Living on three time scales: the dynamics of plasma cell and antibody populations illustrated for hepatitis a virus

Envelope protein-specific B cell receptors direct lentiviral vector tropism in vivo

While studying transgene expression after systemic administration of lentiviral vectors, we found that splenic B cells are robustly transduced, regardless of the types of pseudotyped envelope proteins. However, the administration of two different pseudotypes resulted in transduction of two distinct B cell populations, suggesting that each pseudotype uses unique and specific receptors for its attachment and entry into splenic B cells. Single-cell RNA sequencing analysis of the transduced cells demonstrated that different pseudotypes transduce distinct B cell subpopulations characterized by specific B cell receptor (BCR) genotypes. Functional analysis of the BCRs of the transduced cells demonstrated that BCRs specific to the pseudotyping envelope proteins mediate viral entry, enabling the vectors to selectively transduce the B cell populations that are capable of producing antibodies specific to their envelope proteins. Lentiviral vector entry via the BCR activated the transduced B cells and induced proliferation and differentiation into mature effectors, such as memory B and plasma cells. BCR-mediated viral entry into clonally specific B cell subpopulations raises new concepts for understanding the biodistribution of transgene expression after systemic administration of lentiviral vectors and offers new opportunities for BCR-targeted gene delivery by pseudotyped lentiviral vectors.

Tuning of plasma cell lifespan by competition explains the longevity and heterogeneity of antibody persistence

Plasma cells that emerge after infection or vaccination exhibit heterogeneous lifespans; most survive for days to months, whereas others persist for decades, providing antigen-specific long-term protection. We developed a mathematical framework to explore the dynamics of plasma cell removal and its regulation by survival factors. Analyses of antibody persistence following hepatitis A and B and HPV vaccination revealed specific patterns of longevity and heterogeneity within and between responses, implying that this process is fine-tuned near a critical "flat" state between two dynamic regimes. This critical state reflects the tuning of rates of the underlying regulatory network and is highly sensitive to variation in parameters, which amplifies lifespan differences between cells. We propose that fine-tuning is the generic outcome of competition over shared survival signals, with a competition-based mechanism providing a unifying explanation for a wide range of experimental observations, including the dynamics of plasma cell accumulation and the effects of survival factor deletion. Our theory is testable, and we provide specific predictions.

Examining B-cell dynamics and responsiveness in different inflammatory milieus using an agent-based model

INTRODUCTION

B-cells are essential components of the immune system that neutralize infectious agents through the generation of antigen-specific antibodies and through the phagocytic functions of naïve and memory B-cells. However, the B-cell response can become compromised by a variety of conditions that alter the overall inflammatory milieu, be that due to substantial, acute insults as seen in sepsis, or due to those that produce low-level, smoldering background inflammation such as diabetes, obesity, or advanced age. This B-cell dysfunction, mediated by the inflammatory cytokines Interleukin-6 (IL-6) and Tumor Necrosis Factor-alpha (TNF-α), increases the susceptibility of late-stage sepsis patients to nosocomial infections and increases the incidence or severity of recurrent infections, such as SARS-CoV-2, in those with chronic conditions. We propose that modeling B-cell dynamics can aid the investigation of their responses to different levels and patterns of systemic inflammation.

METHODS

The B-cell Immunity Agent-based Model (BCIABM) was developed by integrating knowledge regarding naïve B-cells, short-lived plasma cells, long-lived plasma cells, memory B-cells, and regulatory B-cells, along with their various differentiation pathways and cytokines/mediators. The BCIABM was calibrated to reflect physiologic behaviors in response to: 1) mild antigen stimuli expected to result in immune sensitization through the generation of effective immune memory, and 2) severe antigen challenges representing the acute substantial inflammation seen during sepsis, previously documented in studies on B-cell behavior in septic patients. Once calibrated, the BCIABM was used to simulate the B-cell response to repeat antigen stimuli during states of low, chronic background inflammation, implemented as low background levels of IL-6 and TNF-α often seen in patients with conditions such as diabetes, obesity, or advanced age. The levels of immune responsiveness were evaluated and validated by comparing to a Veteran's Administration (VA) patient cohort with COVID-19 infection known to have a higher incidence of such comorbidities.

RESULTS

The BCIABM was successfully able to reproduce the expected appropriate development of immune memory to mild antigen exposure, as well as the immunoparalysis seen in septic patients. Simulation experiments then revealed significantly decreased B-cell responsiveness as levels of background chronic inflammation increased, reproducing the different COVID-19 infection data seen in a VA population.

CONCLUSION

The BCIABM proved useful in dynamically representing known mechanisms of B-cell function and reproduced immune memory responses across a range of different antigen exposures and inflammatory statuses. These results elucidate previous studies demonstrating a similar negative correlation between the B-cell response and background inflammation by positing an established and conserved mechanism that explains B-cell dysfunction across a wide range of phenotypic presentations.

Prediction of long-term humoral response induced by the two-dose heterologous Ad26.ZEBOV, MVA-BN-Filo vaccine against Ebola

The persistence of the long-term immune response induced by the heterologous Ad26.ZEBOV, MVA-BN-Filo two-dose vaccination regimen against Ebola has been investigated in several clinical trials. Longitudinal data on IgG-binding antibody concentrations were analyzed from 487 participants enrolled in six Phase I and Phase II clinical trials conducted by the EBOVAC1 and EBOVAC2 consortia. A model based on ordinary differential equations describing the dynamics of antibodies and short- and long-lived antibody-secreting cells (ASCs) was used to model the humoral response from 7 days after the second vaccination to a follow-up period of 2 years. Using a population-based approach, we first assessed the robustness of the model, which was originally estimated based on Phase I data, against all data. Then we assessed the longevity of the humoral response and identified factors that influence these dynamics. We estimated a half-life of the long-lived ASC of at least 15 years and found an influence of geographic region, sex, and age on the humoral response dynamics, with longer antibody persistence in Europeans and women and higher production of antibodies in younger participants.

The Wood equation allows consistent fitting of individual antibody-response profiles of Zika virus or SARS-CoV-2 infected patients

Antibody kinetic curves obtained during a viral infection are often fitted using aggregated patient data, hiding the heterogeneity of individual humoral immune responses. Individual antibody responses can be modeled using the Wood equation and grouped according to their profile. Such modeling takes into account several important kinetic parameters, such as the day when antibody detection becomes positive [daypos], the day of the maximal response [daymax], the maximum antibody level [levelmax], and the day when antibody detection becomes negative [dayneg]. Potential associations between these profiles and studied factors can then be tested.

serosim: An R package for simulating serological data arising from vaccination, epidemiological and antibody kinetics processes

serosim is an open-source R package designed to aid inference from serological studies, by simulating data arising from user-specified vaccine and antibody kinetics processes using a random effects model. Serological data are used to assess population immunity by directly measuring individuals' antibody titers. They uncover locations and/or populations which are susceptible and provide evidence of past infection or vaccination to help inform public health measures and surveillance. Both serological data and new analytical techniques used to interpret them are increasingly widespread. This creates a need for tools to simulate serological studies and the processes underlying observed titer values, as this will enable researchers to identify best practices for serological study design, and provide a standardized framework to evaluate the performance of different inference methods. serosim allows users to specify and adjust model inputs representing underlying processes responsible for generating the observed titer values like time-varying patterns of infection and vaccination, population demography, immunity and antibody kinetics, and serological sampling design in order to best represent the population and disease system(s) of interest. This package will be useful for planning sampling design of future serological studies, understanding determinants of observed serological data, and validating the accuracy and power of new statistical methods.

Within-host modeling to measure dynamics of antibody responses after natural infection or vaccination: A systematic review

BACKGROUND

Within-host models describe the dynamics of immune cells when encountering a pathogen, and how these dynamics can lead to an individual-specific immune response. This systematic review aims to summarize which within-host methodology has been used to study and quantify antibody kinetics after infection or vaccination. In particular, we focus on data-driven and theory-driven mechanistic models.

