SUMMARY
HIV vaccine efficacy trials have been complicated by low rates of exposure and low levels of protection.
Yet, despite these barriers, crucial correlates of infection risk (CoR) have been defined from trials that failed to
meet overall efficacy criteria. Much has been learned about protective immune responses, host genetics, and
viral susceptibility from analysis of ineffective and marginally effective trials. In particular, while neutralizing Ab
breadth has long been considered key to vaccine-mediated protection, breadth of Fc-mediated effector
functions has only more recently begun to be explored. Given the rich data from natural infection, passive Ab
transfer studies probing mechanism of action, preclinical vaccine efficacy studies, and prior human HIV-1
vaccine efficacy trials that support the potential role of Ab effector functions to contribute to protection from
infection, these activities represent an important avenue of investigation and optimization in vaccine research
and development.
To define these CoR, case-control analysis is typically conducted by comparing the response profiles of
infected (case) and uninfected (control) subjects. However, the “control", or uninfected subject class is a
mixture of individuals that lack the protective response and were simply not exposed to the pathogen, and
those that possess the protective response and either were or were not exposed. For poorly effective vaccines,
the majority of the control subjects are expected to show a response phenotype indistinguishable from the
cases. Thus, traditional CoR analysis suffers from the dilution of the protected subjects with these unprotected
but unexposed subjects. We propose to evaluate novel machine learning (ML) techniques that can robustly
infer the protection status of vaccinated individuals on the basis of immunogenicity (or other) data in order to
facilitate correlates discovery under these challenging circumstances.
Accordingly, we propose tandem approaches to develop new insights into HIV vaccine efficacy
· by developing new analytical approaches to correlates analysis relevant not only to this but other HIV
vaccine trials and beyond, and
· by collecting new humoral immune response data defining the breadth and potency of antibody effector
function for the HVTN702 trial.