Abstract
Objectives
During the recent wave of coronavirus disease 2019 (COVID-19) infections in China, most individuals have been vaccinated and exposed to the omicron variant. In the present study, two cohorts were observed in the vaccinated population: vaccinated individuals with symptoms (VIWS) and those without symptoms (VIWOS). Our study aimed to characterize the antibody response in two cohorts: VIWS and VIWOS.
Methods
A questionnaire survey was conducted in the community. Blood and saliva samples were collected from 124 individuals in the VIWS and VIWOS cohorts. Capture enzyme-linked immunosorbent assay (ELISA) was performed to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies.
Results
The questionnaire survey revealed that 30.0 % (302/1005) of individuals in the older adult group (≥65 years) experienced no symptoms, whereas the rate of individuals without symptoms in the younger group (<65 years) was 17.8 % (166/932). Nucleocapsid (N)-specific IgM (N-IgM) was detected in the blood samples at a rate of 69.2 % (54/78) in the VIWS cohort. The positivity rate for N-specific IgA (N-IgA) was 93.6 % (73/78). In addition, the positivity rates of spike (S)-specific IgA (S-IgA) and N-IgA detected in saliva samples were 42 % (21/50) and 54 % (27/50), respectively. Both N-IgA positivity and negativity were observed in the VIWOS cohort. The detection rate of N-IgM positivity was 57.1 % (12/21) in the N-IgA-positive group. In addition, 54.3 % (25/46) of the vaccinated individuals without symptoms were IgA-negative.
Conclusions
Our study indicates that substantial N-specific antibodies were induced during omicron infection and that testing for N-IgA in both blood and saliva may aid in the diagnosis of SARS-CoV-2 infection in vaccinated populations.
Keywords: Breakthrough infections, Diagnosis, IgA, IgM, Nucleocapsid, Severe acute respiratory syndrome coronavirus 2
1. Introduction
The emergence of the omicron variant has led to extreme rates of coronavirus disease 2019 (COVID-19) occurrence worldwide [1]. Omicron has been associated with a milder disease than that caused by previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains [[2], [3], [4]]. Individuals with omicron infection may present with symptoms such as fever, sore throat, fatigue, cough, body aches, runny nose, loss of taste or smell, nausea, and vomiting, or may be asymptomatic but test positive for viral nucleic acid [[5], [6], [7]]. Asymptomatic individuals have a viral load in the upper respiratory tract [8] and can unknowingly spread the virus.
Owing to the cancellation of the zero-COVID policy, SARS-CoV-2 omicron (BA5.2 and BF.7) spread rapidly throughout the population in mainland China within 1 month from early December 2022. This new outbreak resulted in a significant increase in the number of infected cases, with a seropositivity rate of up to 80 % [9]. However, a small number of individuals had no symptoms despite a confirmed history of exposure to SARS-CoV-2 (living with infected persons). This raises the question of whether they are truly asymptomatic or simply not infected.
Typically, viral shedding peaks at 5–6 d after the onset [8]. Therefore, antibody testing for SARS-CoV-2 has become increasingly important for tracking latent and asymptomatic infections [10,11]. Anti-spike (anti-S) and anti-nucleocapsid (anti-N) antibodies are produced during SARS-CoV-2 infection. However, anti-S antibodies have also been detected [[12], [13], [14], [15]]. The types of vaccines include messenger RNA (mRNA) vaccines, vector vaccines, protein subunit vaccines, and inactivated whole virus vaccines, which produce or contain the S protein. In addition, whole-virus inactivated vaccines can induce anti-N antibodies in vaccinees; but the level of anti-N Abs in vaccinees without infection is lower than that in infected individuals [[16], [17], [18], [19], [20]]. Anti-N IgG is commonly used to investigate past or current COVID-19 infections in vaccinated population [6,10,18]. Recently, anti-SARS-CoV-2 IgA has been used to diagnose breakthrough infections in vaccinees [11,21]. However, the anti-N antibody response in inactivated virus vaccinees with omicron infections is not well understood.
During this new omicron surge in China, two cohorts were observed in the vaccinated population: vaccinated individuals with symptoms (VIWS) and vaccinated individuals without symptoms (VIWOS). In this study, we characterized the antibody response in both cohorts, VIWS and VIWOS, in a community-based population, with a focus on the anti-N antibody response. Our results indicate that testing for N-IgA in both blood and saliva may aid in the diagnosis of SARS-CoV-2 infection in vaccinated populations, especially in inactivated vaccine-immunized populations.
