring hospitalization and critical care. The most severe presentations seem to be related with a delayed, deregulated immune response leading to exacerbated inflammation and organ damage with close similarities to sepsis. In order to improve the understanding on the relation between host immune response and disease course, we have studied the differences in the cellular (monocytes, CD8+ T and NK cells) and soluble (cytokines, chemokines and immunoregulatory ligands) immune response in blood between Healthy Donors (HD), COVID19 and a group of patients with non-COVID19 respiratory tract infections (NON-COV-RTI). In addition, the immune response profile has been analyzed in COVID19 patients according to disease severity. In comparison to HDs and patients with NON-COV-RTI, COVID19 patients show a heterogeneous immune response with the presence of both activated and exhausted CD8+ T and NK cells characterised by the expression of the immune checkpoint LAG3 and the presence of the adaptive NK cell subset. An increased frequency of adaptive NK cells and a reduction of NK cells expressing the activating receptors NKp30 and NKp46 correlated with disease severity. Although both activated and exhausted NK cells expressing LAG3 were increased in moderate/severe cases, unsupervised cell clustering analyses revealed a more complex scenario with single NK cells expressing more than one immune checkpoint (PD1, TIM3 and/or LAG3). A general increased level of inflammatory cytokines and chemokines was found in COVID19 patients, some of which like IL18, IL1RA, IL36B and IL31, IL2, IFNα and TNFα, CXCL10, CCL2 and CCL8 were able to differentiate between COVID19 and NON-COV-RTI and correlated with bad prognosis (IL2, TNFα, IL1RA, CCL2, CXCL10 and CXCL9). Notably, we found that soluble NKG2D ligands from the MIC and ULBPs families were increased in COVID19 compared to NON-COV-RTI and correlated with disease severity. Our results provide a detailed comprehensive analysis of the presence of activated and exhausted CD8+T, NK and monocyte cell subsets as well as extracellular inflammatory factors beyond cytokines/chemokines, specifically associated to COVID19. Importantly, multivariate analysis including clinical, demographical and immunological experimental variables have allowed us to reveal specific immune signatures to i) differentiate COVID19 from other infections and ii) predict disease severity and the risk of death.

摘要

新型冠状病毒病 2019(COVID19)由 SARS-CoV-2 引起,是一种复杂的疾病,具有多种临床表现,从无症状感染或类似轻度感冒的症状到需要住院和重症监护的更严重病例不等。最严重的表现似乎与延迟、失调的免疫反应有关,导致炎症加剧和器官损伤,与败血症非常相似。为了更好地了解宿主免疫反应与疾病进程之间的关系,我们研究了血液中健康供体(HD)、COVID19 和一组非 COVID19 呼吸道感染(NON-COV-RTI)患者之间细胞(单核细胞、CD8+T 和 NK 细胞)和可溶性(细胞因子、趋化因子和免疫调节配体)免疫反应的差异。此外,根据疾病严重程度分析了 COVID19 患者的免疫反应特征。与 HD 和 NON-COV-RTI 患者相比,COVID19 患者表现出异质性免疫反应,存在激活和耗竭的 CD8+T 和 NK 细胞,其特征是表达免疫检查点 LAG3 和存在适应性 NK 细胞亚群。适应性 NK 细胞的频率增加和表达激活受体 NKp30 和 NKp46 的 NK 细胞减少与疾病严重程度相关。虽然中度/重度病例中均增加了表达 LAG3 的激活和耗竭 NK 细胞,但无监督细胞聚类分析显示出更复杂的情况,单个 NK 细胞表达不止一种免疫检查点(PD1、TIM3 和/或 LAG3)。COVID19 患者中发现了炎症细胞因子和趋化因子水平普遍升高,其中一些细胞因子,如 IL18、IL1RA、IL36B 和 IL31、IL2、IFNα 和 TNFα、CXCL10、CCL2 和 CCL8,能够区分 COVID19 和 NON-COV-RTI ,并与不良预后相关(IL2、TNFα、IL1RA、CCL2、CXCL10 和 CXCL9)。值得注意的是,我们发现与 NON-COV-RTI 相比,COVID19 患者的 MIC 和 ULBPs 家族的可溶性 NKG2D 配体增加,并与疾病严重程度相关。我们的研究结果提供了对激活和耗竭的 CD8+T、NK 和单核细胞亚群以及细胞外炎症因子的详细综合分析,这些因子不仅包括细胞因子/趋化因子,还与 COVID19 具体相关。重要的是,包括临床、人口统计学和免疫学实验变量的多变量分析使我们能够揭示特定的免疫特征,以 i)将 COVID19 与其他感染区分开来,ii)预测疾病严重程度和死亡风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c775/8690910/14944a794211/thnov12p0290g001.jpg

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