The phase III RV144 HIV-1 vaccine trial estimated vaccine efficacy (VE) to be 31.2%. This trial demonstrated that the presence of HIV-1–specific IgG-binding Abs to envelope (Env) V1V2 inversely correlated with infection risk, while the presence of Env-specific plasma IgA Abs directly correlated with risk of HIV-1 infection. Moreover, Ab-dependent cellular cytotoxicity responses inversely correlated with risk of infection in vaccine recipients with low IgA; therefore, we hypothesized that vaccine-induced Fc receptor–mediated (FcR-mediated) Ab function is indicative of vaccine protection. We sequenced exons and surrounding areas of FcR-encoding genes and found one FCGR2C tag SNP (rs114945036) that associated with VE against HIV-1 subtype CRF01_AE, with lysine at position 169 (169K) in the V2 loop (CRF01_AE 169K). Individuals carrying CC in this SNP had an estimated VE of 15%, while individuals carrying CT or TT exhibited a VE of 91%. Furthermore, the rs114945036 SNP was highly associated with 3 other FCGR2C SNPs (rs138747765, rs78603008, and rs373013207). Env-specific IgG and IgG3 Abs, IgG avidity, and neutralizing Abs inversely correlated with CRF01_AE 169K HIV-1 infection risk in the CT- or TT-carrying vaccine recipients only. These data suggest a potent role of Fc-γ receptors and Fc-mediated Ab function in conferring protection from transmission risk in the RV144 VE trial.
The RV144 clinical trial showed the partial efficacy of a vaccine regimen with an estimated vaccine efficacy (VE) of 31% for protecting low-risk Thai volunteers against acquisition of HIV-1. The impact of vaccine-induced immune responses can be investigated through sieve analysis of HIV-1 breakthrough infections (infected vaccine and placebo recipients). A V1/V2-targeted comparison of the genomes of HIV-1 breakthrough viruses identified two V2 amino acid sites that differed between the vaccine and placebo groups. Here we extended the V1/V2 analysis to the entire HIV-1 genome using an array of methods based on individual sites, k-mers and genes/proteins. We identified 56 amino acid sites or “signatures” and 119 k-mers that differed between the vaccine and placebo groups. Of those, 19 sites and 38 k-mers were located in the regions comprising the RV144 vaccine (Env-gp120, Gag, and Pro). The nine signature sites in Env-gp120 were significantly enriched for known antibody-associated sites (p = 0.0021). In particular, site 317 in the third variable loop (V3) overlapped with a hotspot of antibody recognition, and sites 369 and 424 were linked to CD4 binding site neutralization. The identified signature sites significantly covaried with other sites across the genome (mean = 32.1) more than did non-signature sites (mean = 0.9) (p < 0.0001), suggesting functional and/or structural relevance of the signature sites. Since signature sites were not preferentially restricted to the vaccine immunogens and because most of the associations were insignificant following correction for multiple testing, we predict that few of the genetic differences are strongly linked to the RV144 vaccine-induced immune pressure. In addition to presenting results of the first complete-genome analysis of the breakthrough infections in the RV144 trial, this work describes a set of statistical methods and tools applicable to analysis of breakthrough infection genomes in general vaccine efficacy trials for diverse pathogens.
We present an analysis of the genomes of the HIV viruses that infected some participants of the RV144 Thai trial, which was the first study to show efficacy of a vaccine to prevent HIV infection. We analyzed the HIV genomes of infected vaccine recipients and infected placebo recipients, and found differences between them. These differences coincide with previously-studied genetic features that are relevant to the biology of HIV infection, including features involved in immune recognition of the virus. The findings presented here generate testable hypotheses about the mechanism of the partial protection seen in the Thai trial, and may ultimately lead to improved vaccines. The article also presents a toolkit of methods for computational analyses that can be applied to other vaccine efficacy trials.