2. Materials and methods
2.1. Study population and sampling
The study was conducted with the approval of the Human Ethics Committee of Guangzhou Eighth People's Hospital (202115202).
All individuals (n = 1937) enrolled in this study resided in one community (Jiahe Street, Guangzhou, China) during the SARS-CoV-2 outbreak in Guangzhou between early December 2022 and January 2023 (Fig. 1), regardless of age and vaccination status. The questionnaires were collected between February 2023 and March 2023. The two groups were categorized based on the presence or absence of the symptoms listed in the questionnaire (Supplementary Table 1) [[22], [23], [24]]. Owing to the high vaccination rate in the population, individuals who were not vaccinated were excluded from subsequent antibody testing. Therefore, two cohorts of vaccinated individuals with symptoms (VIWS, n = 78) and vaccinated individuals without symptoms (VIWOS, n = 46) were enrolled for antibody testing (Fig. 1). In the VIWOS cohort, exposure to omicron infection was confirmed by living with infected individuals. A total of 124 blood and 88 saliva samples from each of the two cohorts (Table 1) were collected between February and March 2023 after each participant provided written informed consent.
Fig. 1.
Study design of the VIWS and VIWOS cohorts for the detection of SARS-CoV-2 specific antibodies.
Table 1.
Demographics, symptoms, prior infections, and vaccine regimens of the VIWOS and VIWS cohorts.
| Characteristics | VIWOS cohort |
VIWS cohort |
p value |
|---|---|---|---|
| （n = 46） | （n = 78） | ||
| Age, years | |||
| Median(IQR) | 48.5(33.75–56.25) | 37.5（30.25–46.25） | 0.018 |
| Sex | |||
| Female | 17（37.0 %） | 49（62.8 %） | 0.005 |
| Male | 29（63.0 %） | 29（37.2 %） | |
| Symptoms | |||
| Fever | No | 61（78.2 %） | |
| Sore throat | No | 50（64.1 %） | |
| Fatigue | No | 46（59.0 %） | |
| Cough | No | 39（50.0 %） | |
| Body aches | No | 38（48.7 %） | |
| Runny nose | No | 28（35.9 %） | |
| Loss of taste or smell | No | 20（25.6 %） | |
| Nausea or vomiting | No | 11（14.1 %） | |
| Unknown | No | 7（9.0 %） | |
| Previous SARS-CoV-2 infection | |||
| No previous infection | 45（97.9 %） | 69（88.5 %） | 0.131 |
| Previous infection before this outbreak | 0 | 4（5.1 %） | 0.296 |
| Unknown | 1（2.1 %） | 5（6.4 %） | 0.529 |
| Vaccine | |||
| Inactived vaccine | 37（80.4 %） | 62（79.5 %） | 0.899 |
| Non-replicating vector vaccine | 5（10.9 %） | 4（5.1 %） | 0.405 |
| Protein subunit vaccine | 0 | 2（2.6 %） | 0.53 |
| Unknown | 4（8.7 %） | 10（12.8 %） | 0.684 |
| Days between last vaccination and blood collection | |||
| Median(IQR) | 441.5（145.3–497.8） | 439.5（384.0–509.0） | 0.426 |
VIWOS, vaccinated individuals without symptoms; VIWS, vaccinated individuals with symptoms.
Plasma samples were clarified, aliquoted, and stored at −80 °C until use. The saliva samples were added to an equal volume of diluent (1 % NP-40 and 0.5 % Trition-X-100 in phosphate-buffered saline [PBS]), mixed, and allowed to stand for 10 min. The mixtures were then centrifuged at 2500 rpm for 10 min, and the supernatants were collected and stored at −20 °C until use.
2.2. Detection of SARS-CoV-2 specific IgM, IgA, and IgG
IgM, IgA, and IgG against the S and N proteins of SARS-CoV-2 in blood and saliva samples were measured using capture enzyme-linked immunosorbent assay (ELISA) [25].