MATERIALS

PubMed and Web of Science databases were used to identify eligible papers published until May 2022. Eligible publications included those studying mathematical models that measure antibody kinetics as the primary outcome (ranging from phenomenological to mechanistic models).

RESULTS

We identified 78 eligible publications, of which 8 relied on an Ordinary Differential Equations (ODEs)-based modelling approach to describe antibody kinetics after vaccination, and 12 studies used such models in the context of humoral immunity induced by natural infection. Mechanistic modeling studies were summarized in terms of type of study, sample size, measurements collected, antibody half-life, compartments and parameters included, inferential or analytical method, and model selection.

CONCLUSIONS

Despite the importance of investigating antibody kinetics and underlying mechanisms of (waning of) the humoral immunity, few publications explicitly account for this in a mathematical model. In particular, most research focuses on phenomenological rather than mechanistic models. The limited information on the age groups or other risk factors that might impact antibody kinetics, as well as a lack of experimental or observational data remain important concerns regarding the interpretation of mathematical modeling results. We reviewed the similarities between the kinetics following vaccination and infection, emphasising that it may be worth translating some features from one setting to another. However, we also stress that some biological mechanisms need to be distinguished. We found that data-driven mechanistic models tend to be more simplistic, and theory-driven approaches lack representative data to validate model results.

Quantifying Antibody Persistence After a Single Dose of COVID-19 Vaccine Ad26.COV2.S in Humans Using a Mechanistic Modeling and Simulation Approach

Understanding persistence of humoral immune responses elicited by vaccination against coronavirus disease 2019 (COVID-19) is critical for informing the duration of protection and appropriate booster timing. We developed a mechanistic model to characterize the time course of humoral immune responses in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-seronegative adults after primary vaccination with the Janssen COVID-19 vaccine, Ad26.COV2.S. The persistence of antibody responses was quantified through mechanistic modeling-based simulations. Two biomarkers of humoral immune responses were examined: SARS-CoV-2 neutralizing antibodies determined by wild-type virus neutralization assay (wtVNA) and spike protein-binding antibodies determined by indirect spike protein enzyme-linked immunosorbent assay (S-ELISA). The persistence of antibody responses was defined as the period of time during which wtVNA and S-ELISA titers remained above the lower limit of quantification. A total of 442 wtVNA and 1,185 S-ELISA titers from 82 and 220 participants, respectively, were analyzed following administration of a single dose of Ad26.COV2.S (5 × 10¹⁰ viral particles). The mechanistic model adequately described the time course of observed wtVNA and S-ELISA serum titers and its associated variability up to 8 months following vaccination. Mechanistic model-based simulations show that single-dose Ad26.COV2.S elicits durable but waning antibody responses up to 24 months following immunization. Of the estimated model parameters, the production rate of memory B cells was decreased in older adults relative to younger adults, and the antibody production rate mediated by long-lived plasma cells was increased in women relative to men. A steeper waning of antibody responses was predicted in men and in older adults.

Modeling antibody dynamics following herpes zoster indicates that higher varicella-zoster virus viremia generates more VZV-specific antibodies

Introduction

Studying antibody dynamics following re-exposure to infection and/or vaccination is crucial for a better understanding of fundamental immunological processes, vaccine development, and health policy research.

Methods

We adopted a nonlinear mixed modeling approach based on ordinary differential equations (ODE) to characterize varicella-zoster virus specific antibody dynamics during and after clinical herpes zoster. Our ODEs models convert underlying immunological processes into mathematical formulations, allowing for testable data analysis. In order to cope with inter- and intra-individual variability, mixed models include population-averaged parameters (fixed effects) and individual-specific parameters (random effects). We explored the use of various ODE-based nonlinear mixed models to describe longitudinally collected markers of immunological response in 61 herpes zoster patients.

Results

Starting from a general formulation of such models, we study different plausible processes underlying observed antibody titer concentrations over time, including various individual-specific parameters. Among the converged models, the best fitting and most parsimonious model implies that once Varicella-zoster virus (VZV) reactivation is clinically apparent (i.e., Herpes-zoster (HZ) can be diagnosed), short-living and long-living antibody secreting cells (SASC and LASC, respectively) will not expand anymore. Additionally, we investigated the relationship between age and viral load on SASC using a covariate model to gain a deeper understanding of the population's characteristics.

Conclusion

The results of this study provide crucial and unique insights that can aid in improving our understanding of VZV antibody dynamics and in making more accurate projections regarding the potential impact of vaccines.

Declining neutralizing antibody levels after SARS-CoV-2 mRNA vaccination: observational data from community point-of-care testing service in Brno, Czechia

OBJECTIVES

Understanding immune response is critical for control of COVID-19 pandemic. However, recent studies show that vaccine-induced humoral immunity may not be long-lasting and weaker in SARS-CoV-2 variants of concern.

METHODS

In May 2021, 253 self-nominated persons were tested for antibodies against SARS-CoV-2 in 1 to 104 days (mean 41, median 28) after two doses of Moderna and Pfizer-BioNTech vaccines in the city of Brno, Czechia. Two point-of-care iCHROMA™ II immunofluorescence assays were used: COVID-19 Ab against mix of SARS-CoV-2 nucleocapsid and spike proteins (IgG Ab); and COVID-19 nAb against S1-RBD protein (nAb). Results were analysed in relation to gender, age, vaccine, and past COVID-19 disease.

RESULTS

Antibodies nAb were detectable in 92.9% (95% CI: 89.7-96.0) of vaccinees. We observed statistically insignificant decrease of positive results from 93.9% (95% CI: 89.5-98.3) and 97.0% (95% CI: 92.8-100.0) in the first and second month after vaccination, respectively, to 91.7% (95% CI: 83.8-99.5) and 78.3% (95% CI: 61.4-95.1) in the third and fourth month, respectively. Quantitative results showed decreasing level of nAb in both genders, age groups and vaccines. Higher levels of nAb were found in younger age group and in COVID-19 convalescents. IgG Ab showed little dynamics in time.

CONCLUSIONS

We found robust humoral response after vaccination with mRNA vaccines, however, decreasing nAb levels suggest that vaccine-induced humoral immunity is rapidly waning. This finding is relevant for adjustment of vaccination strategies with regard to inclusion of booster dose(s).

Influenza virus infection history shapes antibody responses to influenza vaccination

Studies of successive vaccination suggest that immunological memory against past influenza viruses may limit responses to vaccines containing current strains. The impact of memory induced by prior infection is rarely considered and is difficult to ascertain, because infections are often subclinical. This study investigated influenza vaccination among adults from the Ha Nam cohort (Vietnam), who were purposefully selected to include 72 with and 28 without documented influenza A(H3N2) infection during the preceding 9 years (Australian New Zealand Clinical Trials Registry 12621000110886). The primary outcome was the effect of prior influenza A(H3N2) infection on hemagglutinin-inhibiting antibody responses induced by a locally available influenza vaccine administered in November 2016. Baseline and postvaccination sera were titrated against 40 influenza A(H3N2) strains spanning 1968-2018. At each time point (baseline, day 14 and day 280), geometric mean antibody titers against 2008-2018 strains were higher among participants with recent infection (34 (29-40), 187 (154-227) and 86 (72-103)) than among participants without recent infection (19 (17-22), 91 (64-130) and 38 (30-49)). On days 14 and 280, mean titer rises against 2014-2018 strains were 6.1-fold (5.0- to 7.4-fold) and 2.6-fold (2.2- to 3.1-fold) for participants with recent infection versus 4.8-fold (3.5- to 6.7-fold) and 1.9-fold (1.5- to 2.3-fold) for those without. One of 72 vaccinees with recent infection versus 4 of 28 without developed symptomatic A(H3N2) infection in the season after vaccination (P = 0.021). The range of A(H3N2) viruses recognized by vaccine-induced antibodies was associated with the prior infection strain. These results suggest that recall of immunological memory induced by prior infection enhances antibody responses to inactivated influenza vaccine and is important to attain protective antibody titers.

