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Antibody levels predict vaccine efficacy Symptomatic COVID-19 infection can be prevented by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines. A “correlate of protection” is a molecular biomarker to measure how much immunity is needed to fight infection and is key for successful global immunization programs. Gilbert et al . determined that antibodies are the correlate of protection in vaccinated individuals enrolled in the Moderna COVE phase 3 clinical trial (see the Perspective by Openshaw). By measuring binding and neutralizing antibodies against the viral spike protein, the authors found that the levels of both antibodies correlated with the degree of vaccine efficacy. The higher the antibody level, the greater the protection afforded by the messenger RNA (mRNA) vaccine. Antibody levels that predict mRNA vaccine efficacy can therefore be used to guide vaccine regimen modifications and support regulatory approvals for a broader spectrum of the population. —PNK

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.

Analysis of correlates of risk of infection in the RV144 HIV-1 vaccine efficacy trial demonstrated that plasma IgG against the HIV-1 envelope (Env) variable region 1 and 2 inversely correlated with risk, whereas HIV-1 Env-specific plasma IgA responses directly correlated with risk. In the secondary analysis, antibody-dependent cellular cytotoxicity (ADCC) was another inverse correlate of risk, but only in the presence of low plasma IgA Env-specific antibodies. Thus, we investigated the hypothesis that IgA could attenuate the protective effect of IgG responses through competition for the same Env binding sites. We report that Env-specific plasma IgA/IgG ratios are higher in infected than in uninfected vaccine recipients in RV144. Moreover, Env-specific IgA antibodies from RV144 vaccinees blocked the binding of ADCC-mediating mAb to HIV-1 Env glycoprotein 120 (gp120). An Env-specific monomeric IgA mAb isolated from an RV144 vaccinee also inhibited the ability of natural killer cells to kill HIV-1-infected CD4 + T cells coated with RV144-induced IgG antibodies. We show that monomeric Env-specific IgA, as part of postvaccination polyclonal antibody response, may modulate vaccine-induced immunity by diminishing ADCC effector function.T he phase III RV144 ALVAC/AIDSVAX B/E HIV-1 vaccine efficacy trial in Thailand demonstrated 31.2% estimated vaccine efficacy through 42 mo of follow-up (1). Analysis of correlates of risk of infection indicated that envelope (Env)-specific plasma antibody responses were associated with a lower infection risk in vaccinees (2). Though plasma Env variable region 1 and 2 (V1/V2) IgG correlated with decreased infection risk, high levels of anti-HIV-1 Env plasma IgA correlated with increased infection risk (2). Interaction analyses demonstrated that, in the presence of low IgA Env antibodies, antibody-dependent cellular cytotoxicity (ADCC) responses inversely correlated with risk of infection, whereas in the presence of high IgA Env plasma antibodies, there was no correlation with risk of infection (2). Because there was no overall enhancement of infection risk in the trial (1), we hypothesized that Env IgA might block potentially protective effector functions of Env IgG antibodies.Antibody function depends, in part, on ability to bind to Fc receptors (FcR) on effector cells. The antibody isotype and subclass influences its affinity for different cellular FcRs (3, 4). IgG antibodies that mediate ADCC through natural killer (NK) cells bind to FcγRIIIa (CD16). In contrast, IgA antibodies do not bind to FcγRIIIa, but, rather, have high affinity for FcαRI (CD89) expressed by monocytes/macrophages and polymorphonuclear cells (PMN). This differential profile of FcR binding by IgG and IgA antibodies impacts the effector function capabilities of these antibody isotypes.Here, we examined plasma IgA and monomeric IgA monoclonal antibodies from RV144 vaccine recipients to test the hypothesis that some fraction of the vaccine-elicited IgA response could block IgG-mediated ADCC function. We found that a f...

