Abstract
Studies of successive vaccination suggest that immunological memory against past influenza viruses may limit responses to vaccines containing current strains. The impact of memory induced by prior infection is rarely considered and is difficult to ascertain, because infections are often subclinical. This study investigated influenza vaccination among adults from the Ha Nam cohort (Vietnam), who were purposefully selected to include 72 with and 28 without documented influenza A(H3N2) infection during the preceding 9 years (Australian New Zealand Clinical Trials Registry 12621000110886). The primary outcome was the effect of prior influenza A(H3N2) infection on hemagglutinin-inhibiting antibody responses induced by a locally available influenza vaccine administered in November 2016. Baseline and postvaccination sera were titrated against 40 influenza A(H3N2) strains spanning 1968–2018. At each time point (baseline, day 14 and day 280), geometric mean antibody titers against 2008–2018 strains were higher among participants with recent infection (34 (29–40), 187 (154–227) and 86 (72–103)) than among participants without recent infection (19 (17–22), 91 (64–130) and 38 (30–49)). On days 14 and 280, mean titer rises against 2014–2018 strains were 6.1-fold (5.0- to 7.4-fold) and 2.6-fold (2.2- to 3.1-fold) for participants with recent infection versus 4.8-fold (3.5- to 6.7-fold) and 1.9-fold (1.5- to 2.3-fold) for those without. One of 72 vaccinees with recent infection versus 4 of 28 without developed symptomatic A(H3N2) infection in the season after vaccination (P = 0.021). The range of A(H3N2) viruses recognized by vaccine-induced antibodies was associated with the prior infection strain. These results suggest that recall of immunological memory induced by prior infection enhances antibody responses to inactivated influenza vaccine and is important to attain protective antibody titers.
Similar content being viewed by others
Data availability
The protocol is available at https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380758&isReview=true. Participant data were recorded into a secure, auditable online database called CliRes, which was developed by the Oxford University Clinical Research Unit, Vietnam (https://clires.oucru.org/). Serological data were linked to participant data using Microsoft Access version 15.0.5349.1000. The dataset used for analysis will be made available on request and will be publicly available at https://melbourne.figshare.com/ within one year of this publication. Plots showing titers for each antigen and time point for each individual are also presented in Supplementary Fig. 8. HA (±NA) sequences of influenza viruses included in the analyses are available on GISAID. GISAID accession codes are listed in Supplementary Table 8.
References
Sanjuan, R., Nebot, M. R., Chirico, N., Mansky, L. M. & Belshaw, R. Viral mutation rates. J. Virol. 84, 9733–9748 (2010).
Taubenberger, J. K. & Morens, D. M. The pathology of influenza virus infections. Annu. Rev. Pathol. 3, 499–522 (2008).
Belongia, E. A. et al. Variable influenza vaccine effectiveness by subtype: a systematic review and meta-analysis of test-negative design studies. Lancet Infect. Dis. 16, 942–951 (2016).
Zost, S. J. et al. Contemporary H3N2 influenza viruses have a glycosylation site that alters binding of antibodies elicited by egg-adapted vaccine strains. Proc. Natl Acad. Sci. USA 114, 12578–12583 (2017).
Wu, N. C. et al. Preventing an antigenically disruptive mutation in egg-based H3N2 seasonal influenza vaccines by mutational incompatibility. Cell Host Microbe 25, 836–844 e835 (2019).
Francis, T. On the doctrine of original antigenic sin. Proc. Am. Phil. Soc. 104, 572–578 (1960).
Thompson, M. et al. Effects of repeated annual inactivated influenza vaccination among healthcare personnel on serum hemagglutinin inhibition antibody response to A/Perth/16/2009 (H3N2)-like virus during 2010–11. Vaccine 34, 981–988 (2016).
Ohmit, S. E. et al. Influenza vaccine effectiveness in the community and the household. Clin. Infect. Dis. 56, 1363–1369 (2013).
McLean, H. Q. et al. Impact of repeated vaccination on vaccine effectiveness against influenza A(H3N2) and B during 8 seasons. Clin. Infect. Dis. 59, 1375–1385 (2014).
Skowronski, D. M. et al. A perfect storm: impact of genomic variation and serial vaccination on low influenza vaccine effectiveness during the 2014–2015 season. Clin. Infect. Dis. 63, 21–32 (2016).
