Comparative analysis of eleven SARS-CoV-2 immunoassays and neutralisation data: time to enhance standardisation and correlation of protection

To infer a reliable SARS-CoV-2 antibody protection level from a serological test, an appropriate quantitative threshold and solid equivalence across serological tests are needed. Additionally, tests should show a solid correlation with neutralising assays and with the protection observed in large population cohorts even against emerging variants. We studied convalescent and vaccinated populations using 11 commercial antibody assays. Results were compared to evaluate discrepancies across tests. Neutralisation capacity was measured in a subset of the samples with a lentiviral-based assay. Serum from convalescent (<i>n</i> = 121) and vaccinated individuals (<i>n</i> = 471, 260 with Comirnaty, 110 with Spikevax, and 96 with Vaxzevria) was assessed using 11 different assays, including two from Abbott, Euroimmun, Liaison, Roche, and Vircell, and one from Siemens. A spike protein-lentiviral vector with a fluorescent reporter was used for neutralisation assay of serum from convalescent (<i>n</i> = 26) and vaccinated (<i>n</i> = 39) individuals. Positivity ranged between 81.3 and 94.3% after infection and 99.4 and 99.7% after vaccination, depending on the assay. Both cohorts showed a high level of qualitative agreement across tests (Fleiss’ kappa = 0.598 and 0.719 for convalescent and vaccinated respectively). Spikevax vaccine recipients showed the highest level of antibodies in all tests. Effectiveness of each test predicting SARS-CoV-2 neutralising capacity depended on assay type and target, with CLIA and anti-S being more effective than ELISA and anti-N assays, respectively. High-throughput immunoassays are good predictors of neutralising capacity. Updated targets and better standardisation would be required to find an effective correlate of protection, especially to account for antibodies against new variants.

若要通过血清学检测准确推断严重急性呼吸综合征冠状病毒2（SARS-CoV-2）抗体的保护水平，需设定合理的定量阈值，并确保不同血清学检测方法间具备可靠的等效性。此外，检测方法还需与中和试验以及大型人群队列中观察到的保护效应（甚至针对新型变异株）呈现显著相关性。本研究采用11种商业化抗体检测方法，对康复人群与疫苗接种人群展开分析，并比对检测结果以评估不同方法间的差异。研究通过基于慢病毒的试验，对部分样本的中和能力进行了检测。康复者血清（n=121）与疫苗接种者血清（n=471，其中接种Comirnaty者260例、Spikevax者110例、Vaxzevria者96例）通过11种不同检测方法进行评估，这些方法包括Abbott、欧蒙（Euroimmun）、利发（Liaison）、罗氏（Roche）、维尔塞尔（Vircell）各提供的2款试剂，以及西门子（Siemens）提供的1款试剂。本研究采用携带荧光报告基因的刺突蛋白-慢病毒载体，对26名康复者与39名疫苗接种者的血清样本开展中和试验检测。不同检测方法下，康复人群的阳性率介于81.3%至94.3%之间，疫苗接种人群的阳性率则介于99.4%至99.7%之间。两个队列的检测结果均在定性层面展现出较高的一致性：康复队列与疫苗接种队列的弗莱伊斯Kappa值（Fleiss’ kappa）分别为0.598与0.719。在所有检测方法中，接种Spikevax疫苗的人群抗体水平最高。各检测方法对SARS-CoV-2中和能力的预测效能取决于检测类型与靶标：化学发光免疫分析（CLIA）类检测的预测效能优于酶联免疫吸附试验（ELISA），抗刺突蛋白（anti-S）检测的预测效能则优于抗核衣壳蛋白（anti-N）检测。高通量免疫检测方法可较好地预测中和能力。若要找到可靠的保护相关性指标，尤其是针对新型变异株的抗体相关指标，需更新检测靶标并进一步优化标准化流程。