Next Article in Journal
Double Auxotrophy to Improve the Safety of a Live Anti-Pseudomonas aeruginosa Vaccine
Next Article in Special Issue
Long-Term Dynamic Humoral Response to SARS-CoV-2 mRNA Vaccines in Patients on Peritoneal Dialysis
Previous Article in Journal
Vaccine against Streptococcus suis Infection in Pig Based on Alternative Carrier Protein Conjugate
Previous Article in Special Issue
Therapeutic Role of Neutralizing Antibody for the Treatment against SARS-CoV-2 and Its Emerging Variants: A Clinical and Pre-Clinical Perspective
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Vaccines
Volume 10
Issue 10
10.3390/vaccines10101621
vaccines-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Relationship between Humoral Response in COVID-19 and Seasonal Influenza Vaccination

by
Barbara Poniedziałek
1,
Ewelina Hallmann
2,
Dominika Sikora
1,3,
Karol Szymański
2,
Katarzyna Kondratiuk
2,
Jakub Żurawski
4,
Piotr Rzymski
1,5,* and
Lidia Brydak
2
1
Department of Environmental Medicine, Poznań University of Medical Sciences, 60-806 Poznan, Poland
2
Department of Influenza Research, National Influenza Center at the National Institute of Public Health NIH—National Research Institute in Warsaw, Chocimska St. 24, 00-791 Warsaw, Poland
3
Doctoral School, Poznan University of Medical Sciences, Fredry St. 10, 61-701 Poznan, Poland
4
Department of Immunobiology, Poznan University of Medical Sciences, 60-806 Poznan, Poland
5
Integrated Science Association (ISA), Universal Scientific Education and Research Network (USERN), 60-806 Poznan, Poland
*
Author to whom correspondence should be addressed.
Vaccines 2022, 10(10), 1621; https://doi.org/10.3390/vaccines10101621
Submission received: 5 September 2022 / Revised: 23 September 2022 / Accepted: 25 September 2022 / Published: 27 September 2022
(This article belongs to the Special Issue Advances in COVID-19 Vaccines and Neutralizing Antibody)
Browse Figure
Versions Notes

Abstract

:
There is evidence that vaccination against seasonal influenza can improve innate immune responses to COVID-19 and decrease disease severity. However, less is known about whether it could also impact the humoral immunity in SARS-CoV-2 infected patients. The present study aimed to compare the SARS-CoV-2 specific humoral responses (IgG antibodies against nucleocapsid; anti-N, receptor binding domain; anti-RBD, subunit S2; anti-S2, and envelope protein; anti-E) between non-hospitalized, COVID-19 unvaccinated, and mild COVID-19 convalescent patients who were and were not vaccinated against influenza during the 2019/2020 epidemic season (n = 489 and n = 292, respectively). The influenza-vaccinated group had significantly higher frequency and titers of anti-N antibodies (75 vs. 66%; mean 559 vs. 520 U/mL) and anti-RBD antibodies (85 vs. 76%; mean 580 vs. 540 U/mL). The prevalence and concentrations of anti-S2 and anti-E antibodies did not differ between groups (40–43%; mean 370–375 U/mL and 1.4–1.7%; mean 261–294 U/mL) and were significantly lower compared to those of anti-RBD and anti-N. In both groups, age, comorbidities, and gender did not affect the prevalence and concentrations of studied antibodies. The results indicate that influenza vaccination can improve serum antibody levels produced in response to SARS-CoV-2 infection.

1. Introduction

A broad range of factors can affect the host immune response to viral infection, including the pathogen’s immunogenicity, the disease’s clinical course, human age, sex, and health status [1,2,3]. During the pandemic of coronavirus disease 2019 (COVID-19), increasing attention has been given to the cross-protective effects of different vaccinations. As demonstrated by selected epidemiological studies, individuals vaccinated against influenza had lower odds of SARS-CoV-2 infection, hospitalization, need for mechanical ventilation, and death due to COVID-19 [4,5,6]. The data also demonstrate that the bacillus Calmette−Guérin (BCG) vaccine against tuberculosis can confer protection against other infectious diseases, including influenza staphylococci and yellow fever [7,8,9]. This phenomenon has been attributed to the so-called “trained immunity”, a process of epigenetic reprogramming of transcriptional pathways induced by infections and vaccinations that ultimately allows the innate immune system to exhibit adaptive characteristics [10,11].
However, there is also initial evidence that previous vaccinations against other respiratory diseases could improve the humoral response to the COVID-19 vaccine. In one study, individuals receiving concomitant influenza and pneumococcal or only influenza vaccination revealed significantly increased micro-neutralization titers after administration of the BNT162b2 vaccine (BioNTech/Pfizer, Germany, Mainz/New York, NY, USA) compared to those not vaccinated against influenza/pneumococcal disease [12]. Another study recently confirmed this finding, demonstrating higher titers of antibodies against the SARS-CoV-2 receptor binding domain following BNT162b2 vaccination in healthcare workers who previously received the seasonal influenza vaccine [13]. The exact molecular mechanisms behind this effect are yet to be elucidated.
The first investigations of the humoral response to hemagglutinins of the influenza virus during the COVID-19 pandemic [14] provided the passage for further studies evaluating whether vaccination against seasonal influenza could also impact the humoral immunity in SARS-CoV-2 infected patients is less known. Therefore, the present study aimed to compare the SARS-CoV-2 specific humoral responses between non-hospitalized, COVID-19 unvaccinated, and mild COVID-19 convalescent patients who were and were not previously vaccinated against influenza during the 2019/2020 epidemic season. To this end, the prevalence and concentrations of four IgG antibodies specific to SARS-CoV-2 were evaluated in both groups.