Sullivan, S. G. et al. Low interim influenza vaccine effectiveness, Australia, 1 May to 24 September 2017. Euro. Surveill. 22, 17-00707 (2017).
Belongia, E. A. et al. Repeated annual influenza vaccination and vaccine effectiveness: review of evidence. Expert Rev. Vaccines 16, 1–14 (2017).
Smith, D. J., Forrest, S., Ackley, D. H. & Perelson, A. S. Variable efficacy of repeated annual influenza vaccination. Proc. Natl Acad. Sci. USA 96, 14001–14006 (1999).
Cobey, S. & Hensley, S. E. Immune history and influenza virus susceptibility. Curr. Opin. Virol. 22, 105–111 (2017).
Zost, S. J. et al. Identification of antibodies targeting the H3N2 hemagglutinin receptor binding site following vaccination of humans. Cell Rep. 29, 4460–4470 (2019).
Wiley, D. C., Wilson, I. A. & Skehel, J. J. Structural identification of the antibody-binding sites of Hong Kong influenza haemagglutinin and their involvement in antigenic variation. Nature 289, 373–378 (1981).
Lee, M. S. & Chen, J. S. Predicting antigenic variants of influenza A/H3N2 viruses. Emerg. Infect. Dis. 10, 1385–1390 (2004).
Koel, B. F. et al. Substitutions near the receptor binding site determine major antigenic change during influenza virus evolution. Science 342, 976–979 (2013).
Horby, P. et al. The epidemiology of interpandemic and pandemic influenza in Vietnam, 2007-2010: the Ha Nam household cohort study I. Am. J. Epidemiol. 175, 1062–1074 (2012).
Hayward, A. C. et al. Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study. Lancet Respir. Med. 2, 445–454 (2014).
Fonville, J. M. et al. Antibody landscapes after influenza virus infection or vaccination. Science 346, 996–1000 (2014).
Hoa, L. N. M. et al. Influenza A(H1N1)pdm09 but not A(H3N2) virus infection induces durable seroprotection: results from the Ha Nam cohort. J. Infect. Dis. https://doi.org/10.1093/infdis/jiaa293 (2020).
Lessler, J. et al. Evidence for antigenic seniority in influenza A (H3N2) antibody responses in southern China. PLoS Pathog. 8, e1002802 (2012).
Murphy, B. R. et al. Secretory and systemic immunological response in children infected with live attenuated influenza A virus vaccines. Infect. Immun. 36, 1102–1108 (1982).
Meade, P. et al. Influenza virus infection induces a narrow antibody response in children but a broad recall response in adults. mBio 11, e03243-19 (2020).
Henry, C. et al. Influenza virus vaccination elicits poorly adapted B cell responses in elderly individuals. Cell Host Microbe 25, 357–366 (2019).
Ranjeva, S. et al. Age-specific differences in the dynamics of protective immunity to influenza. Nat. Commun. 10, 1660 (2019).
Li, Y. et al. Immune history shapes specificity of pandemic H1N1 influenza antibody responses. J. Exp. Med. 210, 1493–1500 (2013).
Linderman, S. L. et al. Potential antigenic explanation for atypical H1N1 infections among middle-aged adults during the 2013-2014 influenza season. Proc. Natl Acad. Sci. USA 111, 15798–15803 (2014).
Wrammert, J. et al. Rapid cloning of high-affinity human monoclonal antibodies against influenza virus. Nature 453, 667–671 (2008).
Good, K. L., Avery, D. T. & Tangye, S. G. Resting human memory B cells are intrinsically programmed for enhanced survival and responsiveness to diverse stimuli compared to naive B cells. J. Immunol. 182, 890–901 (2009).
Auladell, M. et al. Distinguishing naive- from memory-derived human B cells during acute responses. Clin. Transl. Immunol. 8, e01090 (2019).
Houser, K. V., Pearce, M. B., Katz, J. M. & Tumpey, T. M. Impact of prior seasonal H3N2 influenza vaccination or infection on protection and transmission of emerging variants of influenza A(H3N2)v virus in ferrets. J. Virol. 87, 13480–13489 (2013).
Kim, J. et al. Prior infection with influenza virus but not vaccination leaves a long-term immunological imprint that intensifies the protective efficacy of antigenically drifted vaccine strains. Vaccine 34, 495–502 (2016).
Kreijtz, J. H. C. M., Fouchier, R. A. M. & Rimmelzwaan, G. F. Immune responses to influenza virus infection. Virus Res. 162, 19–30 (2011).
