Sensitivity analysis for the assessment of causal vaccine effects on viral load in HIV vaccine trials

Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002, Biometrics 58, 21-29), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias.     

A comparison of eight methods for the dual-endpoint evaluation of efficacy in a proof-of-concept HIV vaccine trial

To support the design of the world's first proof-of-concept (POC) efficacy trial of a cell-mediated immunity-based HIV vaccine, we evaluate eight methods for testing the composite null hypothesis of no-vaccine effect on either the incidence of HIV infection or the viral load set point among those infected, relative to placebo. The first two methods use a single test applied to the actual values or ranks of a burden-of-illness (BOI) outcome that combines the infection and viral load endpoints. The other six methods combine separate tests for the two endpoints using unweighted or weighted versions of the two-part z, Simes', and Fisher's methods. Based on extensive simulations that were used to design the landmark POC trial, the BOI methods are shown to have generally low power for rejecting the composite null hypothesis (and hence advancing the vaccine to a subsequent large-scale efficacy trial). The unweighted Simes' and Fisher's combination methods perform best overall. Importantly, this conclusion holds even after the test for the viral load component is adjusted for bias that can be introduced by conditioning on a postrandomization event (HIV infection). The adjustment is derived using a selection bias model based on the principal stratification framework of causal inference.     

Sensitivity analyses comparing outcomes only existing in a subset selected post-randomization, conditional on covariates, with application to HIV vaccine trials

In many experiments, researchers would like to compare between treatments and outcome that only exists in a subset of participants selected after randomization. For example, in preventive HIV vaccine efficacy trials it is of interest to determine whether randomization to vaccine causes lower HIV viral load, a quantity that only exists in participants who acquire HIV. To make a causal comparison and account for potential selection bias we propose a sensitivity analysis following the principal stratification framework set forth by Frangakis and Rubin (2002, Biometrics58, 21-29). Our goal is to assess the average causal effect of treatment assignment on viral load at a given baseline covariate level in the always infected principal stratum (those who would have been infected whether they had been assigned to vaccine or placebo). We assume stable unit treatment values (SUTVA), randomization, and that subjects randomized to the vaccine arm who became infected would also have become infected if randomized to the placebo arm (monotonicity). It is not known which of those subjects infected in the placebo arm are in the always infected principal stratum, but this can be modeled conditional on covariates, the observed viral load, and a specified sensitivity parameter. Under parametric regression models for viral load, we obtain maximum likelihood estimates of the average causal effect conditional on covariates and the sensitivity parameter. We apply our methods to the world's first phase III HIV vaccine trial.     

Nonhuman primate models and the failure of the Merck HIV-1 vaccine in humans

The adenovirus type 5 (Ad5)-based vaccine developed by Merck failed to either prevent HIV-1 infection or suppress viral load in subsequently infected subjects in the STEP human Phase 2b efficacy trial. Analogous vaccines had previously also failed in the simian immunodeficiency virus (SIV) challenge-rhesus macaque model. In contrast, vaccine protection studies that used challenge with a chimeric simian-human immunodeficiency virus (SHIV89.6P) in macaques did not predict the human trial results. Ad5 vector-based vaccines did not protect macaques from infection after SHIV89.6P challenge but did cause a substantial reduction in viral load and a preservation of CD4+ T cell counts after infection, findings that were not reproduced in the human trials. Although the SIV challenge model is incompletely validated, we propose that its expanded use can help facilitate the prioritization of candidate HIV-1 vaccines, ensuring that resources are focused on the most promising candidates. Vaccine designers must now develop T cell vaccine strategies that reduce viral load after heterologous challenge.     

Commentary on "Principal stratification - a goal or a tool?" by Judea Pearl

This commentary takes up Pearl's welcome challenge to clearly articulate the scientific value of principal stratification estimands that we and colleagues have investigated, in the area of randomized placebo-controlled preventive vaccine efficacy trials, especially trials of HIV vaccines. After briefly arguing that certain principal stratification estimands for studying vaccine effects on post-infection outcomes are of genuine scientific interest, the bulk of our commentary argues that the "causal effect predictiveness" (CEP) principal stratification estimand for evaluating immune biomarkers as surrogate endpoints is not of ultimate scientific interest, because it evaluates surrogacy restricted to the setting of a particular vaccine efficacy trial, but is nevertheless useful for guiding the selection of primary immune biomarker endpoints in Phase I/II vaccine trials and for facilitating assessment of transportability/bridging surrogacy.     