2. Materials and Methods

2.1. Patients and Serum Samples

All serum samples were purchased in 2020 from the Regional Blood Donation and Blood Treatment Centers in Poland from units located in 8 voivodeships in the following cities: Białystok, Warsaw, Radom, Racibórz, Kalisz, Bydgoszcz, Łódź, Szczecin, and Wrocław. All samples were collected between September and December 2020 from SARS-CoV-2 infected patients (confirmed by RT-PCR) 1 month (+/− 2 weeks) after the resolution of symptoms/end of the isolation period. This period was dominated by infections with Nextstrain clades 20A, 20B, and 20C [15], which did not reveal major differences in clinical outcomes [16,17]. In total, we purchased 659 serum samples from individuals vaccinated against influenza during 2019/2020 epidemic season and 659 serum samples from unvaccinated persons. All influenza-vaccinated individuals received the vaccine in the recommended period between September and December 2019, approximately one year prior to infection with SARS-CoV-2. The patient’s age, gender, comorbidities (present or not), and COVID-19 severity were collected for all samples. The frozen samples were transported frozen to the Department of Influenza Research, National Influenza Centre in National Institute of Public Health—National Research Institute. The research project was approved by the Bioethical Committee of the Institute of Public Health—National Research Institute (approval no. 4/2020; date of approval: 6 August 2020) and the Bioethics Committee at Poznan University of Medical Sciences (approval no. 429/22; date of approval: 11 May 2022). Considering that severity of SARS-CoV-2 infection can significantly influence the humoral responses [18,19], individuals who underwent mild COVID-19, not requiring hospitalization, were selected for this analysis. In total, 781 sera samples were analyzed, with 292 originating from individuals not vaccinated against influenza and 489 from those vaccinated in the 2019/2020 epidemic season. As the samples originated from 2020, all individuals were not vaccinated against COVID-19.

2.2. Determination of Anti-SARS-CoV-2-Specific IgG Antibodies

The collected serum samples were tested using the CE-IVD certified Microblot-Array COVID-19 IgG assay (TestLine Clinical Diagnostics, Brno, Czech Republic) for the presence and titer of the specific SARS-CoV-2 IgG antibodies against the receptor binding domain of the spike protein (anti-RBD), S2 subunit of the spike protein (anti-S2), nucleocapsid protein (anti-N), and envelope protein (anti-E). In this assay, recombinant and purified native antigens are immobilized on specific spots of nitrocellulose membrane fixed at the bottom of the microplate well [20]. The concentrations for all four antibodies were given as U/mL and interpreted as positive if above 210 U/mL.

2.3. Statistical Analyses

Data were analyzed with Statistica v.13.3 (StatSoft Inc., Tulsa, OK, USA). Because no assumption of Gaussian distribution was met (Shapiro–Wilk’s test, p < 0.05), a non-parametric Mann–Whitney U test was employed to compare groups vaccinated and unvaccinated against influenza. Comparison of titers of different antibodies was performed with Kruskal–Wallis ANOVA using Dunn’s test as a post hoc method. Spearman’s rank coefficient was used to assess the relationship between concentrations of different antibodies. The prevalence of antibodies in influenza vaccinated and unvaccinated were compared with Pearson’s χ2 test. When p < 0.05, differences were deemed statistically significant.

3. Results

3.1. Demographic Characteristics

Serum samples collected from 781 mild COVID-19 convalescent patients were analyzed, among whom 62.6% were vaccinated against influenza in the 2019/2020 infection season. Groups of patients vaccinated and unvaccinated against influenza did not differ in age and gender, but the former was represented by a higher frequency of comorbidities (Table 1).

3.2. Prevalence of SARS-CoV-2-Specific IgG Antibodies

The prevalence of anti-N, anti-RBD, anti-S2, and anti-E IgG antibodies in the studied cohort was 71.3, 81.6, 41.7, and 1.5%, respectively (Table 2). In general, 12.7% had undetectable levels of any of the considered antibodies, 15.7% tested positive for one, 35.7% for two, 34.4% for three, and 1.4% for all four. Group vaccinated against influenza in the 2019/2020 season revealed a higher prevalence of anti-N (by 8.8%) and anti-RBD (by 8.4%) antibodies compared to those who did not receive such vaccination (Table 2). In both groups, the prevalence of any antibody was not differentiated by age ≥ 50 years, comorbidities (p > 0.05 in all cases, Pearson’s χ2 test), or between women and men (p > 0.05 in all cases, Mann–Whitney U test).

3.3. Titers of SARS-CoV-2-Specific IgG Antibodies

Generally, the serum concentrations of anti-N, anti-RBD, anti-S2, and anti-E IgG antibodies (mean ± SD) in all studied patients who tested positive for their presence were 545.8 ± 212.6, 566.0 ± 217.7, 373.2 ± 165.3, and 280.3 ± 78.8 U/mL, respectively. Group vaccinated against seasonal influenza revealed significantly higher concentrations of anti-N and anti-RBD antibodies than those who did not receive the influenza vaccine; the difference in means was 39.5 (7.6%) and 40.0 (7.4%) U/mL, respectively (Figure 1). Within both subgroups, titers of anti-N and anti-RBD antibodies were higher than that of anti-S2 and anti-E (Figure 1).
In both groups, serum concentration of any antibody was not differentiated by age ≥ 50 years or comorbidities and did not differ between women and men (p > 0.05 in all cases, Mann–Whitney U test). The serum concentrations of anti-N were significantly correlated with anti-RBD and anti-S2 titers in both groups. Additionally, in individuals vaccinated against seasonal influenza, anti-RBD and anti-S2 concentrations were positively associated (Table 3).

