Rapid detection of neutralizing antibodies to SARS-CoV-2 variants in post-vaccination sera

Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study

Objective

Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT₅₀) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan.

Methods

We used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT₅₀ against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG).

Results

Among 123 participants aged 20-74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT₅₀ were 65.5 (51.8-82.8) for D614G, 34.3 (27.1-43.4) for Delta, 14.9 (12.2-18.0) for Omicron BA.1, and 12.9 (11.3-14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R ² with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R ² = 0.850 vs. 0.150) in a validation study with 20 independent samples.

Conclusion

In a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data.

Cross-Reactivity of IgG Antibodies and Virus Neutralization in mRNA-Vaccinated People Against Wild-Type SARS-CoV-2 and the Five Most Common SARS-CoV-2 Variants of Concern

The rapid development, approval, and production of vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in less than 1 year after the first reports of a new infectious disease was a real game changer, providing 80%–90% efficacy in preventing severe etiopathologies of the coronavirus disease 2019 (COVID-19). These vaccines induce an immune response against the SARS-CoV-2 spike (S) protein located on the surface of the virus particle. Antibodies (Abs) recognizing the S-protein can inhibit binding of the virus via the S-protein to the angiotensin-converting enzyme-2 (ACE-2) receptor expressed on different human cells, especially when these Abs bind to the interaction site, the so-called receptor-binding domain (RBD). We have expressed the RBDs of wild-type SARS-CoV-2 and five variants of concern (VOCs) to test the immune response in people before vaccination with mRNA vaccines BNT162b2 and mRNA-1273 and after up to three vaccinations using in-house ELISA and inhibition assays. The methods of both assays are provided. Both vaccines initiated similarly high IgG titers after two vaccinations against the wild-type and even two VOC-RBDs (alpha and delta) and strongly inhibited the corresponding RBD-ACE-2 binding. The IgG titers and inhibition of ACE-2 binding were lower for beta and gamma RBDs and much lower for omicron RBD. The third vaccination after 6 months strongly increased both the IgG titers and the neutralizing effect against all variants, especially for omicron, leading to 63% ± 13% neutralization potential. Importantly, neutralization linearly increased with the IgG titers.

Detecting SARS-CoV-2 neutralizing immunity: highlighting the potential of split nanoluciferase technology

The coronavirus disease 2019 (COVID-19) pandemic has progressed over 2 years since its onset causing significant health concerns all over the world and is currently curtailed by mass vaccination. Immunity acquired against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be following either infection or vaccination. However, one can never be sure whether the acquired immunity is adequate to protect the individual from subsequent infection because of three important factors: individual variations in humoral response dynamics, waning of protective antibodies over time, and the emergence of immune escape mutants. Therefore, a test that can accurately differentiate the protected from the vulnerable is the need of the hour. The plaque reduction neutralization assay is the conventional gold standard test for estimating the titers of neutralizing antibodies that confer protection. However, it has got several drawbacks, which hinder the practical application of this test for wide-scale usage. Hence, various tests have been developed to detect protective immunity against SARS-CoV-2 that directly or indirectly assess the presence of neutralizing antibodies to SARS-CoV-2 in a lower biosafety setting. In this review, the pros and cons of the currently available assays are elaborated in detail and special focus is put on the scope of the novel split nanoluciferase technology for detecting SARS-CoV-2 neutralizing antibodies.

A Faster, Novel Technique to Detect COVID-19 Neutralizing Antibodies

BACKGROUND The COVID-19 pandemic has spread globally in a short period of time. It is known that antibody (nAb) level can effectively predict vaccine efficacy, which leads to the exploration of vaccine trials for efficacy assessment. Thus, the current study aimed to develop a platform to quantify nAb levels faster, at lower cost, and with better efficiency. MATERIAL AND METHODS A total of 69 sera samples were collected for the research, 28 of which were from unvaccinated participants. The other 27 samples and the remaining 14 samples were from the participants who had received the first and second dose, respectively, of AZ vaccine 1 month before. With cPass assays (Genscript cPass nAb ELISA assay) used as a criterion standard and lateral flow immunoassay kit (Healgen Scientific - LFIA test kit) coupled with a spectrometer (LFIA+S) for checking each specimen, we aimed to detect the presence of neutralizing antibodies in sera and to confirm the relationship between the inhibition rate from cPass assays and the nAb index from the LFIA+S. RESULTS Data analysis of the research were taken from the certified ELISA and LFIA+S, which indicated a high consistency (Pearson's r =0.864; ICC=0.90138) between the 2 methods. CONCLUSIONS The dataset demonstrated that LFIA+S was affordable, had a strong correlation with results of the cPass nAbs detection kit, and has potential clinical applications, with an exclusive feature that allows non-experts to use it with ease. It is believed that the proposed platform can be promoted in the near future.