Dengue and Zika virus infections in children elicit cross-reactive protective and enhancing antibodies that persist long term

[Figure: see text].

Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2

Background

Antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been shown to neutralize the virus in vitro and prevent disease in animal challenge models on reexposure. However, the current understanding of SARS-CoV-2 humoral dynamics and longevity is conflicting.

Methods

The COVID-19 Staff Testing of Antibody Responses Study (Co-Stars) prospectively enrolled 3679 healthcare workers to comprehensively characterize the kinetics of SARS-CoV-2 spike protein (S), receptor-binding domain, and nucleoprotein (N) antibodies in parallel. Participants screening seropositive had serial monthly serological testing for a maximum of 7 months with the Meso Scale Discovery Assay. Survival analysis determined the proportion of seroreversion, while 2 hierarchical gamma models predicted the upper and lower bounds of long-term antibody trajectory.

Results

A total of 1163 monthly samples were provided from 349 seropositive participants. At 200 days after symptoms, >95% of participants had detectable S antibodies, compared with 75% with detectable N antibodies. S antibody was predicted to remain detectable in 95% of participants until 465 days (95% confidence interval, 370–575 days) using a “continuous-decay” model and indefinitely using a “decay-to-plateau” model to account for antibody secretion by long-lived plasma cells. S-antibody titers were correlated strongly with surrogate neutralization in vitro (R² = 0.72). N antibodies, however, decayed rapidly with a half-life of 60 days (95% confidence interval, 52–68 days).

Conclusions

The Co-Stars data presented here provide evidence for long-term persistence of neutralizing S antibodies. This has important implications for the duration of functional immunity after SARS-CoV-2 infection. In contrast, the rapid decay of N antibodies must be considered in future seroprevalence studies and public health decision-making. This is the first study to establish a mathematical framework capable of predicting long-term humoral dynamics after SARS-CoV-2 infection.

Clinical Trials Registration

NCT04380896.

A study based on four immunoassays: Hepatitis C virus antibody against different antigens may have unequal contributions to detection

Background

All commercial Hepatitis C virus antibody (anti-HCV) assays use a combination of recombinant antigens to detect antibody response. Antibody responses to individual antigenic regions (core, NS3/4 and NS5) used in assays have not been investigated.

Methods

In this study, we quantified HCV viral load, tested anti-HCV with four commercial assays (Ortho-ELISA, Murex-ELISA, Architect-CMIA and Elecsys-ECLIA) in 682 plasma specimens. In antigenic region ELISA platform, microwells were coated with three antigens: core (c22-3), NS3/4 (c200) and NS5 individually. The signal-to-cutoff (S/Co) values of different assays, and antibody responses to individual antigens were compared. The specimens were divided into HCV RNA positive group, anti-HCV consistent group, and anti-HCV discrepant group.

Results

Anti-core and anti-NS3/4 were simultaneously detected in 99.2% of HCV RNA positive specimens and showed great consistency with total anti-HCV signals. Responses to the core region were more robust than those to the NS3/4 region in anti-HCV consistent group (p < 0.001). Anti-NS5 only occurred in companying with responses to the core and NS3/4 antigens, and failed to affect the final anti-HCV positive signals. In anti-HCV discrepant group, 39.0% of positive signals could not be traced back to any single antigenic region.

Conclusion

Antibody responses to the core and NS3/4 antigens were stronger, whereas responses to the NS5 antigen were the weakest, indicating that individual antigenic regions played different roles in total anti-HCV signals. This study provides an impetus for optimizing commercial anti-HCV assays.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-021-01608-x.

Dynamics of antibodies to SARS-CoV-2 in convalescent plasma donors

OBJECTIVES

Characterisation of the human antibody response to SARS-CoV-2 infection is vital for serosurveillance purposes and for treatment options such as transfusion with convalescent plasma or immunoglobulin products derived from convalescent plasma. In this study, we longitudinally and quantitatively analysed antibody responses in RT-PCR-positive SARS-CoV-2 convalescent adults during the first 250 days after onset of symptoms.

METHODS

We measured antibody responses to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and the nucleocapsid protein in 844 longitudinal samples from 151 RT-PCR-positive SARS-CoV-2 convalescent adults. With a median of 5 (range 2-18) samples per individual, this allowed quantitative analysis of individual longitudinal antibody profiles. Kinetic profiles were analysed by mixed-effects modelling.

RESULTS

All donors were seropositive at the first sampling moment, and only one donor seroreverted during follow-up analysis. Anti-RBD IgG and anti-nucleocapsid IgG levels declined with median half-lives of 62 and 59 days, respectively, 2-5 months after symptom onset, and several-fold variation in half-lives of individuals was observed. The rate of decline of antibody levels diminished during extended follow-up, which points towards long-term immunological memory. The magnitude of the anti-RBD IgG response correlated well with neutralisation capacity measured in a classic plaque reduction assay and in an in-house developed competitive assay.

CONCLUSION

The result of this study gives valuable insight into the long-term longitudinal response of antibodies to SARS-CoV-2.

Hepatitis A vaccination and its immunological and epidemiological long-term effects - a review of the evidence

Hepatitis A virus (HAV) infections continue to represent a significant disease burden causing approximately 200 million infections, 30 million symptomatic illnesses and 30,000 deaths each year. Effective and safe hepatitis A vaccines have been available since the early 1990s. Initially developed for individual prophylaxis, HAV vaccines are now increasingly used to control hepatitis A in endemic areas. The human enteral HAV is eradicable in principle, however, HAV eradication is currently not being pursued. Inactivated HAV vaccines are safe and, after two doses, elicit seroprotection in healthy children, adolescents, and young adults for an estimated 30-40 years, if not lifelong, with no need for a later second booster. The long-term effects of the single-dose live-attenuated HAV vaccines are less well documented but available data suggest they are safe and provide long-lasting immunity and protection. A universal mass vaccination strategy (UMV) based on two doses of inactivated vaccine is commonly implemented in endemic countries and eliminates clinical hepatitis A disease in toddlers within a few years. Consequently, older age groups also benefit due to the herd protection effects. Single-dose UMV programs have shown promising outcomes but need to be monitored for many more years in order to document an effective immune memory persistence. In non-endemic countries, prevention efforts need to focus on 'new' risk groups, such as men having sex with men, prisoners, the homeless, and families visiting friends and relatives in endemic countries. This narrative review presents the current evidence regarding the immunological and epidemiological long-term effects of the hepatitis A vaccination and finally discusses emerging issues and areas for research.

Innate Immunity Plays a Key Role in Controlling Viral Load in COVID-19: Mechanistic Insights from a Whole-Body Infection Dynamics Model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. To develop disease management strategies, a better understanding of SARS-CoV-2 pathogenesis and population susceptibility to infection are needed. To this end, mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency for infection) of the virus and by incorporating cellular-scale viral dynamics and innate and adaptive immune responses, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body (respiratory tract, gut, liver, spleen, heart, kidneys, and brain). Following parameter quantification with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, we ranked model parameters through sensitivity analysis for their significance in governing clearance of viral load to understand the effects of physiological factors and underlying conditions on viral load dynamics. Antiviral drug therapy, interferon therapy, and their combination were simulated to study the effects on viral load kinetics of SARS-CoV-2. The model revealed the dominant role of innate immunity (specifically interferons and resident macrophages) in controlling viral load, and the importance of timing when initiating therapy after infection.

Multiplex assays for the identification of serological signatures of SARS-CoV-2 infection: an antibody-based diagnostic and machine learning study

BACKGROUND

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces an antibody response targeting multiple antigens that changes over time. This study aims to take advantage of this complexity to develop more accurate serological diagnostics.

