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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 <i>P. falciparum</i> 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⁺CD24^hiCD38^hiCD69⁺ 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.