Systems biology of immunity to MF59-adjuvanted versus nonadjuvanted trivalent seasonal influenza vaccines in early childhood

Abstract

The dynamics and molecular mechanisms underlying vaccine immunity in early childhood remain poorly understood. Here we applied systems approaches to investigate the innate and adaptive responses to trivalent inactivated influenza vaccine (TIV) and MF59-adjuvanted TIV (ATIV) in 90 14- to 24-mo-old healthy children. MF59 enhanced the magnitude and kinetics of serum antibody titers following vaccination, and induced a greater frequency of vaccine specific, multicytokine-producing CD4(+) T cells. Compared with transcriptional responses to TIV vaccination previously reported in adults, responses to TIV in infants were markedly attenuated, limited to genes regulating antiviral and antigen presentation pathways, and observed only in a subset of vaccinees. In contrast, transcriptional responses to ATIV boost were more homogenous and robust. Interestingly, a day 1 gene signature characteristic of the innate response (antiviral IFN genes, dendritic cell, and monocyte responses) correlated with hemagglutination at day 28. These findings demonstrate that MF59 enhances the magnitude, kinetics, and consistency of the innate and adaptive response to vaccination with the seasonal influenza vaccine during early childhood, and identify potential molecular correlates of antibody responses.

Keywords: MF59; adjuvant; children; influenza vaccine; systems biology.

Conflict of interest statement

Conflict of interest statement: R.R. and G.D.G. are full-time employees at Glaxo-Smith-Kline Vaccines. C.-A.S. is a member of several advisory committees on vaccination and has received research grants from vaccine manufacturers for preclinical and clinical research, all unrelated to this work. A.J.P. chairs the United Kingdom Department of Health’s Joint Committee on Vaccination and Immunization and the European Medicines Agency scientific advisory group on vaccines. He has previously conducted clinical trials in behalf of Oxford University funded by vaccine manufacturers, including manufacturers of influenza vaccines, but no longer does so.

Figures

Fig. S1.

Experimental approach and accumulation of HAI titres. (A) Study design and sample prioritization. Ninety 14- to 24-mo-old children were recruited and randomized to receive two doses of either TIV or ATIV, 28 d apart. Blood samples were obtained at the time points indicated by the circles. The numbers inside the circles represent the number of children from which blood was collected. Microarray experiments and HAI assays were used to obtain, respectively, the gene-expression profiles and antibody responses of children vaccinated with trivalent influenza vaccine with (ATIV, blue) or without (TIV, red) MF59 adjuvant. A maximum volume of 6 mL blood was drawn at the indicated time points. The first 1 mL was prioritized for transcriptomics and added to a Paxgene tube. The remaining volume of blood was added to a preservative-free heparin tube and used for T-cell phenotyping, and the remainder for isolation of plasma for HAI and PBMCs for IFN-γ ELISpots, frozen T cells, B-cell ELISpots, and B-cell phenotyping. (B) HAI titer accumulation in individual patients. Strain-specific HAI titers are shown for each subject in each of the three cohorts. Red color indicates subjects that received TIV vaccine; blue is the ATIV vaccine. Bold lines indicate average values across all vaccines in the cohort. (C) Antibody responses induced by vaccination. The circos plot shows the log2 fold-induction of HAI titers on day 28 postboost compared with preimmunization for each one of the three Influenza virus strains (“HAI” heat maps) and for the highest fold-induction among all three strains (i.e., the Max HAI; histogram). Vaccinees with log2 fold-induction ≥6 and <6 are shown, respectively, as red and blue bars in the histogram. The inner heat maps show the log2 fold-induction of IgM- and IgG-secreting cells (ELISpots) on day 28 postboost compared with preimmunization for each one of the three Influenza virus strains (“IgG” and “IgM” heat maps) and for Tet.

Fig. 1.

Humoral immunity to influenza vaccination in children. (A) Box plot showing the HAI response of ATIV and TIV vaccinees on day 28 postboost compared with preimmunization for each one of the three Influenza virus strains and for the highest fold-induction among all three strains (P value for t test; two-tailed test). Numbers above each box represent the mean fold-change values. (B) Vaccine-specific (H1N1, H3N2, and B/Hubei) and Tet control plasma cells frequency by ex vivo ELISpot on days 1, 3, or 7 following two doses of vaccine. The number of IgM- and IgG-secreting plasma cells is shown on a log-scale with the median and interquartile ranges indicated by the line and error bars.

Fig. S2.

Plasma cell responses. Children were immunized on day 0 and day 28 with either TIV (red) or ATIV (blue) and the frequency of vaccine specific plasma cells was determined by ex vivo ELISpot from subgroups of children bled either on day 1, 3, or 7 postboost. The number of IgM- and IgG-secreting plasma cells is shown on a log scale with the median and interquartile ranges indicated by the line and error bars. A response was determined to be >four spots per million ex vivo PBMCs and percentage of responders is given above each plot with (n = responders) in parenthesis.

Fig. S3.

Memory B-cell responses. Children were immunized on day 0 and day 28 with either TIV (red) or ATIV (blue) and the frequency of vaccine specific BMEM was determined following polyclonal stimulation of PBMCs in vitro to expand memory cell populations. BMEM ELISpot were undertaken before immunization and on 1 mo after the second dose of vaccine. The number of IgM and IgG BMEM is shown on a log scale with the median and interquartile ranges indicated by the line and error bars. A response was determined to be ≥fourfold rise from baseline and the percentage of responders is given above each plot with (n = responders) in parenthesis.

Fig. 2.