METHODS

A multiplex serological assay was developed to measure IgG and IgM antibody responses to seven SARS-CoV-2 spike or nucleoprotein antigens, two antigens for the nucleoproteins of the 229E and NL63 seasonal coronaviruses, and three non-coronavirus antigens. Antibodies were measured in serum samples collected up to 39 days after symptom onset from 215 adults in four French hospitals (53 patients and 162 health-care workers) with quantitative RT-PCR-confirmed SARS-CoV-2 infection, and negative control serum samples collected from healthy adult blood donors before the start of the SARS-CoV-2 epidemic (335 samples from France, Thailand, and Peru). Machine learning classifiers were trained with the multiplex data to classify individuals with previous SARS-CoV-2 infection, with the best classification performance displayed by a random forests algorithm. A Bayesian mathematical model of antibody kinetics informed by prior information from other coronaviruses was used to estimate time-varying antibody responses and assess the sensitivity and classification performance of serological diagnostics during the first year following symptom onset. A statistical estimator is presented that can provide estimates of seroprevalence in very low-transmission settings.

FINDINGS

IgG antibody responses to trimeric spike protein (Stri) identified individuals with previous SARS-CoV-2 infection with 91·6% (95% CI 87·5-94·5) sensitivity and 99·1% (97·4-99·7) specificity. Using a serological signature of IgG and IgM to multiple antigens, it was possible to identify infected individuals with 98·8% (96·5-99·6) sensitivity and 99·3% (97·6-99·8) specificity. Informed by existing data from other coronaviruses, we estimate that 1 year after infection, a monoplex assay with optimal anti-Stri IgG cutoff has 88·7% (95% credible interval 63·4-97·4) sensitivity and that a four-antigen multiplex assay can increase sensitivity to 96·4% (80·9-100·0). When applied to population-level serological surveys, statistical analysis of multiplex data allows estimation of seroprevalence levels less than 2%, below the false-positivity rate of many other assays.

INTERPRETATION

Serological signatures based on antibody responses to multiple antigens can provide accurate and robust serological classification of individuals with previous SARS-CoV-2 infection. This provides potential solutions to two pressing challenges for SARS-CoV-2 serological surveillance: classifying individuals who were infected more than 6 months ago and measuring seroprevalence in serological surveys in very low-transmission settings.

FUNDING

European Research Council. Fondation pour la Recherche Médicale. Institut Pasteur Task Force COVID-19.

Air Pollution and Polyclonal Elevation of Serum Free Light Chains: An Assessment of Adaptive Immune Responses in the Prospective Heinz Nixdorf Recall Study

BACKGROUND

Residential exposure to air pollution (AP) has been shown to activate the immune system (IS). Although innate immune responses to AP have been studied extensively, investigations on the adaptive IS are scarce.

OBJECTIVES

The aim of this study was to investigate the association between short- to long-term AP exposure and polyclonal free light chains (FLC) produced by plasma cells.

METHODS

We used repeated data from three examinations (t0: 2000-2003; t1: 2006-2008; and t2: 2011-2015) of the population-based German Heinz Nixdorf Recall cohort of initially 4,814 participants (45-75 y old). Residential exposure to total and source-specific particulate matter (PM) with an aerodynamic diameter of 10 or 2.5μm (PM10 and PM2.5 respectively), nitrogen dioxide (NO2), and particle number concentrations (accumulation mode; PNAM) was estimated using a chemistry transport model with different time windows (1- to 365-d mean ± standard deviation) before blood draw. We applied linear mixed models with a random participant intercept to estimate associations between total, traffic- and industry-related AP exposures and log-transformed FLC, controlling for examination time, sociodemographic and lifestyle variables, estimated glomerular filtration rate and season.

RESULTS

Analyzing 9,933 observations from 4,455 participants, we observed generally positive associations between AP exposures and FLC. We observed strongest associations with middle-term exposures, e.g., 3.0% increase in FLC (95% confidence interval: 1.8%, 4.3%) per interquartile range increase in 91-d mean of NO2 (14.1μg/m³). Across the different pollutants, NO2 showed strongest associations with FLC, followed by PM10 and PNAM. Effect estimates for traffic-related exposures were mostly higher compared with total exposures. Although NO2 and PNAM estimates remained stable upon adjustment for PM, PM estimates decreased considerably upon adjustment for NO2 and PNAM.

DISCUSSION

Our results suggest that middle-term AP exposures in particular might be positively associated with activation of the adaptive IS. Traffic-related PM, PNAM, and NO2 showed strongest associations. https://doi.org/10.1289/EHP7164.

Durability of humoral immune responses to rubella following MMR vaccination

BACKGROUND

While administration of the measles-mumps-rubella (MMR-II®) vaccine has been effective at preventing rubella infection in the United States, the durability of humoral immunity to the rubella component of MMR vaccine has not been widely studied among older adolescents and adults.

METHODS

In this longitudinal study, we sought to assess the durability of rubella virus (RV)-specific humoral immunity in a healthy population (n = 98) of adolescents and young adults at two timepoints: ~7 and ~17 years after two doses of MMR-II® vaccination. Levels of circulating antibodies specific to RV were measured by ELISA and an immune-colorimetric neutralization assay. RV-specific memory B cell responses were also measured by ELISpot.

RESULTS

Rubella-specific IgG antibody titers, neutralizing antibody titers, and memory B cell responses declined with increasing time since vaccination; however, these decreases were relatively moderate. Memory B cell responses exhibited a greater decline in men compared to women.

CONCLUSIONS

Collectively, rubella-specific humoral immunity declines following vaccination, although subjects' antibody titers remain well above the currently recognized threshold for protective immunity. Clinical correlates of protection based on neutralizing antibody titer and memory B cell ELISpot response should be defined.

Innate immunity plays a key role in controlling viral load in COVID-19: mechanistic insights from a whole-body infection dynamics model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. To develop disease management strategies, a better understanding of SARS-CoV-2 pathogenesis and population susceptibility to infection are needed. To this end, physiologically-relevant mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency for infection) of the virus, and by incorporating cellular-scale viral dynamics and innate and adaptive immune responses, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body (respiratory tract, gut, liver, spleen, heart, kidneys, and brain). Following calibration with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, we conducted global sensitivity analysis of model parameters and ranked them for their significance in governing clearance of viral load to understand the effects of physiological factors and underlying conditions on viral load dynamics. Antiviral drug therapy, interferon therapy, and their combination was simulated to study the effects on viral load kinetics of SARS-CoV-2. The model revealed the dominant role of innate immunity (specifically interferons and resident macrophages) in controlling viral load, and the importance of timing when initiating therapy following infection.

Impact of vaccine type on HIV-1 vaccine elicited antibody durability and B cell gene signature

Efficacious HIV-1 vaccination requires elicitation of long-lived antibody responses. However, our understanding of how different vaccine types elicit durable antibody responses is lacking. To assess the impact of vaccine type on antibody responses, we measured IgG isotypes against four consensus HIV antigens from 2 weeks to 10 years post HIV-1 vaccination and used mixed effects models to estimate half-life of responses in four human clinical trials. Compared to protein-boosted regimens, half-lives of gp120-specific antibodies were longer but peak magnitudes were lower in Modified Vaccinia Ankara (MVA)-boosted regimens. Furthermore, gp120-specific B cell transcriptomics from MVA-boosted and protein-boosted vaccines revealed a distinct signature at a peak (2 weeks after last vaccination) including CD19, CD40, and FCRL2-5 activation along with increased B cell receptor signaling. Additional analysis revealed contributions of RIG-I-like receptor pathway and genes such as SMAD5 and IL-32 to antibody durability. Thus, this study provides novel insights into vaccine induced antibody durability and B-cell receptor signaling.

Influenza A(H1N1)pdm09 but not A(H3N2) virus infection induces durable sero-protection: results from the Ha Nam Cohort

Background

The extent to which influenza recurrence depends upon waning immunity from prior infection is undefined. We used antibody titers of Ha-Nam cohort participants to estimate protection curves and decay trajectories.

