Refocus on Immunogenic Characteristics of Convalescent COVID-19 Challenged by Prototype SARS-CoV-2

Background: Mass basic and booster immunization programs effectively contained the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus, also known as COVID-19. However, the emerging Variants of Concern (VOCs) of COVID-19 evade the immune protection of the vaccine and increase the risk of reinfection. Methods: Serum antibodies of 384 COVID-19 cases recovered from SARS-CoV-2 infection were examined. Correlations between clinical symptoms and antibodies against VOCs were analyzed. Result: All 384 cases (aged 43, range 1–90) were from 15 cities of Guangdong, China. The specific IgA, IgG, and IgM antibodies could be detected within 4–6 weeks after infection. A broad cross-reaction between SARS-CoV-2 and Severe Acute Respiratory Syndrome Coronavirus, but not with Middle East Respiratory Syndrome Coronavirus was found. The titers of neutralization antibodies (NAbs) were significantly correlated with IgG (r = 0.667, p < 0.001), but showed poor neutralizing effects against VOCs. Age, fever, and hormone therapy were independent risk factors for NAbs titers reduction against VOCs. Conclusion: Humoral immunity antibodies from the original strain of COVID-19 showed weak neutralization effects against VOCs, and decreased neutralizing ability was associated with initial age, fever, and hormone therapy, which hindered the effects of the COVID-19 vaccine developed from the SARS-CoV-2 prototype virus.

COVID-19 first appeared in China in 2019, and the World Health Organization declared it a worldwide pandemic in early 2020. In the ensuing three years, the pandemic has caused irreversible destruction in global public health and caused great social and economic burdens [2]. As of October 2022, cumulative COVID-19 cases were over 618 million,

Patients' Information
In total, 384 COVID-19 convalescent hospitalized cases (309 moderate, 56 severe, and 19 critical cases) were collected from 21 hospitals in 15 cities of Guangdong province from January to February 2020. All the cases were laboratory-confirmed COVID-19 cases. Clinical data, including case demographics and date of onset, were retrieved from hospital records. The study was approved by the institutional review committee of the Guangdong provincial center for disease control and prevention. The case was defined according to the COVID-19 clinical guidelines for prevention and control (ninth edition).

Specimen Collection and Storage
According to the clinical diagnosis and treatment guidelines, 384 blood specimens were collected from COVID-19 cases. The specimens were collected and stored at 4 • C (Table S1) and transported to the Guangdong provincial center for disease control and prevention under the same conditions. All blood specimens were separated from serum on the day of collection. The evacuated blood were centrifuged at 3000 rpm/min for 5 min (Thermo Fisher Scientific, Dreieich, Germany), and the serum was transferred into new 2 mL cryogenic vials. All serum specimens were then stored at −80 • C and thermally inactivated at 56 • C for 30 min before assay.

Landscape Assay of Coronavirus by Enzyme-Linked Immunosorbent Assay
The S, N, and RBD proteins of SARS-CoV-2 and the S and N proteins of the other six human coronaviruses were from Sino Biological Inc. (Beijing, China). All proteins were suspended at 1 µg/mL in PBST (SARS-CoV-2 S protein was suspended at 2 µg/mL). The protein suspension was added to each well of the 96-well plate (100 µL/well) and incubated overnight at 4 • C. Then, plate wells were washed three times with 300 µL of PBST each time on the automatic plate washing machine (BioTek 405 TS, Winooski, VT, USA). Nonfat dry milk (10%) prepared in PBST as a blocking solution was added to the plates (200 µL/well) and incubated at 37 • C for 1 h. Plate wells were washed again (under the same conditions as before). The serum specimens diluted in nonfat dry milk prepared in PBST (100 µL/well, serum specimens were heat inactivated for 30 min at 56 • C and diluted at 1:100). The diluted specimens were incubated for 1 h at 37 • C, and then plate wells were washed for three times. The anti-human IgM-HRP or anti-human IgG-HRP was added to the plates (100 µL/well) and incubated at 37 • C for 1 h. Plate wells were washed again. The TMB substrate was added to each well (100 µL/well) and incubated for 15 min, followed by the addition of stopping solution (50 µL/well). The optical density (OD) of each well at 450 nm was measured on the enzyme-labeled instrument (BioTek Epoch, Winooski, VT, USA). The wells without the addition of serum served as a background control.
According to the analysis results of SPSS, all the values were subtracted from the blank value before the next comparison. The median of the negative controls for the same protein and the same antibody type was calculated, and then its standard deviations (SD) value was calculated using the median + 2SD as the cut-off value.

Statistical Analysis
The statistical analyses for the authentic virus neutralization assessments were performed using GraphPad Prism for calculation of mean value for each data point. Each specimen was tested in duplicate. The neutralization antibody (NAb) titers of the prototype virus and VOCs were log2-transformed prior to analysis, and compared by t and z test. The correlation between the NAb titers of the prototype virus and IgA, IgM, and IgG antibodies levels were measured using Spearman's rank correlation coefficient. For analyzing the factors affecting the NAb titers, we first conducted the univariate variance analyses of all the clinical characteristics to select the independent variables that significantly correlated with the change in the outcome measure. Then, the variables selected from the univariate variance analyses were included in the multivariate linear regression model. The level of statistical significance was set at 0.05.

