Since late 2019, COVID-19, the disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused more than 392 million infections and 5.7 million deaths. Among SARS-CoV-2 infected patients in general, 81% showed mild to moderate symptoms, 14% had severe symptoms, and 5% had critical symptoms, with a case-fatality rate of 2.3%. To February of 2022, approximately 4.8 billion people have been vaccinated; however, more than 1 million cases of infection are recorded daily. It is unknown why the manifestation of COVID-19 is heterogeneous (that is, differs from patient to patient), and many studies have highlighted the role of the patient's underlying conditions and host immune factors, such as the generation of neutralizing antibodies and T cells in disease severity. However, whether there are other host factors or immune factors is not entirely clear.
Neutralizing antibodies (NAbs) play crucial roles in controlling and clearing virus infections, such as influenza, smallpox, and polio.[3–7] NAbs elicited by human coronaviruses, including SARS-CoV, Middle East respiratory syndrome coronavirus, and seasonal coronaviruses, have been shown to provide protection against infection.[8,9] However, in the case of seasonal coronaviruses, the protection of neutralizing antibodies is incomplete and disappears quickly over time. Neutralizing antibodies against SARS-CoV-2, which block the binding of the virus to its host receptor angiotensin-converting enzyme 2,[11,12] can be detected from day 4 to 6 and peak from day 10 to 15 after disease onset; 94% (165 of 175) of patients recovered from COVID-19 showed a significantly higher level of NAbs at the time of discharge compared with uninfected people. However, studies have indicated that the NAb titers of COVID-19 patients are extremely variable.[13,14] At the time of discharge, NAbs were found to be below the detectable level in some patients, whereas other patients showed higher NAb titers than the 50% inhibitory dose (ID50) level of 15,989. The fact that all patients recovered despite highly variable NAb titers at discharge suggests that NAbs are not the unique determining factor of COVID-19 recovery. Furthermore, several studies have reported that some COVID-19 vaccinations elicit low levels of neutralizing antibodies.[15,16] However, vaccinations have been proven to prevent symptoms and severity post SARS-CoV-2 infection, and vaccines can provide protection from new variants at a lower level than ancestral strains.[17,18] Considering these results together, we suggest that other immune mechanisms are involved in providing broad protection against SARS-CoV-2 infection.
Several studies have shown that NAbs decline rapidly and even disappear, which is associated with a decrease in systemic anti-RBD IgA antibody levels.[19,20] A study of infected healthcare workers demonstrated that NAbs substantially decrease at 3 months after disease onset. Given the short duration of NAbs and the scarcity of reported cases of re-infection, it is supposed that, in addition to neutralization, other non-neutralizing antibody-dependent effectors may contribute to the long-term protection against SARS-CoV-2 infection, such as antibody-dependent phagocytosis (ADCP), antibody-dependent cytotoxicity (ADCC), and complement-dependent cytotoxicity. ADCC is mediated by NK cells that directly bind to the antibodies through Fc gamma receptors (FcγR) on the infected cell surface, leading to signaling cascades with the release of perforin/granzymes as well as the expression of antiviral mediators, such as IFN-γ and TNF-α. ADCC response has been reported to significantly inhibit the replication of human immunodeficiency virus, and a higher ADCC response is associated with slower disease progression.[21,22] The same antiviral effect of ADCC was found with influenza, Ebola, herpesvirus, and coronavirus 229E.[23–26] For SARS-CoV-2, RBD-specific antibodies from convalescent serum and nasal wash were found to mediate ADCP by crosslinking with the Fc receptor (FcR). However, the link between immunopathology and ADCC during acute SARS-CoV-2 infection has not been reported. Thus, a general understanding of whether ADCC responses are evoked by SARS-CoV-2 infection and how the ADCC response balances protective and potential pathogenic roles against SARS-CoV-2 is critically needed. Therefore, in this study, we compared the NK cell-mediated ADCC response of acute SARS-CoV-2 infected patients and recovery patients and determined the timing of initiation and duration of ADCC response. In addition, the correlation between ADCC responses and disease progression was analyzed to identify the protective function of the ADCC response against SARS-CoV-2 infection.