Methods

Households (270) participated in influenza-like–illness (ILI) surveillance and provided blood at intervals spanning laboratory–confirmed virus transmission. Sera were tested in hemagglutination inhibition assay. Infection was defined as influenza virus-positive ILI and/or seroconversion. Median protective titers were estimated using scaled-logistic regression to model pretransmission titer against infection status in that season, limiting analysis to households with infection(s). Titers were modelled against month since infection using mixed-effects linear regression to estimate decay and when titers fell below protection thresholds.

Results

From December 2008–2012, 295 and 314 participants were infected with H1N1pdm09-like and A/Perth/16/09-like (H3N2Pe09) viruses, respectively. The proportion protected rose more steeply with titer for H1N1pdm09 than for H3N2Pe09, and estimated 50% protection titers were 19.6 and 37.3, respectively. Postinfection titers started higher against H3N2Pe09 but decayed more steeply than against H1N1pdm09. Seroprotection was estimated to be sustained against H1N1pdm09 but to wane by 8-months for H3N2Pe09.

Conclusions

Estimates indicate that infection induces durable seroprotection against H1N1pdm09 but not H3N2Pe09, which could in part account for the younger age of A(H1N1) versus A(H3N2) cases.

Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study

Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a major neglected tropical disease (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve individual-level and population-level understanding of this Leptospira reservoir system. We create a "host-pathogen space" by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to characterize changes in these values through time. Data from these individuals describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health but sampled only once. Our framework enables us to determine an individual's location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and use these to impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space using quantitative biomarker data enables more nuanced understanding of an individual's time course of infection, duration of immunity, and probability of being infectious. Such maps also make efficient use of limited data for rare or poorly understood diseases, by providing a means to rapidly assess the range and extent of potential clinical and immunological profiles. These approaches yield benefits for clinicians needing to triage patients, prevent transmission, and assess immunity, and for disease ecologists or epidemiologists working to develop appropriate risk management strategies to reduce transmission risk on a population scale (e.g. model parameterization using more accurate estimates of duration of immunity and infectiousness) and to assess health impacts on a population scale.

The seroprevalence of cytomegalovirus infection in Belgium anno 2002 and 2006: a comparative analysis with hepatitis A virus seroprevalence

Cytomegalovirus (CMV) infection is endemic worldwide but its seroprevalence varies widely. The goal of this study was to estimate the age-specific seroprevalence of CMV infection in Belgium based on two cross-sectional serological datasets from 2002 and 2006. The seroprevalence was estimated relying on diagnostic test results based on cut-off values pre-specified by the manufacturers of the tests as well as relying on mixture models applied to continuous pathogen-specific immunoglobulin G antibody titre concentrations. The age-specific seroprevalence of hepatitis A virus (HAV), based on three Belgian cross-sectional serological datasets from 1993, 2002 and 2006, was used as a comparator since individuals acquire lifelong immunity upon recovery, implying an increasing seroprevalence with age. The age group weighted overall CMV seroprevalence derived from the mixture model was 32% (95% confidence interval (CI) 31-34%) in 2002 and 31% (95% CI 30-32%) in 2006. We demonstrated that CMV epidemiology differs from the immunizing infection HAV. This was the first large-scale study of CMV and HAV serial datasets in Belgium, estimating seroprevalence specified by age and birth cohort.

Post-treatment human papillomavirus antibody kinetics in cervical cancer patients

Antibodies to the E6 and E7 oncoproteins of high-risk human papillomavirus (HPV) types are strongly associated with HPV-driven cancer, while antibodies against the capsid protein L1 are considered cumulative exposure markers. To test the hypothesis that L1 antibody levels are stable over time, whereas E6 and E7 levels undergo decay after cervical cancer (CxCa) treatment, we performed multiplex serology for HPV16 and 18 antigens E6, E7 and L1 in a post-treatment study of 184 patients with invasive CxCa that were characterized with a median follow-up time of 725 days, and 2-12 sera per patient. Antibody titers significantly decreased within the first six months for HPV16 E6 and E7 but not L1, and stabilized for the following 12 months on a high level, with few patients showing seroreversion. Of 67 patients seropositive for HPV16 E6 at diagnosis, 28 (41.8%) showed a decrease in antibody titers of at least 50% within the first 18 months. Similarly, of 50 HPV16 E7 seropositives, 33 (66.0%) showed decreasing antibody levels, whereas antibody decay was less frequent for HPV16 L1 (12 of 47, 25.5%). Using a power-law mathematical model to characterize antibody decay kinetics, the mean (±s.e.) durations to a 50% reduction in antibody titers within individual patients were estimated to be 56.9 (±26.1) and 56.3 (±19.0) days for HPV16 E6 and E7, respectively. In summary, HPV16 E6 and E7 antibodies undergo a slow but significant decrease in antibody titers within the first 6-18 months following CxCa treatment. However, larger studies are needed to confirm the utility of serology for prediction of disease progression and time to relapse based on antibody decay kinetics. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.

A model for establishment, maintenance and reactivation of the immune response after vaccination against Ebola virus

The 2014-2016 Ebola outbreak in West Africa has triggered accelerated development of several preventive vaccines against Ebola virus. Under the EBOVAC1 consortium, three phase I studies were carried out to assess safety and immunogenicity of a two-dose heterologous vaccination regimen developed by Janssen Vaccines and Prevention in collaboration with Bavarian Nordic. To describe the immune response induced by the two-dose heterologous vaccine regimen, we propose a mechanistic ODE based model, which takes into account the role of immunological memory. We perform identifiability and sensitivity analysis of the proposed model to establish which kind of biological data are ideally needed in order to accurately estimate parameters, and additionally, which of those are non-identifiable based on the available data. Antibody concentrations data from phase I studies have been used to calibrate the model and show its ability in reproducing the observed antibody dynamics. Together with other factors, the establishment of an effective and reactive immunological memory is of pivotal importance for several prophylactic vaccines. We show that introducing a memory compartment in our calibrated model allows to evaluate the magnitude of the immune response induced by a booster dose and its long-term persistence afterwards.

HPV-Specific Systemic Antibody Responses and Memory B Cells are Independently Maintained up to 6 Years and in a Vaccine-Specific Manner Following Immunization with Cervarix and Gardasil in Adolescent and Young Adult Women in Vaccination Programs in Italy

Human papillomavirus (HPV) persistent infections are associated with cervical cancer and other HPV-related diseases and tumors. Thus, the characterization of long lasting immunity to currently available HPV vaccines is important. A total of 149 female subjects vaccinated with Cervarix or Gardasil participated to the study and they were stratified according to age (10–12-year-old and 16–20-year-old). Humoral immune responses (IgG and neutralizing antibody titers, antibody avidity) and circulating memory B cells were analyzed after an average of 4–6 years from the third immunization. The humoral responses against HPV-16 and HPV-18 (and HPV-6 and HPV-11 for Gardasil) were high in both age groups and vaccines up to six years from the third dose. However, Cervarix induced significantly higher and more persistent antibody responses, while the two vaccines were rather equivalent in inducing memory B cells against HPV-16 and HPV-18. Moreover, the percentage of subjects with vaccine-specific memory B cells was even superior among Gardasil vaccinees and, conversely, Cervarix vaccinated individuals with circulating antibodies, but undetectable memory B cells were found. Finally, a higher proportion of Cervarix-vaccinated subjects displayed cross-neutralizing responses against non-vaccine types HPV-31 and HPV-45. Gardasil and Cervarix may, thus, differently affect long-lasting humoral immunity from both the quantitative and qualitative point of view.