4. Discussion

The present study demonstrated some beneficial relationship between seasonal influenza vaccination and humoral response in SARS-CoV-2 infection. Individuals who received the influenza vaccine during the 2019/2020 epidemic season revealed higher frequency and titers of anti-N and anti-RBD IgG antibodies. The increased levels of these antibodies can translate into better protection against reinfection or exert neutralization effects if the virus still replicates in tissues [21]. Although age, gender, and comorbidities were previously observed as potential factors influencing humoral responses in COVID-19 [22,23,24,25], this was not the case in the present cohort of patients who underwent mild disease. These findings add to the body of knowledge on the positive effects of influenza vaccination in COVID-19 [4,5,6,26,27].
Our results suggest that influenza vaccination may increase the strength of the adaptive response to other viral infections. Although the mechanisms behind this phenomenon are not known, it can be speculated that vaccination positively affects the production of interleukin-4 by T-helper 2 cells, leading to better clonal expansion of B cells and/or interleukin-5 and interleukin-6, which contribute to later phases of B-cell activation by driving their differentiation and supporting antibody production [28]. Moreover, it is suggested that influenza vaccination may induce innate immune training in myeloid cells by altering cytokine production through epigenetic changes [29,30,31]. It is plausible that such trained myeloid cells may also support humoral responses during SARS-CoV-2 infection. Further investigations are required to understand better the exact nature of immunological events in play and their role in the cross-protective effects of influenza vaccination against heterologous infection.
Compared to anti-RBD IgG antibodies, anti-N were less prevalent in the studied cohort (by 10.3%), as well as in subsets of individuals vaccinated (by 10.5%) and unvaccinated (by 10.9%) against seasonal influenza. This is in line with other studies, which also reported a lower prevalence of anti-N IgG antibodies compared to anti-RBD [32,33]. This is due to the different dynamics of these antibodies, from which anti-N are detected earlier and have a significantly lower half-life [33,34]. Moreover, a lower prevalence of anti-N antibodies is likely also due to the location of nucleocapsid protein inside the lipid bilayer envelope, which can blunt its recognition by immune cells [35,36]. In turn, less than 50% of analyzed serum samples were positive for anti-S2 IgG antibodies. Experimental vaccine research revealed that the S2 subunit of SARS-CoV-2 S protein, which has distinct domains involved in mediating viral fusion of viral envelope, can be similarly immunogenic as S1, which contains RBD and the N-terminal domain [37]. However, these observations relate to the immunogenicity comparison of different subunit vaccine candidates, whereas in the case of the virion, S2 is much less accessible for immune cell recognition and contains a lower number of predicted epitopes than S1 [38]. Similarly to our observations, other studies also reported a low prevalence of anti-S2 IgG antibodies. For example, an Italian serological study found that the prevalence of anti-S2 IgG antibodies in SARS-CoV-2 infected patients was 42% compared to 87% for anti-S1 and 93% for anti-RBD [39]. Notably, the S2 subunit is more conserved among coronaviruses than S1 [40], while anti-S2 antibodies can harbor Fc-dependent effect function [41] and reveal pan-betacoronavirus neutralization potencies [42,43,44]. Therefore, their presence can enhance the host’s antiviral humoral immunity. In our study, the prevalence of anti-S2 Igg antibodies in individuals vaccinated against influenza was only slightly and statistically insignificantly higher compared to unvaccinated patients (by 3.2%), while serum concentrations in both groups were similar. However, in the former subset of subjects, the anti-S2 titers were positively correlated with those of anti-RBD. Although the exact nature of this relationship remains unclear, it may suggest that vaccination against influenza could enhance the simultaneous recognition of S2 and RBD in some individuals.
We also found that influenza vaccination was not associated with a more frequent presence or higher serum levels of anti-E IgG antibodies. Moreover, these antibodies were very rare in the studied cohort, and their concentration was significantly lower than that of anti-N and anti-RBD. Other serological research also observed a very low or zero prevalence of anti-E IgG antibodies [20,45]. The envelope protein is the smallest structural protein of SARS-CoV-2 (length 75 amino acids) and has a low protrusion of its ectodomains that could be recognized as epitopes [35,46]. Although it is abundantly expressed inside the infected cell, only a small portion is incorporated into the virion envelope [47,48].
Our study has some limitations. Firstly, serum samples were collected before the emergence of SARS-CoV-2 variants of concern, such as Alpha, Delta, and Omicron, which may differ in clinical severity and antigenicity [17,49]. Secondly, due to the unavailability of data, the study did not include some patient characteristics, which may also influence humoral responses, e.g., body mass index, specific comorbidities, or the use of medications (prior to and during the SARS-CoV-2 infection). However, one should note that the studied individuals underwent mild COVID-19 and did not require hospitalization. Thus, it is unlikely they were ordered any specific anti-SARS-CoV-2 treatment that could affect humoral responses (e.g., glucocorticoid), as such treatment was not recommended at the time of our study (September–December 2020), while specific anti-SARS-CoV-2 medications were not available [50,51]. Further research is required to understand whether influenza vaccination could be associated with modified humoral response in asymptomatic and severe SARS-CoV-2 infections. Moreover, it is unknown whether influenza vaccination could also be associated with the response of other immunoglobulin classes that play an important role in SARS-CoV-2 infection, i.e., IgM and IgA [52]. The potential association between repeated influenza vaccination with humoral responses in COVID-19 also remains to be investigated since some data show that it may blunt immune reactions and lead to a decline in the effectiveness of influenza vaccines (although this phenomenon remains controversial, while the underlying mechanism is not clear) [53,54]. One should also bear in mind that our study did not investigate the function of anti-SARS-CoV-2 antibodies. Therefore, whether higher antibody concentrations found for influenza-vaccinated individuals would translate into better virus neutralization requires further research. However, it was demonstrated that the presence of antibodies, such as IgG anti-N, the prevalence of which was higher in individuals vaccinated against influenza, was associated with a substantially reduced risk of reinfection [55,56]. Last but not least, adaptive cellular immunity that underpins protection against severe disease [57] was not a subject of this study.