The recombinant S or N protein with a D7 tag at the C-terminus was captured in 96-well plates using a pre-coated D7-tag capture antibody [26]. A 1:100 or 1:4 dilution of the plasma or saliva antibody was used in the capture ELISA. All samples were tested in duplicates. Optical density (OD) at 450 nm was measured using a microplate reader spectrophotometer (Varioskan lux, ThermoFisher, USA). The threshold value was calculated from the OD value of the negative controls with the standard deviation (SD) in each microplate.
2.3. Statistical analysis
Statistical analyses were performed using IBM SPSS Statistics software (version 27.0; SPSS Inc., Chicago, IL, USA). Categorical variables were compared using the chi-square test (χ2) or Fisher's exact test. Continuous variables were analyzed using the Mann-Whitney U test. The OD values of the ELISA are expressed as mean values. Differences between the two groups were compared using the Mann–Whitney U test. p < 0.05 was considered statistically significant.
3. Results
3.1. Some individuals exhibited no symptoms during this new omicron outbreak
A survey was conducted in the Jiahe Street community in Guangzhou, China using a questionnaire applet, and information was collected from 1937 respondents (Fig. 1). Among individuals aged ≥65 years (n = 1005), 30.0 % (302/1005) had no symptoms of omicron infection. In the <65 years age group (n = 932), the rate of individuals with no symptoms was 17.8 % (166/932).
3.2. Comparison of IgM, IgA, and IgG antibodies detected in the VIWS and VIWOS cohorts
As described in the Materials and Methods section 2.1. The two cohorts, vaccinated individuals with symptoms (VIWS) and vaccinated individuals without symptoms (VIWOS), were grouped into a community-based population. In total, 124 blood samples were collected from the VIWS (n = 78) and VIWOS (n = 46) cohorts. Viral antigen capture ELISA was performed on 124 blood samples to detect IgM, IgA, and IgG antibodies directed against the S and N proteins of wild-type SARS-CoV-2 (Fig. 2A–C, Supplementary Tables 2–3).
Fig. 2.
Quantification of SARS-CoV-2 specific antibodies in blood using ELISA. The OD values and positive rates of IgM, IgA, and IgG in blood detected in the VIWS and VIWOS cohorts (A–C) and in the VIWOS with IgA positive and IgA negative (D–E). Plasma Ab at a 1:100 was used in the capture ELISA. All samples were assayed in duplicate. The threshold value was calculated from the OD value of the negative controls with SD in each microplate. The OD values of the ELISA were expressed as the mean value. Differences between two groups were compared using the Mann-Whitney U test. Statistical significance was set at p < 0.05. VIWS, vaccinated individuals with symptoms; VIWOS, vaccinated individuals without symptoms; ns, not significant; ****p < 0.0001.
S-specific IgM (S-IgM) was not detected in either the VIWOS (0/46) or the VIWS cohorts (0/78, Fig. 2A). In contrast, we detected IgM against the conserved N protein (N-IgM) in 69.2 % (54/78) of the individuals in the VIWS cohort. Notably, both S-IgA and N-IgA were detected in 15.4 % (12/78) and 93.6 % (73/78) of the patients in the VIWS cohort, respectively (Fig. 2B). As expected, all IgG antibodies detected in the VIWS cohort were positive for either S or N protein (Fig. 2C).
SARS-CoV-2 specific antibodies, IgM IgA, and IgG antibodies were also detected in the VIWOS cohort. However, the levels of the N-specific antibodies N-IgM, N-IgA, and N-IgG were notably lower than those in the VIWS cohort (p = 0.0001, Fig. 2A–C). For S-specific antibodies, the positive rate for S-IgG in the VIWOS cohort was 91.3 % (42/46); however, the level of S-IgG was lower than that in the VIWS cohort (p = 0.0001, Fig. 2C). Our data indicate that omicron infection induces substantial N-specific antibodies, as well as S-IgG, in a vaccinated population.