Expansion of multicytokine-producing vaccine-specific CD4+ T cells. (A) Percentage of cytokine-producing vaccine-specific CD4+ T cells before immunization and 28 d postboost in TIV- (blue) and ATIV- (red) vaccinated individuals, respectively. Significant differences are indicated (Wilcoxon signed-rank test, n = 12). TNF-α+, IFN-γ+, IL-2− T cells and TNF-α− T cells are not illustrated because no difference was found. (B) IFN-γ ELISpot assays were used to identify hemagglutinin-specific T cells. Significant differences are indicated (Wilcoxon signed-rank test, TIV n = 27, ATIV n = 26).

Fig. 3.

Blood transcriptome analyses of ATIV and TIV vaccinees. (A) Impact in the blood transcriptome of ATIV and TIV vaccinees. Number of differentially expressed genes (y axis) using different paired t test two-tailed P value cut-offs (x axis) identified in response to ATIV (blue lines) or TIV (red lines) vaccination on children, or in response to TIV vaccination on young adults (green lines) (25). The time points after vaccination compared with before are represented above each line. (B) Number of differentially expressed genes identified using P value < 0.01. Circle sizes are proportional to the number of genes (shown inside the circle) up- or down-regulated postboost. (C) Heterogeneity in blood-expression profiles. The heat map shows 785 and 675 genes with twofold difference (up-regulated in red and down-regulated in blue) in at least 25% of TIV and ATIV vaccinees, respectively, on day 1 postboost compared with preimmunization.

Fig. S4.

Average transcriptional responses at days 1, 3, and 7 postboost. Each dot represents a probe set. Fold-changes and statistical significance are shown for days 1, 3, and 7 postboost compared with prevaccination time point. Vertical dashed lines are drawn at 1.5-fold change level; horizontal dashed lines correspond to P value of 0.001. At each time point, probe sets up-regulated (red) or repressed (blue) in ATIV vaccinees are shown in the TIV vaccinees for comparison purposes.

Fig. S5.

Subject-to-subject heterogeneity. Top 50 most up-regulated on average probe sets were selected in ATIV (Left) and TIV (Right) at D1 following the boost immunization. Heat maps demonstrate the expression of these probe sets in each subject at D1 relative to preimmunization time point.

Fig. S6.

Comparison of blood transcriptomics between ATIV (x axis) and TIV (y axis) vaccinees in different days postboost. GSEA (1,000 permutations) was used to obtain the NES between BTMs (gene sets) and preranked gene lists, where genes were ranked according to their fold-change between expression on a given day postboost and baseline. Each dot represents a BTM and the colors represent the high level annotation of BTMs. R and P values are for Pearson correlation.

Fig. 4.

GSEA applied to individual ATIV and TIV vaccinees. (A) GSEA (nominal P < 0.05; 1,000 permutations) was used to identify positive (red), negative (blue), or no (white) enrichment between BTMs (gene sets) and preranked gene lists, where genes were ranked according to their fold-change between expression on day 1 postboost and before immunization for each subject. ATIV and TIV vaccinees are shown in columns and BTMs in rows. (B) Genes in BTM M7.0; each “edge” (gray line) represents a coexpression relationship, as described in Li et al. (13); colors represent the mean fold-change for all ATIV vaccinees on day 1 postboost compared with before immunization. (C) Genes in BTM M40; same as in iB. (D) Genes in BTM M53; same as in B.

Fig. S7.

Gene signatures associated with HAI response in children and adults. (A) Temporal activity pattern of top correlated BTMs at D1 postboost. GSEA (nominal P < 0.05; 1,000 permutations) was used to identify BTMs (gene sets) whose genes were enriched in preranked lists (i.e., genes ranked according to their correlation between expression fold-change and maximum HAI response). Graph shows the NES of each selected BTM in the different time points. (B) Genes in BTM M75; each “edge” (gray line) represents a coexpression relationship, as described in Li et al. (13); colors represent the Pearson correlation between gene expression on day 1 postboost compared with baseline and the maximum HAI response. (C) Comparison of HAI-correlated signatures between infants and adults. Gene sets (rows) were defined as the top 200 genes with highest positive (Upper) or negative (Lower) correlation between gene expression at given time point (shown on the right of the heat map) and the HAI response. GSEA (1,000 permutations) was used to obtain the NES of those gene sets in preranked lists (columns; genes ranked according to their correlation between expression fold-change and HAI response for different datasets). Colors represent positive (red) or negative (blue) enrichment. The green rectangles indicate that D3-correlated signatures in infants are very different from those in adults. Adults-1 and Adults-2 datasets were obtained from GEO database: GSE48024 (21) and GSE29619 (15), respectively.

Fig. 5.

Kinetics of signatures of immunogenicity to TIV and ATIV vaccination. (A) Hierarchical clustering of children and adults using BTMs, whose activity correlates with HAI response. GSEA (nominal P < 0.05; 1,000 permutations) was used to identify positive (red), negative (blue), or no (white) enrichment between BTMs (rows) and preranked gene lists (columns), where genes were ranked according to their correlation between expression fold-change at a given time point (shown inside the squares) and HAI response (euclidean distance and average clustering method). Shown are 112 BTMs significantly enriched in at least 4 of 12 lists. (B) Temporal activity pattern of selected BTMs. Graph shows the normalized enrichment score (NES) of each selected BTM in the different time points for ATIV (blue lines), TIV (red lines), Adults-1 (purple bars), and Adults-2 (brown bars) cohorts. (C) Heat map of selected BTMs whose activity is positively correlated in several lists. (D) Heat map of selected BTMs whose activity is negatively correlated in several lists.