Assessing Vaccine Effects in HIV-1 Vaccine Trials: Antigenic Maps, Antigen Selection, and Sieve Analysis

Abstract

The goal of vaccination against infectious disease is a net population effect on the risk of infection and/or disease progression. In HIV-1 vaccine development efforts to date only a single HIV-1 vaccine trial has shown any efficacy by either of these measures. Despite this lack of success, we hope to inform future vaccine design by analyzing vaccine effects in HIV-1 vaccine trials. We expect to detect these effects through one of three measures: 1) differential vaccine-elicited responses among cases and controls in an immune correlates of risk analysis, 2) differential host genetics by treatment assignment among infected trial participants, or 3) differential viral genetics of breakthrough infecting strains by treatment assignment of the host (known as a sieve effect). In this thesis we begin by developing methods for aggregating biomarkers for use in an immune correlates of risk analysis via antigenic maps. We show that antigenic maps can be used as a bridge to understand connections between immune correlates of risk analysis results, differential host genetics and local effects in a sieve analysis. Next, we discuss the critical step of identifying panels of antigens for use in bioassays that can be used to generate antigenic maps and compare immune response outcomes between HIV-1 vaccine trials. The last part of this thesis develops sieve analysis methods that focus on epitopes, the underlying unit of the adaptive immune system response.