Material and methods
The study was approved and supervised by the First Affiliated Hospital of Guangzhou Medical University (GMUH) Ethics Committee (No. 2020-51).
Nineteen acute COVID-19 patients at the First Affiliated Hospital of Guangzhou Medical University from January to February, 2020 and 55 recovery COVID-19 patients at the Second Peoples Hospital of Changde City from February, 2020 to February, 2021 were recruited in this study. Among 19 acute patients, longitudinal plasma samples from 12 acute COVID-19 patients were analyzed; six patients with regressing radiological scores and six with no improvements in imaging scores were further divided into recovery (AR) and severe (AS) groups, respectively. Among 55 recovery COVID-19 patients, the plasma of 44 COVID-19 patients was collected at approximately 2 and 12 months after disease onset. The severe cases were transferred from other hospitals to the intensive care unit (ICU) of GMUH when symptoms became severe or critical; on admission, most of these patients were at ∼d10 of disease onset. Viral RNA levels were measured daily from throat swabs, sputum, urine, and serum using real-time RT-PCR. Blood was drawn for one or more tests at 3 to 4 days intervals, and symptoms were closely monitored.
Enzyme-linked immunosorbent assay (ELISA)
To evaluate the specific IgG in the plasma of COVID-19 patients, direct ELISA was conducted against SARS-CoV-2 S protein RBD domain and N protein, respectively. Plasma samples at a dilution of 1:100 were tested using commercial ELISA kits (Darui Biotechnology, Guangzhou, China), following a protocol provided by the manufacturer. Plasma from a healthy donor and washing buffer were used as the negative and blank controls, respectively. The absorbance was measured at 450 nm. The data were analyzed as a ratio of OD450/cut-off value, and a ratio >1 was defined as positive.
Focus reduction neutralization test (FRNT)
SARS-CoV-2 FRNT was performed in a BSL-3 laboratory, as described previously. Vero E6 cells were first seeded in 96-well plates and cultured to 95% to 100% confluency. Plasma samples were serially diluted in DMEM and mixed with an equal volume of medium containing 150 to 200 SARS-CoV-2 PFU/well. Following incubation at 37°C for 1 hour, aliquots of pre-mixed virus and plasma were added to cultures of Vero E6 cells in 96-well plates and incubated at 37°C in 5% CO2 for 1 hour. Plates were then overlaid with 1.6% carboxymethylcellulose. After 24 hours, the cells were fixed with 4% paraformaldehyde and permeabilized with 0.2% Triton X-100. The virus was then detected with rabbit anti-SARS-CoV-2 nucleocapsid protein polyclonal antibody at 1:10000 dilution (40143-T62, Sino Biological) followed by HRP-labeled goat anti-rabbit secondary antibody at 1:1500 dilution (111-035-144, Jackson). The foci were visualized using TrueBlue reagent and counted using an ELISPOT reader (CTL S6 Ultra). For each sample, an FRNT 50 value was calculated as the serum dilution resulting in a 50% reduction in foci using the formula.
ADCC NK cell activation assay
A newly described virus-specific ADCC assay was performed to study the COVID-19 plasma samples. In brief, 96-well plates were coated with SARS-CoV-2 N protein or S protein RBD domain. Plasma samples from acute and recovery COVID-19 patients at a 1:10 dilution were incubated with coated N protein and S protein RBD domains for 2 hours at 37°C. After washing six times to remove unbound antibodies, 4 × 105 peripheral blood mononuclear cells (PBMCs) from a healthy donor were added and incubated at 37°C in 5% CO2 for 5 hours. In the meantime, anti-human CD107a allophycocyanin antibody at 1:100 dilution (H4A3, 560664; Pharmingen), 5 μg·mL−1 brefeldin (BD Bioscience) and 5 μg·mL−1 monensin (BD Bioscience) were added to each well. PBMC were then stained with surface antibodies of anti-human CD3 FITC (FIT3a; BD Bioscience) and anti-human CD56 PE-Cy7 (B159; BD Bioscience) for 30 minutes at 4°C in the dark. After fixation and permeabilization with Cytofix/CytopermTM solution (BD Bioscience) for 15 minutes at 4°C, the cells were further incubated with anti-human IFN-γ PE (B27; BD Bioscience) at 4°C for 30 minutes. The acquisition was performed with a Verse flow cytometer (BD Bioscience) with 1 × 105 events. Gating was performed using FlowJo X software, and the percentage of IFN-γ and CD107a positive NK cells was measured.