Consistency of NAbs Titers with IgA/IgM/IgG
To assess the antibody response of cases infected with prototype SARS-CoV-2, we measured NAb levels by micro-neutralization assay and IgA/IgM/IgG antibody levels by ELISA assay. The distributions of NAbs titers and IgA, IgM, or IgG were plotted, and the trends of the curves of NAb titers were correlated with those of IgG (Figure 2A,D). The trends of IgA and IgM curves were similar ( Figure 2B,C). The Spearman correlation assay between NAb titers and IgA, IgM, and IgG showed that NAb titers were more correlated with IgG (r = 0.667, p < 0.001) than IgA (r = 0.415, p < 0.001) and IgM (r = 0.447, p < 0.001). . Figure 1. Cross-reactivity of antibodies with six other coronaviruses. The crossover rate was calculated using the actual number of serum specimens involved in the assay as the denominator and the number of positive specimens detected as the numerator.

Consistency of NAbs Titers with IgA/IgM/IgG
To assess the antibody response of cases infected with prototype SARS-CoV-2, we measured NAb levels by micro-neutralization assay and IgA/IgM/IgG antibody levels by ELISA assay. The distributions of NAbs titers and IgA, IgM, or IgG were plotted, and the trends of the curves of NAb titers were correlated with those of IgG (Figure 2A,D). The trends of IgA and IgM curves were similar ( Figure 2B,C). The Spearman correlation assay between NAb titers and IgA, IgM, and IgG showed that NAb titers were more correlated with IgG (r = 0.667, p < 0.001) than IgA (r = 0.415, p < 0.001) and IgM (r = 0.447, p < 0.001).  . Figure 1. Cross-reactivity of antibodies with six other coronaviruses. The crossover rate was calculated using the actual number of serum specimens involved in the assay as the denominator and the number of positive specimens detected as the numerator.

Consistency of NAbs Titers with IgA/IgM/IgG
To assess the antibody response of cases infected with prototype SARS-CoV-2, we measured NAb levels by micro-neutralization assay and IgA/IgM/IgG antibody levels by ELISA assay. The distributions of NAbs titers and IgA, IgM, or IgG were plotted, and the trends of the curves of NAb titers were correlated with those of IgG (Figure 2A,D). The trends of IgA and IgM curves were similar ( Figure 2B,C). The Spearman correlation assay between NAb titers and IgA, IgM, and IgG showed that NAb titers were more correlated with IgG (r = 0.667, p < 0.001) than IgA (r = 0.415, p < 0.001) and IgM (r = 0.447, p < 0.001).

The Decline of NAb Titers of VOCs
We evaluated the NAb titers of 36 serum specimens of COVID-19 convalescent cases against the prototype virus and four preventative VOCs. The results showed the NAb titers were significantly decreased against VOCs compared to the prototype virus ( Figure 3). The geometric mean titers (GMT) dropped from 58 against the prototype virus to 19 against Beta (2.05 fold, p < 0.001), 33 against Delta (0.76 fold, p = 0.015), 7 against Omicron BA.1 (7.29 fold, p < 0.001), and 5 against Omicron BA.2 (10.6 fold, p < 0.001). The most significant decrease of NAb titers was against Omicron VOCs. In addition, we detected negative neutralizing activity in 4 (4/36, 11.11%), 7 (

The Factors Affecting the NAb Titers
The logarithmic of NAb titers was used as the dependent variable, and univariate regression analysis was applied to each variable. The results showed that NAb titers in COVID-19 patients were significantly correlated (p < 0.05) with age, occupation, severe disease typing (highest clinical severity), sampling time, fever, whether myalgia was present, mode of oxygenation, whether a noninvasive ventilator was used, whether ICU was required, whether hormone therapy was used, body temperature, neutrophil count, and lymphocyte count (Table S3). Based on the significant correlation factors in the univariate analysis, we further developed a multiple linear regression model to further analyze their correlations. We found that the NAb titers were significantly correlated with age, febrile, and hormone therapy ( Table 2).

The Factors Affecting the NAb Titers
The logarithmic of NAb titers was used as the dependent variable, and univariate regression analysis was applied to each variable. The results showed that NAb titers in COVID-19 patients were significantly correlated (p < 0.05) with age, occupation, severe disease typing (highest clinical severity), sampling time, fever, whether myalgia was present, mode of oxygenation, whether a noninvasive ventilator was used, whether ICU was required, whether hormone therapy was used, body temperature, neutrophil count, and lymphocyte count (Table S3). Based on the significant correlation factors in the univariate analysis, we further developed a multiple linear regression model to further analyze their correlations. We found that the NAb titers were significantly correlated with age, febrile, and hormone therapy ( Table 2).
We further evaluated the factors affecting the decline of NAb titers, and the titers of Beta VOCs were an example. The results showed that the decrease rate of NAb was significantly correlated with age, fever, and hormone therapy (p < 0.05) ( Table 3), which were the same with factors affecting the NAb titers. The values in parentheses are converted from the median by a logarithm based on 2; p < 0.05 (two-sided) as statistically significant.

