Neutralizing antibody detection can assess the incidence of COVID-19 and the effectiveness of vaccines. However, commercial reagents for neutralizing antibodies were developed after the anti–SARS-CoV-2 immunoglobulin (Ig) G and IgM antibodies. Therefore, some laboratories did not perform neutralizing antibody testing services because of multiple factors.
To find a fast, accurate, and economic alternative for the detection of neutralizing antibodies for the development of COVID-19 screening programs.
The response and correlation of 3 antibodies (anti–spike protein neutralizing antibody, total anti–receptor-binding domain [RBD] antibody, and anti-RBD IgG) were determined by observing the dynamics in 61 participants for 160 days after vaccination.
The levels of neutralizing and anti-RBD IgG antibodies reached their peak values on day 42 after vaccination (120.75 IU/mL and 14.38 signal-to-cutoff ratio [S/CO], respectively). The total antibody levels peaked at 138.47 S/CO on day 35 after vaccination. The strongest correlation was found between neutralizing and anti-RBD IgG antibody levels (r = 0.894, P < .001). The area under the receiver operating characteristic curve for total antibody levels for the prediction of seropositivity for neutralizing antibodies was 0.881 (P < .001), and that for anti-RBD IgG antibody levels was 0.937 (P < .001).
Neutralizing and anti-RBD IgG antibody levels were strongly correlated, and thus anti-RBD IgG antibody levels can be used for the accurate assessment of immunity following SARS-CoV-2 infection or vaccination.
SARS-CoV-2 is a highly transmissible and pathogenic virus that has caused serious harm to human health and public safety during the ongoing COVID-19 global pandemic.1,2 Global COVID-19 cases now stand at 352 million, and nearly 5.6 million people have died. COVID-19 vaccines are the only effective way to control the disease in the long term.2,3 Although most of the population in Europe and the Americas have received at least 1 dose, the World Health Organization (WHO) target of full vaccination rates of 40% in every country by the end of 2021 has not been achieved in most of the African countries. The specific neutralizing antibody levels are key indicators for evaluating vaccine efficacy and monitoring the epidemic. Neutralizing antibodies against the receptor-binding domain (RBD) of the spike protein (S) inhibit binding of the same to the angiotensin-converting enzyme 2 (ACE2) receptor, thereby blocking viral entry into human cells and consequently exerting an antiviral effect.4 A few studies have used chemiluminescent immunoassay to measure neutralizing antibodies to evaluate the neutralization values of the serum samples collected from COVID-19 patients5 or blood donors.6 Neutralizing antibody results can be used to predict the severity of COVID-197 and to evaluate SARS-CoV-2 vaccine efficacy.8–10 Detection of neutralizing antibodies could be added to blood donor screening protocols to increase the number of plasma donation cases used to treat patients with severe COVID-19. It provides a useful tool for large-scale screening of convalescent plasma for safe COVID-19 treatment.11 Nevertheless, commercial reagents for neutralizing antibodies were developed after the anti–SARS-CoV-2 immunoglobulin (Ig) G and IgM antibodies. Therefore, some laboratories did not carry out neutralizing antibody testing services because of customary, economic, or policy factors. When neutralizing antibody detection kits cannot be purchased because of policy or commercial factors, it is necessary to find alternative methods for neutralizing antibody detection. Given that RBD is a key target for viral neutralization, anti-RBD antibodies are expected to be more effective at viral neutralization than those against the nucleocapsid (N), S2, or other domains on S1.12 The present study assessed the presence of the 3 antibodies, namely anti-S, total anti-RBD, and anti-RBD IgG antibodies. Further, the dynamics and correlation between the 3 antibodies were observed in 61 participants for 160 days following vaccination in an attempt to predict the neutralizing activity of the vaccines and the consequent acquisition of immunity.
MATERIALS AND METHODS
Study Population and Design
Enrollment criteria for the inclusion of participants in the primary study included: (1) no prior history of SARS-CoV-2 infection; (2) no known allergic reactions to the vaccine ingredients or history of Ig or blood product administration in the past 4 months; and (3) no history of medical conditions that may affect the vaccine's effectiveness or safety, such as neurologic disorders or acute febrile disease, as well as acute onset and uncontrolled severe chronic diseases. Based on the above criteria, 61 participants from Xiamen Boson Biotech Co Ltd, Fujian, China, were enrolled in the study.
