196 words), main text (3,483 words) 2 ABSTRACT Background RTS,S is the leading malaria vaccine candidate, but only confers partial efficacy against malaria in children. RTS,S is based on the major Plasmodium falciparum sporozoite surface antigen, circumsporozoite protein (CSP). The induction of anti-CSP antibodies is important for protection, however, it is unclear how protective antibodies function. MethodsWe quantified the induction of functional anti-CSP antibody responses in healthy malarianaïve adults (N=45) vaccinated with RTS,S/AS01. This included the ability to mediate effector functions via the fragment crystallizable (Fc) region, such as interacting with human complement proteins and Fcγ-receptors (FcγRs) that are expressed on immune cells, which promote various immunological functions. ResultsOur major findings were i) RTS,S-induced antibodies mediate Fc-dependent effector functions, ii) functional antibodies were generally highest after the second vaccine dose; iii) functional antibodies targeted multiple regions of CSP, iv) participants with higher levels of functional antibodies had a reduced probability of developing parasitemia following homologous challenge (p<0.05); v) non-protected subjects had higher levels of anti-CSP IgM. ConclusionsOur data suggests a role for Fc-dependent antibody effector functions in RTS,S-induced immunity. Enhancing the induction of these functional activities may be a strategy to improve the protective efficacy of RTS,S or other malaria vaccines.3
Background RTS,S is the leading malaria vaccine candidate but only confers partial efficacy against malaria in children. RTS,S is based on the major Plasmodium falciparum sporozoite surface antigen, circumsporozoite protein (CSP). The induction of anti-CSP antibodies is important for protection; however, it is unclear how these protective antibodies function. Methods We quantified the induction of functional anti-CSP antibody responses in healthy malaria-naive adults (N = 45) vaccinated with RTS,S/AS01. This included the ability to mediate effector functions via the fragment crystallizable (Fc) region, such as interacting with human complement proteins and Fcγ-receptors (FcγRs) that are expressed on immune cells, which promote various immunological functions. Results Our major findings were (1) RTS,S-induced antibodies mediated Fc-dependent effector functions, (2) functional antibodies were generally highest after the second vaccine dose, (3) functional antibodies targeted multiple regions of CSP, (4) participants with higher levels of functional antibodies had a reduced probability of developing parasitemia following homologous challenge (P < .05), and (5) nonprotected subjects had higher levels of anti-CSP IgM. Conclusions Our data suggest a role for Fc-dependent antibody effector functions in RTS,S-induced immunity. Enhancing the induction of these functional activities may be a strategy to improve the protective efficacy of RTS,S or other malaria vaccines. Clinical Trials Registration NCT00075049
Adjuvants have long been critical components of vaccines, but the exact mechanisms of their action and precisely how they alter or enhance vaccine-induced immune responses are often unclear. In this study, we used broad immunoprofiling of antibody, cellular, and cytokine responses, combined with data integration and machine learning to gain insight into the impact of different adjuvant formulations on vaccine-induced immune responses. A Self-Assembling Protein Nanoparticles (SAPN) presenting the malarial circumsporozoite protein (CSP) was used as a model vaccine, adjuvanted with three different liposomal formulations: liposome plus Alum (ALFA), liposome plus QS21 (ALFQ), and both (ALFQA). Using a computational approach to integrate the immunoprofiling data, we identified distinct vaccine-induced immune responses and developed a multivariate model that could predict the adjuvant condition from immune response data alone with 92% accuracy (p = 0.003). The data integration also revealed that commonly used readouts (i.e. serology, frequency of T cells producing IFN-γ, IL2, TNFα) missed important differences between adjuvants. In summary, broad immune-profiling in combination with machine learning methods enabled the reliable and clear definition of immune signatures for different adjuvant formulations, providing a means for quantitatively characterizing the complex roles that adjuvants can play in vaccine-induced immunity. The approach described here provides a powerful tool for identifying potential immune correlates of protection, a prerequisite for the rational pairing of vaccines candidates and adjuvants.
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 indepth characterization demonstrated an unexpected induction of CD8 + T cells by the recombinant subunit vaccine, which is rare and highly relevant for future vaccine design.
Immune correlates of protection remain elusive for most vaccines. An identified immune correlate would accelerate the down-selection of vaccine formulations by reducing the need for human pathogen challenge studies that are currently required to determine vaccine efficacy. Immunization via mosquito-delivered, radiation-attenuated P. falciparum sporozoites (IMRAS) is a well-established model for efficacious malaria vaccines, inducing greater than 90% sterile immunity. The current immunoprofiling study utilized samples from a clinical trial in which vaccine dosing was adjusted to achieve only 50% protection, thus enabling a comparison between protective and non-protective immune signatures. In-depth immunoprofiling was conducted by assessing a wide range of antigen-specific serological and cellular parameters and applying our newly developed computational tools, including machine learning. The computational component of the study pinpointed previously un-identified cellular T cell subsets (namely, TNFα-secreting CD8+CXCR3−CCR6− T cells, IFNγ-secreting CD8+CCR6+ T cells and TNFα/FNγ-secreting CD4+CXCR3−CCR6− T cells) and B cell subsets (i.e., CD19+CD24hiCD38hiCD69+ transitional B cells) as important factors predictive of protection (92% accuracy). Our study emphasizes the need for in-depth immunoprofiling and subsequent data integration with computational tools to identify immune correlates of protection. The described process of computational data analysis is applicable to other disease and vaccine models.
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