3.3. Comparison of IgM and IgG antibodies detected in the VIWOS with N-IgA-positive and -negative cohorts
The positivity rate for N-IgA was higher than that for N-IgM in the VIWS cohort (93.6 % [73/78] vs. 69.2 % [54/78], p < 0.001). The N-IgA level in the VIWS cohort was higher than that in the VIWOS cohort (p = 0.0001; Fig. 2B). We hypothesized that asymptomatic individuals may exist in the VIWOS cohort and be N-IgA-positive. Based on the N-IgA test results, the VIWOS cohort was further classified into two groups: IgA-positive (n = 21) and IgA-negative (n = 25) (Fig. 2D and E, Supplementary Table 3). In the N-IgA-positive group, the detection rate of N-IgM was 57.1 % (12/21), whereas that in the N-IgA-negative group the detection rate was 4.0 % (1/25) (Fig. 2D). Differences in N-IgG and S-IgG levels were also observed between the N-IgA positive and N-negative VIWOS groups (p = 0.0001, Fig. 2E). In addition, 54.3 % (25/46, Supplementary Table 3) of the vaccinated individuals without symptoms were IgA-negative.
3.4. Detection of specific IgA and IgG in saliva
SARS-CoV-2-specific IgA and IgG assays were performed on 88 saliva samples collected from 124 individuals (Fig. 3, Supplementary Tables 2–3). As shown in Fig. 3A, the positivity rates for S-IgA and N-IgA were 42 % (21/50) and 54 % (27/50), respectively, among individuals in the VIWS cohort. Additionally, S-IgA (13.2 %, 5/38) and N-IgA (21.5 %, 8/38) were detected in the VIWOS cohort, which was significantly different from the rates in the VIWS cohort (p = 0.07 for S-IgA and p = 0.02 for N-IgA). The positive rates for S-IgG and N-IgG were also higher in the VIWS cohort than those in the VIWOS cohort (Fig. 3B), especially for N-IgG (80 %, [40/50] vs. 34.2 %, [13/38], p < 0.001). A similar trend in the positive rates of IgG was observed between the two groups of the VIWOS cohort with IgA positivity and IgA negativity (Fig. 3C and D).
Fig. 3.
Quantification of SARS-CoV-2 specific antibodies in saliva using ELISA. The OD values and positive rates of IgA and IgG in saliva detected in the VIWS and VIWOS cohorts (A–B) and in the VIWOS with IgA positive and IgA negative (C–D). Saliva Ab at a 1:4 dilution was used in the capture ELISA. All samples were assayed in duplicate. The threshold value was calculated from the OD value of the negative controls with SD in each microplate. The OD values of the ELISA were expressed as the mean value. Differences between two groups were compared using the Mann-Whitney U test. p < 0.05 was considered statistically. sIgA, salivary IgA; sIgG, salivary IgG; VIWS, vaccinated individuals with symptoms; VIWOS, vaccinated individuals without symptoms; ns, not significant; *p < 0.05; ***p < 0.001.
4. Discussion
Omicrons tend to cause relatively mild symptoms or no symptoms at all in vaccinated individuals [[2], [3], [4]]. Among omicron variant-positive individuals, 25.5–32.4 % of asymptomatic infections have been reported [5,27]. Due to strict control measures for COVID-19 in China, most people will remain vaccinated until the new SARS-CoV-2 (BA5.2 and BF.7) outbreak starts in early December 2022. In our study 84.4%–92.7 % of the individuals were vaccinated with two or more doses of the vaccine (Supplementary Table 1). Our survey showed that most people exposed to SARS-CoV-2 during this outbreak developed illness, presenting with fever (63 %), sore throat (48.6 %), and cough (48.2 %), whereas a minority (17.8%–30.0 %) showed no symptoms.
Conventionally, the presence of virus-specific IgM antibodies indicates a recent infection [28]. However, in the present study, S-IgM was undetectable in both the VIWS and VIWOS cohorts. This could be attributed to the vaccinated individuals, as S-IgM may not have been sufficiently elicited by subsequent omicron infections (mainly BA.5.2 in Guangzhou). As expected, N-IgM was detected in 69.2 % of the symptomatic individuals. Notably, the N-IgA positivity rate in the VIWS cohort was 93.6 %. Most individuals ( 79.5 %, Table 1) were vaccinated with to 2–3 doses of an inactivated COVID-19 vaccine, which can induce low levels of SARS-CoV-2-specific IgA [21]. Because the interval between the last dose injection and the blood sample collection was >1 year, with a median of 439.5 d (IQR, 384.0–509.0, Table 1), the S-IgA and N-IgA detected in the symptomatic group were likely to have originated from the recent omicron infection. The potential use of IgA in serosurveys has not been established [11,21]. Our results suggest that N-IgA is more appropriate than N-IgM for diagnosing omicron infections in vaccinated populations. Our study also demonstrated that SARS-CoV-2 specific IgG (S-IgG and N-IgG) was induced during omicron infections in a vaccinated population. Because of pre-existing IgG antibodies in the vaccinated individuals, samples from two time points, pre-epidemic and post-epidemic, were required for the diagnosis of infection.