All participants were administered 2 intramuscular doses of the CoronaVac vaccine (0.5 mL; Sinovac Life Sciences, Beijing, China) on days 0 and 28. Blood samples were collected 0, 7, 14, 21, 28, 35, 42, 49, 56, 130, and 160 days after vaccination to measure the levels of anti-S neutralizing antibodies (hereafter referred to as neutralizing antibodies), total anti-RBD antibodies (hereafter referred to as total antibodies), and anti-RBD IgG antibodies.
The study was approved by the Institutional Ethics Committee of Zhongshan Hospital, Xiamen University, Xiamen, China, and was conducted in accordance with all applicable regulatory requirements, including the Declaration of Helsinki. All participants signed a written informed consent form prior to enrollment.
Serum Sampling and Antibody Detection
Approximately 3 mL of blood was collected after 8 hours of fasting and sent for analysis within 6 hours. Separated serum samples were tested by chemiluminescence microparticle immunoassay (Xiamen Innovax Biotech Co Ltd) using reagent-matching chemiluminescence immune detection. The neutralizing antibodies were detected by a competitive assay, where they competed with biotinylated 2019-CoV–specific antibodies for binding to the acridine ester–labeled spike protein to form “biotinylated 2019-nCoV-specific antibody–acridine ester spike protein” complexes. The addition of streptavidin-coated microparticles resulted in the formation of larger complexes via interactions between biotin and streptavidin. The resultant chemiluminescence measured in relative light units (RLUs) was generated from complexes that contained the biotinylated 2019-CoV–specific antibodies, and consequently the concentration of the competing neutralizing antibodies in the samples was inversely proportional to the detected RLUs. Neutralizing antibody titers in the samples were calculated using a standard curve. Total antibodies were detected by the double-antigen sandwich method. The double-antigen sandwich method was performed by binding anti–SARS-CoV-2 antibodies in samples to magnetic particles coated with SARS-CoV-2 recombinant antigen. SARS-CoV-2 recombinant antigen-labeled acridine ester was added to form the “SARS-CoV-2 recombinant antigen-coated magnetic particle–anti-SARS-CoV-2 antibodies–SARS-CoV-2 antigen-labeled acridine ester” complex. Then, the resulting chemiluminescence reaction signal was measured, where the level of total antibodies was proportional to the RLUs detected, and it was recorded as the signal-to-cutoff ratio (S/CO; RLU of samples to be tested/cutoff). Chemiluminescence particle immunoassay was employed to detect IgG levels in the samples, which was recorded as S/CO.
Values are expressed as medians (25th–75th percentiles) for continuous variables. Repeated-measures analysis of variance was applied to explore differences in antibody titers at different time points. A multilevel model with a random intercept and random slope was used to fit the trajectory of the neutralization titers. The half-lives of the 3 antibody titers in all participants during the time interval of 160 days were calculated by the same multilevel model using the lme4 package in R version 4.1.2. Spearman correlation analysis was used to analyze the correlation between the levels of neutralizing antibodies and that of other antibodies. The area under the receiver operating characteristic curve (ROC-AUC) for total antibody and anti-RBD IgG levels to predict the seropositivity of anti-S neutralizing antibody was calculated, and the cutoff levels for the same were determined from the ROC. IBM SPSS 20 (SPSS Inc, Chicago, Illinois) and MedCalc version 19.4 (MedCalc Software, Ostend, Belgium) were used for statistical analysis. GraphPad Prism (version 5.0; GraphPad Software, San Diego, California) and R software were used to visualize the results.
Clinical Characteristics of 61 Individuals Administered 2 Intramuscular Doses of the CoronaVac Vaccine
A total of 61 participants within 160 days of vaccination were included in this study, 44 women (72%; median age, 36 years) and 17 men (28%; median age, 37 years). There was no significant difference in age distribution between men and women (P = .35; Table 1). At the time of vaccination, none of the participants had any of the following 10 symptoms of COVID-19: fever, cough, fatigue, sore throat, runny nose, diarrhea, muscle aches, shortness of breath, or loss of or change to sense of smell and taste.