Sangster, M. Y., Nguyen, P. Q. T. & Topham, D. J. Role of memory B cells in hemagglutinin-specific antibody production following human influenza A virus infection. Pathogens 8, 167 (2019).
Cauchemez, S. et al. Influenza infection rates, measurement errors and the interpretation of paired serology. PLoS Pathog. 8, e1003061 (2012).
Tricoche, A. D. et al. Symptoms, infection duration, and hemagglutinin inhibition antibody response in influenza A infections. J. Infect. Dis. 223, 838–842 (2021).
Lin, Y. P. et al. Neuraminidase receptor binding variants of human influenza A(H3N2) viruses resulting from substitution of aspartic acid 151 in the catalytic site: a role in virus attachment? J. Virol. 84, 6769–6781 (2010).
Hoffmann, E., Neumann, G., Kawaoka, Y., Hobom, G. & Webster, R. G. A DNA transfection system for generation of influenza A virus from eight plasmids. Proc. Natl Acad. Sci. USA 97, 6108–6113 (2000).
WHO Global Influenza Surveillance Network WHO Global Influenza Surveillance Network: Manual for the Laboratory Diagnosis and Virological Surveillance of Influenza (WHO Press, 2011).
Andraud, M. et al. Living on three time scales: the dynamics of plasma cell and antibody populations illustrated for hepatitis a virus. PLoS Comput. Biol. 8, e1002418 (2012).
Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73, 3–36 (2011).
R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017).
Acknowledgements
Funding for this study was provided by the National Health and Medical Research Council, Australia (grant 1103367 to A.F.) and National Foundation for Science and Technology Development (NAFOSTED 108.04-2019.08, L.T.Q.M.). The WHO Collaborating Centre for Reference and Research on Influenza is funded by the Australian Government Department of Health. The Oxford University Clinical Research Unit – Hanoi and H.R.v.D. are funded through Wellcome Africa Asia program grants (089276/Z/09/Z and 106680/Z/14/Z). We are grateful to the Ha Nam Preventive Medicine Centre and People’s Committees of Thanh Liem District for their support and the people of Thanh Ha Commune for participating in this study. We would like to thank the Thanh Ha Commune health workers for their dedication to conducting active surveillance and cross-sectional surveys. We also wish to thank the Ministry of Health of Vietnam for their continuing support of the research collaboration between the Oxford University Clinical Research Unit and the National Institute for Hygiene and Epidemiology. We are grateful to members of the Oxford University Clinical Research Unit, including P. Horby for his role in establishing the Ha Nam cohort, N. Nguyen Minh Trang for project coordination and B. Huyen Trang for administrative support. A. Malet, H. Peck and Y.-M. Deng and their staff at Melbourne WHO Collaborating Centre for Reference and Research performed initial isolation and characterization of many of the influenza viruses used. We thank S. Sanchez for assisting with microneutralization assays. Thanks also to K. Subbarao and N. Thi Hoang Oanh for helpful comments on the manuscript. K.K. was supported by the Australian National Health and Medical Research Council (Leadership Investigator Fellowship 1173871). M.A. and L.H. were supported by the Melbourne International Research Scholarship and the Melbourne International Fee Remission Scholarship from the University of Melbourne. The funders had no role in the conduct of the study.
