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

Biomarkers in Detection of Hepatitis C Virus Infection

The hepatitis C virus (HCV) infection affects 58 million people worldwide. In the United States, the incidence rate of acute hepatitis C has doubled since 2014; during 2021, this increased to 5% from 2020. Acute hepatitis C is defined by any symptom of acute viral hepatitis plus either jaundice or elevated serum alanine aminotransferase (ALT) activity with the detection of HCV RNA, the anti-HCV antibody, or hepatitis C virus antigen(s). However, most patients with acute infection are asymptomatic. In addition, ALT activity and HCV RNA levels can fluctuate, and a delayed detection of the anti-HCV antibody can occur among some immunocompromised persons with HCV infection. The detection of specific biomarkers can be of great value in the early detection of HCV infection at an asymptomatic stage. The high rate of HCV replication (which is approximately 1010 to 1012 virions per day) and the lack of proofreading by the viral RNA polymerase leads to enormous genetic diversity, creating a major challenge for the host immune response. This broad genetic diversity contributes to the likelihood of developing chronic infection, thus leading to the development of cirrhosis and liver cancer. Direct-acting antiviral (DAA) therapies for HCV infection are highly effective with a cure rate of up to 99%. At the same time, many patients with HCV infection are unaware of their infection status because of the mostly asymptomatic nature of hepatitis C, so they remain undiagnosed until the liver damage has advanced. Molecular mechanisms induced by HCV have been intensely investigated to find biomarkers for diagnosing the acute and chronic phases of the infection. However, there are no clinically verified biomarkers for patients with hepatitis C. In this review, we discuss the biomarkers that can differentiate acute from chronic hepatitis C, and we summarize the current state of the literature on the useful biomarkers that are detectable during acute and chronic HCV infection, liver fibrosis/cirrhosis, and hepatocellular carcinoma (HCC).

Methods and indicators to validate country reductions in incidence of hepatitis C virus infection to elimination levels set by WHO

One of the main goals of the 2016 Global Health Sector Strategy on viral hepatitis is the elimination of hepatitis C virus (HCV) as a public health problem by 2030, defined as an 80% reduction in incidence and 65% reduction in mortality relative to 2015. Although monitoring HCV incidence is key to validating HCV elimination, use of the gold-standard method, which involves prospective HCV retesting of people at risk, can be prohibitively resource-intensive. Additionally, few countries collected quality data in 2015 to enable an 80% decrease by 2030 to be calculated. Here, we first review different methods of monitoring HCV incidence and discuss their resource implications and applicability to various populations. Second, using mathematical models developed for various global settings, we assess whether trends in HCV chronic prevalence or HCV antibody prevalence or scale-up levels for HCV testing, treatment, and preventative interventions can be used as reliable alternative indicators to validate the HCV incidence target. Third, we discuss the advantages and disadvantages of an absolute HCV incidence target and suggest a suitable threshold. Finally, we propose three options that countries can use to validate the HCV incidence target, depending on the available surveillance infrastructure.

Estimating HIV, HCV and HSV2 incidence from emergency department serosurvey

Background: Our understanding of pathogens and disease transmission has improved dramatically over the past 100 years, but coinfection, how different pathogens interact with each other, remains a challenge. Cross-sectional serological studies including multiple pathogens offer a crucial insight into this problem.  Methods: We use data from three cross-sectional serological surveys (in 2003, 2007 and 2013) in a Baltimore emergency department to predict the prevalence for HIV, hepatitis C virus (HCV) and herpes simplex virus, type 2 (HSV2), in a fourth survey (in 2016). We develop a mathematical model to make this prediction and to estimate the incidence of infection and coinfection in each age and ethnic group in each year. Results: Overall we find a much stronger age cohort effect than a time effect, so that, while incidence at a given age may decrease over time, individuals born at similar times experience a more constant force of infection over time. Conclusions: These results emphasise the importance of age-cohort counselling and early intervention while people are young. Our approach adds value to data such as these by providing age- and time-specific incidence estimates which could not be obtained any other way, and allows forecasting to enable future public health planning.