5. Conclusions

This study showed better anti-N and anti-RBD antibody response to SARS-CoV-2 infection in individuals vaccinated against seasonal influenza than in those who did not receive such vaccination. Further research is required to understand the mechanisms underlying this phenomenon. Nevertheless, the results add to accumulating evidence on the broadly beneficial effects of influenza vaccination in COVID-19.

Author Contributions

Conceptualization, P.R. and L.B.; methodology, B.P., J.Ż. and P.R.; investigation, B.P., E.H., D.S., K.S., K.K., P.R. and L.B.; resources, B.P., J.Ż., P.R. and L.B.; writing—original draft preparation, P.R.; writing—review and editing, B.P. and E.H.; supervision, P.R. and L.B.; funding acquisition, B.P. and L.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of Public Health NIH—National Research Institute, grant number 1BIBW/2022.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of the Institute of Public Health—National Research Institute (protocol code 4/2020, 6 August 2020) and the Bioethics Committee at the Poznan University of Medical Sciences (protocol code 429/22, 11 May 2022).

Informed Consent Statement

Patient consent was waived because serum samples for research were purchased from Regional Blood Donor Centers in Poland.

Data Availability Statement

The data presented in this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Fink, A.L.; Klein, S.L. The Evolution of Greater Humoral Immunity in Females than Males: Implications for Vaccine Efficacy. Curr. Opin. Physiol. 2018, 6, 16–20. [Google Scholar] [CrossRef] [PubMed]
  2. Fulton, R.B.; Varga, S.M. Effects of Aging on the Adaptive Immune Response to Respiratory Virus Infections. Aging Health 2009, 5, 775. [Google Scholar] [CrossRef] [PubMed]
  3. Bajaj, V.; Gadi, N.; Spihlman, A.P.; Wu, S.C.; Choi, C.H.; Moulton, V.R. Aging, Immunity, and COVID-19: How Age Influences the Host Immune Response to Coronavirus Infections? Front Physiol. 2020, 11, 571416. [Google Scholar] [CrossRef]
  4. Conlon, A.; Ashur, C.; Washer, L.; Eagle, K.A.; Hofmann Bowman, M.A. Impact of the Influenza Vaccine on COVID-19 Infection Rates and Severity. Am. J. Infect. Control. 2021, 49, 694–700. [Google Scholar] [CrossRef]
  5. Wilcox, C.R.; Islam, N.; Dambha-Miller, H. Association between Influenza Vaccination and Hospitalisation or All-Cause Mortality in People with COVID-19: A Retrospective Cohort Study. BMJ Open Respir. Res. 2021, 8, e000857. [Google Scholar] [CrossRef] [PubMed]
  6. Su, W.; Wang, H.; Sun, C.; Li, N.; Guo, X.; Song, Q.; Liang, Q.; Liang, M.; Ding, X.; Sun, Y. The Association between Previous Influenza Vaccination and COVID-19 Infection Risk and Severity: A Systematic Review and Meta-Analysis. Am. J. Prev. Med. 2022, 63, 121–130. [Google Scholar] [CrossRef]
  7. Escobar, L.E.; Molina-Cruz, A.; Barillas-Mury, C. BCG Vaccine Protection from Severe Coronavirus Disease 2019 (COVID-19). Proc. Natl. Acad. Sci. USA 2020, 117, 17720–17726. [Google Scholar] [CrossRef]
  8. Kovačić, D.; Gajić, A.A.; Latinović, D.; Softić, A. Hypothetical Immunological and Immunogenetic Model of Heterogenous Effects of BCG Vaccination in SARS-CoV-2 Infections: BCG-Induced Trained and Heterologous Immunity. J. Med. Sci. 2021, 90, e551. [Google Scholar] [CrossRef]
  9. Kleinnijenhuis, J.; Quintin, J.; Preijers, F.; Joosten, L.A.B.; Ifrim, D.C.; Saeed, S.; Jacobs, C.; van Loenhout, J.; de Jong, D.; Stunnenberg, H.G.; et al. Bacille Calmette-Guérin Induces NOD2-Dependent Nonspecific Protection from Reinfection via Epigenetic Reprogramming of Monocytes. Proc. Natl. Acad. Sci. USA 2012, 109, 17537–17542. [Google Scholar] [CrossRef]
  10. Netea, M.G.; Domínguez-Andrés, J.; Barreiro, L.B.; Chavakis, T.; Divangahi, M.; Fuchs, E.; Joosten, L.A.B.; van der Meer, J.W.M.; Mhlanga, M.M.; Mulder, W.J.M.; et al. Defining Trained Immunity and Its Role in Health and Disease. Nat. Rev. Immunol. 2020, 20, 375–388. [Google Scholar] [CrossRef] [Green Version]
  11. Arts, R.J.W.; Moorlag, S.J.C.F.M.; Novakovic, B.; Li, Y.; Wang, S.-Y.; Oosting, M.; Kumar, V.; Xavier, R.J.; Wijmenga, C.; Joosten, L.A.B.; et al. BCG Vaccination Protects against Experimental Viral Infection in Humans through the Induction of Cytokines Associated with Trained Immunity. Cell Host Microbe 2018, 23, 89–100e5. [Google Scholar] [CrossRef] [PubMed]
