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The COVID-19 immune landscape is dynamically and reversibly correlated with disease severity.COVID-19 的免疫图谱与疾病严重程度呈动态和可逆相关。
J Clin Invest. 2021 Feb 1;131(3). doi: 10.1172/JCI143648.
2
Dysregulated Innate and Adaptive Immune Responses Discriminate Disease Severity in COVID-19.失调的固有和适应性免疫反应可区分 COVID-19 的疾病严重程度。
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Front Immunol. 2024 Jul 29;15:1381091. doi: 10.3389/fimmu.2024.1381091. eCollection 2024.
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Life Sci Alliance. 2020 Dec 24;4(2). doi: 10.26508/lsa.202000955. Print 2021 Feb.
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Chem Biol Interact. 2022 Jan 25;352:109777. doi: 10.1016/j.cbi.2021.109777. Epub 2021 Dec 9.

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Crit Care Explor. 2025 Jan 31;7(2):e1203. doi: 10.1097/CCE.0000000000001203. eCollection 2025 Feb 1.
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Cell Rep. 2024 Nov 26;43(11):114933. doi: 10.1016/j.celrep.2024.114933. Epub 2024 Nov 5.
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Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosis.新型冠状病毒肺炎相关继发性噬血细胞性淋巴组织细胞增生症生物标志物的鉴定
bioRxiv. 2024 Aug 15:2024.08.13.607855. doi: 10.1101/2024.08.13.607855.
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Distinct subsets of anti-pulmonary autoantibodies correlate with disease severity and survival in severe COVID-19 patients.在重症 COVID-19 患者中,抗肺自身抗体的不同亚群与疾病严重程度和生存相关。
Geroscience. 2024 Apr;46(2):1561-1574. doi: 10.1007/s11357-023-00887-2. Epub 2023 Sep 1.
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Neutrophils during SARS-CoV-2 infection: Friend or foe?新冠病毒感染期间的中性粒细胞:是敌是友?
Immunol Rev. 2023 Mar;314(1):399-412. doi: 10.1111/imr.13175. Epub 2022 Nov 28.
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Bioinformatics. 2023 Jan 1;39(1). doi: 10.1093/bioinformatics/btac751.
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Correlation between Type I Interferon Associated Factors and COVID-19 Severity.I 型干扰素相关因素与 COVID-19 严重程度的相关性。
Int J Mol Sci. 2022 Sep 19;23(18):10968. doi: 10.3390/ijms231810968.
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Low quantity and quality of anti-spike humoral response is linked to CD4 T-cell apoptosis in COVID-19 patients.在 COVID-19 患者中,抗刺突体液免疫应答的数量和质量低与 CD4 T 细胞凋亡有关。
Cell Death Dis. 2022 Aug 27;13(8):741. doi: 10.1038/s41419-022-05190-0.

本文引用的文献

1
Systems-Level Immunomonitoring from Acute to Recovery Phase of Severe COVID-19.从严重 COVID-19 的急性期到恢复期的系统免疫监测。
Cell Rep Med. 2020 Aug 25;1(5):100078. doi: 10.1016/j.xcrm.2020.100078. Epub 2020 Aug 5.
2
A dynamic COVID-19 immune signature includes associations with poor prognosis.一个动态的 COVID-19 免疫特征包括与预后不良的关联。
Nat Med. 2020 Oct;26(10):1623-1635. doi: 10.1038/s41591-020-1038-6. Epub 2020 Aug 17.
3
Assessment of COVID-19 Hospitalizations by Race/Ethnicity in 12 States.12 个州的基于种族/族裔的 COVID-19 住院评估。
JAMA Intern Med. 2021 Jan 1;181(1):131-134. doi: 10.1001/jamainternmed.2020.3857.
4
Associations of type 1 and type 2 diabetes with COVID-19-related mortality in England: a whole-population study.1 型和 2 型糖尿病与英格兰 COVID-19 相关死亡率的关联:一项全人群研究。
Lancet Diabetes Endocrinol. 2020 Oct;8(10):813-822. doi: 10.1016/S2213-8587(20)30272-2. Epub 2020 Aug 13.
5
Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study.英格兰 1 型和 2 型糖尿病患者 COVID-19 相关死亡率的风险因素:一项基于人群的队列研究。
Lancet Diabetes Endocrinol. 2020 Oct;8(10):823-833. doi: 10.1016/S2213-8587(20)30271-0. Epub 2020 Aug 13.
6
Immune Phenotyping Based on the Neutrophil-to-Lymphocyte Ratio and IgG Level Predicts Disease Severity and Outcome for Patients With COVID-19.基于中性粒细胞与淋巴细胞比值和IgG水平的免疫表型分析可预测COVID-19患者的疾病严重程度和预后。
Front Mol Biosci. 2020 Jul 3;7:157. doi: 10.3389/fmolb.2020.00157. eCollection 2020.
7
Longitudinal analyses reveal immunological misfiring in severe COVID-19.纵向分析揭示了重症 COVID-19 中的免疫失调。
Nature. 2020 Aug;584(7821):463-469. doi: 10.1038/s41586-020-2588-y. Epub 2020 Jul 27.
8
Risk Factors for Intensive Care Unit Admission and In-hospital Mortality Among Hospitalized Adults Identified through the US Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET).通过美国 2019 年冠状病毒病(COVID-19)相关住院监测网络(COVID-NET)确定的住院成年患者入住重症监护病房和院内死亡的危险因素。
Clin Infect Dis. 2021 May 4;72(9):e206-e214. doi: 10.1093/cid/ciaa1012.
9
Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications.深度免疫剖析 COVID-19 患者,揭示具有治疗意义的不同免疫类型。
Science. 2020 Sep 4;369(6508). doi: 10.1126/science.abc8511. Epub 2020 Jul 15.
10
Comprehensive mapping of immune perturbations associated with severe COVID-19.全面绘制与严重 COVID-19 相关的免疫扰动图谱。
Sci Immunol. 2020 Jul 15;5(49). doi: 10.1126/sciimmunol.abd7114.