Comparison of approaches for IgG avidity calculation and a new highly sensitive and specific method with broad dynamic range

BACKGROUND

Antimicrobial IgG avidity is measured in the diagnosis of infectious disease, for dating of primary infection or immunization. It is generally determined by either of two approaches, termed here the avidity index (AI) or end-point ratio (EPR), which differ in complexity and workload. While several variants of these approaches have been introduced, little comparative information exists on their clinical utility.

METHODS

This study was performed to systematically compare the performances of these approaches and to design a new sensitive and specific calculation method, for easy implementation in the laboratory. The avidities obtained by AI, EPR, and the newly developed approach were compared, across parvovirus B19, cytomegalovirus, Toxoplasma gondii, rubella virus, and Epstein-Barr virus panels comprising 460 sera from individuals with a recent primary infection or long-term immunity.

RESULTS

With optimal IgG concentrations, all approaches performed equally, appropriately discriminating primary infections from past immunity (area under the receiver operating characteristic curve (AUC) 0.93-0.94). However, at lower IgG concentrations, the avidity status (low, borderline, high) changed in 17% of samples using AI (AUC 0.88), as opposed to 4% using EPR (AUC 0.91) and 6% using the new method (AUC 0.93).

CONCLUSIONS

The new method measures IgG avidity accurately, in a broad range of IgG levels, while the popular AI approach calls for a sufficiently high antibody concentration.

Regression with interval-censored covariates: Application to cross-sectional incidence estimation

A method for generalized linear regression with interval-censored covariates is described, extending previous approaches. A scenario is considered in which an interval-censored covariate of interest is defined as a function of other variables. Instead of directly modeling the distribution of the interval-censored covariate of interest, the distributions of the variables which determine that covariate are modeled, and the distribution of the covariate of interest is inferred indirectly. This approach leads to an estimation procedure using the Expectation-Maximization (EM) algorithm. The performance of this approach is compared to two alternative approaches, one in which the censoring interval midpoints are used as estimates of the censored covariate values, and another in which the censored values are multiply imputed using uniform distributions over the censoring intervals. A simulation framework is constructed to assess these methods' accuracies across a range of scenarios. The proposed approach is found to have less bias than midpoint analysis and uniform imputation, at the cost of small increases in standard error.

Antibody avidity-based approach to estimate population-level incidence of hepatitis C

BACKGROUND & AIMS

Accurate 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.

METHODS

An 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.

RESULTS

An 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.

CONCLUSIONS

This 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 SUMMARY

Determining 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.

Establishment of an anti-hepatitis C virus IgG avidity test for dried serum/plasma spots

Monitoring recency of infection helps to identify current transmission in vulnerable populations for effective disease control. We have established an in-house avidity based hepatitis C virus (HCV) recency assay based on the Monolisa Anti-HCV PLUS Version 3 ELISA kit for use of dried serum/plasma spots (DS/PS) in order to distinguish recent and long-term infections. A first panel of DS/PS (n = 218; genotype 1 n = 170 and non-genotype 1 n = 48) consisting of primary and at least one follow up sample was used to analyze the temporal changes of the Avidity Index (AI) over time. Sub-panels of longitudinal DS/PS (n = 66) and acute cases (<26 weeks; n = 34) were taken to calculate the Mean Duration of Recent Infection (MDRI) and the False Long-term Rate (FLTR), respectively. A second panel of DS/PS >104 weeks (n = 132) and a third panel of DS/PS prepared from resolved infections (≥180 days since last positive; n = 32) were used to calculate the False Recent Rate (FRR). For all genotypes, the optimal AI cut-off was determined to be 40% resulting in an MDRI of 364 days (95% CI: 223-485). FLTR was 5.9% (95% CI: 0.7-19.7), 8.3% (95% CI: 1-27), and 0% (-) and FRR was 13.6% (95% CI: 8.3-20.7), 11.7% (95% CI: 6.6-19), and 30.6% (95% CI: 9.1-61.4) for all genotypes, genotype 1, and non-genotype 1 infections, respectively. For resolved infections, the FRR was 53.1% (95% CI: 35.8-70.4). Thus, this assay performs particularly well for genotype 1 reaching a high rate of correct discriminations between infections acquired less than a year before diagnosis and those acquired earlier by applying an AI cut-off of 40%. Due to a rapid decline in avidity post resolution of an HCV infection this assay is not recommended to be used in HCV RNA negative patients.

A comparison of two biological markers of recent hepatitis C virus (HCV) infection: implications for the monitoring of interventions and strategies to reduce HCV transmission among people who inject drugs

BackgroundMonitoring hepatitis C virus (HCV) incidence is important for assessing intervention impact. Longitudinal studies of people who inject drugs (PWID), using repeated biological tests, are costly; alternatively, incidence can be estimated using biological markers of recent infection in cross-sectional studies.AimWe aimed to compare incidence estimates obtained from two different biological markers of recent infection in a cross-sectional study to inform monitoring approaches for HCV elimination strategies.MethodSamples from an unlinked anonymous bio-behavioural survey of PWID were tested for two recent infection markers: HCV RNA with anti-HCV negative ('RNA') and low-avidity anti-HCV with HCV RNA present ('avidity'). These two markers were used separately and in combination to estimate HCV incidence.ResultsBetween 2011 and 2013, 2,816 anti-HIV-negative PWID (25% female) who had injected during the preceding year were either HCV-negative or had one of the two markers of recent infection: 57 (2.0%) had the RNA marker and 90 (3.2%) the avidity marker. The two markers had similar distributions of risk and demographic factors. Pooled estimated incidence was 12.3 per 100 person-years (pyrs) (95% credible interval: 8.8-17.0) and not significantly different to avidity-only (p = 0.865) and RNA-only (p = 0.691) estimates. However, the RNA marker is limited by its short duration before anti-HCV seroconversion and the avidity marker by uncertainty around its duration.ConclusionBoth markers have utility in monitoring HCV incidence among PWID. When HCV transmission is high, one marker may provide an accurate estimate of incidence; when it is low or decreasing, a combination may be required.

Direct-acting antiviral treatment of acute hepatitis C virus infections

INTRODUCTION

Hepatitis C contributes to significant morbidity and mortality worldwide. AHCV is defined as documented infection within 6 months of exposure. Treating acute hepatitis C virus (AHCV) with direct-acting antiviral agents in persons who inject drugs, HIV-positive men who have sex with men, and patients who acquire HCV nosocomially can contribute to the elimination of disease globally, preclude the morbidity and mortality of chronic disease, and prevent further transmission. Areas covered: In this review, we describe the epidemiology of AHCV, its natural history, the considerations involved in the decision of whether to treat AHCV, and the most current DAA therapy guidelines. PubMed was queried using key words and bibliographies were evaluated for relevant articles. Expert commentary: Despite the obvious benefits of AHCV treatment, clinical management is limited by the ability to identify asymptomatic cases and the absence of fully supported guidelines. However, clinical research is advancing and identifying specific regimens, decreasing treatment durations, and creating strategies to target at risk groups and screen for AHCV.

Prevalence and mapping of hepatitis C infections among men who have sex with men in New York City

