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独特的免疫学特征可区分 COVID-19 重症与非 SARS-CoV-2 驱动的重症肺炎。

Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia.

机构信息

Institute of Experimental Immunology, University of Zurich, 8057 Zurich, Switzerland; German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Partner Site Freiburg, 79106 Freiburg, Germany.

Institute of Experimental Immunology, University of Zurich, 8057 Zurich, Switzerland.

出版信息

Immunity. 2021 Jul 13;54(7):1578-1593.e5. doi: 10.1016/j.immuni.2021.05.002. Epub 2021 May 9.

Abstract

Immune profiling of COVID-19 patients has identified numerous alterations in both innate and adaptive immunity. However, whether those changes are specific to SARS-CoV-2 or driven by a general inflammatory response shared across severely ill pneumonia patients remains unknown. Here, we compared the immune profile of severe COVID-19 with non-SARS-CoV-2 pneumonia ICU patients using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided analysis. COVID-19 and non-SARS-CoV-2 pneumonia both showed increased emergency myelopoiesis and displayed features of adaptive immune paralysis. However, pathological immune signatures suggestive of T cell exhaustion were exclusive to COVID-19. The integration of single-cell profiling with a predicted binding capacity of SARS-CoV-2 peptides to the patients' HLA profile further linked the COVID-19 immunopathology to impaired virus recognition. Toward clinical translation, circulating NKT cell frequency was identified as a predictive biomarker for patient outcome. Our comparative immune map serves to delineate treatment strategies to interfere with the immunopathologic cascade exclusive to severe COVID-19.

摘要

对 COVID-19 患者的免疫分析已经确定了先天和适应性免疫的许多改变。然而,这些变化是否是由 SARS-CoV-2 特异性引起的,还是由严重肺炎患者共有的一般炎症反应驱动的,目前尚不清楚。在这里,我们使用纵向、高维单细胞光谱细胞术和基于算法的分析比较了严重 COVID-19 和非 SARS-CoV-2 肺炎 ICU 患者的免疫谱。COVID-19 和非 SARS-CoV-2 肺炎均表现出紧急髓系生成增加,并表现出适应性免疫麻痹的特征。然而,提示 T 细胞耗竭的病理性免疫特征仅见于 COVID-19。单细胞分析与 SARS-CoV-2 肽与患者 HLA 谱的预测结合能力的整合进一步将 COVID-19 免疫病理学与受损的病毒识别联系起来。为了实现临床转化,循环 NKT 细胞频率被确定为预测患者预后的生物标志物。我们的比较免疫图谱有助于制定治疗策略,以干扰严重 COVID-19 特有的免疫病理级联反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15f2/8284599/d9ce948cfe36/fx1.jpg

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