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Influenza virus infection history shapes antibody responses to influenza vaccination

Nature Medicine volume 28, pages 363–372 (2022)Cite this article

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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.

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Fig. 1: Participant selection and investigation of previously circulating A(H3N2) viruses.
Fig. 2: Kinetic and strain coverage of the A(H3N2) virus-reactive antibody response to vaccination.
Fig. 3: Recent A(H3N2) virus infection enhances the titer and strain coverage of A(H3N2)-reactive antibodies induced by vaccination.
Fig. 4: The strain coverage of antibodies induced by vaccination is influenced by the A(H3N2) strain that caused prior infection.
Fig. 5: Antibody titer landscapes associated with infection in the season after vaccination.

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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.

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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

Author notes

  1. These authors jointly supervised this work: Maria Auladell, Hoang Vu Mai Phuong.

Authors and Affiliations

  1. Department of Microbiology and Immunology, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia

    Maria Auladell, Luca Hensen, Katherine Kedzierska & Annette Fox

  2. National Institute of Hygiene and Epidemiology, Ha Noi, Vietnam

    Hoang Vu Mai Phuong, Le Thi Quynh Mai, Pham Quang Thai, Nguyen Le Khang Hang, Le Thi Thanh, Tran Nhu Duong & Dang Duc Anh

  3. WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia

    Yeu-Yang Tseng, Louise Carolan, Arseniy Khvorov, Ian Barr, Sheena Sullivan & Annette Fox

  4. Department of Infectious Diseases, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia

    Yeu-Yang Tseng, Arseniy Khvorov, Sheena Sullivan & Annette Fox

  5. Centre for Pathogen Evolution, Department of Zoology, University of Cambridge, Cambridge, UK

    Sam Wilks & Derek Smith

  6. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia

    David Price

  7. Victorian Infectious Diseases Reference Laboratory Epidemiology Unit and The Peter Doherty Institute for Infection and Immunity, University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia

    David Price

  8. Ha Nam Centre for Preventive Medicine, Ha Nam, Vietnam

    Nguyen Thanh Duong

  9. Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam

    Nguyen Thi Hong Thuong, Tran Thi Kieu Huong, Nguyen Thi Ngoc Diep, Vu Thi Ngoc Bich, Heiman Wertheim & H. Rogier van Doorn

  10. Department of Medical Microbiology, Radboudumc Center for Infectious Diseases, Radboudumc, Nijmegen, The Netherlands

    Heiman Wertheim

  11. Stanford University Medical Centre, Stanford University, Stanford, CA, USA

    Scott D. Boyd

  12. Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia

    Kim L. Good-Jacobson

  13. Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Kim L. Good-Jacobson

  14. Centre of Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK

    H. Rogier van Doorn

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  1. Maria Auladell
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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

Correspondence to Annette Fox.

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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.

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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.

Extended Data Table 1 Distribution of prior A(H3N2) virus infections by year and strain
Full size table
Extended Data Table 2 GMTs against 2004–2018 A(H3N2) virus strains
Full size table
Extended Data Table 3 Geometric mean ratios against A(H3N2) viruses circulating between 1968 and 2018
Full size table
Extended Data Table 4 Comparison of vaccinees who developed symptomatic A(H3N2) virus infection with unaffected vaccinees from their households
Full size table

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.

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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

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