  12. Puro, V.; Castilletti, C.; Agrati, C.; Goletti, D.; Leone, S.; Agresta, A.; Cimini, E.; Tartaglia, E.; Casetti, R.; Colavita, F.; et al. Impact of Prior Influenza and Pneumoccocal Vaccines on Humoral and Cellular Response to SARS-CoV-2 BNT162b2 Vaccination. Vaccines 2021, 9, 615. [Google Scholar] [CrossRef] [PubMed]
  13. Greco, M.; Cucci, F.; Portulano, P.; Lazzari, R.A.; Caldararo, C.; Sicuro, F.; Catanese, C.; Lobreglio, G. Effects of Influenza Vaccination on the Response to BNT162b2 Messenger RNA COVID-19 Vaccine in Healthcare Workers. J. Clin. Med. Res. 2021, 13, 549–555. [Google Scholar] [CrossRef] [PubMed]
  14. Brydak, L.B.; Szymański, K.; Kondratiuk, K.; Poznańska, A.; Kolondra, A.; Hallmann, E. Importance of Influenza Anti-Hemagglutinin Antibodies during the SARS-CoV-2 Pandemic in the 2019/2020 Epidemic Season in Poland. Med. Sci. Monit. 2022, 28, e936495. [Google Scholar] [CrossRef] [PubMed]
  15. Genomic Epidemiology of SARS-CoV-2 with Subsampling Focused Globally since Pandemic Start. Available online: https://nextstrain.org/ncov/gisaid/global/ (accessed on 22 September 2022).
  16. Hoang, V.-T.; Colson, P.; Levasseur, A.; Delerce, J.; Lagier, J.-C.; Parola, P.; Million, M.; Fournier, P.-E.; Raoult, D.; Gautret, P. Clinical Outcomes in Patients Infected with Different SARS-CoV-2 Variants at One Hospital during Three Phases of the COVID-19 Epidemic in Marseille, France. Infect. Genet. Evol. 2021, 95, 105092. [Google Scholar] [CrossRef]
  17. Flisiak, R.; Rzymski, P.; Zarębska-Michaluk, D.; Rogalska, M.; Rorat, M.; Czupryna, P.; Lorenc, B.; Ciechanowski, P.; Kozielewicz, D.; Piekarska, A.; et al. Demographic and Clinical Overview of Hospitalized COVID-19 Patients during the First 17 Months of the Pandemic in Poland. J. Clin. Med. 2021, 11, 117. [Google Scholar] [CrossRef]
  18. Chen, X.; Pan, Z.; Yue, S.; Yu, F.; Zhang, J.; Yang, Y.; Li, R.; Liu, B.; Yang, X.; Gao, L.; et al. Disease Severity Dictates SARS-CoV-2-Specific Neutralizing Antibody Responses in COVID-Signal. Transduct. Target Ther. 2020, 5, 180. [Google Scholar] [CrossRef]
  19. Long, Q.-X.; Tang, X.-J.; Shi, Q.-L.; Li, Q.; Deng, H.-J.; Yuan, J.; Hu, J.-L.; Xu, W.; Zhang, Y.; Lv, F.-J.; et al. Clinical and Immunological Assessment of Asymptomatic SARS-CoV-2 Infections. Nat. Med. 2020, 26, 1200–1204. [Google Scholar] [CrossRef]
  20. Montesinos, I.; Dahma, H.; Wolff, F.; Dauby, N.; Delaunoy, S.; Wuyts, M.; Detemmerman, C.; Duterme, C.; Vandenberg, O.; Martin, C.; et al. Neutralizing Antibody Responses Following Natural SARS-CoV-2 Infection: Dynamics and Correlation with Commercial Serologic Tests. J. Clin. Virol. 2021, 144, 104988. [Google Scholar] [CrossRef]
  21. Kubale, J.; Gleason, C.; Carreño, J.M.; Srivastava, K.; Singh, G.; PARIS Study Team; Gordon, A.; Krammer, F.; Simon, V. SARS-CoV-2 Spike-Binding Antibody Longevity and Protection from Reinfection with Antigenically Similar SARS-CoV-2 Variants. MBio 2022, e0178422. [Google Scholar] [CrossRef]
  22. Sasson, J.M.; Campo, J.J.; Carpenter, R.M.; Young, M.K.; Randall, A.Z.; Trappl-Kimmons, K.; Oberai, A.; Hung, C.; Edgar, J.; Teng, A.A.; et al. Diverse Humoral Immune Responses in Younger and Older Adult COVID-19 Patients. MBio 2021, 12, e0122921. [Google Scholar] [CrossRef] [PubMed]
  23. Kong, W.-H.; Zhao, R.; Zhou, J.-B.; Wang, F.; Kong, D.-G.; Sun, J.-B.; Ruan, Q.-F.; Liu, M.-Q. Serologic Response to SARS-CoV-2 in COVID-19 Patients with Different Severity. Virol. Sin. 2020, 35, 752–757. [Google Scholar] [CrossRef] [PubMed]
  24. Shields, A.M.; Faustini, S.E.; Perez-Toledo, M.; Jossi, S.; Allen, J.D.; Al-Taei, S.; Backhouse, C.; Dunbar, L.A.; Ebanks, D.; Emmanuel, B.; et al. Serological Responses to SARS-CoV-2 Following Non-Hospitalised Infection: Clinical and Ethnodemographic Features Associated with the Magnitude of the Antibody Response. BMJ Open Respir. Res. 2021, 8, e000872. [Google Scholar] [CrossRef] [PubMed]
  25. Fafi-Kremer, S.; Bruel, T.; Madec, Y.; Grant, R.; Tondeur, L.; Grzelak, L.; Staropoli, I.; Anna, F.; Souque, P.; Fernandes-Pellerin, S.; et al. Serologic Responses to SARS-CoV-2 Infection among Hospital Staff with Mild Disease in Eastern France. EBioMedicine 2020, 59, 102915. [Google Scholar] [CrossRef]