Normally distributed continuous variables were presented as means ± standard deviation and non-normally distributed continuous variables as medians (interquartile ranges; IQR). Continuous variables were compared by the Student's t test or the paired t test. To examine the association between two biomarkers, Y and Z, for a set of clinical data where measurements are grouped by patient, we fit the following linear mixed-effect model to the data:
where represents the predicted biomarker level for patient i at time t (note that each patient may have measurements at different time points); a and bi are fixed and patient-specific random effects of the intercept; and bi follows a normal distribution with a zero mean, that is, ; c is the coefficient of the other biomarker ; is the observation error, which follows .The term in the model is the null hypothesis. The alternative hypothesis assumes , that is, no correlation between Y and Z, which yields the alternative model:
We performed a likelihood ratio test to examine whether we should accept or reject the null hypothesis (ie, accept/reject if Y and Z have a statistically significant association) based on a confidence level of 95%.
The analysis was performed in R (version 4.0.2) using the package “lme4.”
Dynamic ADCC response during SARS-CoV-2 infection and after recovery from both anti-RBD and anti-N antibodies
We performed an ADCC assay based on anti-RBD and anti-N antibodies for corresponding samples. The goal of this step was to discern the kinetics of SARS-CoV-2 specific ADCC in COVID-19 patients during the acute infection phase and after recovery and to study the role of antibodies targeting the nucleocapsid (N); such antibodies were detected in nearly all COVID-19 patients, but it was not clear whether they were infection-induced immune products or play an anti-viral role. The expression of IFN-γ and CD107a by CD3–CD56+ NK cells and gating strategy are described in Figure 1A. Compared to the plasma of healthy donors and blank controls, COVID-19 plasma triggered the ADCC response detected by the expression of IFN-γ/CD107a in NK cells [Figure 1B]. Our data also showed that the ADCC response was derived from the antibodies against RBD and N protein, and 0.86% (95%CI 0.69%–1.03%) of IFN-γ+CD107a+ NK cells were induced by anti RBD antibodies, which was significantly higher than that of anti N antibodies (0.54%, 95%CI 0.44%–0.64%) [Figure 1C].
First, the kinetics of the ADCC response in acute and recovery COVID-19 patients was investigated. We found that patients started to show ADCC response with 0.36% (95%CI 0–0.74%) and 0.43% (0–1.16%) of IFN-γ+CD107a+ NK cells on admission induced by anti RBD and anti N protein respectively. ADCC response peaked at approximately 3 weeks after disease onset with 1.16% (95%CI 0.66%–1.66%) and 0.63% (0.39%–0.88%) of IFN-γ+CD107a+ NK cells induced by anti RBD and anti N protein respectively [Figure 2A]. The results showed that in acute patients anti RBD and anti N protein induced 0.86% (95%CI 0.70%–1.03%) and 0.55% (95%CI 0.46%–0.65%) of IFN-γ+CD107a+ NK cells respectively, which was significantly higher than those in recovery patients with 0.32% (95%CI 0.27%–0.37%) and 0.32% (95%CI 0.27%–0.36%) of IFN-γ+CD107a+ NK cells respectively, which is in agreement with the known kinetics of IgG antibodies against RBD and N protein.[30,31] Thus, we suspect that the ADCC response was robustly stimulated in patients with severe viral infection, as a response to the viral infection. To confirm this hypothesis, we analyzed the differences between asymptomatic and symptomatic recovery patients. The data showed that in symptomatic patients anti RBD and anti N protein antibodies induced 0.38% (95%CI 0.33%–0.43%) and 0.38% (95%CI 0.34%–0.43%) of IFN-γ+CD107a+ NK cells respectively, which was significantly higher than that in asymptomatic patients [Figure 2C]. We then analyzed the long-term profile of ADCC response in recovery of COVID-19 patients, and the results show that 59% of patients still presented with ADCC response induced by anti RBD antibodies at 12 months after disease onset. However, only 0.29% (95%CI 0.20%–0.38%) of IFN-γ+CD107a+ NK cells were detected, which was significantly lower than that at 2 months after disease onset [0.59% (95%CI 0.48%–0.71%)] [Figure 3].