Impact of gene-modified T cells on HIV infection dynamics

Previous clinical trials in HIV-infected patients involving infusion of T cells protected by an antiviral gene have failed to show any therapeutic benefit. The value of such a treatment approach is thus still highly controversial. In this study, the anticipated effects of gene-modified cells on virus and T-cell kinetics are analysed by mathematical modeling. Because technically only a small fraction of all T cells in a patient can be manipulated ex vivo, therapeutic success will depend on the accumulation of gene-modified cells after infusion into the patient by in vivo selection. Our simulations predict that a significant therapeutic benefit is conferred only by antiviral genes that inhibit HIV replication before virus integration (class I genes). Genes that inhibit viral protein expression (class II, used in previous clinical trials), require a much higher inhibitory activity than class I genes to promote the regeneration of T cells and reduce the viral load. Inhibition of virus assembly and release alone (class III) confers no selective advantage to the T cell and is therefore ineffective unless combined with class I (or, possibly, class II) genes. Also crucial in determining the clinical outcome are the regenerative capacity of the gene-modified cells and the level of HIV replication in the patient. These results can be important for guiding future strategies in the field of gene therapy for HIV infection.     

Human immunodeficiency virus (HIV) vaccine trials: a novel assay for differential diagnosis of HIV infections in the face of vaccine-generated antibodies

All current human immunodeficiency virus (HIV) vaccine candidates contain multiple viral components and elicit antibodies that react positively in licensed HIV diagnostic tests, which contain similar viral products. Thus, vaccine trial participants could be falsely diagnosed as infected with HIV. Additionally, uninfected, seropositive vaccinees may encounter long-term social and economic harms. Moreover, this also interferes with early detection of true HIV infections during preventive HIV vaccine trials. An HIV-seropositive test result among uninfected vaccine trial participants is a major public health concern for volunteers who want to participate in future HIV vaccine trials. Based on the increased number of HIV vaccines being tested globally, it is essential to differentiate vaccine- from virus-induced antibodies. Using a whole-HIV-genome phage display library, we identified conserved sequences in Env-gp41 and Gag-p6 which are recognized soon after infection, do not contain protective epitopes, and are not part of most current HIV vaccines. We established a new HIV serodetection assay based on these peptides. To date, this assay, termed HIV-SELECTEST, demonstrates >99% specificity and sensitivity. Importantly, in testing of plasma samples from multiple HIV vaccine trials, uninfected trial participants scored negative, while all intercurrent infections were detected within 1 to 3 months of HIV infection. The new HIV-SELECTEST is a simple but robust diagnostic tool for easy implementation in HIV vaccine trials and blood banks worldwide.     

High Heritability Is Compatible with the Broad Distribution of Set Point Viral Load in HIV Carriers

Set point viral load in HIV patients ranges over several orders of magnitude and is a key determinant of disease progression in HIV. A number of recent studies have reported high heritability of set point viral load implying that viral genetic factors contribute substantially to the overall variation in viral load. The high heritability is surprising given the diversity of host factors associated with controlling viral infection. Here we develop an analytical model that describes the temporal changes of the distribution of set point viral load as a function of heritability. This model shows that high heritability is the most parsimonious explanation for the observed variance of set point viral load. Our results thus not only reinforce the credibility of previous estimates of heritability but also shed new light onto mechanisms of viral pathogenesis.     

Multiple independent origins of a protease inhibitor resistance mutation in salvage therapy patients

With the continuing march of the AIDS epidemic and little hope for an effective vaccine in the near future, work to develop a topical strategy to prevent HIV infection is increasingly important. This stated, the track record of large scale "microbicide" trials has been disappointing with nonspecific inhibitors either failing to protect women from infection or even increasing HIV acquisition. Newer strategies that target directly the elements needed for viral entry into cells have shown promise in non-human primate models of HIV transmission and as these agents have not yet been broadly introduced in regions of highest HIV prevalence, they are particularly attractive for prophylaxis. We review here the agents that can block HIV cellular entry and that show promise as topical strategies or "virustats" to prevent mucosal transmission of HIV infection     

HIV-1 Vaccine-Induced T-Cell Reponses Cluster in Epitope Hotspots that Differ from Those Induced in Natural Infection with HIV-1