Author information
Authors and Affiliations
Contributions
M.A. assisted with virus propagation, performed serology, assisted with data analysis and codrafted the manuscript. H.V.M.P. comanaged the Ha Nam cohort, including sample collection and processing and diagnostic testing over the course of the vaccination study, and critically reviewed the manuscript. L.C. assisted with virus propagation and serology, sequenced virus HA and NA genes, performed microneutralization antibody assays, plaqued viruses and critically reviewed the manuscript. L.T.Q.M. coconceived and codesigned the study, comanaged the Ha Nam cohort sample collection and processing and diagnostic testing over the 9-year course of cohort investigation and vaccination study and critically reviewed the manuscript. Y.Y.T. constructed reverse genetics viruses and performed HI with these viruses, performed components of the data analysis, and critically reviewed the manuscript. S.W. performed components of the data analysis and critically reviewed the manuscript. P.Q.T. codesigned the study, comanaged Ha Nam cohort field work and data collection over the 9-year course of cohort investigation and over the vaccination study and critically reviewed the manuscript. D.P. assisted with data analysis and critically reviewed the manuscript. N.T.D. assisted with study design, managed all activities of the health care workers to collect samples and data, managed communication with participants and critically reviewed the manuscript. N.L.K.H., L.T.T., N.T.H.T., T.T.K.H., N.T.N.D. and V.T.N.B. processed samples, performed influenza diagnostic testing and virus isolation over 9 years of cohort investigation (between 2007 and 2016) and over the course of vaccination and subsequent follow-up, assisted with data cleaning, and critically reviewed the manuscript. A.K. assisted with data analysis and critically reviewed the manuscript. L.H. assisted with virus propagation and critically reviewed the manuscript. T.N.D. and D.D.A. comanaged the Ha Nam cohort over the 9-year course of cohort investigation and over the vaccination study and critically reviewed the manuscript. K.K. contributed to data interpretation and critical review of the manuscript. S.D.B., K.L.G.-J., D.S., I.B. and H.W. codesigned the study and critically reviewed the manuscript. S.S. assisted with data analysis and critically reviewed the manuscript. H.R.v.D. coconceived and codesigned the study, comanaged the Ha Nam cohort over the course of the vaccination study and critically reviewed the manuscript. A.F. conceived the study; comanaged Ha Nam cohort sample collection and processing and diagnostic testing over the 9-year course of cohort investigation and over the vaccination study; assisted with sample processing, virus propagation and serology; managed data and data analysis; and codrafted the manuscript.
Corresponding author
Ethics declarations
Competing interests
H.R.v.D. was funded by Sanofi (travel and consultancy fees) to present at, and attend a meeting about, the potential role of influenza vaccination in antimicrobial resistance in 2019. S.D.B reports grants from NIH during the conduct of the study. All other authors declare no competing interests.
Peer review
Peer review information
Nature Medicine thanks Gail Potter and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Alison Farrell was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Flowchart depicting participant selection for the vaccine study.
Participants included and excluded at each step are indicated by blue and white text boxes, respectively. Percentages female (F) and median age in years (Y) are shown at each step. Selection for the vaccine study was limited to participants aged ≥ 18 years (n = 556), who registered interest in participating in sub-studies involving vaccination and/or additional blood samples when re-consented in July 2016 (n = 371). Selection was further limited participants who had provided blood samples at all 12 time points since Dec-2007, and who had been present during all influenza transmission periods (n = 161). Only 32 participants lacked a detectable A(H3N2) infection, and all were selected. 82/129 who had an A(H3N2) infection were then selected based on similarity of age to participants without prior infection, and sex. For each participant lacking recent infection, we selected two to three recently infected participants who were nearest in age, while selecting 3 females selected for every 2 males (S. Table 1). 14 of 114 selected participants were excluded or did not consent. Age and proportion female were similar among non-selected, selected and consenting participants, with the exception that participants with missing blood collections and/or absent during surveillance periods were younger and fewer were female.
Extended Data Fig. 2 Antibody responses to the vaccine A(H3N2) strain, by age and prior A(H3N2) infection status and age group.
a, Titers against egg-grown A/Hong Kong/4801/2014 are plotted against participant age and prior infection status (color coded, legend) for the time points indicated. Linear regression lines are shown for each group with 95% confidence intervals. Pearsons correlation coefficients are shown with 2-sided p values. b, GMTs and c, GMRs are shown for participants stratified by prior infection and age group (color coded, legend) at the indicated time points. Symbols indicate mean values and error bars indicate 95% confidence intervals. Numbers per age group with no recent A(H3N2) are: 1935–59, n = 8; 1960–60, n = 9; 1970–79, n = 6; 1980–86, n = 5. Numbers per age group with recent A(H3N2) are: 1935–59, n = 16; 1960–60, n = 27; 1970–79, n = 21; 1980–86, n = 8. Horizontal lines indicate cut-offs for seropositivity or seroconversion.
Extended Data Fig. 3 Antibody titers across age groups in participants with and without A(H3N2) virus infection since 2007.
GAMs were used to fit titres and titre increments by virus circulation year and participant age. Participants with (n = 72) and without (n = 28) recent A(H3N2) virus infection are compared. Titre rise against the oldest strains was limited among the youngest participants and increased with increasing participant age. Titres and titre rises across strains were greater among participants with prior infection irrespective of age, indicating that effects of recent infection were not strongly age dependent.