ADCC was negatively associated with the age of patients but not correlated with disease severity
To investigate the role of NK cells in immune recovery in severe cases of COVID-19, the correlation between ADCC and disease progression was evaluated based on the ADCC results and the sequential organ failure assessment (SOFA) score of patients with acute COVID-19. No significant correlation was observed between ADCC and disease progression neither in AR group (R2 = 0.04, P = 0.457) nor AS group (R2 = 0.04, P = 0.558) of acute COVID-19, indicating that ADCC does not play a major role in reducing or evoking the severity of COVID-19 [Figure 4]. Interestingly, although we did not find a correlation between age and ADCC during the recovery phase (R2 = 0, P = 0.835), we found that the ADCC against RBD within acute infection was negatively correlated with the age of the patients (R2 = 0.42, P = 0.007) [Figure 5].
ADCC was significantly correlated with serum IgG titers of patients in the recovery but not acute phase of COVID-19
As ADCC is dependent on the antigen-binding antibodies, we aimed to determine whether more serum IgG antibodies against RBD or anti-N or more neutralizing antibodies indicate a high level of ADCC. The anti-RBD and anti-N IgG titers of all the acute and recovery patients were tested [Figure 6A and B]. ADCC was found to be correlated with anti-RBD IgG titers in patients recovering from COVID-19 (R2 = 0.33, P < 0.001, Figure 6D), whereas no correlation was observed in acute cases (R2 = 0.05, P = 0.123) [Figure 6C]. Furthermore, we also found that the ADCC response against RBD was not correlated with NAb titers, either in patients with acute infection (R2 = 0, P = 0.861) or those in recovery (R2 = 0.02, P = 0.285) [Figure 7], indicating that another type of antibody may contribute to the stimulation of ADCC in addition to neutralizing antibodies.
The ADCC response has been proven to contribute to antiviral effects and control virus replication in many viruses.[23–26] The role of the ADCC response in combating an emerging virus, namely SARS-CoV-2, remains unknown. Here, we characterized the ADCC response of COVID-19 infected patients in the acute and recovery phases to determine whether the ADCC response can play a role in combating COVID-19.
It is not surprising that neutralizing antibodies of S RBD can stimulate ADCC response, given that the RBD domain protrudes from the viral surface; and this observation is consistent with previous findings in studies of influenza A, in which antibodies and neutralizing antibodies against surface proteins HA and NA could also induce high ADCC.[25,28,32] SARS-CoV-2 N protein can elicit abundant IgG, IgM, and IgA antibodies. However, N protein is an abundantly and early expressed protein located in virions and infected cells; therefore, it is difficult for anti-N antibodies to identify infected cells that contain N within them, causing the ADCC effect. Thus, in theory, anti-N antibodies may only represent passive immune responsive reactions rather than active immune responses to combat SARS-CoV-2 infection. Similarly, in the case of antibodies targeting the nucleocapsid (NP) protein of influenza A virus, it is debatable whether anti-NP protein could provide some protection.[34,35] Interestingly, our data clearly show that anti-N antibodies have the potential to stimulate ADCC responses during and after SARS-CoV-2 infection. Whether this anti-N ADCC activity plays an important role in the protection against SARS-CoV-2 infection needs further investigation.