Several recent large clinical trials evaluated HIV vaccine candidates that were based on recombinant adenovirus serotype 5 (rAd-5) vectors expressing HIV-derived antigens. These vaccines primarily elicited T-cell responses, which are known to be critical for controlling HIV infection. In the current study, we present a meta-analysis of epitope mapping data from 177 participants in three clinical trials that tested two different HIV vaccines: MRKAd-5 HIV and VRC-HIVAD014-00VP. We characterized the population-level epitope responses in these trials by generating population-based epitope maps, and also designed such maps using a large cohort of 372 naturally infected individuals. We used these maps to address several questions: (1) Are vaccine-induced responses randomly distributed across vaccine inserts, or do they cluster into immunodominant epitope hotspots? (2) Are the immunodominance patterns observed for these two vaccines in three vaccine trials different from one another? (3) Do vaccine-induced hotspots overlap with epitope hotspots induced by chronic natural infection with HIV-1? (4) Do immunodominant hotspots target evolutionarily conserved regions of the HIV genome? (5) Can epitope prediction methods be used to identify these hotspots? We found that vaccine responses clustered into epitope hotspots in all three vaccine trials and some of these hotspots were not observed in chronic natural infection. We also found significant differences between the immunodominance patterns generated in each trial, even comparing two trials that tested the same vaccine in different populations. Some of the vaccine-induced immunodominant hotspots were located in highly variable regions of the HIV genome, and this was more evident for the MRKAd-5 HIV vaccine. Finally, we found that epitope prediction methods can partially predict the location of vaccine-induced epitope hotspots. Our findings have implications for vaccine design and suggest a framework by which different vaccine candidates can be compared in early phases of evaluation.     

From fundamental immunology to development of vaccinology

In the last ten years research in vaccinology has been developed in the world to conceive new vaccine approaches against infections like HIV/AIDS. Jean-Gérard Guillet is a pioneer in the development of new vaccine strategies. From the first results he obtained in the late 80's on the presentation of antigenic peptides to T cells, he axed his work on the study of induction mechanisms of T cell mediated immune responses. The selection of antigenic peptides and the search to enhance antigen immunogenicity led him to elaborate lipopeptides as new vaccine formulae. The efficacy of these preparations was tested in animal models (mouse, macaque) and, thereafter, in humans with clinical trials promoted by the French National Agency for AIDS and viral hepatitis (ANRS). The study of T-cell induced responses in vaccinated volunteers was implemented following the creation of two facilities, an immuno-monitoring platform and the Clinical Investigation Centre Cochin-Pasteur, a structure specialized in vaccinology.     

Translation of HLA-HIV associations to the cellular level: HIV adapts to inflate CD8 T cell responses against Nef and HLA-adapted variant epitopes

Strong statistical associations between polymorphisms in HIV-1 population sequences and carriage of HLA class I alleles have been widely used to identify possible sites of CD8 T cell immune selection in vivo. However, there have been few attempts to prospectively and systematically test these genetic hypotheses arising from population-based studies at a cellular, functional level. We assayed CD8 T cell epitope-specific IFN-γ responses in 290 individuals from the same cohort, which gave rise to 874 HLA-HIV associations in genetic analyses, taking into account autologous viral sequences and individual HLA genotypes. We found immunological evidence for 58% of 374 associations tested as sites of primary immune selection and identified up to 50 novel HIV-1 epitopes using this reverse-genomics approach. Many HLA-adapted epitopes elicited equivalent or higher-magnitude IFN-γ responses than did the nonadapted epitopes, particularly in Nef. At a population level, inclusion of all of the immunoreactive variant CD8 T cell epitopes in Gag, Pol, Nef, and Env suggested that HIV adaptation leads to an inflation of Nef-directed immune responses relative to other proteins. We concluded that HLA-HIV associations mark viral epitopes subject to CD8 T cell selection. These results can be used to guide functional studies of specific epitopes and escape mutations, as well as to test, train, and evaluate analytical models of viral escape and fitness. The inflation of Nef and HLA-adapted variant responses may have negative effects on natural and vaccine immunity against HIV and, therefore, has implications for diversity coverage approaches in HIV vaccine design.     