Cause-specific proportional hazards models are commonly used for analyzing competing risks data in clinical studies. Motivated by the objective to assess differential vaccine protection against distinct pathogen types in randomized preventive vaccine efficacy trials, we present an alternative case-only method to standard maximum partial likelihood estimation that applies to a rare failure event, e.g. acquisition of HIV infection. A logistic regression model is fit to the counts of cause-specific events (infecting pathogen type) within study arms, with an offset adjusting for the randomization ratio. This formulation of cause-specific hazard ratio estimation permits immediate incorporation of host-genetic factors to be assessed as effect modifiers, an important area of vaccine research for identifying immune correlates of protection, thus inheriting the estimation efficiency, and cost benefits of the case-only estimator commonly used for assessing gene–treatment interactions. The method is used to reassess HIV genotype-specific vaccine efficacy in the RV144 trial, providing nearly identical results to standard Cox methods, and to assess if and how this vaccine efficacy depends on Fc-γ receptor genes.
Gene–treatment interaction; Sieve analysis; Vaccine efficacy
Elevated risk of HIV-1 infection among recipients of an adenovirus serotype 5 (Ad5)-vectored HIV-1 vaccine was previously reported in the Step HIV-1 vaccine efficacy trial. We assessed pre-infection cellular immune responses measured at 4 weeks after the second vaccination to determine their roles in HIV-1 infection susceptibility among Step study male participants.
We examined ex vivo interferon-γ (IFN-γ) secretion from peripheral blood mononuclear cells (PBMC) using an ELISpot assay in 112 HIV-infected and 962 uninfected participants. In addition, we performed flow cytometric assays to examine T-cell activation, and ex vivo IFN-γ and interleukin-2 secretion from CD4+ and CD8+ T cells. We accounted for the sub-sampling design in Cox proportional hazards models to estimate hazard ratios (HRs) of HIV-1 infection per 1-loge increase of the immune responses.
We found that HIV-specific immune responses were not associated with risk of HIV-1 infection. However, each 1-loge increase of mock responses measured by the ELISpot assay (i.e., IFN-γ secretion in the absence of antigen-specific stimulation) was associated with a 62% increase of HIV-1 infection risk among vaccine recipients (HR = 1.62, 95% CI: (1.28, 2.04), p<0.001). This association remains after accounting for CD4+ or CD8+ T-cell activation. We observed a moderate correlation between ELISpot mock responses and CD4+ T-cells secreting IFN-γ (ρ = 0.33, p = 0.007). In addition, the effect of the Step vaccine on infection risk appeared to vary with ELISpot mock response levels, especially among participants who had pre-existing anti-Ad5 antibodies (interaction p = 0.04).
The proportion of cells, likely CD4+ T-cells, producing IFN-γ without stimulation by exogenous antigen appears to carry information beyond T-cell activation and baseline characteristics that predict risk of HIV-1 infection. These results motivate additional investigation to understand the potential link between IFN-γ secretion and underlying causes of elevated HIV-1 infection risk among vaccine recipients in the Step study.
The contribution of host T-cell immunity and HLA class I alleles to the control of human immunodeficiency virus (HIV-1) replication in natural infection is widely recognized. We assessed whether vaccine-induced T-cell immunity, or expression of certain HLA alleles, impacted HIV-1 control after infection in the Step MRKAd5/HIV-1 gag/pol/nef study. Vaccine-induced T cells were associated with reduced plasma viremia, with subjects targeting ≥3 gag peptides presenting with half-log lower mean viral loads than subjects without Gag responses. This effect was stronger in participants infected proximal to vaccination and was independent of our observed association of HLA-B*27, –B*57 and –B*58:01 alleles with lower HIV-1 viremia. These findings support the ability of vaccine-induced T-cell responses to influence postinfection outcome and provide a rationale for the generation of T-cell responses by vaccination to reduce viremia if protection from acquisition is not achieved. Clinical trials identifier: NCT00095576.
HIV-1 vaccine; Step study; Gag-specific T cells; HLA class I alleles
HIV-1–specific immunoglobulin G (IgG) subclass antibodies bind to distinct cellular Fc receptors. Antibodies of the same epitope specificity but of a different subclass therefore can have different antibody effector functions. The study of IgG subclass profiles between different vaccine regimens used in clinical trials with divergent efficacy outcomes can provide information on the quality of the vaccine-induced B cell response. We show that HIV-1–specific IgG3 distinguished two HIV-1 vaccine efficacy studies (RV144 and VAX003 clinical trials) and correlated with decreased risk of HIV-1 infection in a blinded follow-up case-control study with the RV144 vaccine. HIV-1–specific IgG3 responses were not long-lived, which was consistent with the waning efficacy of the RV144 vaccine. These data suggest that specific vaccine-induced HIV-1 IgG3 should be tested in future studies of immune correlates in HIV-1 vaccine efficacy trials.
