Author:
Young William Chad,Carpp Lindsay N.,Chaudhury Sidhartha,Regules Jason A.,Bergmann-Leitner Elke S.,Ockenhouse Christian,Wille-Reece Ulrike,deCamp Allan C.,Hughes Ellis,Mahoney Celia,Pallikkuth Suresh,Pahwa Savita,Dennison S. Moses,Mudrak Sarah V.,Alam S. Munir,Seaton Kelly E.,Spreng Rachel L.,Fallon Jon,Michell Ashlin,Ulloa-Montoya Fernando,Coccia Margherita,Jongert Erik,Alter Galit,Tomaras Georgia D.,Gottardo Raphael
Abstract
RTS,S/AS01 (GSK) is the world’s first malaria vaccine. However, despite initial efficacy of almost 70% over the first 6 months of follow-up, efficacy waned over time. A deeper understanding of the immune features that contribute to RTS,S/AS01-mediated protection could be beneficial for further vaccine development. In two recent controlled human malaria infection (CHMI) trials of the RTS,S/AS01 vaccine in malaria-naïve adults, MAL068 and MAL071, vaccine efficacy against patent parasitemia ranged from 44% to 87% across studies and arms (each study included a standard RTS,S/AS01 arm with three vaccine doses delivered in four-week-intervals, as well as an alternative arm with a modified version of this regimen). In each trial, RTS,S/AS01 immunogenicity was interrogated using a broad range of immunological assays, assessing cellular and humoral immune parameters as well as gene expression. Here, we used a predictive modeling framework to identify immune biomarkers measured at day-of-challenge that could predict sterile protection against malaria infection. Using cross-validation on MAL068 data (either the standard RTS,S/AS01 arm alone, or across both the standard RTS,S/AS01 arm and the alternative arm), top-performing univariate models identified variables related to Fc effector functions and titer of antibodies that bind to the central repeat region (NANP6) of CSP as the most predictive variables; all NANP6-related variables consistently associated with protection. In cross-study prediction analyses of MAL071 outcomes (the standard RTS,S/AS01 arm), top-performing univariate models again identified variables related to Fc effector functions of NANP6-targeting antibodies as highly predictive. We found little benefit–with this dataset–in terms of improved prediction accuracy in bivariate models vs. univariate models. These findings await validation in children living in malaria-endemic regions, and in vaccinees administered a fourth RTS,S/AS01 dose. Our findings support a “quality as well as quantity” hypothesis for RTS,S/AS01-elicited antibodies against NANP6, implying that malaria vaccine clinical trials should assess both titer and Fc effector functions of anti-NANP6 antibodies.
Funder
National Institute of Allergy and Infectious Diseases
Bill and Melinda Gates Foundation
GlaxoSmithKline
Ragon Institute of MGH, MIT and Harvard
National Institutes of Health
Subject
Artificial Intelligence,Information Systems,Computer Science (miscellaneous)
Cited by
11 articles.
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