Combining immunoprofiling with machine learning to assess the effects of adjuvant formulation on human vaccine-induced immunity

Abstract

Adjuvants produce complex, but often subtle, effects on vaccine-induced immune responses that, nonetheless, play a critical role in vaccine efficacy. In-depth profiling of vaccine-induced cytokine, cellular, and antibody responses ("immunoprofiling") combined with machine-learning holds the promise of identifying adjuvant-specific immune response characteristics that can guide rational adjuvant selection. Here, we profiled human immune responses induced by vaccines adjuvanted with two similar, clinically relevant adjuvants, AS01B and AS02A, and identified key distinguishing characteristics, or immune signatures, they imprint on vaccine-induced immunity. Samples for this side-by-side comparison were from malaria-naïve individuals who had received a recombinant malaria subunit vaccine (AMA-1) that targets the pre-erythrocytic stage of the parasite. Both adjuvant formulations contain the same immunostimulatory components, QS21 and MPL, thus this study reveals the subtle impact that adjuvant formulation has on immunogenicity. Adjuvant-mediated immune signatures were established through a two-step approach: First, we generated a broad immunoprofile (serological, functional and cellular characterization of vaccine-induced responses). Second, we integrated the immunoprofiling data and identify what combination of immune features was most clearly able to distinguish vaccine-induced responses by adjuvant using machine learning. The computational analysis revealed statistically significant differences in cellular and antibody responses between cohorts and identified a combination of immune features that was able to distinguish subjects by adjuvant with 71% accuracy. Moreover, the in-depth characterization demonstrated an unexpected induction of CD8⁺ T cells by the recombinant subunit vaccine, which is rare and highly relevant for future vaccine design.

Keywords: Apical Membrane Antigen; Immunoprofile; Plasmodium falciparum; adjuvant; protection; vaccine.

Figure 1.

Correlation matrix of all collected immune measures. Serological (Sero), cytokine (Cyto), B cell ELISPOT (BELI), and T cell flow cytometry (TFC) measures are shown. Pearson correlation coefficient is shown from −1 (red) to 1 (blue). Only correlations with statistical significance of p < .05 are shown. Notable correlation clusters are highlight for positive (red) and negative (blue) interactions.

Figure 2.

Hierarchical clustering of all immune measurements. Clusters were defined by a cutoff of a Pearson correlation coefficient of 0.60 and are color-coded. Immune measures that are classified as ‘vaccine-induced’ are highlighted with light, medium, and dark gray, corresponding to statistical significance (vs. pre-immune). Immune measures that are classified as showing adjuvant-specific differences are shown in light, medium, and dark blue based on its statistical significance (AS01B vs. AS01A).

Figure 3.

Cytokine concentration following ex vivo stimulation by allele-specific AMA-1 peptide pools. Cytokine concentrations following stimulation by AMA1 (3D7) peptide pool (a) and AMA1 (HB3) peptide pool (b) for pre-immune (gray) samples and AS01B and AS02A vaccinees (red and blue, respectively) collected at the pre-challenge time point. Vaccine-induced differences (vs. pre-immune) are shown in black, adjuvant-specific differences (AS01B vs. AS02A) are shown in magenta (* p < .05, ** p < .01, *** p < .001).

Figure 4.

Vaccine-induced and adjuvant-specific immune responses for Tfh CD4⁺ and CD8⁺ cells. (a) Relative frequency of activated Tfh cells (CD154⁺ CXCR5⁺) and the relative frequency of TFH1, TFH2, TFH17 subsets of the TFH population. (b) Relative frequency of activated CD8⁺ T cells and the relative frequency of naïve, effector, and memory subsets of the activated CD8⁺ T cell population. Vaccine-induced differences (vs. pre-immune) are shown in black; adjuvant-specific differences (AS01B vs. AS02A) are shown in magenta (* p < .05, ** p < .01, *** p < .001).

Figure 5.

Vaccine-induced and adjuvant-specific immune responses in antibody responses. (a) Growth inhibition assay for AS01B and AS02A adjuvanted vaccine-induced antibody responses. (b) ELISA assay using recombinant AMA1 antigen across time points from pre-immune (T0) to post-challenge (T7). Linear mixed model was used to assess time point-specific (black) and adjuvant-specific (magenta) effects. Selected pair-wise comparisons between time points and adjuvant conditions are shown using curved lines with corresponding p-values (* p < .05; ** p < .01; *** p < 10⁻³ ***).

Figure 6.

Principal component analysis (PCA) for vaccine-induced responses. (a) PCA plot for representative parameters for all vaccine-induced responses, summarized in Table 1. Vectors corresponding to each measure are shown. Points are labeled for AS01B vaccinees (pink) and AS02A vaccinees (blue). (b) PCA plot for parameters identified using machine learning to have predictive value in distinguishing AS01B and AS02A vaccinees.