Dynamics of the Humoral Immune Response to a Prime-Boost Ebola Vaccine: Quantification and Sources of Variation

The Ebola vaccine based on Ad26.ZEBOV/MVA-BN-Filo prime-boost regimens is being evaluated in multiple clinical trials. The long-term immune response to the vaccine is unknown, including factors associated with the response and variability around the response. We analyzed data from three phase 1 trials performed by the EBOVAC1 Consortium in four countries: the United Kingdom, Kenya, Tanzania, and Uganda. Participants were randomized into four groups based on the interval between prime and boost immunizations (28 or 56 days) and the sequence in which Ad26.ZEBOV and MVA-BN-Filo were administered. Consecutive enzyme-linked immunosorbent assay (ELISA) measurements of the IgG binding antibody concentrations against the Kikwit glycoprotein (GP) were available for 177 participants to assess the humoral immune response up to 1 year postprime. Using a mathematical model for the dynamics of the humoral response, from 7 days after the boost immunization up to 1 year after the prime immunization, we estimated the durability of the antibody response and the influence of different factors on the dynamics of the humoral response. Ordinary differential equations (ODEs) described the dynamics of antibody response and two populations of antibody-secreting cells (ASCs), short-lived (SL) and long-lived (LL). Parameters of the ODEs were estimated using a population approach. We estimated that half of the LL ASCs could persist for at least 5 years. The vaccine regimen significantly affected the SL ASCs and the antibody peak but not the long-term response. The LL ASC compartment dynamics differed significantly by geographic regions analyzed, with a higher long-term antibody persistence in European subjects. These differences could not be explained by the observed differences in cellular immune response.IMPORTANCE With no available licensed vaccines or therapies, the West African Ebola virus disease epidemic of 2014 to 2016 caused 11,310 deaths. Following this outbreak, the development of vaccines has been accelerated. Combining different vector-based vaccines as heterologous regimens could induce a durable immune response, assessed through antibody concentrations. Based on data from phase 1 trials in East Africa and Europe, the dynamics of the humoral immune response from 7 days after the boost immunization onwards were modeled to estimate the durability of the response and understand its variability. Antibody production is maintained by a population of long-lived cells. Estimation suggests that half of these cells can persist for at least 5 years in humans. Differences in prime-boost vaccine regimens affect only the short-term immune response. Geographical differences in long-lived cell dynamics were inferred, with higher long-term antibody concentrations induced in European participants.

Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets

The strength and breadth of an individual's antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.

An ODE-based mixed modelling approach for B- and T-cell dynamics induced by Varicella-Zoster Virus vaccines in adults shows higher T-cell proliferation with Shingrix than with Varilrix

Clinical trials covering the immunogenicity of a vaccine aim to study the longitudinal dynamics of certain immune cells after vaccination. The corresponding immunogenicity datasets are mainly analyzed by the use of statistical (mixed effects) models. This paper proposes the use of mathematical ordinary differential equation (ODE) models, combined with a mixed effects approach. ODE models are capable of translating underlying immunological post vaccination processes into mathematical formulas thereby enabling a testable data analysis. Mixed models include both population-averaged parameters (fixed effects) and individual-specific parameters (random effects) for dealing with inter- and intra-individual variability, respectively. This paper models B-cell and T-cell datasets of a phase I/II, open-label, randomized, parallel-group study (NCT00492648) in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix). Since few significant correlations were found between the B-cell and T-cell datasets, each dataset was modeled separately. By following a general approach to both the formulation of several different models and the procedure of selecting the most suitable model, we were able to propose a mathematical ODE mixed-effects model for each dataset. As such, the use of ODE-based mixed effects models offers a suitable framework for handling longitudinal vaccine immunogenicity data. Moreover, this approach allows testing for differences in immunological processes between vaccines or schedules. We found that the Shingrix vaccination schedule led to a more pronounced proliferation of T-cells, without a difference in T-cell decay rate compared to the Varilrix vaccination schedule.

B Cells as a Therapeutic Target in Paediatric Rheumatic Disease

B cells carry out a central role in the pathogenesis of autoimmune disease. In addition to the production of autoantibodies, B cells can contribute to disease development by presenting autoantigens to autoreactive T cells and by secreting pro-inflammatory cytokines and chemokines which leads to the amplification of the inflammatory response. Targeting both the antibody-dependent and antibody-independent function of B cells in adult rheumatic disease has led to the advent of B cell targeted therapies in clinical practice. To date, whether B cell depletion could also be utilized for the treatment of pediatric disease is relatively under explored. In this review, we will discuss the role of B cells in the pathogenesis of the pediatric rheumatic diseases Juvenile Idiopathic Arthritis (JIA), Juvenile Systemic Lupus Erythematosus (JSLE) and Juvenile Dermatomyositis (JDM). We will also explore the rationale behind the use of B cell-targeted therapies in pediatric rheumatic disease by highlighting new case studies that points to their efficacy in JIA, JSLE, and JDM.

Antibody kinetics following vaccination with MenAfriVac: an analysis of serological data from randomised trials

BACKGROUND

A meningococcal group A conjugate vaccine, PsA-TT (also known as MenAfriVac), was developed with the support of the Meningitis Vaccine Project. Around 280 million individuals aged 1-29 years have been immunised across the African meningitis belt. We analysed the kinetics of vaccine-induced antibody response and assessed the possible implications for duration of protection.

METHODS

We obtained data from two longitudinal studies done in The Gambia, Mali, and Senegal of antibody responses in 193 children aged 12-23 months and 604 participants aged 2-29 years following MenAfriVac vaccination. Antibodies were measured using two methods: group A serum bactericidal antibody (SBA) assay and group A-specific IgG ELISA. Data on antibody responses were analysed using a mixed-effects statistical model accounting for the mean response and variation in patterns of antibody kinetics. Determinants of antibody duration were investigated using regression analysis.

FINDINGS

In children age 12-23 months, the reduction in MenAfriVac-induced antibody levels assessed by SBA titres had two phases: with 97·0% (95% credible interval [CrI] 95·1-98·3) of the response being short lived and decaying within the first 6 months and the remainder being long lived and decaying with a half-life of 2690 days (95% CrI 1016-15 078). Antibody levels assessed by SBA titres in participants aged 2-29 years were more persistent, with 95·0% (85·7-98·1) of the response being short lived, and the long lived phase decaying with a half-life of 6007 days (95% CrI 2826-14 279). Greater pre-vaccination antibody levels were associated with greater immunogenicity following vaccination, as well as greater antibody persistence. Despite rapid antibody declines in the first phase, antibodies in the second phase persisted at SBA titres greater than 128. Although there is no strong evidence base for a correlate of protection against infection with Neisseria meningitidis serogroup A, we use an assumed SBA titre of 128 as a threshold of protection to predict that 20 years after vaccination with a single dose of MenAfriVac, vaccine efficacy will be 52% (29-73) in children vaccinated at age 12-23 months and 70% (60-79) in participants vaccinated at age 2-29 years.

INTERPRETATION

Population-level immunity induced by routine vaccination with the Expanded Programme on Immunization is predicted to persist at levels sufficient to confer more than 50% protection over a 20-year time period. Further increases in population-level immunity could be obtained via mass campaigns or by delaying the age of vaccination through the Expanded Programme on Immunization. However, the benefits of such a strategy would need to be weighed against the risks of leaving young children unvaccinated for longer.

FUNDING

Meningitis Vaccine Project and Institut Pasteur.

Immunization against Hepatitis E

Soon after the 1991 molecular cloning of hepatitis E virus (HEV), recombinant viral capsid antigens were expressed and tested in nonhuman primates for protection against liver disease and infection. Two genotype 1 subunit vaccine candidates entered clinical development: a 56 kDA vaccine expressed in insect cells and HEV 239 vaccine expressed in Escherichia coli Both were highly protective against hepatitis E and acceptably safe. The HEV 239 vaccine was approved in China in 2011, but it is not yet prequalified by the World Health Organization, a necessary step for introduction into those low- and middle-income countries where the disease burden is highest. Nevertheless, the stage is set for the final act in the hepatitis E vaccine story-policymaking, advocacy, and pilot introduction of vaccine in at-risk populations, in which it is expected to be cost-effective.