  26. Behrouzi, B.; Campoverde, M.V.A.; Liang, K.; Talbot, H.K.; Bogoch, I.I.; McGeer, A.; Fröbert, O.; Loeb, M.; Vardeny, O.; Solomon, S.D.; et al. Influenza Vaccination to Reduce Cardiovascular Morbidity and Mortality in Patients with COVID-19: JACC State-of-the-Art Review. J. Am. Coll. Cardiol. 2020, 76, 1777–1794. [Google Scholar] [CrossRef]
  27. Bujani, Z.M.; Behnampour, M.; Rahimi, N.; Safari, T.; Feizabad, K.A.; Sarbazi, A.H.; Baniasadi, M.; Rezaei, N.; Moghaddam, A.A. The Effect of Influenza Vaccination on COVID-19 Morbidity, Severity and Mortality: Systematic Review and Meta-Analysis. Malays. J. Med. Sci. 2021, 28, 20–31. [Google Scholar]
  28. Janeway, C.A., Jr.; Travers, P.; Walport, M.; Shlomchik, M.J. B-Cell Activation by Armed Helper T Cells; Garland Science: New York, NY, USA, 2001. [Google Scholar]
  29. Debisarun, P.A.; Gössling, K.L.; Bulut, O.; Kilic, G.; Zoodsma, M.; Liu, Z.; Oldenburg, M.; Rüchel, N.; Zhang, B.; Xu, C.-J.; et al. Induction of Trained Immunity by Influenza Vaccination-Impact on COVID-19. PLoS Pathog. 2021, 17, e1009928. [Google Scholar] [CrossRef]
  30. Wagstaffe, H.R.; Pickering, H.; Houghton, J.; Mooney, J.P.; Wolf, A.-S.; Prevatt, N.; Behrens, R.H.; Holland, M.J.; Riley, E.M.; Goodier, M.R. Influenza Vaccination Primes Human Myeloid Cell Cytokine Secretion and NK Cell Function. J. Immunol. 2019, 203, 1609–1618. [Google Scholar] [CrossRef]
  31. Geckin, B.; Föhse, F.K.; Domínguez-Andrés, J.; Netea, M.G. Trained Immunity: Implications for Vaccination. Curr. Opin. Immunol. 2022, 77, 102190. [Google Scholar] [CrossRef]
  32. Lumley, S.F.; Wei, J.; O’Donnell, D.; Stoesser, N.E.; Matthews, P.C.; Howarth, A.; Hatch, S.B.; Marsden, B.D.; Cox, S.; James, T.; et al. The Duration, Dynamics, and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Responses in Individual Healthcare Workers. Clin. Infect. Dis. 2021, 73, e699–e709. [Google Scholar] [CrossRef]
  33. Alfego, D.; Sullivan, A.; Poirier, B.; Williams, J.; Adcock, D.; Letovsky, S. A Population-Based Analysis of the Longevity of SARS-CoV-2 Antibody Seropositivity in the United States. EClinicalMedicine 2021, 36, 100902. [Google Scholar] [CrossRef] [PubMed]
  34. Wheatley, A.K.; Juno, J.A.; Wang, J.J.; Selva, K.J.; Reynaldi, A.; Tan, H.-X.; Lee, W.S.; Wragg, K.M.; Kelly, H.G.; Esterbauer, R.; et al. Evolution of Immune Responses to SARS-CoV-2 in Mild-Moderate COVID-19. Nat. Commun. 2021, 12, 1162. [Google Scholar] [CrossRef] [PubMed]
  35. Chaudhary, J.K.; Yadav, R.; Chaudhary, P.K.; Maurya, A.; Kant, N.; Rugaie, O.A.; Haokip, H.R.; Yadav, D.; Roshan, R.; Prasad, R.; et al. Insights into COVID-19 Vaccine Development Based on Immunogenic Structural Proteins of SARS-CoV-2, Host Immune Responses, and Herd Immunity. Cells 2021, 10, 2949. [Google Scholar] [CrossRef] [PubMed]
  36. Sun, J.; Zhuang, Z.; Zheng, J.; Li, K.; Wong, R.L.-Y.; Liu, D.; Huang, J.; He, J.; Zhu, A.; Zhao, J.; et al. Generation of a Broadly Useful Model for COVID-19 Pathogenesis, Vaccination, and Treatment. Cell 2020, 182, 734–743.e5. [Google Scholar] [CrossRef] [PubMed]
  37. Kim, K.-H.; Bhatnagar, N.; Jeeva, S.; Oh, J.; Park, B.R.; Shin, C.H.; Wang, B.-Z.; Kang, S.-M. Immunogenicity and Neutralizing Activity Comparison of SARS-CoV-2 Spike Full-Length and Subunit Domain Proteins in Young Adult and Old-Aged Mice. Vaccines 2021, 9, 316. [Google Scholar] [CrossRef]
  38. Khare, S.; Azevedo, M.; Parajuli, P.; Gokulan, K. Conformational Changes of the Receptor Binding Domain of SARS-CoV-2 Spike Protein and Prediction of a B-Cell Antigenic Epitope Using Structural Data. Front Artif. Intell. 2021, 4, 630955. [Google Scholar] [CrossRef]
  39. Coppola, A.; Buonerba, C.; Cardinale, D.; Conte, G.L.; Sansone, D.; Rofrano, G.; Vita, S.D.; Morgante, M.; Triassi, M.; Atripaldi, L.; et al. Durability of Humoral Immune Responses to SARS-CoV-2 in Citizens of Ariano Irpino (Campania, Italy): A Longitudinal Observational Study with an 11.5-Month Follow-Up. Front Public Health 2021, 9, 801609. [Google Scholar] [CrossRef]
  40. Okba, N.M.A.; Müller, M.A.; Li, W.; Wang, C.; GeurtsvanKessel, C.H.; Corman, V.M.; Lamers, M.M.; Sikkema, R.S.; de Bruin, E.; Chandler, F.D.; et al. Severe Acute Respiratory Syndrome Coronavirus 2-Specific Antibody Responses in Coronavirus Disease Patients. Emerg. Infect. Dis. 2020, 26, 1478–1488. [Google Scholar] [CrossRef]