A new generation of HIV vaccines

WHO estimates that currently there are 40 million individuals living with HIV and there are 16000 new infections daily, worldwide. The best strategy to control the AIDS epidemic would be the development of an effective vaccine. New strategies for vaccine development have gained momentum over the past decade, some of which show greater promise in macaque models than did earlier protein-subunit or recombinant-canarypox strategies. These new vaccines include DNA vaccines and live viral vectors, and have been based on the generation of high levels of antiviral T cells. These vaccines do not prevent infection, but rather control virus replication with a rapid expansion and then contraction of antiviral T cells in response to the challenge infection. These recent vaccine successes in macaques raise hope that a vaccine can be developed that will successfully limit both the development of AIDS and viral transmission.     

Modeling the short-, middle- and long-term viral load responses for comparing estimated dynamic parameters

A virologic marker, the number of HIV RNA copies or viral load, is currently used to evaluate antiviral therapies in AIDS clinical trials. This marker can be used to assess the antiviral potency of therapies, but is easily affected by drug exposures, drug resistance and other factors during the long-term treatment evaluation process. The study of HIV dynamics is one of the most important development in recent AIDS research for understanding the pathogenesis of HIV-1 infection and antiviral treatment strategies. Although many HIV dynamic models have been proposed by AIDS researchers in the last decade, they have only been used to quantify short-term viral dynamics and do not correctly describe long-term virologic responses to antiretroviral treatment. In other words, these simple viral dynamic models can only be used to fit short-term viral load data for estimating dynamic parameters. In this paper, a mechanism-based differential equation models is introduced for characterizing the long-term viral dynamics with antiretroviral therapy. We applied this model to fit different segments of the viral load trajectory data from a simulation experiment and an AIDS clinical trial study, and found that the estimates of dynamic parameters from our modeling approach are very consistent. We may conclude that our model can not only characterize long-term viral dynamics, but can also quantify short- and middle-term viral dynamics. It suggests that if there are enough data in the early stage of the treatment, the results from our modeling based on short-term information can be used to capture the performance of long-term care with HIV-1 infected patients.     

Relevance of studying T cell responses in SIV-infected rhesus macaques

HIV infection, once established, is never cleared. Rare individuals do, however, control viral replication to low levels. These successful immune responses are primarily linked to certain class I MHC alleles (MHC-I). Because of this association, many AIDS vaccines in development are designed to generate virus-specific CD8+ T cells. The Merck STEP phase 2b efficacy trial of one such vaccine was recently halted, and declared a failure. Thus, basic questions regarding what constitutes an effective T cell response and how such responses could be elicited by vaccination remain open. The best animal model available to explore such issues is simian immunodeficiency virus infection of rhesus macaques, which serves as the primary proving ground for AIDS vaccines.     

Proliferative capacity of epitope-specific CD8 T-cell responses is inversely related to viral load in chronic human immunodeficiency virus type 1 infection

The relationship between the function of human immunodeficiency virus (HIV)-specific CD8 T-cell responses and viral load has not been defined. In this study, we used a panel of major histocompatibility complex class I tetramers to examine responses to frequently targeted CD8 T-cell epitopes in a large cohort of antiretroviral-therapy-na?ve HIV type 1 clade C virus-infected persons in KwaZulu Natal, South Africa. In terms of effector functions of proliferation, cytokine production, and degranulation, only proliferation showed a significant correlation with viral load. This robust inverse relationship provides an important functional correlate of viral control relevant to both vaccine design and evaluation.     

Identification of Effective Subdominant Anti-HIV-1 CD8+ T Cells Within Entire Post-infection and Post-vaccination Immune Responses

Defining the components of an HIV immunogen that could induce effective CD8+ T cell responses is critical to vaccine development. We addressed this question by investigating the viral targets of CD8+ T cells that potently inhibit HIV replication in vitro, as this is highly predictive of virus control in vivo. We observed broad and potent ex vivo CD8+ T cell-mediated viral inhibitory activity against a panel of HIV isolates among viremic controllers (VC, viral loads <5000 copies/ml), in contrast to unselected HIV-infected HIV Vaccine trials Network (HVTN) participants. Viral inhibition of clade-matched HIV isolates was strongly correlated with the frequency of CD8+ T cells targeting vulnerable regions within Gag, Pol, Nef and Vif that had been identified in an independent study of nearly 1000 chronically infected individuals. These vulnerable and so-called “beneficial” regions were of low entropy overall, yet several were not predicted by stringent conservation algorithms. Consistent with this, stronger inhibition of clade-matched than mismatched viruses was observed in the majority of subjects, indicating better targeting of clade-specific than conserved epitopes. The magnitude of CD8+ T cell responses to beneficial regions, together with viral entropy and HLA class I genotype, explained up to 59% of the variation in viral inhibitory activity, with magnitude of the T cell response making the strongest unique contribution. However, beneficial regions were infrequently targeted by CD8+ T cells elicited by vaccines encoding full-length HIV proteins, when the latter were administered to healthy volunteers and HIV-positive ART-treated subjects, suggesting that immunodominance hierarchies undermine effective anti-HIV CD8+ T cell responses. Taken together, our data support HIV immunogen design that is based on systematic selection of empirically defined vulnerable regions within the viral proteome, with exclusion of immunodominant decoy epitopes that are irrelevant for HIV control.     