Estimating Parameters Related to the Lifespan of Passively Transferred and Vaccine-Induced Porcine Reproductive and Respiratory Syndrome Virus Type I Antibodies by Modeling Field Data

The outputs of epidemiological models are strongly related to the structure of the model and input parameters. The latter are defined by fitting theoretical concepts to actual data derived from field or experimental studies. However, some parameters may remain difficult to estimate and are subject to uncertainty or sensitivity analyses to determine their variation range and their global impact on model outcomes. As such, the evaluation of immunity duration is often a puzzling issue requiring long-term follow-up data that are, most of time, not available. The present analysis aims at characterizing the kinetics of antibodies against Porcine Reproductive and Respiratory Syndrome virus (PRRSv) from longitudinal data sets. The first data set consisted in the serological follow-up of 22 vaccinated gilts during 21 weeks post-vaccination (PV). The second one gathered the maternally derived antibodies (MDAs) kinetics in piglets from three different farms up to 14 weeks of age. The peak of the PV serological response against PRRSv was reached 6.9 weeks PV on average with an average duration of antibodies persistence of 26.5 weeks. In the monitored cohort of piglets, the duration of passive immunity was found relatively short, with an average duration of 4.8 weeks. The level of PRRSv-MDAs was found correlated with the dams' antibody titer at birth, and the antibody persistence was strongly related to the initial MDAs titers in piglets. These results evidenced the importance of PRRSv vaccination schedule in sows, to optimize the delivery of antibodies to suckling piglets. These estimates of the duration of active and passive immunity could be further used as input parameters of epidemiological models to analyze their impact on the persistence of PRRSv within farms.

Quantification of plasma cell dynamics using mathematical modelling

Plasma cells (PCs) are the main antibody-producing cells in humans. They are long-lived so that specific antibodies against either pathogens or vaccines are produced for decades. PC longevity is attributed to specific areas within the bone marrow micro-environment, the so-called 'niche', providing the cells with required growth and survival factors. With antigen encounters, e.g. infection or vaccination, new PCs are generated and home to the bone marrow where they compete with resident PCs for the niche. We propose a parametrized mathematical model describing healthy PC dynamics in the bone marrow. The model accounts for competition for the niche between newly produced PCs owing to vaccination and resident PCs. Mathematical analysis and numerical simulations of the model allow explanation of the recovery of PC homoeostasis after a vaccine-induced perturbation, and the fraction of vaccine-specific PCs inside the niche. The model enables quantification of the niche-related dynamics of PCs, i.e. the duration of PC transition into the niche and the impact of different rates for PC transitions into and out of the niche on the observed cell dynamics. Ultimately, it provides a potential basis for further investigations in health and disease.

A model for the regulation of follicular dendritic cells predicts invariant reciprocal-time decay of post-vaccine antibody response

Follicular dendritic cells (FDC) play a crucial role in the regulation of humoral immunity. They are believed to be responsible for long-term persistence of antibody, due to their role in antibody response induction and their ability to retain antigen in immunogenic form for long periods. In this article, a regulatory control model is proposed which links persistence of humoral immunity with cellular processes associated with FDCs. The argument comprises three elements. The first is a literature review of population-level studies of post-vaccination antibody persistence. It is found that reciprocal-time (∝1/t) decay of antibody levels is widely reported, over a range of ages, observation times and vaccine types. The second element is a mathematical control model for cell population decay for which reciprocal-time decay is a stable attractor. Additionally, control effectors are easily identified, leading to models of homeostatic control of the reciprocal-time decay rate. The final element is a literature review of FDC functionality. This reveals a striking concordance between cell properties required by the model and those widely observed of FDCs, some of which are unique to this cell type. The proposed model is able to unify a wide range of disparate observations of FDC function under one regulatory principle, and to characterize precisely forms of FDC regulation and dysregulation. Many infectious and immunological diseases are increasingly being linked to FDC regulation, therefore a precise understanding of the underlying mechanisms would be of significant benefit for the development of new therapies.

Multidisciplinary study of the secondary immune response in grandparents re-exposed to chickenpox

Re-exposure to chickenpox may boost varicella-zoster virus (VZV) immunity in the elderly. This secondary immune response is hypothesized to confer protection against herpes zoster. We longitudinally sampled 36 adults over the course of one year after re-exposure to chickenpox. The resulting 183 samples and those of 14 controls were assessed for VZV-specific T-cell immunity and antibody titres. The percentages of VZV-specific CD4+ IL-2-producing T-cells were increased in re-exposed grandparents compared to control participants up to 9 months after re-exposure. Using a longitudinal mixture modelling approach, we found that 25% and 17% of re-exposed grandparents showed a boosting of VZV-specific CD4+ IL-2-producing T-cells and VZV-specific antibodies, respectively. The antibody boosting occurred exclusively in cytomegalovirus (CMV) IgG-positive participants. CMV IgG-positive participants also had higher VZV IE62-specific CD4+ IFN-γ-producing T-cell percentages and VZV-specific antibody titres. The protective effect of re-exposure to chickenpox is likely limited, as boosting only occurred in 17–25% of the VZV re-exposed grandparents and for less than one year.

Inferring infection hazard in wildlife populations by linking data across individual and population scales

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

Predictors of durable immune responses six months after the last vaccination in preventive HIV vaccine trials

BACKGROUND

The evaluation of durable immune responses is important in HIV vaccine research and development. The efficiency of such evaluation could be increased by incorporating predictors of the responses in the statistical analysis. In this paper, we investigated whether and how baseline demographic variables and immune responses measured two weeks after vaccination predicted durable immune responses measured six months later.

METHODS

We included data from seven preventive HIV vaccine regimens evaluated in three clinical trials: a Phase 1 study of four DNA, NYVAC and/or AIDSVAX vaccine regimens (HVTN096), a Phase 2 study of two DNA and/or MVA vaccine regimens (HVTN205), and a Phase 3 study of a single ALVAC/AIDSVAX regimen (RV144). Regularized random forests and linear regression models were used to identify and evaluate predictors of the positivity and magnitude of durable immune responses.

RESULTS

We analyzed 201 vaccine recipients with data from 10 to 127 immune response biomarkers, and 3-5 demographic variables. The best prediction of participants' durable response positivity based on two-week responses rendered up to close-to-perfect accuracy; the best prediction of participants' durable response magnitude rendered correlation coefficients between the observed and predicted responses ranging up to 0.91. Though prediction performances differed among biomarkers, durable immune responses were best predicted by the two-week response level of the same biomarker. Adding demographic information and two-week response levels of different biomarkers provided little or no improvement in the predictions.

CONCLUSIONS

For some biomarkers and for the vaccines we studied, two-week post-vaccination responses can well predict durable responses six months later. Therefore, if immune response durability is only assessed in a sub-sample of vaccine recipients, statistical analyses of durable responses will have increased efficiency by incorporating two-week response data. Further research is needed to generalize the findings to other vaccine regimens and biomarkers. Clinicaltrials.gov identifiers: NCT01799954, NCT00820846, NCT00223080.

Serological markers to measure recent changes in malaria at population level in Cambodia

Background

Serological markers for exposure to different Plasmodium species have recently been used in multiplex immunoassays based on the Luminex technology. However, interpretation of the assay results requires consideration of the half-life of specific antibodies against these markers. Therefore, the aim of the present study was to document the half-life of malaria specific serological makers, as well as assessing the sensitivity of these markers to pick up recent changes in malaria exposure.

Methods

A recently developed multiplex immunoassay was used to measure the intensity of antibody (Ab) responses against 19 different Plasmodium specific antigens, covering different human malaria parasites and two vector saliva antigens. Therefore, 8439 blood samples from five cross-sectional surveys in Ratanakiri, Cambodia, were analysed. These involve a random selection from two selected surveys, and an additional set of blood samples of individuals that were randomly re-sampled three, four or five times. A generalized estimating equation model and linear regression models were fitted on log transformed antibody intensity data.

