Dataset Information

Reconstruction of antibody dynamics and infection histories to evaluate dengue risk.

ABSTRACT: As with many pathogens, most dengue infections are subclinical and therefore unobserved 1 . Coupled with limited understanding of the dynamic behaviour of potential serological markers of infection, this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how these change over time, between assay interpretations and with cohort design. Here we develop a framework that simultaneously characterizes antibody dynamics and identifies subclinical infections via Bayesian augmentation from detailed cohort data (3,451 individuals with blood draws every 91 days, 143,548 haemagglutination inhibition assay titre measurements)2,3. We identify 1,149 infections (95% confidence interval, 1,135-1,163) that were not detected by active surveillance and estimate that 65% of infections are subclinical. After infection, individuals develop a stable set point antibody load after one year that places them within or outside a risk window. Individuals with pre-existing titres of ≤1:40 develop haemorrhagic fever 7.4 (95% confidence interval, 2.5-8.2) times more often than naive individuals compared to 0.0 times for individuals with titres >1:40 (95% confidence interval: 0.0-1.3). Plaque reduction neutralization test titres ≤1:100 were similarly associated with severe disease. Across the population, variability in the size of epidemics results in large-scale temporal changes in infection and disease risk that correlate poorly with age.

SUBMITTER: Salje H

PROVIDER: S-EPMC6064976 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Publications

Reconstruction of antibody dynamics and infection histories to evaluate dengue risk.

Salje Henrik H Cummings Derek A T DAT Rodriguez-Barraquer Isabel I Katzelnick Leah C LC Lessler Justin J Klungthong Chonticha C Thaisomboonsuk Butsaya B Nisalak Ananda A Weg Alden A Ellison Damon D Macareo Louis L Yoon In-Kyu IK Jarman Richard R Thomas Stephen S Rothman Alan L AL Endy Timothy T Cauchemez Simon S

Nature 20180523 7707

As with many pathogens, most dengue infections are subclinical and therefore unobserved <sup>1</sup> . Coupled with limited understanding of the dynamic behaviour of potential serological markers of infection, this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how these change over time, between assay interpretations and with cohort design. Here we develop a framework tha ...[more]

PMID: 29795354

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Project description:Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns in humans and to investigate how influenza incidence varies over time, space, and age in this population. We estimated median annual influenza infection rates to be approximately 19% from 1968 to 2015, but with substantial variation between years; 88% of individuals were estimated to have been infected at least once during the study period (2009 to 2015), and 20% were estimated to have 3 or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long-term epidemiological trends, within-host processes, and immunity when analysed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

Project description:Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology remains unclear. Here, we used a multi-level mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns and to investigate how influenza incidence varies over time, space and age in this population. We estimated median annual influenza infection rates to be approximately 18% from 1968 to 2015, but with substantial variation between years. 88% of individuals were estimated to have been infected at least once during the study period (2009-2015), and 20% were estimated to have three or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long term, epidemiological trends, within-host processes and immunity when analyzed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

Project description:Dengue is a major public health problem in tropical and sub-tropical regions worldwide. Since the Zika epidemic and the increased co-circulation of other arboviruses, the serology-based diagnosis of dengue has become more problematic due to the high antigenic resemblance, especially among the flavivirus family. Therefore, a more comprehensive understanding of the diversity, specificity and temporal evolution of the antibody response following dengue infection is needed. In order to close this knowledge gap, we used a high-density peptide microarray of 9,072 linear peptides covering the entire proteome diversity of dengue, Zika, yellow fever and chikungunya viruses. The IgM and IgG antibody responses were measured against the designed microarray in symptomatic dengue infected individuals from an arbovirus endemic area in Peru and in overseas travelers returning to Belgium, as representatives of multiple-exposed and primary infections, respectively. Serum samples were collected longitudinally across four time points over the period of six months in Peru and over two time points in travelers. We show that epitopes eliciting the strongest flavivirus cross-reactive antibodies, in both primary and secondary infections were concentrated in the capsid, E, NS1, NS3 and NS5 proteins. The IgG antibody responses against NS1 and NS3 followed a rise-and-fall pattern, with peak titers between two to four weeks after onset of illness. The response to the E and NS5 proteins increased rapidly in the acute phase and was maintained at stable levels until at least 6 months after illness. A more scattered IgM antibody reactivity across the viral proteome was observed in the acute phase of the disease and that persisted through the 6-month window. The magnitude, breadth (i.e. number of unique epitopes targeted) and depth (i.e. number of epitope variants recognized) of the IgG response was higher in secondary infections compared to primary infections. For IgM antibodies, the magnitude of the response was higher in primary infected individuals whereas the breadth and depth of the response was lower in this group compared with the endemic subjects. Finally, through this arboviral proteome-wide epitope mapping, we were able to identify IgM and IgG dengue-specific epitopes which can be useful serological markers for dengue diagnosis and serostatus determination.

Dataset Information

Reconstruction of antibody dynamics and infection histories to evaluate dengue risk.

Publications

Reconstruction of antibody dynamics and infection histories to evaluate dengue risk.

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