Purpose of review
The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine.
The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 and RV144, led to numerous studies in the last five years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses.
Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons while correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection.
HIV-1 breakthrough infections; sieve analysis; viral genetics; vaccine-induced immune responses
The RV144 HIV-1 vaccine trial demonstrated partial efficacy of 31% against HIV-1 infection. Studies into possible correlates of protection found that antibodies specific to the V1 and V2 (V1/V2) region of envelope correlated inversely with infection risk and that viruses isolated from trial participants contained genetic signatures of vaccine-induced pressure in the V1/V2 region. We explored the hypothesis that the genetic signatures in V1 and V2 could be partly attributed to selection by vaccine-primed T cells. We performed a T-cell-based sieve analysis of breakthrough viruses in the RV144 trial and found evidence of predicted HLA binding escape that was greater in vaccine versus placebo recipients. The predicted escape depended on class I HLA A*02- and A*11-restricted epitopes in the MN strain rgp120 vaccine immunogen. Though we hypothesized that this was indicative of postacquisition selection pressure, we also found that vaccine efficacy (VE) was greater in A*02-positive (A*02+) participants than in A*02− participants (VE = 54% versus 3%, P = 0.05). Vaccine efficacy against viruses with a lysine residue at site 169, important to antibody binding and implicated in vaccine-induced immune pressure, was also greater in A*02+ participants (VE = 74% versus 15%, P = 0.02). Additionally, a reanalysis of vaccine-induced immune responses that focused on those that were shown to correlate with infection risk suggested that the humoral responses may have differed in A*02+ participants. These exploratory and hypothesis-generating analyses indicate there may be an association between a class I HLA allele and vaccine efficacy, highlighting the importance of considering HLA alleles and host immune genetics in HIV vaccine trials.
IMPORTANCE The RV144 trial was the first to show efficacy against HIV-1 infection. Subsequently, much effort has been directed toward understanding the mechanisms of protection. Here, we conducted a T-cell-based sieve analysis, which compared the genetic sequences of viruses isolated from infected vaccine and placebo recipients. Though we hypothesized that the observed sieve effect indicated postacquisition T-cell selection, we also found that vaccine efficacy was greater for participants who expressed HLA A*02, an allele implicated in the sieve analysis. Though HLA alleles have been associated with disease progression and viral load in HIV-1 infection, these data are the first to suggest the association of a class I HLA allele and vaccine efficacy. While these statistical analyses do not provide mechanistic evidence of protection in RV144, they generate testable hypotheses for the HIV vaccine community and they highlight the importance of assessing the impact of host immune genetics in vaccine-induced immunity and protection. (This study has been registered at ClinicalTrials.gov under registration no. NCT00223080.)
To overcome the problem of HIV-1 variability, candidate vaccine antigens have been designed to be composed of conserved elements of the HIV-1 proteome. Such candidate vaccines could be improved with a better understanding of both HIV-1 evolutionary constraints and the fitness cost of specific mutations. We evaluated the in vitro fitness cost of 23 mutations engineered in the HIV-1 subtype B Gag-p24 Center-of-Tree (COT) protein through fitness competition assays. While some mutations at conserved sites exacted a high fitness cost, as expected under the assumption that the most conserved residue confers the highest fitness, there was no overall strong relationship between sequence conservation and replicative capacity. By comparing sites that have evolved since the beginning of the epidemic to those that have remain unchanged, we found that sites that have evolved over time were more likely to correspond to HLA-associated sites and that their mutation had limited fitness costs. Our data showed no transcendent link between high conservation and high fitness cost, indicating that merely focusing on conserved segments of HIV-1 would not be sufficient for a successful vaccine strategy. Nonetheless, a subset of sites exacted a high fitness cost upon mutation—these sites have been under selective pressure to change since the beginning of the epidemic but have proved virtually nonmutable and could constitute preferred targets for vaccine design.
