Influenza Immunization in the Context of Preexisting Immunity

Abstract

Although we develop influenza immunity from an early age, it is insufficient to prevent future infection with antigenically novel strains. One proposed way to generate long-term protective immunity against a broad range of influenza virus strains is to boost responses to the conserved epitopes on the hemagglutinin, the major surface glycoprotein on the influenza virus. Influenza-specific humoral immunity comprises a large fraction of the overall immune memory in humans, and it has been long recognized that preexisting immunity to influenza shapes the response to subsequent influenza infections and vaccinations. However, the mechanisms by which preexisting immunity modulates the response to influenza vaccination are still not completely understood. Using a set of mathematical models, we explore several hypotheses that may contribute to diminished boosting of antibodies to conserved epitopes after repeated vaccinations.

Figure 1.

Adults have high levels of preexisting immunity to influenza. Influenza vaccine–reactive IgG, IgA, and IgM antibody titers were measured in healthy human adults by ELISA (n = 38) (A). Frequency of antigen-specific memory B cells specific for mumps, measles, rubella, and influenza (B), or of VZV and influenza (C) were measured by stimulation of PBMCs and quantification by ELISpot as previously described (Rasheed et al. 2019; Eberhardt et al. 2020). VZV and influenza-specific IgG bone marrow plasma cells were quantified by ELISpot and plotted as the percentage of total IgG secreting bone marrow plasma cells (D).

Figure 2.

Boosting of antibodies after influenza vaccination. Influenza vaccine antigen binding antibody titers were measured by ELISA before and 14 d postvaccination in individuals who had been vaccinated the previous year (annual), and those who had skipped influenza vaccination for at least 3 years (skipped). (A) The relationship between the pre- and postvaccination antibody titers. (B) The relationship between fold increase in antibody titers and prevaccination titers. (C) A schematic outlining how preexisting MBCs and antibody titers may affect the recall response after seasonal influenza vaccination.

Figure 3.

Antibody responses to the head and stem of hemagglutinin (HA). Boosting of HA head- and stem-specific antibodies following vaccination with inactivated H1N1 (from seasonal trivalent influenza vaccine [TIV], [A,D], high-dose H5N1 [ B,E], and low-dose H5N1 with adjuvant [C,F]). For H5N1 we use the data from the boost vaccination (see also Fig. 6). (A–C) Plot of post- versus prevaccination antibody titers. If antibody titers remain unchanged after vaccination, the data points would fall on the line with slope = 1 (dashed line). The best fit line (solid line, slope < 1) shows that there is more boosting when the initial titers are low. (D–F) Prevaccination immunity reduces the boost and the relationship is approximately linear on log-log plot. (Panels created with data from Ellebedy et al. 2014, .)

Figure 4.

Schematic for mathematical models to explain reduced boosting of antibody responses. (A) Schematic for the basic one-epitope model and its three modifications incorporating three different mechanisms: enhanced antibody-bound antigen clearance (ACM, in green), FcγR-mediated inhibition (FIM, in blue), and epitope masking (EMM, in orange). (B) The one-epitope model is extended to a two-epitope model by including one epitope on the head of HA (H) and one epitope on the stem of HA (S). Binding of head-specific antibody (A_H) and stem-specific antibody (A_S) defines four possible states of the antigen: free antigen with no antibody bound (HS), antigen bound by antibody to the head (OS), antigen bound by antibody to the stem (HO), and antigen bound by both antibodies (OO).

Figure 5.

Model discrimination. (A) Model predictions for the basic model and its modifications incorporating three different mechanisms: antigen clearance (ACM), Fc-receptor mediated inhibition of B-cell activation (FIM), and epitope masking (EMM). Using a two-epitope model, we predict how different levels of prevaccination head- and stem-specific antibodies affect the boosting of antibody titers to head and stem of HA. Ten different sets of various prevaccination head- and stem- antibody titers (imitating 10 different individuals) were used for prediction of the postvaccination fold boost in antibody titers. Responses to the head (red circle) and stem (blue triangle) in each individual are connected by a line. (B) The corresponding plots from three experimental studies. (C) Schematic illustrating how prevaccination memory B cells and antibody affect the responses to prime and boost vaccinations with novel pandemic H5N1. High prevaccination frequency of stem-specific memory B cells defines the primary response with a strong recall of stem-specific antibodies. However, increased titers of stem-specific antibodies after the first H5N1 vaccination suppress further boosting of stem-specific antibodies following the secondary vaccination. Instead, the newly generated antibodies after the second vaccination are predominantly head-specific.

Figure 6.

Boosting of antibody response to the stem of HA during prime vaccination with adjuvanted H5N1 vaccine and lack of boosting after the boost vaccination. Filled triangles and open triangles are the responses to the stem of HA after prime and boost vaccinations, respectively. Prevaccination immunity reduces the boost, and the relationship is approximately linear on log-log plot. (Figure created from data in Ellebedy et al. 2020.)