Response and Duration of Anti–SARS-CoV-2 Antibodies After Vaccination
We determined the levels of neutralizing antibodies, total antibodies, and anti-RBD IgG antibodies in vaccinated participants at different times during a 160-day period. The antibody levels were significantly different at each time point for all 3 antibodies (P < .001; Table 2). The neutralizing antibody response was minimal after the first dose, and a rise from 2.30 IU/mL (interquartile range [IQR], 2.30–2.30 IU/mL) at day 7 to 2.30 IU/mL (IQR, 2.30–17.83 IU/mL) at day 28 was observed. However, a rapid increase to 106.95 IU/mL (IQR, 39.10–208.73 IU/mL) 1 week after administration of the second dose (day 35), and a subsequent peak of 120.75 IU/mL (IQR, 46.58–355.93 IU/mL) at day 42, followed by a drop to 19.55 IU/mL (IQR, 11.03–35.08 IU/mL) at day 160 was observed (Figure 1, A). The decay of the neutralizing antibody levels was measured using a multilevel model with a random intercept and random slope. The half-life of the neutralizing antibodies was determined to be 48.69 days (95% CI, 42.76–56.53 days; Figure 1, B).
The response and duration of the anti-RBD IgG and total antibodies were similar to those of the neutralizing antibodies (Table 2). The total antibody level was about 0.04 (0.03–0.65) S/CO in the first week after vaccination, but it soared to 138.47 (37.43–249.05) S/CO by day 35 before finally dropping to 8.86 (3.45–25.21) S/CO on day 160 (Figure 1, C). The half-life of the total antibodies was found to be 28.02 days (95% CI, 24.83–32.16 days; Figure 1, D). The anti-RBD IgG antibody levels marginally increased from 0.10 (0.07–0.18) S/CO at day 7 to 1.94 (1.05–4.80) S/CO at day 28. After administration of the second dose, the levels rose rapidly to peak at 14.38 (11.88–17.61) S/CO at day 42, and they subsequently plateaued from days 42 to 56 before declining to 1.61 (0.88–2.50) S/CO by day 160 (Figure 1, E). The half-life of the IgG antibodies was found to be 37.67 days (95% CI, 35.16–40.56 days; Figure 1, F).
The Correlation of Neutralizing Antibody Levels With Other Antibody Levels
Spearman correlation analysis was conducted to correlate neutralizing antibody levels with those of total and anti-RBD IgG antibody levels. An association was seen between the neutralizing and total antibody levels (r = 0.759; P < .001; Figure 2, A), and a stronger correlation was observed between the neutralizing and anti-RBD IgG antibody levels (r = 0.894; P < .001; Figure 2, B).
As per the trends displayed by the 3 antibody levels, day 42 was taken as the cutoff point, and the period from days 0 to 42 was defined as the ascending phase of antibody levels. Similarly, the period from days 42 to 160 was defined as the descent phase. Subsequently, the correlation between neutralizing and the other 2 antibody levels in different periods was observed (Table 3). The correlation of the neutralizing antibody levels with the anti-RBD IgG antibody levels was stronger than that with the total antibody levels in both ascending and descending phases, which was consistent with the overall analysis results. In the ascending phase, the correlation coefficient of the neutralizing antibody levels with the total antibody levels was 0.634 (P < .001) and that with anti-RBD IgG antibody levels was 0.839 (P < .001). In the descent phase, the correlation coefficient of the neutralizing antibody levels with total antibody levels was 0.651 (P < .001) and that with anti-RBD IgG antibody levels was 0.777 (P < .001).
In different groups classified based on age and sex, the neutralizing antibody levels were correlated better with the anti-RBD IgG antibody levels than with the total antibody levels (Table 3). The 2 correlation coefficients were relatively close only in men aged 31 to 40 years. Between age groups, the neutralizing antibody level was best correlated with total antibody levels in the participants aged 31 to 40 years (r = 0.856, P < .001) and least correlated in those older than 41 years (r = 0.688, P < .001). In contrast, the neutralizing antibody level was best correlated with anti-RBD IgG antibody levels in participants older than 41 years (r = 0.915, P < .001) and least correlated in those between 31 and 40 years (r = 0.885, P < .001). Male participants demonstrated a higher correlation between neutralizing and total antibody levels than female participants, which was contrary to the general trend in results obtained by correlation analysis of the neutralizing and anti-RBD IgG antibody levels.
ROC Analysis for Total and Anti-RBD IgG Antibody Levels for Prediction of Seropositivity for Neutralizing Antibodies
Using ROC curve analysis, a cutoff of 56.56 S/CO for total antibody levels was found to have a sensitivity of 73.0% and a specificity of 91.5% (AUC, 0.881; 95% CI, 0.853–0.906; P < .001) for the prediction of neutralizing antibody seropositivity (Figure 3, A; Table 4). Additionally, a cutoff of 9.95 S/CO for anti-RBD IgG antibody levels had a sensitivity of 84.0% and a specificity of 86.3% (AUC, 0.937; 95% CI, 0.919–0.956; P < .001) for the prediction of neutralizing antibody seropositivity (Figure 3, B; Table 4).
