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SARS-CoV-2 感染后抗病毒记忆的不同轨迹。

Divergent trajectories of antiviral memory after SARS-CoV-2 infection.

机构信息

Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK.

Peter Medawar Building for Pathogen Research, Nuffield Dept. of Clinical Medicine, University of Oxford, Oxford, UK.

出版信息

Nat Commun. 2022 Mar 10;13(1):1251. doi: 10.1038/s41467-022-28898-1.

Abstract

The trajectories of acquired immunity to severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We present a detailed longitudinal cohort study of UK healthcare workers prior to vaccination, presenting April-June 2020 with asymptomatic or symptomatic infection. Here we show a highly variable range of responses, some of which (T cell interferon-gamma ELISpot, N-specific antibody) wane over time, while others (spike-specific antibody, B cell memory ELISpot) are stable. We use integrative analysis and a machine-learning approach (SIMON - Sequential Iterative Modeling OverNight) to explore this heterogeneity. We identify a subgroup of participants with higher antibody responses and interferon-gamma ELISpot T cell responses, and a robust trajectory for longer term immunity associates with higher levels of neutralising antibodies against the infecting (Victoria) strain and also against variants B.1.1.7 (alpha) and B.1.351 (beta). These variable trajectories following early priming may define subsequent protection from severe disease from novel variants.

摘要

获得性对严重急性呼吸综合征冠状病毒 2 感染的免疫轨迹尚不完全清楚。我们在接种疫苗前对英国医护人员进行了详细的纵向队列研究,他们在 2020 年 4 月至 6 月期间出现无症状或有症状的感染。在这里,我们展示了范围广泛的高度可变的反应,其中一些(T 细胞干扰素-γ ELISpot、N 特异性抗体)随着时间的推移而减弱,而另一些(刺突特异性抗体、B 细胞记忆 ELISpot)则保持稳定。我们使用综合分析和机器学习方法(SIMON-Sequential Iterative Modeling OverNight)来探索这种异质性。我们确定了一组具有更高抗体和干扰素-γ ELISpot T 细胞反应的参与者,并且与更长时间免疫相关的稳健轨迹与针对感染(维多利亚)株以及变体 B.1.1.7(alpha)和 B.1.351(beta)的更高水平中和抗体相关。这些早期启动后的可变轨迹可能定义了随后对新型变体的严重疾病的保护。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b325/8913789/10eaab80917d/41467_2022_28898_Fig1_HTML.jpg

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