A safe and effective vaccine for the prevention of human immunodeficiency virus type 1 (HIV-1) infection is a global priority. We tested the efficacy of a DNA prime–recombinant adenovirus type 5 boost (DNA/rAd5) vaccine regimen in persons at increased risk for HIV-1 infection in the United States.
At 21 sites, we randomly assigned 2504 men or transgender women who have sex with men to receive the DNA/rAd5 vaccine (1253 participants) or placebo (1251 participants). We assessed HIV-1 acquisition from week 28 through month 24 (termed week 28+ infection), viral-load set point (mean plasma HIV-1 RNA level 10 to 20 weeks after diagnosis), and safety. The 6-plasmid DNA vaccine (expressing clade B Gag, Pol, and Nef and Env proteins from clades A, B, and C) was administered at weeks 0, 4, and 8. The rAd5 vector boost (expressing clade B Gag-Pol fusion protein and Env glycoproteins from clades A, B, and C) was administered at week 24.
In April 2013, the data and safety monitoring board recommended halting vaccinations for lack of efficacy. The primary analysis showed that week 28+ infection had been diagnosed in 27 participants in the vaccine group and 21 in the placebo group (vaccine efficacy, −25.0%; 95% confidence interval, −121.2 to 29.3; P = 0.44), with mean viral-load set points of 4.46 and 4.47 HIV-1 RNA log10 copies per milliliter, respectively. Analysis of all infections during the study period (41 in the vaccine group and 31 in the placebo group) also showed lack of vaccine efficacy (P = 0.28). The vaccine regimen had an acceptable side-effect profile.
The DNA/rAd5 vaccine regimen did not reduce either the rate of HIV-1 acquisition or the viral-load set point in the population studied. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT00865566.)
Neutralizing antibody assays are widely used in research toward development of a preventive HIV-1 vaccine. Currently, the neutralization potency of an antibody is typically quantified by the inhibitory concentration (IC) values (e.g., IC50), and the neutralization breadth is estimated by the empirical method. In this paper, we propose the AUC and pAUC measures for summarizing the titration curve, which complement the commonly used IC measure. We present multiple advantages of AUC over IC50, which include no complications due to censoring, the capability to explore low-level neutralization, and improved coverage probabilities and efficiency of estimators. We also propose statistical methods for determining positive neutralization and for estimating the neutralization breadth. The simulation results suggest that the AUC measure is preferable in particular as IC50s get closer to the highest concentration of antibodies tested. For the majority of the assay data, the AUC method is more powerful than the IC50 method. However, since these methods test different hypotheses, it is not unexpected that some virus-antibody combinations are AUC positive but IC50 negative or vice versa.
AUC; breadth; HIV-1; neutralization assay; polynomial model; titration curve
In the RV144 HIV-1 vaccine efficacy trial, IgG antibody (Ab) binding levels to variable regions 1 and 2 (V1V2) of the HIV-1 envelope glycoprotein gp120 were an inverse correlate of risk of HIV-1 infection. To determine if V1V2-specific Abs cross-react with V1V2 from different HIV-1 subtypes, if the nature of the V1V2 antigen used to asses cross-reactivity influenced infection risk, and to identify immune assays for upcoming HIV-1 vaccine efficacy trials, new V1V2-scaffold antigens were designed and tested. Protein scaffold antigens carrying the V1V2 regions from HIV-1 subtypes A, B, C, D or CRF01_AE were assayed in pilot studies, and six were selected to assess cross-reactive Abs in the plasma from the original RV144 case-control cohort (41 infected vaccinees, 205 frequency-matched uninfected vaccinees, and 40 placebo recipients) using ELISA and a binding Ab multiplex assay. IgG levels to these antigens were assessed as correlates of risk in vaccine recipients using weighted logistic regression models. Levels of Abs reactive with subtype A, B, C and CRF01_AE V1V2-scaffold antigens were all significant inverse correlates of risk (p-values of 0.0008–0.05; estimated odds ratios of 0.53–0.68 per 1 standard deviation increase). Thus, levels of vaccine-induced IgG Abs recognizing V1V2 regions from multiple HIV-1 subtypes, and presented on different scaffolds, constitute inverse correlates of risk for HIV-1 infection in the RV144 vaccine trial. The V1V2 antigens provide a link between RV144 and upcoming HIV-1 vaccine trials, and identify reagents and methods for evaluating V1V2 Abs as possible correlates of protection against HIV-1 infection.
