Brady Caolann, Tipton Tom, Carnell Oliver, Longet Stephanie, Gooch Karen, Hall Yper, Salguero Javier, Tomic Adriana, Carroll Miles
Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
NPJ Vaccines. 2025 Apr 14;10(1):69. doi: 10.1038/s41541-025-01103-2.
Correlates of protection (CoPs) for SARS-CoV-2 have yet to be sufficiently defined. This study uses the machine learning platform, SIMON, to accurately predict the immunological parameters that reduced clinical pathology or viral load following SARS-CoV-2 challenge in a cohort of 90 non-human primates. We found that anti-SARS-CoV-2 spike antibody and neutralising antibody titres were the best predictors of clinical protection and low viral load in the lung. Since antibodies to SARS-CoV-2 spike showed the greatest association with clinical protection and reduced viral load, we next used SIMON to investigate the immunological features that predict high antibody titres. It was found that a pre-immunisation response to seasonal beta-HCoVs and a high frequency of peripheral intermediate and non-classical monocytes predicted low SARS-CoV-2 spike IgG titres. In contrast, an elevated T cell response as measured by IFNγ ELISpot predicted high IgG titres. Additional predictors of clinical protection and low SARS-CoV-2 burden included a high abundance of peripheral T cells. In contrast, increased numbers of intermediate monocytes predicted clinical pathology and high viral burden in the throat. We also conclude that an immunisation strategy that minimises pathology post-challenge did not necessarily mediate viral control. This would be an important finding to take forward into the development of future vaccines aimed at limiting the transmission of SARS-CoV-2. These results contribute to SARS-CoV-2 CoP definition and shed light on the factors influencing the success of SARS-CoV-2 vaccination.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的保护相关因素（CoP）尚未得到充分定义。本研究使用机器学习平台SIMON，准确预测了90只非人灵长类动物在感染SARS-CoV-2后可减轻临床病理或病毒载量的免疫参数。我们发现，抗SARS-CoV-2刺突抗体和中和抗体滴度是临床保护和肺部低病毒载量的最佳预测指标。由于针对SARS-CoV-2刺突的抗体与临床保护和病毒载量降低的关联最为密切，我们接下来使用SIMON研究预测高抗体滴度的免疫特征。结果发现，对季节性β冠状病毒的免疫前反应以及外周中间单核细胞和非经典单核细胞的高频率预示着较低的SARS-CoV-2刺突IgG滴度。相反，通过IFNγ ELISpot检测到的T细胞反应升高预示着高IgG滴度。临床保护和低SARS-CoV-2负担的其他预测指标包括外周T细胞的高丰度。相比之下，中间单核细胞数量增加预示着临床病理和咽喉部高病毒负担。我们还得出结论，一种能将攻击后病理反应降至最低的免疫策略不一定能介导病毒控制。这将是一个重要的发现，有助于推进未来旨在限制SARS-CoV-2传播的疫苗的开发。这些结果有助于定义SARS-CoV-2的CoP，并阐明影响SARS-CoV-2疫苗接种成功的因素。