Interestingly, among the individuals with no symptoms, N-IgA-positive and N-IgA-negative groups could be categorized, and the detection rate of N-IgM was 57.1 % in the N-IgA-positive group, suggesting that some individuals may have developed asymptomatic infections while still eliciting adaptive immune responses to SARS-CoV-2 infection. Additionally, we observed that 54.3 % of the N-IgA-negative individuals in the VIWOS cohort, except for one N-IgM-positive patient (Supplementary Table 3), remained asymptomatic during this new omicron outbreak, indicating potential resistance to the SARS-CoV-2 variant infection [29]. Further understanding of the protective immune response against SARS-CoV-2 infection in these exposed but uninfected individuals will inform vaccine development.
Secretory IgA (SIgA), the dominant antibody class in mucosal secretions, is also present in saliva and breast milk [30]. In our study, the positivity rates of S-IgA and N-IgA were 42 % and 54 %, respectively, in symptomatic individuals. Saliva is easily accessible and noninvasive, making the detection of salivary N-IgA a valuable tool for the diagnosis of SARS-CoV-2 infection.
In conclusion, our study suggests that substantial N-specific antibodies are induced during omicron infection, and that testing for N-IgA in both blood and saliva may aid in the diagnosis of SARS-CoV-2 infection in vaccinated populations. The antibody responses we have characterized here in both the VIWS and VIWOS cohorts, particularly the specific IgA response, will inform the diagnosis of other respiratory viral infections and the management of post-COVID19 syndrome in the future.
Our study had several limitations. First, participants received the survey via a questionnaire applet, which may have led to potential underreporting of manifestations owing to unawareness of some minor symptoms, especially in the older adult population. Second, the number of samples in each VIWS or VIWOS cohort was small, and the samples were collected 2–3 months after the outbreak. The kinetic levels of specific antibodies are lacking. Although the limited sample size may not fully represent the broader population, it still provides insights into the characteristics of the antibody response in the two cohorts, VIWS and VIWOS, in a community-based population.
Ethics statement
This study was reviewed and approved by the Human Ethics Committee of Guangzhou Eighth People's Hospita, with the approval number: 202115202. All participants provided informed consent to participate in the study.
Funding
This work was supported by the Guangzhou Municipal Science and Technology Bureau (202201020528 and 202201020527).
Data availability statement
The data supporting the findings of this study are available in the manuscript or supplementary tables.
CRediT authorship contribution statement
Ming Gao: Writing - original draft, Resources, Methodology, Investigation. Xiaomin Xing: Writing - original draft, Methodology, Investigation. Wenbiao Hao: Resources, Methodology. Xulei Zhang: Methodology, Investigation. Kexin Zhong: Methodology, Investigation. Canhui Lu: Supervision, Resources. Xilong Deng: Supervision, Resources, Investigation, Funding acquisition, Conceptualization. Lei Yu: Writing - review & editing, Writing - original draft, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e24030.
Contributor Information
Xilong Deng, Email: gz8hdxl@126.com.
Lei Yu, Email: leiyu11393@126.com.
Appendix A. Supplementary data
The following is/are the supplementary data to this article.