COVID-19 的免疫图谱与疾病严重程度呈动态和可逆相关。

The COVID-19 immune landscape is dynamically and reversibly correlated with disease severity.

机构信息

Center for Systems Immunology, Benaroya Research Institute (BRI) at Virginia Mason, Seattle, Washington, USA.

Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

出版信息

J Clin Invest. 2021 Feb 1;131(3). doi: 10.1172/JCI143648.

DOI:10.1172/JCI143648
PMID:33529167
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7843226/
Abstract

BACKGROUNDDespite a rapidly growing body of literature on coronavirus disease 2019 (COVID-19), our understanding of the immune correlates of disease severity, course, and outcome remains poor.METHODSUsing mass cytometry, we assessed the immune landscape in longitudinal whole-blood specimens from 59 patients presenting with acute COVID-19 and classified based on maximal disease severity. Hospitalized patients negative for SARS-CoV-2 were used as controls.RESULTSWe found that the immune landscape in COVID-19 formed 3 dominant clusters, which correlated with disease severity. Longitudinal analysis identified a pattern of productive innate and adaptive immune responses in individuals who had a moderate disease course, whereas those with severe disease had features suggestive of a protracted and dysregulated immune response. Further, we identified coordinate immune alterations accompanying clinical improvement and decline that were also seen in patients who received IL-6 pathway blockade.CONCLUSIONThe hospitalized COVID-19 negative cohort allowed us to identify immune alterations that were shared between severe COVID-19 and other critically ill patients. Collectively, our findings indicate that selection of immune interventions should be based in part on disease presentation and early disease trajectory due to the profound differences in the immune response in those with mild to moderate disease and those with the most severe disease.FUNDINGBenaroya Family Foundation, the Leonard and Norma Klorfine Foundation, Glenn and Mary Lynn Mounger, and the National Institutes of Health.

摘要

背景

尽管关于 2019 年冠状病毒病(COVID-19)的文献迅速增加,但我们对疾病严重程度、病程和结局的免疫相关性的理解仍然很差。

方法

使用液质联用技术,我们评估了 59 名急性 COVID-19 患者的纵向全血标本中的免疫图谱,并根据最大疾病严重程度进行分类。将 SARS-CoV-2 阴性的住院患者作为对照。

结果

我们发现 COVID-19 中的免疫图谱形成了 3 个主要簇,与疾病严重程度相关。纵向分析在疾病病程中度的个体中发现了具有生产力的固有和适应性免疫反应模式,而严重疾病患者则具有提示延长和失调免疫反应的特征。此外,我们还发现了伴随临床改善和下降的协调免疫改变,这些改变也见于接受 IL-6 途径阻断的患者。

结论

住院 COVID-19 阴性队列使我们能够识别 COVID-19 与其他危重病患者共有的免疫改变。总的来说,我们的发现表明,由于轻度至中度疾病患者和最严重疾病患者的免疫反应存在显著差异,免疫干预的选择部分应基于疾病表现和早期疾病轨迹。

资助

贝纳罗亚家族基金会、伦纳德和诺尔玛·克洛菲纳基金会、格伦和玛丽·林恩·芒格以及美国国立卫生研究院。