Assays for detecting levels of antiretroviral drugs in study participants are increasingly popular in preexposure prophylaxis (PrEP) trials, since they provide an objective measure of adherence. Current correlation analyses of drug concentration data are prone to bias. In this article, we formulate the causal estimand of prevention efficacy among drug compliers, those who would have had a threshold level of drug concentration had they been assigned to the drug arm of the trial. The identifiability of the causal estimand is facilitated by exploiting the exclusion restriction; that is, drug noncompliers do not acquire any prevention benefit. In addition, we develop an approach to sensitivity analysis that relaxes the exclusion restriction. Applications to published data from 2 PrEP trials, namely the Preexposure Prophylaxis Initiative (iPrEx) trial and the Centre for the AIDS Programme of Research in South Africa (CAPRISA) 004 trial, suggest high efficacy estimates among drug compliers (in the iPrEx trial, odds ratio = 0.097 (95% confidence interval: 0.027, 0.352); in the CAPRISA 004 trial, odds ratio = 0.104 (95% confidence interval: 0.024, 0.447)). In summary, the proposed inferential method provides an unbiased assessment of PrEP efficacy among drug compliers, thus adding to the primary intention-to-treat analysis and correlation analyses of drug concentration data.
causal inference; compliance; exclusion restriction; potential outcome; principal stratification; two-phase sampling
For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates (Prentice and others, 1978. The analysis of failure time in the presence of competing risks. Biometrics 34, 541–554). Inspired by previous research in HIV vaccine efficacy trials, the cause of failure is replaced by a continuous mark observed only in subjects who fail. This article studies an extension of this approach to allow a multivariate continuum of competing risks, to better account for the fact that the candidate HIV vaccines tested in efficacy trials have contained multiple HIV sequences, with a purpose to elicit multiple types of immune response that recognize and block different types of HIV viruses. We develop inference for the proportional hazards model in which the regression parameters depend parametrically on the marks, to avoid the curse of dimensionality, and the baseline hazard depends nonparametrically on both time and marks. Goodness-of-fit tests are constructed based on generalized weighted martingale residuals. The finite-sample performance of the proposed methods is examined through extensive simulations. The methods are applied to a vaccine efficacy trial to examine whether and how certain antigens represented inside the vaccine are relevant for protection or anti-protection against the exposing HIVs.
Competing risks; Failure time data; Goodness-of-fit test; HIV vaccine trial; Hypothesis testing; Mark-specific relative risk; Multivariate data; Partial likelihood estimation; Semiparametric model; STEP trial
Assessing per-protocol treatment effcacy on a time-to-event endpoint is a common
objective of randomized clinical trials. The typical analysis uses the same method employed for the
intention-to-treat analysis (e.g., standard survival analysis) applied to the subgroup meeting
protocol adherence criteria. However, due to potential post-randomization selection bias, this
analysis may mislead about treatment efficacy. Moreover, while there is extensive literature on
methods for assessing causal treatment effects in compliers, these methods do not apply to a common
class of trials where a) the primary objective compares survival curves, b) it is inconceivable to
assign participants to be adherent and event-free before adherence is measured, and c) the exclusion
restriction assumption fails to hold. HIV vaccine efficacy trials including the recent RV144 trial
exemplify this class, because many primary endpoints (e.g., HIV infections) occur before adherence
is measured, and nonadherent subjects who receive some of the planned immunizations may be partially
protected. Therefore, we develop methods for assessing per-protocol treatment efficacy for this
problem class, considering three causal estimands of interest. Because these estimands are not
identifiable from the observable data, we develop nonparametric bounds and semiparametric
sensitivity analysis methods that yield estimated ignorance and uncertainty intervals. The methods
are applied to RV144.