References
- 1.WHO . 2023. One Year since the Emergence of COVID-19 Virus Variant Omicron.https://www.who.int/news-room/feature-stories/detail/one-year-since-the-emergence-of-omicron.html [Google Scholar]
- 2.Arabi M., Al-Najjar Y., Mhaimeed N., Salameh M.A., Paul P., Alanni J., et al. Severity of the Omicron SARS-CoV-2 variant compared with the previous lineages: a systematic review. J. Cell Mol. Med. 2023;27(11):1443–1464. doi: 10.1111/jcmm.17747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Gili R., Burioni R. SARS-CoV-2 before and after Omicron: two different viruses and two different diseases? J. Transl. Med. 2023;21(1):251. doi: 10.1186/s12967-023-04095-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Menni C., Valdes A.M., Polidori L., Antonelli M., Penamakuri S., Nogal A., et al. Symptom prevalence, duration, and risk of hospital admission in individuals infected with SARS-CoV-2 during periods of omicron and delta variant dominance: a prospective observational study from the ZOE COVID Study. Lancet. 2022;399(10335):1618–1624. doi: 10.1016/S0140-6736(22)00327-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Shang W., Kang L., Cao G., Wang Y., Gao P., Liu J., et al. Percentage of asymptomatic infections among SARS-CoV-2 omicron variant-positive individuals: a systematic review and meta-analysis. Vaccines (Basel) 2022;10(7):1049. doi: 10.3390/vaccines10071049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Joung S.Y., Ebinger J.E., Sun N., Liu Y., Wu M., Tang A.B., et al. Awareness of SARS-CoV-2 omicron variant infection among adults with recent COVID-19 seropositivity. JAMA Netw. Open. 2022;5(8) doi: 10.1001/jamanetworkopen.2022.27241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Doll M.K., Waghmare A., Heit A., Levenson Shakoor B., Kimball L.E., Ozbek N., et al. 2022. Acute and Post-Acute COVID-19 Outcomes Among Immunologically Naive Adults during Delta versus Omicron Waves. medRxiv. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yang Y., Guo L., Yuan J., Xu Z., Gu Y., Zhang J., et al. Viral and antibody dynamics of acute infection with SARS-CoV-2 omicron variant (B.1.1.529): a prospective cohort study from Shenzhen, China. Lancet Microbe. 2023;4(8):e632–e641. doi: 10.1016/S2666-5247(23)00139-8. [DOI] [PubMed] [Google Scholar]
- 9.Huang J., Zhao S., Chong K.C., Zhou Y., Lu W., Fang F., et al. Infection rate in Guangzhou after easing the zero-COVID policy: seroprevalence results to ORF8 antigen. Lancet Infect. Dis. 2023;23(4):403–404. doi: 10.1016/S1473-3099(23)00112-3. [DOI] [PubMed] [Google Scholar]
- 10.Lei Q., Li Y., Hou H.Y., Wang F., Ouyang Z.Q., Zhang Y., et al. Antibody dynamics to SARS-CoV-2 in asymptomatic COVID-19 infections. Allergy. 2021;76(2):551–561. doi: 10.1111/all.14622. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Montague Bt, Wipperman Mf, Hooper At, Hamon Sc, Crow R., Elemo F., et al. Anti-SARS-CoV-2 IgA identifies asymptomatic infection in first responders. J. Infect. Dis. 2022;225(4):578–586. doi: 10.1093/infdis/jiab524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kanji J.N., Bailey A., Fenton J., Ling S.H., Rivera R., Plitt S., et al. Detection of SARS-CoV-2 antibodies formed in response to the BNT162b2 and mRNA-1237 mRNA vaccine by commercial antibody tests. Vaccine. 2021;39(39):5563–5570. doi: 10.1016/j.vaccine.2021.08.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tretyn A., Szczepanek J., Skorupa M., Jarkiewicz-Tretyn J., Sandomierz D., Dejewska J., et al. Differences in the concentration of anti-SARS-CoV-2 IgG antibodies post-COVID-19 recovery or post-vaccination. Cells. 2021;10(8):1952. doi: 10.3390/cells10081952. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Hua Q., Zhang H., Yao P., Xu N., Sun Y., Lu H., et al. Immunogenicity and immune-persistence of the CoronaVac or Covilo inactivated COVID-19 Vaccine: a 6-month population-based cohort study. Front. Immunol. 2022;13 doi: 10.3389/fimmu.2022.939311. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Montague B.T., Wipperman M.F., Chio E., Crow R., Hooper A.T., O'brien M.P., et al. Elevated serum IgA following vaccination against SARS-CoV-2 in a cohort of high-risk first responders. Sci. Rep. 2022;12(1) doi: 10.1038/s41598-022-19095-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Muena N.A., Garcia-Salum T., Pardo-Roa C., Avendano M.J., Serrano E.F., Levican J., et al. Induction of SARS-CoV-2 neutralizing antibodies by CoronaVac and BNT162b2 vaccines in naive and previously infected individuals. EBioMedicine. 