Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
National Centre for Infectious Diseases, Singapore.
Lancet Microbe. 2021 Jun;2(6):e240-e249. doi: 10.1016/S2666-5247(21)00025-2. Epub 2021 Mar 23.
Studies have found different waning rates of neutralising antibodies compared with binding antibodies against SARS-CoV-2. The impact of neutralising antibody waning rate at the individual patient level on the longevity of immunity remains unknown. We aimed to investigate the peak levels and dynamics of neutralising antibody waning and IgG avidity maturation over time, and correlate this with clinical parameters, cytokines, and T-cell responses.
We did a longitudinal study of patients who had recovered from COVID-19 up to day 180 post-symptom onset by monitoring changes in neutralising antibody levels using a previously validated surrogate virus neutralisation test. Changes in antibody avidities and other immune markers at different convalescent stages were determined and correlated with clinical features. Using a machine learning algorithm, temporal change in neutralising antibody levels was classified into five groups and used to predict the longevity of neutralising antibody-mediated immunity.
We approached 517 patients for participation in the study, of whom 288 consented for outpatient follow-up and collection of serial blood samples. 164 patients were followed up and had adequate blood samples collected for analysis, with a total of 546 serum samples collected, including 128 blood samples taken up to 180 days post-symptom onset. We identified five distinctive patterns of neutralising antibody dynamics as follows: negative, individuals who did not, at our intervals of sampling, develop neutralising antibodies at the 30% inhibition level (19 [12%] of 164 patients); rapid waning, individuals who had varying levels of neutralising antibodies from around 20 days after symptom onset, but seroreverted in less than 180 days (44 [27%] of 164 patients); slow waning, individuals who remained neutralising antibody-positive at 180 days post-symptom onset (46 [28%] of 164 patients); persistent, although with varying peak neutralising antibody levels, these individuals had minimal neutralising antibody decay (52 [32%] of 164 patients); and delayed response, a small group that showed an unexpected increase of neutralising antibodies during late convalescence (at 90 or 180 days after symptom onset; three [2%] of 164 patients). Persistence of neutralising antibodies was associated with disease severity and sustained level of pro-inflammatory cytokines, chemokines, and growth factors. By contrast, T-cell responses were similar among the different neutralising antibody dynamics groups. On the basis of the different decay dynamics, we established a prediction algorithm that revealed a wide range of neutralising antibody longevity, varying from around 40 days to many decades.
Neutralising antibody response dynamics in patients who have recovered from COVID-19 vary greatly, and prediction of immune longevity can only be accurately determined at the individual level. Our findings emphasise the importance of public health and social measures in the ongoing pandemic outbreak response, and might have implications for longevity of immunity after vaccination.
National Medical Research Council, Biomedical Research Council, and A*STAR, Singapore.
研究发现,针对 SARS-CoV-2 的中和抗体与结合抗体的衰减率不同。中和抗体衰减率在个体患者水平上对免疫持久性的影响尚不清楚。我们旨在研究中和抗体衰减的峰值水平和动态以及 IgG 亲和力成熟随时间的变化,并将其与临床参数、细胞因子和 T 细胞反应相关联。
我们通过使用先前验证的替代病毒中和试验监测中和抗体水平的变化,对从症状出现后第 180 天的 COVID-19 康复患者进行了一项纵向研究。在不同的恢复期确定了抗体亲和性和其他免疫标志物的变化,并与临床特征相关联。使用机器学习算法,将中和抗体水平的时间变化分为五组,并用于预测中和抗体介导的免疫持久性。
我们联系了 517 名患者参与研究,其中 288 名同意进行门诊随访和连续采集血样。对 164 名患者进行了随访,并采集了足够的血样进行分析,共采集了 546 份血清样本,其中 128 份血样采集于症状出现后 180 天内。我们确定了五种不同的中和抗体动态模式:阴性,在我们的采样间隔内,164 名患者中有 19 名(12%)没有产生 30%抑制水平的中和抗体;快速衰减,164 名患者中有 44 名(27%)在症状出现后约 20 天内有不同水平的中和抗体,但在 180 天内血清学转换;缓慢衰减,164 名患者中有 46 名(28%)在症状出现后 180 天仍为中和抗体阳性;持续存在,尽管中和抗体峰值水平不同,但这些患者的中和抗体衰减最小;延迟反应,一小部分患者在恢复期晚期(症状出现后 90 或 180 天)出现意外的中和抗体增加;(164 名患者中有 3 名[2%])。中和抗体的持续存在与疾病严重程度和促炎细胞因子、趋化因子和生长因子的持续水平相关。相比之下,不同中和抗体动力学组之间的 T 细胞反应相似。基于不同的衰减动力学,我们建立了一个预测算法,揭示了中和抗体寿命的广泛范围,从大约 40 天到几十年不等。
从 COVID-19 中康复的患者的中和抗体反应动态差异很大,免疫持久性的预测只能在个体水平上准确确定。我们的发现强调了公共卫生和社会措施在持续大流行应对中的重要性,并且可能对疫苗接种后的免疫持久性产生影响。
新加坡国家医学研究理事会、生物医学研究理事会和 A*STAR。