  41. Planchais, C.; Fernández, I.; Bruel, T.; de Melo, G.D.; Prot, M.; Beretta, M.; Guardado-Calvo, P.; Dufloo, J.; Molinos-Albert, L.M.; Backovic, M.; et al. Potent Human Broadly SARS-CoV-2-Neutralizing IgA and IgG Antibodies Effective against Omicron BA.1 and BA.2. J. Exp. Med. 2022, 219, e20220638. [Google Scholar] [CrossRef]
  42. Zhou, P.; Song, G.; He, W.-T.; Beutler, N.; Tse, L.V.; Martinez, D.R.; Schäfer, A.; Anzanello, F.; Yong, P.; Peng, L.; et al. Broadly Neutralizing Anti-S2 Antibodies Protect against All Three Human Betacoronaviruses That Cause Severe Disease. bioRxiv 2022. [Google Scholar] [CrossRef]
  43. Pinto, D.; Sauer, M.M.; Czudnochowski, N.; Low, J.S.; Tortorici, M.A.; Housley, M.P.; Noack, J.; Walls, A.C.; Bowen, J.E.; Guarino, B.; et al. Broad Betacoronavirus Neutralization by a Stem Helix-Specific Human Antibody. Science 2021, 373, 1109–1116. [Google Scholar] [CrossRef] [PubMed]
  44. Zhou, P.; Yuan, M.; Song, G.; Beutler, N.; Shaabani, N.; Huang, D.; He, W.-T.; Zhu, X.; Callaghan, S.; Yong, P.; et al. A Human Antibody Reveals a Conserved Site on Beta-Coronavirus Spike Proteins and Confers Protection against SARS-CoV-2 Infection. Sci. Transl. Med. 2022, 14, eabi9215. [Google Scholar] [CrossRef] [PubMed]
  45. Budziar, W.; Gembara, K.; Harhala, M.; Szymczak, A.; Jędruchniewicz, N.; Baniecki, K.; Pikies, A.; Nahorecki, A.; Hoffmann, A.; Kardaś, A.; et al. Hidden Fraction of Polish Population Immune to SARS-CoV-2 in May 2021. PLoS ONE 2022, 17, e0253638. [Google Scholar] [CrossRef]
  46. Du, L.; He, Y.; Jiang, S.; Zheng, B.-J. Development of Subunit Vaccines against Severe Acute Respiratory Syndrome. Drugs Today 2008, 44, 63–73. [Google Scholar]
  47. Schoeman, D.; Fielding, B.C. Coronavirus Envelope Protein: Current Knowledge. Virol. J. 2019, 16, 69. [Google Scholar] [CrossRef]
  48. Venkatagopalan, P.; Daskalova, S.M.; Lopez, L.A.; Dolezal, K.A.; Hogue, B.G. Coronavirus Envelope (E) Protein Remains at the Site of Assembly. Virology 2015, 478, 75–85. [Google Scholar] [CrossRef]
  49. Li, Q.; Zhang, M.; Liang, Z.; Zhang, L.; Wu, X.; Yang, C.; An, Y.; Tong, J.; Liu, S.; Li, T.; et al. Antigenicity Comparison of SARS-CoV-2 Omicron Sublineages with Other Variants Contained Multiple Mutations in RBD. MedComm 2022, 3, e130. [Google Scholar] [CrossRef]
  50. Rahmah, L.; Abarikwu, S.O.; Arero, A.G.; Essouma, M.; Jibril, A.T.; Fal, A.; Flisiak, R.; Makuku, R.; Marquez, L.; Mohamed, K.; et al. Oral Antiviral Treatments for COVID-19: Opportunities and Challenges. Pharmacol. Rep. 2022. [Google Scholar] [CrossRef]
  51. Flisiak, R.; Parczewski, M.; Horban, A.; Jaroszewicz, J.; Kozielewicz, D.; Pawłowska, M.; Piekarska, A.; Simon, K.; Tomasiewicz, K.; Zarębska-Michaluk, D. Management of SARS-CoV-2 Infection: Recommendations of the Polish Association of Epidemiologists and Infectiologists. Annex No. 2 as of October 13, 2020. Pol. Arch. Intern. Med. 2020, 130, 915–918. [Google Scholar] [CrossRef]
  52. Ma, H.; Zeng, W.; He, H.; Zhao, D.; Jiang, D.; Zhou, P.; Cheng, L.; Li, Y.; Ma, X.; Jin, T. Serum IgA, IgM, and IgG Responses in COVID-Cell. Mol. Immunol. 2020, 17, 773–775. [Google Scholar] [CrossRef]
  53. Thompson, M.G.; Cowling, B.J. How Repeated Influenza Vaccination Effects Might Apply to COVID-19 Vaccines. Lancet Respir. Med. 2022, 10, 636–638. [Google Scholar] [CrossRef]
  54. Örtqvist, Å.; Brytting, M.; Leval, A.; Hergens, M.-P. Impact of Repeated Influenza Vaccinations in Persons over 65 Years of Age: A Large Population-Based Cohort Study of Severe Influenza over Six Consecutive Seasons, 2011/12-2016/17. Vaccine 2018, 36, 5556–5564. [Google Scholar] [CrossRef] [PubMed]
  55. Murchu, E.O.; Byrne, P.; Carty, P.G.; Gascun, C.D.; Keogan, M.; O’Neill, M.; Harrington, P.; Ryan, M. Quantifying the Risk of SARS-CoV-2 Reinfection over Time. Rev. Med. Virol. 2022, 32, e2260. [Google Scholar] [CrossRef] [PubMed]
  56. Ali, A.M.; Ali, K.M.; Fatah, M.H.; Tawfeeq, H.M.; Rostam, H.M. SARS-CoV-2 Reinfection in Patients Negative for Immunoglobulin G Following Recovery from COVID-19. New Microbes New Infect. 2021, 43, 100926. [Google Scholar] [CrossRef]