2022;78 doi: 10.1016/j.ebiom.2022.103972. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Qaqish A., Abbas M.M., Al-Tamimi M., Abbas M.A., Al-Omari M., Alqassieh R. SARS-CoV-2 antinucleocapsid antibody response of mRNA and inactivated virus vaccines compared to unvaccinated individuals. Vaccines (Basel) 2022;10(5):643. doi: 10.3390/vaccines10050643. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lau J.J., Cheng S.M.S., Leung K., Lee C.K., Hachim A., Tsang L.C.H., et al. Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive population. Nat. Med. 2023;29(2):348–357. doi: 10.1038/s41591-023-02219-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Vikkurthi R., Ansari A., Pai A.R., Jha S.N., Sachan S., Pandit S., et al. Inactivated whole-virion vaccine BBV152/Covaxin elicits robust cellular immune memory to SARS-CoV-2 and variants of concern. Nat Microbiol. 2022;7(7):974–985. doi: 10.1038/s41564-022-01161-5. [DOI] [PubMed] [Google Scholar]
- 20.Azak E., Karadenizli A., Uzuner H., Karakaya N., Canturk N.Z., Hulagu S. Comparison of an inactivated Covid19 vaccine-induced antibody response with concurrent natural Covid19 infection. Int. J. Infect. Dis. 2021;113:58–64. doi: 10.1016/j.ijid.2021.09.060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Cheng Z.J., Zheng P., Xue M., Chen Y., Sun B. Identifying COVID-19 infections from a vaccinated population using specific IgA antibody test. Front. Immunol. 2022;13 doi: 10.3389/fimmu.2022.821218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Diagnosis and treatment protocol for COVID-19 patients (tentative 9th version) Infect Dis Immun. 2022;2(3):135–144. doi: 10.1097/ID9.0000000000000059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.He Y., Zhang F., Liu Y., Xiong Z., Zheng S., Liu W., et al. Clinical characteristics of mild patients with breakthrough infection of omicron variant in China after relaxing the dynamic zero COVID-19 policy. Vaccines (Basel) 2023;11(5):968. doi: 10.3390/vaccines11050968. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kang W., Yang P., Dang B., Zhang W., Gang Y., Wang W., et al. Dynamics of disease characteristics and viral RNA decay in patients with asymptomatic and mild infections during the Omicron wave in Shanghai, China: a retrospective cohort study. Int. J. Infect. Dis. 2023;(60–70):130. doi: 10.1016/j.ijid.2023.02.020. [DOI] [PubMed] [Google Scholar]
- 25.Yu L., Wang R., Gao F., Li M., Liu J., Wang J., et al. Delineating antibody recognition against Zika virus during natural infection. JCI Insight. 2017;2(12) doi: 10.1172/jci.insight.93042. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Guan Y., Sajadi M.M., Kamin-Lewis R., Fouts T.R., Dimitrov A., Zhang Z., et al. Discordant memory B cell and circulating anti-Env antibody responses in HIV-1 infection. Proc. Natl. Acad. Sci. U. S. A. 2009;106(10):3952–3957. doi: 10.1073/pnas.0813392106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Yu W., Guo Y., Zhang S., Kong Y., Shen Z., Zhang J. Proportion of asymptomatic infection and nonsevere disease caused by SARS-CoV-2 Omicron variant: a systematic review and analysis. J. Med. Virol. 2022;94(12):5790–5801. doi: 10.1002/jmv.28066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Fraussen J. IgM responses following SARS-CoV-2 vaccination: insights into protective and pre-existing immunity. EBioMedicine. 2022;77 doi: 10.1016/j.ebiom.2022.103922. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Netea M.G., Dominguez-Andres J., Van De Veerdonk F.L., Van Crevel R., Pulendran B., Van Der Meer J.W.M. Natural resistance against infections: focus on COVID-19. Trends Immunol. 2022;43(2):106–116. doi: 10.1016/j.it.2021.12.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Sheikh-Mohamed S., Isho B., Chao G.Y.C., Zuo M., Cohen C., Lustig Y., et al. Systemic and mucosal IgA responses are variably induced in response to SARS-CoV-2 mRNA vaccination and are associated with protection against subsequent infection. Mucosal Immunol. 2022;15(5):799–808. doi: 10.1038/s41385-022-00511-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Data Availability Statement
The data supporting the findings of this study are available in the manuscript or supplementary tables.