As-treated; Bounds; Causal inference; Exclusion restriction; Ignorance region; Intention to treat; Principal stratification; Selection bias; Survival analysis
This paper considers generalized linear quantile regression for competing risks data when the failure type may be missing. Two estimation procedures for the regression co-efficients, including an inverse probability weighted complete-case estimator and an augmented inverse probability weighted estimator, are discussed under the assumption that the failure type is missing at random. The proposed estimation procedures utilize supplemental auxiliary variables for predicting the missing failure type and for informing its distribution. The asymptotic properties of the two estimators are derived and their asymptotic efficiencies are compared. We show that the augmented estimator is more efficient and possesses a double robustness property against misspecification of either the model for missingness or for the failure type. The asymptotic covariances are estimated using the local functional linearity of the estimating functions. The finite sample performance of the proposed estimation procedures are evaluated through a simulation study. The methods are applied to analyze the ‘Mashi’ trial data for investigating the effect of formula-versus breast-feeding plus extended infant zidovudine prophylaxis on HIV-related death of infants born to HIV-infected mothers in Botswana.
Augmented inverse probability weighted; Auxiliary variables; Competing risks; Double robustness; Efficient estimator; Estimating equation; Inverse probability weighted; Local functional linearity; Logistic regression; Mashi trial; Missing at random; Quantile regression
The RV144 vaccine trial in Thailand demonstrated that an HIV vaccine could prevent infection in humans and highlights the importance of understanding protective immunity against HIV. We used a nonhuman primate model to define immune and genetic mechanisms of protection against mucosal infection by the simian immunodeficiency virus (SIV). A plasmid DNA prime/recombinant adenovirus serotype 5 (rAd5) boost vaccine regimen was evaluated for its ability to protect monkeys from infection by SIVmac251 or SIVsmE660 isolates after repeat intrarectal challenges. Although this prime-boost vaccine regimen failed to protect against SIVmac251 infection, 50% of vaccinated monkeys were protected from infection with SIVsmE660. Among SIVsmE660-infected animals, there was an about one-log reduction in peak plasma virus RNA in monkeys expressing the major histocompatibility complex class I allele Mamu-A*01, implicating cytotoxic T lymphocytes in the control of SIV replication once infection is established. Among Mamu-A*01–negative monkeys challenged with SIVsmE660, no CD8+ T cell response or innate immune response was associated with protection against virus acquisition. However, low levels of neutralizing antibodies and an envelope-specific CD4+ T cell response were associated with vaccine protection in these monkeys. Moreover, monkeys that expressed two TRIM5 alleles that restrict SIV replication were more likely to be protected from infection than monkeys that expressed at least one permissive TRIM5 allele. This study begins to elucidate the mechanism of vaccine protection against immunodeficiency viruses and highlights the need to analyze these immune and genetic correlates of protection in future trials of HIV vaccine strategies.
In vaccine research, immune biomarkers that can reliably predict a vaccine’s effect on the clinical endpoint (i.e., surrogate markers) are important tools for guiding vaccine development. This paper addresses issues on optimizing two-phase sampling study design for evaluating surrogate markers in a principal surrogate framework, motivated by the design of a future HIV vaccine trial. To address the problem of missing potential outcomes in a standard trial design, novel trial designs have been proposed that utilize baseline predictors of the immune response biomarker(s) and/or augment the trial by vaccinating uninfected placebo recipients at the end of the trial and measuring their immune biomarkers. However, inefficient use of the augmented information can lead to counterintuitive results on the precision of estimation. To remedy this problem, we propose a pseudo-score type estimator suitable for the augmented design and characterize its asymptotic properties. This estimator has superior performance compared with existing estimators and allows calculation of analytical variances useful for guiding study design. Based on the new estimator we investigate in detail the problem of optimizing the sampling scheme of a biomarker in a vaccine efficacy trial for efficiently estimating its surrogate effect, as characterized by the vaccine efficacy curve (a causal effect predictiveness curve) and by the predicted overall vaccine efficacy using the biomarker.
Closeout placebo vaccination; Estimated likelihood; Immune correlate; Principal surrogate; Pseudo-score; Two-phase sampling design
A marker of immune function that statistically correlates with protection after vaccination may be either a mechanistic correlate of protection or a nonmechanistic correlate of protection, which does not cause protection, but predicts protection.
Identification of immune correlates of protection after vaccination is an important part of vaccinology for both theoretical and practical reasons. The terminology and definition of correlates have been confusing, because different authors have used variable terms and concepts. Here, we attempt to give precision to the field by defining 3 terms: correlate of protection (CoP), mechanistic correlate of protection (mCoP), and nonmechanistic correlate of protection (nCoP). A CoP is a marker of immune function that statistically correlates with protection after vaccination that may be either an mCoP, which is a mechanistic cause of protection, or an nCoP, which does not cause protection but nevertheless predicts protection through its (partial) correlation with another immune response(s) that mechanistically protects.
It is frequently of interest to estimate the intervention effect that adjusts for post-randomization variables in clinical trials. In the recently completed HPTN 035 trial, there is differential condom use between the three microbicide gel arms and the No Gel control arm, so that intention to treat (ITT) analyses only assess the net treatment effect that includes the indirect treatment effect mediated through differential condom use. Various statistical methods in causal inference have been developed to adjust for post-randomization variables. We extend the principal stratification framework to time-varying behavioral variables in HIV prevention trials with a time-to-event endpoint, using a partially hidden Markov model (pHMM). We formulate the causal estimand of interest, establish assumptions that enable identifiability of the causal parameters, and develop maximum likelihood methods for estimation. Application of our model on the HPTN 035 trial reveals an interesting pattern of prevention effectiveness among different condom-use principal strata.
microbicide; causal inference; posttreatment variables; direct effect
The ALVAC-HIV/AIDSVAX-B/E RV144 vaccine trial showed an estimated efficacy of 31%. RV144 secondary immune correlate analysis demonstrated that the combination of low plasma anti-HIV-1 Env IgA antibodies and high levels of antibody-dependent cellular cytotoxicity (ADCC) inversely correlate with infection risk. One hypothesis is that the observed protection in RV144 is partially due to ADCC-mediating antibodies. We found that the majority (73 to 90%) of a representative group of vaccinees displayed plasma ADCC activity, usually (96.2%) blocked by competition with the C1 region-specific A32 Fab fragment. Using memory B-cell cultures and antigen-specific B-cell sorting, we isolated 23 ADCC-mediating nonclonally related antibodies from 6 vaccine recipients. These antibodies targeted A32-blockable conformational epitopes (n = 19), a non-A32-blockable conformational epitope (n = 1), and the gp120 Env variable loops (n = 3). Fourteen antibodies mediated cross-clade target cell killing. ADCC-mediating antibodies displayed modest levels of V-heavy (VH) chain somatic mutation (0.5 to 1.5%) and also displayed a disproportionate usage of VH1 family genes (74%), a phenomenon recently described for CD4-binding site broadly neutralizing antibodies (bNAbs). Maximal ADCC activity of VH1 antibodies correlated with mutation frequency. The polyclonality and low mutation frequency of these VH1 antibodies reveal fundamental differences in the regulation and maturation of these ADCC-mediating responses compared to VH1 bNAbs.
The RV144 trial demonstrated 31% vaccine efficacy (VE) at preventing HIV-1 infection1. Antibodies against the HIV-1 envelope variable loops 1 and 2 (V1/V2) domain correlated inversely with infection risk2. We hypothesized that vaccine-induced immune responses against V1/V2 would selectively impact, or sieve, HIV-1 breakthrough viruses. 936 HIV-1 genome sequences from 44 vaccine and 66 placebo recipients were examined. We show that vaccine-induced immune responses were associated with two signatures in V1/V2 at amino-acid positions 169 and 181. VE against viruses matching the vaccine at position 169 was 48% (CI: 18 to 66%; p=0.0036), whereas VE against viruses mismatching the vaccine at position 181 was 78% (CI: 35% to 93%; p=0.0028). Residue 169 is in a cationic glycosylated region recognized by broadly neutralizing and RV144-derived antibodies. The predicted distance between the two signatures sites (21±7 Å), and their match/mismatch dichotomy, suggest that multiple factors may be involved in the protection observed in RV144. Genetic signatures of RV144 vaccination in V2 complement the finding of an association between high V1/V2 binding antibodies and reduced risk of HIV-1 acquisition and provide evidence that vaccine-induced V2 responses plausibly played a role in the partial protection conferred by the RV144 regimen.