  57. Moss, P. The T Cell Immune Response against SARS-CoV-2. Nat. Immunol. 2022, 23, 186–193. [Google Scholar] [CrossRef]
Vaccines 10 01621 g001 550
Figure 1. Serum titers (median and interquartile range) of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated (I-VAX-) and vaccinated (I-VAX+) against seasonal influenza. The p-value refers to the difference between these groups examined with the Mann–Whitney U test. Different small letters (a, b) above bars indicate a significant difference between antibody concentrations within the I-VAX- group, while different capital letters (A, B) indicate it within the I-VAX+ group (Kruskal–Wallis ANOVA with Dunn’s post hoc test).
Figure 1. Serum titers (median and interquartile range) of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated (I-VAX-) and vaccinated (I-VAX+) against seasonal influenza. The p-value refers to the difference between these groups examined with the Mann–Whitney U test. Different small letters (a, b) above bars indicate a significant difference between antibody concentrations within the I-VAX- group, while different capital letters (A, B) indicate it within the I-VAX+ group (Kruskal–Wallis ANOVA with Dunn’s post hoc test).
Vaccines 10 01621 g001
Table
Table 1. The demographic characteristics of the studied groups of COVID-19 convalescent patients.
Table 1. The demographic characteristics of the studied groups of COVID-19 convalescent patients.
ParameterUnvaccinated against Influenza (n = 292)Vaccinated against Influenza (n = 489)p-Value
Age (years), mean ± SD35.8 ± 8.537.0 ± 10.3>0.05
≥50 years, % (n)5.1 (15)11.9 (58)0.002
Women/men, % (n)17.1 (50)/82.9 (242)23.3 (114)/76.7 (375)>0.05
Comorbidities, % (n)1.7 (5)5.1 (25)0.02
Table
Table 2. The frequencies (%) of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated and vaccinated against seasonal influenza. The p-value refers to difference between these groups examined with Pearson’s χ2 test.
Table 2. The frequencies (%) of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated and vaccinated against seasonal influenza. The p-value refers to difference between these groups examined with Pearson’s χ2 test.
IgG AntibodiesUnvaccinated against Influenza (n = 292)Vaccinated against Influenza (n = 489)p-ValueTotal
(n = 781)
anti-N65.874.60.00871.3
anti-RBD76.785.10.00181.6
anti-S239.742.9>0.0541.7
anti-E1.71.4>0.051.5
Table
Table 3. Relationship (given as Spearman’s rank correlation coefficient) between serum concentrations of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated and vaccinated against seasonal influenza.
Table 3. Relationship (given as Spearman’s rank correlation coefficient) between serum concentrations of IgG antibodies against SARS-CoV-2 nucleocapsid protein (anti-N), receptor binding domain of spike protein (anti-RBD), subunit S2 of spike protein (anti-S2), and envelope protein (anti-E) in mild COVID-19 convalescent individuals not vaccinated and vaccinated against seasonal influenza.
IgG AntibodiesUnvaccinated against Influenza
(n = 292)		Vaccinated against Influenza
(n = 489)
anti-Nanti-RBDanti-S2anti-Eanti-Nanti-RBDanti-S2anti-E
anti-N-0.560.240.15-0.380.210.14
p < 0.05p < 0.05p > 0.05p < 0.05p < 0.05p > 0.05
anti-RBD--0.190.67--0.380.32
p > 0.05p > 0.05p < 0.05p > 0.05
anti-S2---0.32---0.04
p > 0.05p > 0.05
anti-E--------
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Poniedziałek, B.; Hallmann, E.; Sikora, D.; Szymański, K.; Kondratiuk, K.; Żurawski, J.; Rzymski, P.; Brydak, L. Relationship between Humoral Response in COVID-19 and Seasonal Influenza Vaccination. Vaccines 2022, 10, 1621. https://doi.org/10.3390/vaccines10101621

AMA Style

Poniedziałek B, Hallmann E, Sikora D, Szymański K, Kondratiuk K, Żurawski J, Rzymski P, Brydak L. Relationship between Humoral Response in COVID-19 and Seasonal Influenza Vaccination. Vaccines. 2022; 10(10):1621. https://doi.org/10.3390/vaccines10101621

Chicago/Turabian Style

Poniedziałek, Barbara, Ewelina Hallmann, Dominika Sikora, Karol Szymański, Katarzyna Kondratiuk, Jakub Żurawski, Piotr Rzymski, and Lidia Brydak. 2022. "Relationship between Humoral Response in COVID-19 and Seasonal Influenza Vaccination" Vaccines 10, no. 10: 1621. https://doi.org/10.3390/vaccines10101621

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop