Dataset Information

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection.

ABSTRACT:

Background

Sensitive methods are needed to estimate the population-level incidence of hepatitis C virus (HCV) infection.

Methods

We developed an HCV immunoglobulin G (IgG) antibody avidity assay by modifying the Ortho 3.0 HCV enzyme-linked immunoassay and tested 997 serum or plasma samples from 568 people who inject drugs enrolled in prospective cohort studies. Avidity-based testing algorithms were evaluated by their (1) mean duration of recent infection (MDRI), defined as the average time an individual is identified as having been recently infected, according to a given algorithm; (2) false-recent rate, defined as the proportion of samples collected >2 years after HCV seroconversion that were misclassified as recent; (3) sample sizes needed to estimate incidence; and (4) power to detect a reduction in incidence between serial cross-sectional surveys.

Results

A multiassay algorithm (defined as an avidity index of <30%, followed by HCV viremia detection) had an MDRI of 147 days (95% confidence interval [CI], 125-195 days), and the false-recent rates were 0.7% (95% CI, .2%-1.8%) and 7.6% (95% CI, 4.2%-12.3%) among human immunodeficiency virus (HIV)-negative and HIV-positive persons, respectively. In various simulated high-risk populations, this algorithm required <1000 individuals to estimate incidence (relative standard error, 30%) and had >80% power to detect a 50% reduction in incidence.

Conclusions

Avidity-based algorithms have the capacity to accurately estimate HCV infection incidence and rapidly assess the impact of public health efforts among high-risk populations. Efforts to optimize this method should be prioritized.

SUBMITTER: Patel EU

PROVIDER: S-EPMC4936640 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection.

Patel Eshan U EU Cox Andrea L AL Mehta Shruti H SH Boon Denali D Mullis Caroline E CE Astemborski Jacquie J Osburn William O WO Quinn Jeffrey J Redd Andrew D AD Kirk Gregory D GD Thomas David L DL Quinn Thomas C TC Laeyendecker Oliver O

The Journal of infectious diseases 20160114 3

<h4>Background</h4>Sensitive methods are needed to estimate the population-level incidence of hepatitis C virus (HCV) infection.<h4>Methods</h4>We developed an HCV immunoglobulin G (IgG) antibody avidity assay by modifying the Ortho 3.0 HCV enzyme-linked immunoassay and tested 997 serum or plasma samples from 568 people who inject drugs enrolled in prospective cohort studies. Avidity-based testing algorithms were evaluated by their (1) mean duration of recent infection (MDRI), defined as the ave ...[more]

PMID: 26768250

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Project description:Background & aimsAccurate HCV incidence estimates are critical for monitoring progress towards HCV elimination goals, including an 80% reduction in HCV incidence by 2030. Moreover, incidence estimates can help guide prevention and treatment programming, particularly in the context of the US opioid epidemic.MethodsAn inexpensive, Genedia-based HCV IgG antibody avidity assay was evaluated as a platform to estimate cross-sectional, population-level primary HCV incidence using 1,840 HCV antibody and RNA-positive samples from 875 individuals enrolled in 5 cohort studies in the US and India. Using samples collected <2 years following HCV seroconversion, the mean duration of recent infection (MDRI) was calculated by fitting a maximum likelihood binomial regression model to the probability of appearing recent. Among samples collected ≥2 years post-HCV seroconversion, an individual-level false recent ratio (FRR) was calculated by estimating the probability of appearing recent using an exact binomial test. Factors associated with falsely appearing recent among samples collected ≥2 years post seroconversion were determined by Poisson regression with generalized estimating equations and robust variance estimators.ResultsAn avidity index cut-off of <40% resulted in an MDRI of 113 days (95% CI 84-146), and FRRs of 0.4% (95% CI 0.0-1.2), 4.6% (95% CI 2.2-8.3), and 9.5% (95% CI 3.6-19.6) among individuals who were HIV-uninfected, HIV-infected, and HIV-infected with a CD4 count <200/μl, respectively. No variation was seen between HCV genotypes 1 and 3. In hypothetical scenarios of high-risk settings, a sample size of <1,000 individuals could reliably estimate primary HCV incidence.ConclusionsThis cross-sectional approach can estimate primary HCV incidence for the most common genotypes. This tool can serve as a valuable resource for program and policy planners seeking to monitor and reduce HCV burden.Lay summaryDetermining the rate of new hepatitis C virus (HCV) infections in a population is critical to monitoring progress toward HCV elimination and to appropriately guide control efforts. However, since HCV infections are most often initially asymptomatic, it is difficult to estimate the rate of new HCV infections without following HCV-uninfected people over time and repeatedly testing them for HCV infection. Here, we present a novel, resource-efficient method to estimate the rate of new HCV infections in a population using data from a single timepoint.

Project description:During hepatitis C virus (HCV) infection, broadly neutralizing antibody (bNAb) responses targeting E1E2 envelope glycoproteins are generated in many individuals. It is unclear if these antibodies play a protective or a pathogenic role during chronic infection. In this study, we investigated whether bNAb responses in individuals with chronic infection were associated with differences in clinical presentation. Patient-derived purified serum IgG was used to assess the breadth of HCV E1E2 binding and the neutralization activity of HCV pseudoparticles. The binding and neutralization activity results for two panels bearing viral envelope proteins representing either an intergenotype or an intragenotype 1 group were compared. We found that the HCV load was negatively associated with strong cross-genotypic E1E2 binding (P= 0.03). Overall, we observed only a modest correlation between total E1E2 binding and neutralization ability. The breadth of intergenotype neutralization did not correlate with any clinical parameters; however, analysis of individuals with genotype 1 (gt1) HCV infection (n= 20), using an intragenotype pseudoparticle panel, found a strong association between neutralization breadth and reduced liver fibrosis (P= 0.006). A broad bNAb response in our cohort with chronic infection was associated with a single nucleotide polymorphism (SNP) in theHLA-DQB1 gene (P= 0.038), as previously reported in a cohort with acute disease. Furthermore, the bNAbs in these individuals targeted more than one region of E2-neutralizing epitopes, as assessed through cross-competition of patient bNAbs with well-characterized E2 antibodies. We conclude that the bNAb responses in patients with chronic gt1 infection are associated with lower rates of fibrosis and host genetics may play a role in the ability to raise such responses.Globally, there are 130 million to 150 million people with chronic HCV infection. Typically, the disease is progressive and is a major cause of severe liver cirrhosis and hepatocellular carcinoma. While it is known that neutralizing antibodies have a role in spontaneous clearance during acute infection, little is known about their role in chronic infection. In the present work, we investigated the antibody response in a cohort of chronically infected individuals and found that a broadly neutralizing antibody response is protective and is associated with reduced levels of liver fibrosis and cirrhosis. We also found an association between SNPs in class II HLA genes and the presence of a broadly neutralizing response, indicating that antigen presentation may be important for the production of HCV-neutralizing antibodies.

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Dataset Information

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection.

Background

Methods

Results

Conclusions

Publications

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection.

Similar Datasets

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