Identification of an immune response to vaccination that reliably predicts protection from clinically significant infection, i.e. an immunological surrogate endpoint, is a primary goal of vaccine research. Using this problem of evaluating an immunological surrogate as an illustration, we describe a hierarchy of three criteria for a valid surrogate endpoint and statistical analysis frameworks for evaluating them. Based on a placebo-controlled vaccine efficacy trial, the first level entails assessing the correlation of an immune response with a study endpoint in the study groups, and the second level entails evaluating an immune response as a surrogate for the study endpoint that can be used for predicting vaccine efficacy for a setting similar to that of the vaccine trial. We show that baseline covariates, innovative study design, and a potential outcomes formulation can be helpful for this assessment. The third level entails validation of a surrogate endpoint via meta-analysis, where the goal is to evaluate how well the immune response can be used to predict vaccine efficacy for new settings (building bridges). A simulated vaccine trial and two example vaccine trials are presented, one supporting that certain anti-influenza antibody levels are an excellent surrogate for influenza illness and another supporting that certain anti-HIV antibody levels are not useful as a surrogate for HIV infection.
clinical trial; counterfactual; immune correlate; meta-analysis; potential outcomes; principal surrogate; statistical surrogate
An objective of randomized placebo-controlled preventive HIV vaccine efficacy trials is to assess the relationship between the vaccine effect to prevent infection and the genetic distance of the exposing HIV to the HIV strain represented in the vaccine construct. Motivated by this objective, recently a mark-specific proportional hazards model with a continuum of competing risks has been studied, where the genetic distance of the transmitting strain is the continuous `mark' defined and observable only in failures. A high percentage of genetic marks of interest may be missing for a variety of reasons, predominantly due to rapid evolution of HIV sequences after transmission before a blood sample is drawn from which HIV sequences are measured. This research investigates the stratified mark-specific proportional hazards model with missing marks where the baseline functions may vary with strata. We develop two consistent estimation approaches, the first based on the inverse probability weighted complete-case (IPW) technique, and the second based on augmenting the IPW estimator by incorporating auxiliary information predictive of the mark. We investigate the asymptotic properties and finite-sample performance of the two estimators, and show that the augmented IPW estimator, which satisfies a double robustness property, is more efficient.
Augmented inverse probability weighted complete-case estimator; auxiliary marks; competing risks; double robustness; failure time data; genetic data; HIV vaccine trial; mark-specific vaccine efficacy; missing at random; semiparametric model
The RV144 clinical trial of a prime/boost immunizing regimen using recombinant canary pox (ALVAC-HIV) and two gp120 proteins (AIDSVAX B and E) was previously shown to have a 31.2% efficacy rate. Plasma specimens from vaccine and placebo recipients were used in an extensive set of assays to identify correlates of HIV-1 infection risk. Of six primary variables that were studied, only one displayed a significant inverse correlation with risk of infection: the antibody (Ab) response to a fusion protein containing the V1 and V2 regions of gp120 (gp70-V1V2). This finding prompted a thorough examination of the results generated with the complete panel of 13 assays measuring various V2 Abs in the stored plasma used in the initial pilot studies and those used in the subsequent case-control study. The studies revealed that the ALVAC-HIV/AIDSVAX vaccine induced V2-specific Abs that cross-react with multiple HIV-1 subgroups and recognize both conformational and linear epitopes. The conformational epitope was present on gp70-V1V2, while the predominant linear V2 epitope mapped to residues 165–178, immediately N-terminal to the putative α4β7 binding motif in the mid-loop region of V2. Odds ratios (ORs) were calculated to compare the risk of infection with data from 12 V2 assays, and in 11 of these, the ORs were ≤1, reaching statistical significance for two of the variables: Ab responses to gp70-V1V2 and to overlapping V2 linear peptides. It remains to be determined whether anti-V2 Ab responses were directly responsible for the reduced infection rate in RV144 and whether anti-V2 Abs will prove to be important with other candidate HIV vaccines that show efficacy, however, the results support continued dissection of Ab responses to the V2 region which may illuminate mechanisms of protection from HIV-1 infection and may facilitate the development of an effective HIV-1 vaccine.