Several studies have highlighted the potential of the ADCC response to combat viral infection in severe COVID-19 patients. One study showed that CD57 positive NK cells responsible for the CD16 receptor-mediated signaling pathway were significantly increased in COVID-19 patients. As well, adaptive NK cells were significantly enriched in patients who died from the disease. Pinto et al. found that the monoclonal antibodies (S309 and S306) identified in a severe, acute case of SARS-CoV triggered ADCC in SARS-CoV-2 S protein-transfected cells and may potentially have contributed to viral control. However, in our view, ADCC probably functions more in patients with asymptomatic or mild COVID-19 whose NK cell frequency and function were not greatly influenced by SARS-CoV-2 infection. In patients with severe COVID-19 and having either a lower number of NK cells or dysfunctional NK cells, higher ADCC antibodies were observed; however, further study is warranted to determine how well these antibodies function. Another concern is that ADCC may amplify inflammation by activating NK cells. Higher levels of IgG found in patients admitted to the ICU or deceased patients raise the question of antibody-dependent enhancement of COVID-19. Wu et al. reported that plasma from severely infected elderly patients with a higher level of anti-spike IgG antibodies enhanced the entry of SARS-CoV-2 into cells in vitro. Similarly, Liu et al. found that transferring plasma from recovered monkeys enhanced lung lesions by Fc-mediated macrophage activation, which amplifies inflammation. Notwithstanding the result of these previous studies, our data indicate that ADCC is not correlated with disease severity (SOFA score), which is in agreement with another study showing that convalescent plasma collected from 5000 COVID-19 patients was shown to be safe and improved disease outcomes. Another interesting finding was that ADCC response was not correlated with total IgG titers against S protein RBD and N protein in patients with acute COVID-19, whereas ADCC in recovering patients showed a significant correlation with IgG titer. Moreover, the ADCC response did not correlate with the neutralizing antibody titer in acute cases. Taken together, these findings lead us to speculate that—in the acute phase—in addition to neutralizing antibodies and anti-RBD binding IgG antibodies, other factors could contribute to the activation of ADCC response in COVID-19. In the recovery phase, ADCC response was significantly correlated with anti-RBD IgG titer, indicating that ADCC may be protective against secondary infection.
Considering the long duration of ADCC, our results demonstrated that the plasma from recovery COVID-19 patients could still have considerable ADCC antibodies, even though the level of ADCC is significantly lower than that in the acute infection phase. ADCC response peaked at 3 weeks after disease onset and began to subside to a relatively lower level at approximately 2 months. Furthermore, we found that a lower level of ADCC remained detectable 12 months after disease onset. Importantly, neutralizing antibodies were not detected in some patients in recovery at approximately 2 and 12 months, but ADCC antibodies could still be detected at a relatively high level. Our data indicate that ADCC could function as the first defense against reinfection, especially in convalescing COVID-19 patients with lower NAb titers. In addition, we found that ADCC against the S protein RBD domain in acute cases was negatively correlated with age, suggesting that elderly individuals will have weaker ADCC defense upon re-encounter with SARS-CoV-2.
In conclusion, we found that antibodies from COVID-19 patients against the N protein and S protein RBD domains could stimulate high levels of ADCC response, which could last longer than 12 months at a relatively lower level in patients who have recovered from COVDI-19. Our findings suggest that, in addition to T cell and neutralization responses, ADCC has the potential to provide protection against secondary SARS-CoV-2 infection.
Tingting Cui designed and performed the experiments and wrote the manuscript. Mingzhu Huang performed the experiments. Xiaoling Su and Zhengfang Lin assisted in performing the experiments. Jiaying Zhong and Xiaoyun Yang contributed to plasma samples preparation. Zhongfang Wang designed and coordinated the study and contributed to the interpretation of data and the final version of the manuscript. All authors revised the manuscript and approved the final manuscript.
Conflicts of Interest
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