Results

Results showed that most (17/21) Ab-responses are higher in PCR positive than PCR negative individuals. Furthermore, these antibody-responses follow the same upward trend within each age group. Estimation of the half-lives showed differences between serological markers that reflect short- (seasonal) and long-term (year round) transmission trends. Ab levels declined significantly together with a decrease of PCR prevalence in a group of malaria endemic villages.

Conclusion

For Plasmodium falciparum, antibodies against LSA3.RE, GLURP and Pf.GLURP.R2 are most likely to be a reflexion of recent (range from 6 to 8 months) exposure in the Mekong Subregion. PvEBP is the only Plasmodium vivax Ag responding reasonably well, in spite of an estimated Ab half-life of more than 1 year. The use of Ab intensity data rather dichotomizing the continuous Ab-titre data (positive vs negative) will lead to an improved approach for serological surveillance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1576-z) contains supplementary material, which is available to authorized users.

Estimating Time of Infection Using Prior Serological and Individual Information Can Greatly Improve Incidence Estimation of Human and Wildlife Infections

Diseases of humans and wildlife are typically tracked and studied through incidence, the number of new infections per time unit. Estimating incidence is not without difficulties, as asymptomatic infections, low sampling intervals and low sample sizes can introduce large estimation errors. After infection, biomarkers such as antibodies or pathogens often change predictably over time, and this temporal pattern can contain information about the time since infection that could improve incidence estimation. Antibody level and avidity have been used to estimate time since infection and to recreate incidence, but the errors on these estimates using currently existing methods are generally large. Using a semi-parametric model in a Bayesian framework, we introduce a method that allows the use of multiple sources of information (such as antibody level, pathogen presence in different organs, individual age, season) for estimating individual time since infection. When sufficient background data are available, this method can greatly improve incidence estimation, which we show using arenavirus infection in multimammate mice as a test case. The method performs well, especially compared to the situation in which seroconversion events between sampling sessions are the main data source. The possibility to implement several sources of information allows the use of data that are in many cases already available, which means that existing incidence data can be improved without the need for additional sampling efforts or laboratory assays.

The Tao of myeloma

Multiple myeloma is a plasma cell malignancy in which significant advances have been observed during the last 15 years. Our understanding of the disease has been advanced through its molecular characterization. We have also seen improvements in patient care with the development of 2 new classes of active agents, proteasome inhibitors and immunomodulatory drugs (IMiDs), resulting in a significant improvement in overall survival of myeloma patients such that it can now be debated as to whether some subsets of myeloma patients can be cured. However, the advances in our understanding of myeloma biology occurred in parallel with advances in treatment as opposed to being directly informed by the research. Moreover, the molecular characterization of malignant plasma cells would not have predicted the effectiveness of these novel therapies.We hypothesize that proteasome inhibitors and IMiDs are highly active because malignant plasma cells are constrained by many of the characteristics of their normal counterparts and these novel therapies target both normal plasma cell biology and the cancer biology of myeloma. Thus, a better understanding of normal plasma cell biology will likely yield as many actionable targets as mapping the genomic landscape of this disease.

Modeling the long-term antibody response of a hepatitis E vaccine

BACKGROUND

The first commercialized hepatitis E vaccine, HEV 239, has been shown to be safe and highly immunogenic, the protection as well as the vaccine-induced anti-HEV maintained for at least 4.5 years. However, the longer term persistence of the vaccine-induced anti-HEV responses is unknown.

METHODS

Two statistical models, the power-law model and the modified power-law model, were applied to predict the long-term antibody response of the HEV 239 vaccine. The models were fit using the anti-HEV IgG data from a modeling subpopulation of 1278 baseline seronegative vaccinees who seroconverted within one month after finishing the whole vaccination course in the phase 3 trial of HEV 239. In addition, antibody data from a validation subpopulation were used to validate the robustness of the derived models.

RESULTS

In the vaccinees without pre-vaccination immunity, the power-law model and the modified power-law model estimated that the median duration of the detectable antibody (≥0.077 WU/ml) was 8 years and 13 years, respectively. The power-law model and the modified power-law model estimated that 50% of these vaccinees will maintain detectable levels of anti-HEV IgG for 8 years and >30 years, respectively.

CONCLUSIONS

The recombinant hepatitis E vaccine HEV 239 is predicted to provide from 8 years to nearly life-long persistence of anti-HEV IgG above detectable levels. Model predictions are based on conservative mathematical assumptions. (NCT01014845).

Detection of GB virus C genomic sequence in the cerebrospinal fluid of a HIV-infected patient in China: a case report and literature review

Hepatitis G virus or GB virus C (GBV-C) is a human virus of the Flaviviridae family that is structurally and epidemiologically closest to hepatitis C virus, but replicates primarily in lymphocytes. Co-infection with GBV-C has been reported to confer beneficial outcomes in some HIV-positive patients. Up to now, however, studies on GBV-C infection in the central nervous system (CNS) of HIV-infected patient have rarely been reported. Herein, we report on a 32-year-old HIV-1-infected patient with cerebral toxoplasmosis and fungal encephalitis. GBV-C viral loads were detected in CSF by quantitative real-time reverse transcription polymerase chain reaction (RT-PCR), and the results showed that GBV-C viral load was 6·5 log copies/ml. We amplified and sequenced the E2 and 5'-untranslated regions from the purified viral RNA from CSF by RT-PCR. Both sequences belong to genotype 3 and there were some minor nucleotide divergence among the E2 sequences from the CSF of the patient. These data suggest that GBV-C may be able to penetrate the blood-brain barrier and colonize the CNS of HIV-infected patients. However, the exact mechanisms and potential effect of the infected GBV-C in CNS on HIV-associated neuropathy needs to be further explored.

Antibody persistence and T-cell balance: two key factors confronting HIV vaccine development

The quest for a prophylactic AIDS vaccine is ongoing, but it is now clear that the successful vaccine must elicit protective antibody responses. Accordingly, intense efforts are underway to identify immunogens that elicit these responses. Regardless of the mechanism of antibody-mediated protection, be it neutralization, Fc-mediated effector function, or both, antibody persistence and appropriate T-cell help are significant problems confronting the development of a successful AIDS vaccine. Here, we discuss the evidence illustrating the poor persistence of antibody responses to Env, the envelope glycoprotein of HIV-1, and the related problem of CD4(+) T-cell responses that compromise vaccine efficacy by creating excess cellular targets of HIV-1 infection. Finally, we propose solutions to both problems that are applicable to all Env-based AIDS vaccines regardless of the mechanism of antibody-mediated protection.

Model based estimates of long-term persistence of inactivated hepatitis A vaccine-induced antibodies in adults

BACKGROUND

In this paper, we review the results of existing statistical models of the long-term persistence of hepatitis A vaccine-induced antibodies in light of recently available immunogenicity data from 2 clinical trials (up to 17 years of follow-up).

METHODS

Healthy adult volunteers monitored annually for 17 years after the administration of the first vaccine dose in 2 double-blind, randomized clinical trials were included in this analysis. Vaccination in these studies was administered according to a 2-dose vaccination schedule: 0, 12 months in study A and 0, 6 months in study B (NCT00289757/NCT00291876). Antibodies were measured using an in-house ELISA during the first 11 years of follow-up; a commercially available ELISA was then used up to Year 17 of follow-up. Long-term antibody persistence from studies A and B was estimated using statistical models for longitudinal data. Data from studies A and B were modeled separately.

RESULTS

A total of 173 participants in study A and 108 participants in study B were included in the analysis. A linear mixed model with 2 changepoints allowed all available results to be accounted for. Predictions based on this model indicated that 98% (95%CI: 94-100%) of participants in study A and 97% (95%CI: 94-100%) of participants in study B will remain seropositive 25 years after receiving the first vaccine dose. Other models using part of the data provided consistent results: ≥95% of the participants was projected to remain seropositive for ≥25 years.

CONCLUSION

This analysis, using previously used and newly selected model structures, was consistent with former estimates of seropositivity rates ≥95% for at least 25 years.