Protective Role of NS1-Specific Antibodies in the Immune Response to Dengue Virus through Antibody-Dependent Cellular Cytotoxicity.

BACKGROUND: Dengue virus (DENV) non-structural protein 1 (NS1) has multiple functions within infected cells, on the cell surface, and in secreted form, and is highly immunogenic. Immunity from previous DENV infections is known to exert both positive and negative effects on subsequent DENV infections, but the contribution of NS1-specific antibodies to these effects is incompletely understood. METHODS: We investigated the functions of NS1-specific antibodies and their significance in DENV infection. We analyzed plasma samples collected in a prospective cohort study prior to symptomatic or subclinical secondary DENV infection. We measured binding to purified recombinant NS1 protein and to NS1-expressing CEM cells, antibody-mediated NK cell activation by plate-bound NS1 protein, and antibody-dependent cellular cytotoxicity (ADCC) of NS1-expressing target cells. RESULTS: We found that antibody responses to NS1 were highly serotype-cross-reactive and that subjects who experienced subclinical DENV infection had significantly higher antibody responses to NS1 in pre-infection plasma than subjects who experienced symptomatic infection. We observed strong positive correlations between antibody binding and NK activation. CONCLUSIONS: These findings demonstrate the involvement of NS1-specific antibodies in ADCC and provide evidence for a protective effect of NS1-specific antibodies in secondary DENV infection.

Household immunity and individual risk of infection with dengue virus in a prospective, longitudinal cohort study.

Although it is known that household infections drive the transmission of dengue virus (DENV), it is unclear how household composition and the immune status of inhabitants affect the individual risk of infection. Most population-based studies to date have focused on paediatric cohorts because more severe forms of dengue mainly occur in children, and the role of adults in dengue transmission is understudied. Here we analysed data from a multigenerational cohort study of 470 households, comprising 2,860 individuals, in Kamphaeng Phet, Thailand, to evaluate risk factors for DENV infection. Using a gradient-boosted regression model trained on annual haemagglutination inhibition antibody titre inputs, we identified 1,049 infections, 90% of which were subclinical. By analysing imputed infections, we found that individual antibody titres, household composition and antibody titres of other members in the same household affect an individual's risk of DENV infection. Those individuals living in households with high average antibody titres, or households with more adults, had a reduced risk of infection. We propose that herd immunity to dengue acts at the household level and may provide insight into the drivers of the recent change in the shifting age distribution of dengue cases in Thailand.

Reconciling heterogeneous dengue virus infection risk estimates from different study designs.

Uncovering rates at which susceptible individuals become infected with a pathogen, i.e. the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology are considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis. Significance statement: Dengue virus infections are surging globally. Knowing who, where, and how many people are at risk of infection is crucial in determining means to protect them. Here, we compare three current approaches in measuring risk (two involving blood samples and one involving case counts) to estimate the risk of infection. Estimates derived from each method differed greatly. By accounting for rise and falls of antibodies following infections, noise in the antibody titer measurements, and heterogeneity in infection risk across ages, we reconciled the measurements. As measurements from blood samples and case counts are pillars in uncovering risk of most infectious diseases, our results signifies integrating these processes into risk measurements of pathogens beyond dengue virus.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity.

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross-validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric significantly improved model performance.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity.

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric, significantly improved model performance.

Anti-Arbovirus Antibodies Cross-React With Severe Acute Respiratory Syndrome Coronavirus 2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is found in regions where dengue (DENV) and chikungunya (CHIKV) viruses are endemic. Any serological cross-reactivity between DENV, CHIKV, and SARS-CoV-2 is significant as it could lead to misdiagnosis, increased severity, or cross-protection. This study examined the potential cross-reactivity of anti-DENV and CHIKV antibodies with SARS-CoV-2 using acute and convalescent-phase samples collected before the SARS-CoV-2 pandemic. These included healthy, normal human (NHS, n = 6), CHIKV-positive (n = 14 pairs acute and convalescent), primary DENV-positive (n = 20 pairs), secondary DENV-positive (n = 20 pairs), and other febrile illnesses sera (n = 23 pairs). Samples were tested using an in-house SARS-CoV-2 and a EUROIMMUN IgA and IgG ELISAs. All NHS samples were negative, whereas 3.6% CHIKV, 21.7% primary DENV, 15.7% secondary DENV, and 10.8% febrile diseases sera resulted as anti-SARS-CoV-2 antibody positive. The EUROIMMUN ELISA using spike 1 as the antigen detected more positives among the primary DENV infections than the in-house ELISA using spike 1-receptor binding domain (RBD) protein. Among ELISA-positive samples, four had detectable neutralizing antibodies against SARS-CoV-2 reporter virus particles yet none had detectable neutralizing antibodies against the live Wuhan strain of SARS-CoV-2. These data demonstrated the SARS-CoV-2 diagnostic cross-reactivity, but not neutralizing antibody cross-reactivity, among dengue seropositive cases. IMPORTANCE SARS-CoV-2 continues to cause significant morbidity globally, including in areas where DENV and CHIKV are endemic. Reports using rapid diagnostic and ELISAs have demonstrated that serological cross-reactivity between DENV and SARS-CoV-2 can occur. Furthermore, it has been observed that convalescent DENV patients are at a lower risk of developing COVID-19. This phenomenon can interfere with the accuracy of serological testing and clinical management of both DENV and COVID-19 patients. In this study, the cross-reactivity of primary/secondary anti-DENV, CHIKV, and other febrile illness antibodies with SARS-CoV-2 using two ELISAs has been shown. Among ELISA-positive samples, four had detectable levels of neutralizing antibodies against SARS-CoV-2 reporter virus particles. However, none had detectable neutralizing antibodies against the live Wuhan strain of SARS-CoV-2. These data demonstrated SARS-CoV-2 diagnostic cross-reactivity, but not neutralizing antibody cross-reactivity, among dengue seropositive cases. The data discussed here provide information regarding diagnosis and may help guide appropriate public health interventions.