Subsequently, combined predictors were obtained by binary logistic analysis of total and anti-RBD IgG antibody levels for the prediction of neutralizing antibody seropositivity. ROC analysis for the joint prediction of seropositivity of neutralizing antibodies was subsequently performed using these combined predictors. The cutoff for the combined predictors had a sensitivity of 85.0% and specificity of 88.5% (AUC, 0.943; 95% CI, 0.921–0.960; P < .001; Figure 3, C). The AUC-ROC of the combined predictors was higher than that predicted by the total antibody levels (P < .001) but not significantly different from that predicted by the anti-RBD IgG antibody levels (P = .10; data not shown).
Specific antibodies play a significant role in protective immunity against viral infections. A proper comprehension of the dynamic changes in antibodies produced by humoral reactions after vaccination will serve as the basis for the development of effective vaccination and detection strategies. The 61 participants in our study received 2 doses of the COVID-19 vaccine, and their serum antibody levels (anti-spike neutralizing antibodies, anti–spike-RBD total antibodies, and anti-spike-RBD IgG antibodies) were measured at 11 time points during 160 days. The dynamic variation trend of the 3 antibody levels was parabolic, with obvious upward and downward trends. An extremely low response in terms of serum concentrations of the 3 antibodies was observed in the 28 days following the receipt of the first vaccine dose. Between days 0 and 28, the median serum concentrations of neutralizing antibodies were likely at low levels at all 5 time points. The levels of total and anti-RBD IgG antibodies slowly increased in this duration. The serum concentrations of the 3 antibodies increased rapidly after administration of the second dose and peaked within 2 weeks. The levels of neutralizing and anti-RBD IgG antibodies reached their highest concentrations on day 42. The total antibody levels peaked on day 35, 1 week before the neutralizing and anti-RBD IgG antibodies. However, after attaining their peak values, the rapid decay of all 3 antibodies was particularly obvious. At day 160, the neutralizing antibody levels had decreased to 19.55 IU/mL, whereas the total and anti-RBD IgG antibody levels had decreased to 8.86 and 1.61 S/CO, respectively. The previously reported dynamic antibody response for the mRNA-1273 vaccine demonstrated a rapid increase in antibody levels after the second dose (day 29) and a decline over time after peaking, which is in concordance with our results.13 The dynamic response and duration of sustenance of the 3 anti–SARS-CoV-2 antibodies led us to infer that the immune response of the COVID-19 vaccine is significant, albeit with an obvious decline in antibody levels over time.
The serum levels of neutralizing antibodies are a key indicator for the evaluation of vaccine efficacy. The median level of neutralizing antibodies observed within 28 days of receiving the first dose was only 2.30 IU/mL among our participants, which is short of the 8.10 IU/mL predicted to prevent severe infection.2 However, neutralizing antibody levels reached 106.95 IU/mL within 1 week of administration of the second dose (day 35) and 120.75 IU/mL 2 weeks later (day 42), thus well exceeding the 54.00 IU/mL predicted to be required for 50% protection against infection.2 At the end of the observation period (day 160), the neutralizing antibody levels had dropped to 19.55 IU/mL, a level that is insufficient to provide 50% protection against infection but adequate to prevent severe infection. An infection of the latter kind would manifest as other seasonal diseases, such as influenza and seasonal coronavirus infection. These could result in reinfections approximately 1 year after the initial infection, but would likely be clinically mild.14,15 Accurate and efficient detection of human neutralizing antibody levels is essential to evaluate the antibody status of an individual (consequent to prior natural infections or vaccinations) to prevent SARS-CoV-2 infection by timely administration of booster doses.
For further evaluation of the decay in antibody levels, the half-lives of the 3 antibodies were calculated using a multilevel model with a random intercept and random slope. The half-life of the neutralizing antibodies was 48.69 days, which was lower than that reported for the mRNA-1273 vaccines (65 days) and much lower than the half-life of antibodies of convalescent individuals (240 days).2,13,16 The half-lives of the anti–S-RBD total and IgG antibodies were 28.02 and 37.67 days, respectively, which were similar to those of the other mRNA vaccines but still lower than those of convalescent individuals.13,16,17 The half-lives of the 3 antibodies generated against CoronaVac were thus not significantly different from those generated by the mRNA vaccine, but were significantly different from those of convalescent individuals.