HIV 10 years later-where do we stand now?

A wide variety of up-to-date results and knowledge were presented at the 10th International AIDS Meeting, Yokohama. Epidemiologically, most interest was focused on the discovery of a new HIV subtype O, which cannot be reliably detected by currently available ELISA kits. Clinically, it is gradually appreciated that one single most important parameter is the viral load; the extent of viral load can help explain many clinical observations. Another eye-catching finding was the report of a clinical follow-up of a group of long-term nonprogressors. If the underlying operative mechanism can be elucidated, we can learn the necessary elements for halting HIV infection progression. Therapeutically, the trend has shifted to combination therapy, preferentially 3-drug combination of 2 RT inhibitors and 1 protease inhibitor. For the vaccine development, many novel vectors were introduced, but their potentials are unknown at present. The successful application of single-cell in situ PCR has changed our perception of HIV infection. This powerful technique can detect a single viral genome inside cells and revealed that a large proportion of cells already harbor HIV genomes soon after the entry of HIV into the body. A direct viral effect may fully explain subsequent T cell depletion without invoking a lot of indirect mechanisms such as apoptosis.     

Natural variation in HIV infection: Monte Carlo estimates that include CD8 effector cells

Viral load and CD4 T-cell counts in patients infected with the human immunodeficiency virus (HIV) are commonly used to guide clinical decisions regarding drug therapy or to assess therapeutic outcomes in clinical trials. However, random fluctuations in these markers of infection can obscure clinically significant change. We employ a Monte Carlo simulation to investigate contributing factors in the expected variability in CD4 T-cell count and viral load due solely to the stochastic nature of HIV infection. The simulation includes processes that contribute to the variability in HIV infection including CD4 and CD8 T-cell population dynamics as well as T-cell activation and proliferation. The simulation results may reconcile the wide range of variabilities in viral load observed in clinical studies, by quantifying correlations between viral load measurements taken days or weeks apart. The sensitivity of variability in T-cell count and viral load to changes in the lifetimes of CD4 and CD8 T-cells is investigated, as well as the effects of drug therapy.     

Predicting the impact of a nonsterilizing vaccine against human immunodeficiency virus

Studies of human immunodeficiency virus (HIV) vaccines in animal models suggest that it is difficult to induce complete protection from infection (sterilizing immunity) but that it is possible to reduce the viral load and to slow or prevent disease progression following infection. We have developed an age-structured epidemiological model of the effects of a disease-modifying HIV vaccine that incorporates the intrahost dynamics of infection, a transmission rate and host mortality that depend on the viral load, the possible evolution and transmission of vaccine escape mutant viruses, a finite duration of vaccine protection, and possible changes in sexual behavior. Using this model, we investigated the long-term outcome of a disease-modifying vaccine and utilized uncertainty analysis to quantify the effects of our lack of precise knowledge of various parameters. Our results suggest that the extent of viral load reduction in vaccinated infected individuals (compared to unvaccinated individuals) is the key predictor of vaccine efficacy. Reductions in viral load of about 1 log(10) copies ml(-1) would be sufficient to significantly reduce HIV-associated mortality in the first 20 years after the introduction of vaccination. Changes in sexual risk behavior also had a strong impact on the epidemic outcome. The impact of vaccination is dependent on the population in which it is used, with disease-modifying vaccines predicted to have the most impact in areas of low prevalence and rapid epidemic growth. Surprisingly, the extent to which vaccination alters disease progression, the rate of generation of escape mutants, and the transmission of escape mutants are predicted to have only a weak impact on the epidemic outcome over the first 25 years after the introduction of a vaccine.