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.Trial RegistrationClinicalTrials.gov NCT00223080

Germ cell development in C. elegans requires that the X chromosomes be globally silenced during mitosis and early meiosis. We previously found that the nuclear proteins MES-2, MES-3, MES-4 and MES-6 regulate the different chromatin states of autosomes versus X chromosomes and are required for germline viability. Strikingly, the SET-domain protein MES-4 is concentrated on autosomes and excluded from the X chromosomes. Here, we show that MES-4 has histone H3 methyltransferase (HMT) activity in vitro, and is required for histone H3K36 dimethylation in mitotic and early meiotic germline nuclei and early embryos. MES-4 appears unlinked to transcription elongation, thus distinguishing it from other known H3K36 HMTs. Based on microarray analysis, loss of MES-4 leads to derepression of X-linked genes in the germ line. We discuss how an autosomally associated HMT may participate in silencing genes on the X chromosome, in coordination with the direct silencing effects of the other MES proteins.

Generalized linear mixed models (GLMMs) continue to grow in popularity due to their ability to directly acknowledge multiple levels of dependency and model different data types. For small sample sizes especially, likelihood-based inference can be unreliable with variance components being particularly difficult to estimate. A Bayesian approach is appealing but has been hampered by the lack of a fast implementation, and the difficulty in specifying prior distributions with variance components again being particularly problematic. Here, we briefly review previous approaches to computation in Bayesian implementations of GLMMs and illustrate in detail, the use of integrated nested Laplace approximations in this context. We consider a number of examples, carefully specifying prior distributions on meaningful quantities in each case. The examples cover a wide range of data types including those requiring smoothing over time and a relatively complicated spline model for which we examine our prior specification in terms of the implied degrees of freedom. We conclude that Bayesian inference is now practically feasible for GLMMs and provides an attractive alternative to likelihood-based approaches such as penalized quasi-likelihood. As with likelihood-based approaches, great care is required in the analysis of clustered binary data since approximation strategies may be less accurate for such data.

Background: In the Coronavirus Efficacy (COVE) trial, estimated mRNA-1273 vaccine efficacy against coronavirus disease-19 (COVID-19) was 94%. SARS-CoV-2 antibody measurements were assessed as correlates of COVID-19 risk and as correlates of protection. Methods: Through case-cohort sampling, participants were selected for measurement of four serum antibody markers at Day 1 (first dose), Day 29 (second dose), and Day 57: IgG binding antibodies (bAbs) to Spike, bAbs to Spike receptor-binding domain (RBD), and 50% and 80% inhibitory dilution pseudovirus neutralizing antibody titers calibrated to the WHO International Standard (cID50 and cID80). Participants with no evidence of previous SARS-CoV-2 infection were included. Cox regression assessed in vaccine recipients the association of each Day 29 or 57 serologic marker with COVID-19 through 126 or 100 days of follow-up, respectively, adjusting for risk factors. Results: Day 57 Spike IgG, RBD IgG, cID50, and cID80 neutralization levels were each inversely correlated with risk of COVID-19: hazard ratios 0.66 (95% CI 0.50, 0.88; p=0.005); 0.57 (0.40, 0.82; p=0.002); 0.41 (0.26, 0.65; p<0.001); 0.35 (0.20, 0.60; p<0.001) per 10-fold increase in marker level, respectively, multiplicity adjusted P-values 0.003-0.010. Results were similar for Day 29 markers (multiplicity adjusted P-values <0.001-0.003). For vaccine recipients with Day 57 reciprocal cID50 neutralization titers that were undetectable (<2.42), 100, or 1000, respectively, cumulative incidence of COVID-19 through 100 days post Day 57 was 0.030 (0.010, 0.093), 0.0056 (0.0039, 0.0080), and 0.0023 (0.0013, 0.0036). For vaccine recipients at these titer levels, respectively, vaccine efficacy was 50.8% (-51.2, 83.0%), 90.7% (86.7, 93.6%), and 96.1% (94.0, 97.8%). Causal mediation analysis estimated that the proportion of vaccine efficacy mediated through Day 29 cID50 titer was 68.5% (58.5, 78.4%). Conclusions: Binding and neutralizing antibodies correlated with COVID-19 risk and vaccine efficacy and likely have utility in predicting mRNA-1273 vaccine efficacy against COVID-19. Trial registration number: COVE ClinicalTrials.gov number, NCT04470427