Viral neutralization is thought to be mediated by antibody responses that target spike proteins, specifically those that target the spike-RBD, thereby preventing its interaction with ACE2. Studies have shown that the spike-RBD contains dominant neutralization epitopes and has strong immunogenicity, accounting for 90% of the viral neutralization activity by antibody-positive sera.18–20 On the basis of these results, we speculated about a possible significant correlation between anti–spike neutralizing antibody levels and anti–spike-RBD total and IgG antibody levels. The cohort of 61 participants during 160 days was analyzed to assess this correlation. Neutralizing antibody levels were found to have the strongest correlation with IgG antibody levels, as well as a significant correlation with total antibody levels. Neutralizing antibodies against different epitopes of the spike-RBD exert their effects via different mechanisms. Furthermore, the neutralizing antibodies that target the spike-RBD are mostly of the subclass IgG.21 For instance, C105 and CB6 from COVID-19 convalescent patients function by blocking the hACE2-RBD interaction.22,23 CR3022 from convalescent patients and EY6A from late-stage COVID-19 patients act by trapping the RBD in a less stable conformation, thereby leading to destabilization of the spike protein.24–26 This conclusively establishes that anti-RBD IgG antibodies are a crucial component of the neutralizing antibodies. As previously published, the anti–spike-RBD IgG antibody levels in patients with COVID-19 strongly correlate with the severity of symptoms. Higher titers of anti–spike-RBD IgG antibody levels in patients result in the manifestation of proportionately milder symptoms.27 Therefore, the estimation of anti–spike-RBD IgG antibodies in serum not only reflects acquired immunity to SARS-CoV-2 but may also serve as an indicator of the disease severity.
We assessed the sensitivity and specificity of the total antibody levels versus IgG antibody levels in an attempt to predict the seropositivity of neutralizing antibodies. One finding revealed that a neutralizing antibody level of approximately 54 IU/mL provides 50% protective neutralization,2 and consequently it was taken as the seropositivity threshold for these antibodies. ROC analysis revealed the high sensitivity and specificity of the 2 antibody levels for the prediction of seropositivity. The AUC after performing ROC analysis for anti–spike-RBD total IgG antibody levels for the prediction of seropositivity for neutralizing antibody revealed good results. The sensitivity and specificity of the 2 cutoff values of the ROC curves were also excellent. When the concentration of total antibodies reached 56.56 S/CO, a sensitivity of 73.0% and a specificity of 91.5% for the prediction of seropositivity for neutralizing antibodies were achieved. In contrast, a cutoff anti-RBD IgG antibody level of 9.95 S/CO resulted in a sensitivity of 84.0% and a specificity of 86.3% for the prediction of seropositivity for neutralizing antibodies. We subsequently used the quantitative data of these 2 antibody levels and the qualitative data of the neutralizing antibody to perform a binary logistic analysis to obtain combined predictors. The AUC-ROC of the combined predictor was 0.943, which was significantly different from that of the total antibody but not from that of the anti-RBD IgG. The cutoff for the combined predictors had a sensitivity of 85.0% and a specificity of 88.5%. These results indicate that IgG antibody levels and the combined predictors can be used as a reference for the prediction of the seropositivity for neutralizing antibodies, on account of the high sensitivity and specificity and excellent suitability and capability.
Our study has certain limitations that need to be addressed. First, our study cohort included a small sample size of 61 participants. Further, although our results for neutralizing antibodies are traceable to the First World Health Organization International Standard for anti–SARS-CoV-2 immunoglobulin, the differences between our results and those of neutralization assays using real and pseudo viruses are still unknown. Additionally, our study did not include convalescent patients as experimental subjects; therefore, we could not correlate neutralizing antibody levels and other anti–SARS-CoV-2 antibody levels in the sera of these patients.
In conclusion, our study shows that 2 doses of the vaccine result in a rapid rise in antibody levels that can provide substantial protection. Simultaneously, neutralizing and anti-RBD IgG antibody levels are strongly correlated, and consequently, anti-RBD IgG antibody levels can predict neutralizing antibody levels with excellent reliability. In practical application, therefore, anti-RBD IgG antibodies can be used as an alternative to neutralizing antibodies for timely and convenient assessment of immunity against SARS-CoV-2 to aid in the development of vaccination strategies.
Xue, Wang, Niu, and Liu contributed equally to this manuscript.
The authors have no relevant financial interest in the products or companies described in this article.
Supported by the National Natural Science Foundation of China (grant Nos. 81971147 and 81771312), and the Xiamen Science and Technology Planning Project (grant No. 3502Z20209032).