Immunological features that associate with the strength of antibody responses to BNT162b2 mRNA vaccine against SARS-CoV-2

Predictive clinical factors associated with favorable responses to BNT162b2 mRNA vaccine against SARS-CoV-2 have been reported in some studies; however, there is a subgroup with low antibodytiters without well-known clinical factors reducing antibody responses. To clarify the immunological backgrounds that underlie the difference in antibody responses, we analyzed peripheral blood mononuclear cells (PBMCs) of each 20 individuals with a high anti-SARS-CoV-2 antibody titer and a low antibody titer out of 1774 healthcare workers who received BNT162b2 mRNA vaccine. A higher percentage of B cells before vaccination was associated with a higher antibody titer. Among B cells, naïve and transitional B cell frequencies were positively correlated with a higher antibody titer, whereas the frequencies of late memory B cells and plasmablasts were associated with a lower antibody titer. Fold change in the frequency of activated CD8+ T cells upon vaccination was also correlated with high antibody titers.

The Effects of COVID-19 First Waves in Italy: An Answer Through a Retrospective Analysis of Mortality

Background

Despite the available evidence on its severity, COVID-19 has often been compared with seasonal flu by some conspirators and even scientists. Various public discussions arose about the noncausal correlation between COVID-19 and the observed deaths during the pandemic period in Italy.

Objective

This paper aimed to search for endogenous reasons for the mortality increase recorded in Italy during 2020 to test this controversial hypothesis. Furthermore, we provide a framework for epidemiological analyses of time series.

Methods

We analyzed deaths by age, sex, region, and cause of death in Italy from 2011 to 2019. Ordinary least squares (OLS) linear regression analyses and autoregressive integrated moving average (ARIMA) were used to predict the best value for 2020. A Grubbs 1-sided test was used to assess the significance of the difference between predicted and observed 2020 deaths/mortality. Finally, a 1-sample t test was used to compare the population of regional excess deaths to a null mean. The relationship between mortality and predictive variables was assessed using OLS multiple regression models. Since there is no uniform opinion on multicomparison adjustment and false negatives imply great epidemiological risk, the less-conservative Siegel approach and more-conservative Holm-Bonferroni approach were employed. By doing so, we provided the reader with the means to carry out an independent analysis.

Results

Both ARIMA and OLS linear regression models predicted the number of deaths in Italy during 2020 to be between 640,000 and 660,000 (range of 95% CIs: 620,000-695,000) against the observed value of above 750,000. We found strong evidence supporting that the death increase in all regions (average excess=12.2%) was not due to chance (t₂₁=7.2; adjusted P<.001). Male and female national mortality excesses were 18.4% (P<.001; adjusted P=.006) and 14.1% (P=.005; adjusted P=.12), respectively. However, we found limited significance when comparing male and female mortality residuals’ using the Mann-Whitney U test (P=.27; adjusted P=.99). Finally, mortality was strongly and positively correlated with latitude (R=0.82; adjusted P<.001). In this regard, the significance of the mortality increases during 2020 varied greatly from region to region. Lombardy recorded the highest mortality increase (38% for men, adjusted P<.001; 31% for women, P<.001; adjusted P=.006).

Conclusions

Our findings support the absence of historical endogenous reasons capable of justifying the mortality increase observed in Italy during 2020. Together with the current knowledge on SARS-CoV-2, these results provide decisive evidence on the devastating impact of COVID-19. We suggest that this research be leveraged by government, health, and information authorities to furnish proof against conspiracy hypotheses that minimize COVID-19–related risks. Finally, given the marked concordance between ARIMA and OLS regression, we suggest that these models be exploited for public health surveillance. Specifically, meaningful information can be deduced by comparing predicted and observed epidemiological trends.

Persistence of Robust Humoral Immune Response in Coronavirus Disease 2019 Convalescent Individuals Over 12 Months After Infection

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection elicits varying degrees of protective immunity conferred by neutralizing antibodies (nAbs). In this study, we report the persistence of nAb responses over 12 months after infection despite their decreasing trend noticed from 6 months.