Extended Data Fig. 4 Antibody titers and titer rises by number of recent A(H3N2) infections.
a, GMTs against individual strains spanning 2008 to 2018 are compared for participants with 0, 1 or 2–3 recent infections (legend). b, GMTs and c, GMRs averaged across 2014 to 2018 strains were compared. a–c, symbols indicate mean values and error bars indicate 95% confidence intervals. Horizontal lines represent cut-offs for seropositivity or seroconversion. Red panels in a highlight the vaccine strain. Samples sizes for all plots are shown in panel a.
Extended Data Fig. 5 Antibody titers and titer rises by year of last A(H3N2) infection.
a, GMTs against individual strains spanning 2008 to 2018 are compared by year of last infection (legend). b, GMTs and c, GMRs averaged across 2014 to 2018 strains are compared. a-c, symbols indicate mean values and error bars indicate 95% confidence intervals. Horizontal lines represent cut-offs for seropositivity or seroconversion. Red panels in a highlight the vaccine strain. Samples sizes for all plots are shown in panel a.
Extended Data Fig. 6 Effects of prior A(H3N2) strain on the strain coverage of antibodies induced by vaccination.
a, antibody titre landscape on d280 post-vaccination, constructed as in Fig. 4. b–d, antibody titre rise landscapes on days 7, 14, and 280 post-vaccination. Effects of prior infection, and of the clade causing infection, can be detected by day 7, and are maintained until day 280 after vaccination. Sample sizes are shown in panel a. e, f, ratios of MN titres against Y159S versus wild-type virus. Data presented in Fig. 4g & i, are re-analysed to show participants infected HN09-like and HN12-like viruses separately. P values are shown for two-sided ANOVA, or if significant for post-hoc comparisons between the group infected with HN14-like viruses and either of the earlier viruses using Bonferroni’s Multiple Comparison Test. g, h, HI titers and ratios of titers, against Y159S versus wild-type virus on day 280 post-vaccination. P values are shown for two-sided t-tests, specified as paired tested for within group comparisons across viruses, and as nonpaired tests for across group comparisons within viruses.
Supplementary information
Supplementary Information
Supplementary Table 1. List of eligible and selected participants. Supplementary Table 2. A(H3N2) viruses used for serology, showing passage history and assessment of NA mediated agglutination. Supplementary Figure 1. Antibody titres across A(H3N2) strains for participants stratified by age group. Supplementary Figure 2. Incremental change in antibody landscapes at each study time point. Supplementary Table 3. Participants inclusion in analysis of effects of the prior infecting strain (HN14- versus HN09- or HN12-like). Supplementary Table 4. Antigenic characterization of reverse genetics viruses bearing wild-type and Y159S HA of HK14e. Supplementary Figure 3. Back titration of reverse genetics viruses diluted to 100× the 50% tissue culture infectious dose (TCID50) based on stock virus titration. Supplementary Table 5. Antigenic site positions that vary between HK14e and strains circulating before and after vaccination. Supplementary Table 6. NA sequences and titres of viruses after plaque selection on SIAT cells. Supplementray Figure 4. Serum HI titers against A/Victoria/361/2011 are improved by adding oseltamivir or by plaque selection on SIAT cells. Supplementary Table 7. Viruses used to generate antisera for antigenic characterization and cartography. Supplementary Figure 5. Impact of erythrocyte type on HI titers of ferret first-infection antisera or human sera against A(H3N2) viruses that circulated between 2004 and 2014. Supplementary Figure 6. HI assay reading. Supplementary Figure 7. Replication of HI titers. Supplementary Table 8. Virus sequence GISAID accession numbers. Supplementary Figure 8. Individual antibody landscapes. Supplementary references.
Rights and permissions
About this article
Cite this article
Auladell, M., Phuong, H.V.M., Mai, L.T.Q. et al. Influenza virus infection history shapes antibody responses to influenza vaccination. Nat Med 28, 363–372 (2022). https://doi.org/10.1038/s41591-022-01690-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41591-022-01690-w
- Springer Nature America, Inc.
This article is cited by
-
Immune imprinting in early life shapes cross-reactivity to influenza B virus haemagglutinin
Nature Microbiology (2024)
-
Co-evolution of immunity and seasonal influenza viruses
Nature Reviews Microbiology (2023)
-
Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19
Nature (2023)
-
Seasonal influenza vaccination expands hemagglutinin-specific antibody breadth to older and future A/H3N2 viruses
npj Vaccines (2022)