Conclusions
Antibody profiles of prototype SARS-CoV-2 infection were clarified in many archived studies [17][18][19]. Here, we showed the dynamic antibody profiles of IgA, IgM, and IgG in COVID-19 convalescent patients and found that NAbs were significantly correlated with IgA (r = 0.415, p < 0.001), IgM (r = 0.447, p < 0.001), and IgG (r = 0.667, p < 0.001). In particular, the strongest correlation with IgG indicated that IgG could be used as a substitute marker for NAb production [20].
Then, we tested the landscape cross-reactivity of other six coronaviruses which could cause human infection. The results showed a significant cross-reactivity between SARS-CoV-2 and SARS-CoV, but not with MERS-CoV. Meanwhile, SARS-CoV-2 could cross-react with the other four coronaviruses to variable degrees. Considering that SARS-CoV only temporarily circulated in 2003 to 2004 [21], it is unlikely that most patients were previously infected with SARS-CoV, and the significant cross-reactivity was due to the high sequence homology between SARS-CoV-2 and SARS-CoV (>90%) [19]. No obvious cross-reactivity was observed between SARS-CoV-2 and MERS-CoV, which was consistent with the results derived by Wang et al. [20]. MERS-CoV was predominantly endemic in Middle Eastern countries [22,23]. The genome similarity of SARS-CoV-2 and MERS-CoV was also lower than that with SARS-CoV [24]. Seasonal coronaviruses are common causes of colds, the seropositive rate within the population is generally high [25][26][27], and there are corresponding antibodies in many individuals [28]. Our results showed that positive serum for SARS-CoV-2 exhibits high seropositivity to a variety of seasonal coronaviruses, suggesting that antibodies to other coronaviruses are present in the serum of most COVID-19 convalescent patients. Other studies also reported that COVID-19 infection leads to increased antibody titers to seasonal coronaviruses [29][30][31]. Regardless, our study confirmed that SARS-CoV-2 has crossreactive antibodies with other coronaviruses, which was consistent with the conclusion of Woudenberg et al. [32]. It has been observed that the existing immune response against seasonal coronaviruses is protective against SARS-CoV-2 infection [33][34][35], but some studies have shown that this cross-reactivity may exacerbate the severity in COVID-19 patients [36]. Further studies are needed to confirm the effect of seasonal coronavirus infection on SARS-CoV-2 disease progression.
Compared with prototype SARS-CoV-2 strain, serum from COVID-19 convalescent patients showed a significant decrease in neutralization ability against aa variety of VOCs. This finding showed similar trends with the findings of other investigations in the serum of convalescent patients or healthy individuals who had been vaccinated [37][38][39][40][41]. In particular, both basic and booster vaccination with the first generation vaccine showed poor resistance to the present pandemic of Omicron VOCs, which highlight that a second generation vaccine effective against the prototype and VOCs should be implemented as soon as possible [42,43].
Furthermore, we would like to know whether the decrease of NAbs of convalescent COVID-19 patients was associated with any initial clinical symptoms. We found that age, fever, and hormone therapy were the independent risk factors for a dropdown of NAbs. Numerous studies have shown that age [44,45] and fever [46,47] were the risk factors for the development of COVID-19. The clinical therapy for severe COVID-19 using hormones is quite controversial. Some studies showed that glucocorticoids can reduce the mortality of COVID-19 [48], but others found that the efficacy of hormones was not significant and may even bring side effects. Thus, it was not recommended in clinics [49]. Referring to the latest protocol for the diagnosis and treatment of novel coronavirus pneumonia (Ninth Edition), "glucocorticoids" and "interleukin-6 (IL-6) inhibitors" can be used as appropriate for some severe and critical patients [50]. According to the present data, patients with severe COVID-19 were more likely to receive hormone therapy. Unfortunately, the decrease rate of NAbs among these patients was higher than others, which indicated a fast declining tendency of NAbs. Thus, reinfection or breakthrough infections were inevitable for those with higher NAbs when challenged with novel VOCs, e.g., Omicron variants.
In conclusion, we characterized the serum immunogenic profile of prototype SARS-CoV-2 infected COVID-19 patients and indicated a broad cross-reaction with other coronavirus which may hinder the antibody-based clinic diagnosis of COVID-19. The emerging VOCs, e.g., Omicron variants, decreased the immune NAbs evoked from prototype virus infection, and the declining tendency was associated with initial clinical symptoms, including age, fever, and hormone therapy. Given the continuous circulation of novel VOCs, the herd immunity the SARS-CoV-2 vaccine provided was weakening. Nevertheless, booster immunity with the second generation vaccine including prototype and VOCs should be implemented as soon as possible.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/vaccines11010123/s1, Table S1: Statistical information of demographic, epidemiological and clinical trial indicators of participants; Table S2: Cross-reactivity between SARS-CoV-2 and six other human coronaviruses. Table S3: Univariate variance analyses of all the general characteristics associated with antibody levels.

Institutional Review Board Statement:
The study was approved by the institutional review committee of the Guangdong provincial center for disease control and prevention.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Not applicable.