Methods

The study included sera from 497 individuals who had been infected with SARS-CoV-2 between January and August 2020. Samples were collected at 6 and 12 months after onset. The titers of immunoglobulin (Ig)G to the viral nucleocapsid protein (NP) and receptor-binding domain (RBD) of the spike protein were measured by chemiluminescence enzyme immunoassay. The nAb titer was determined using lentivirus-based pseudovirus or authentic virus.

Results

Antibody titers of NP-IgG, RBD-IgG, and nAbs were higher in severe and moderate cases than in mild cases at 12 months after onset. Although the nAb levels were likely to confer adequate protection against wild-type viral infection, the neutralization activity to recently circulating variants in some of the mild cases (~30%) was undermined, implying the susceptibility to reinfection with the variants of concerns (VOCs).

Conclusions

Coronavirus disease 2019 convalescent individuals have robust humoral immunity even at 12 months after infection albeit that the medical history and background of patients could affect the function and dynamics of antibody response to the VOCs.

Antibody titers against the Alpha, Beta, Gamma, and Delta variants of SARS-CoV-2 induced by BNT162b2 vaccination measured using automated chemiluminescent enzyme immunoassay

Background

Levels of 50% neutralizing titer (NT50) reflect the a vaccine-induced humoral immunity after the vaccination against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Measurements of NT50 are difficult to implement in large quantities. A high-throughput laboratory test is expected for determining the level of herd immunity against SARS-CoV-2.

Methods

We analyzed samples from 168 Japanese healthcare workers who had completed two doses of the BNT162b2 vaccine. We analyzed immunoglobulin G (IgG) index values against spike protein (SP) using automated chemiluminescent enzyme immunoassay system AIA-CL and analyzed the background factors affecting antibody titer. SP IgG index was compared with 50% neutralization titers.

Results

The median SP IgG index values of the subjects (mean age = 43 years; 75% female) were 0.1, 1.35, 60.80, and 97.35 before and at 2, 4, and 6 weeks after the first dose, respectively. At 4 and 6 weeks after the first dose, SP IgG titers were found to have positive correlation with NT50 titer (r = 0.7535 in 4 weeks; r = 0.4376 in 6 weeks). Proportions of the SP IgG index values against the Alpha, Beta, Gamma, and Delta variants compared with the original strain were 2.029, 0.544, 1.017, and 0.6096 respectively. Older age was associated with lower SP IgG titer index 6 weeks after the first dose.

Conclusions

SP IgG index values were rised at 3 weeks after two doses of BNT162b2 vaccination and have positive correlation with NT50. SP IgG index values were lower in the older individuals and against Beta and Delta strain.

Age and Smoking Predict Antibody Titres at 3 Months after the Second Dose of the BNT162b2 COVID-19 Vaccine

Objective: We aimed to determine antibody (Ab) titres 3 months after the second dose of the BNT162b2 coronavirus disease-2019 (COVID-19) vaccine and to explore clinical variables predicting these titres in Japan. Methods: We enrolled 378 healthcare workers (255 women, 123 men) whose blood samples were collected 91 ± 15 days after the second of two inoculations of the BNT162b2 COVID-19 mRNA vaccine (Pfizer/BioNTech) given 3 weeks apart. Medical histories and demographic characteristics were recorded using a structured self-reported questionnaire. The relationships between Ab titres and these factors were analysed. Results: Median age (interquartile range (IQR)) of the participants was 44 (32–54) years. Median Ab titre (IQR) against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike antigen was 764 (423–1140) U/mL. Older participants had significantly lower Ab titres; median (IQR) Ab titres were 942 (675–1390) and 1095 (741–1613) U/mL in men and women in their 20s, respectively, but 490 (297–571) and 519 (285–761) U/mL in men and women in their 60–70s, respectively. In the age-adjusted analysis, the only risk factors for lower Ab titres were male sex and smoking. However, the sex difference may have arisen from the sex difference in smoking rate. Moreover, Ab titres were significantly lower in current smokers than in ex-smokers. Conclusions: The most important factors associated with low Ab titres were age and smoking habit. In particular, current smoking status caused lower Ab titres, and smoking cessation before vaccination may improve the individual efficacy of the BNT162b2 vaccine.