Emerging sexually transmitted hepatitis C virus (HCV) epidemics among men who have sex with men (MSM) have been reported worldwide, with higher HCV infection rates among those who are HIV-infected. This study aims to determine prevalence of recent and chronic HCV infections among community-recruited MSM in New York City (NYC), map HCV infections by home, social, and sexual neighborhoods, and identify clusters of genetically linked HCV variants using phylogenetic analysis. The NYC M2M study recruited MSM via modified time-space, venue-based sampling and internet/mobile app-based recruitment during 2010–13. Participants completed a Google Earth map on neighborhoods of where they lived, socialized, and had sex in the last 3 months, an ACASI questionnaire, and a sexual network inventory about their sex partners. The men received HIV testing and provided serum samples. Testing on stored serum samples included HCV antibody and RNA viral load, HCV antibody avidity assay (avidity index <30% with positive viral load is considered recently infected), and HCV RNA extraction and amplification to generate a 432 base-pair region of Core/E1 for sequencing and phylogenetic analysis. Historic local controls were included in the phylogenetic analysis. Of 1,028 MSM, 79.7% were HIV-negative and 20.3% HIV-positive. Twenty nine MSM (2.8%) were HCV antibody-positive. MSM who were HCV antibody-positive reported a median of 2 male sex partners in last 3 months, with 6.9% aged 18–24, 17.2% 25–29, 13.8% 30–39, and 62.1% 40 and over. 8.1% of HIV-positive MSM were HCV antibody-positive vs. 1.5% of HIV-negative men (p<0.0001). Of 29 HCV-antibody positive MSM, 12 (41%) were HCV RNA-positive (11 subtype 1a and 1 subtype 1b). Two of 12 HCV RNA-positive participants had low antibody avidity values, suggesting recent HCV infection. HCV antibody seropositivity was significantly associated with older age >40 years, adjusted odds ratio (aOR) 3.56 (95% CI 1.57, 8.08), HIV-positive serostatus, aOR 3.18 (95% CI 1.40, 7.22), any sexually transmitted infection (STI) in the last 3 months, aOR 2.81 (95% CI 1.11, 7.13), and injection drug use (IDU) ever, aOR 4.34 (95% CI 1.69, 11.17). Mapping of HCV infections differed slightly by home, social, and sexual neighborhoods. Based on phylogenetic analysis from 12 HCV RNA-positive samples, no evidence of a clustered HCV epidemic was found. Overall HCV seroprevalence was 2.8% among community-recruited MSM in NYC, with higher prevalence among HIV-positive MSM compared to HIV-negative MSM. Only two participants were found to have recent HCV infection, with no evidence of a clustered HCV epidemic based on phylogenetic analysis. Our results support testing of HCV infection among HIV-negative MSM if they report having a recent STI and IDU in the past rather than universal HCV testing in all HIV-negative MSM.

HCV avidity as a tool for detection of recent HCV infection: Sensitivity depends on HCV genotype

Accurate detection of incident hepatitis C virus (HCV) infection is required to target and evaluate public health interventions, but acute infection is largely asymptomatic and difficult to detect using traditional methods. Our aim was to evaluate a previously developed HCV avidity assay to distinguish acute from chronic HCV infection. Plasma samples collected from recent seroconversion subjects in two large Australian cohorts were tested using the avidity assay, and the avidity index (AI) was calculated. Demographic and clinical characteristics of patients with low/high AI were compared via logistic regression. Sensitivity and specificity of the assay for recent infection and the mean duration of recent infection (MDRI) were estimated stratified by HCV genotype. Avidity was assessed in 567 samples (from 215 participants), including 304 with viraemia (defined as ≥250 IU/mL). An inverse relationship between AI and infection duration was found in viraemic samples only. The adjusted odds of a low AI (<30%) decreased with infection duration (odds ratio [OR] per week of 0.93; 95% CI:0.89-0.97), and were lower for G1 compared with G3 samples (OR = 0.14; 95% CI:0.05-0.39). Defining recent infection as <26 weeks, sensitivity (at AI cut-off of 20%) was estimated at 48% (95% CI:39-56%), 36% (95% CI:20-52%), and 65% (95% CI:54-75%) and MDRI was 116, 83, and 152 days for all genotypes, G1, and G3, respectively. Specificity (≥52 weeks infection duration, all genotypes) was 96% (95% CI:90-98%). HCV avidity testing has utility for detecting recent HCV infection in patients, and for assessing progress in reaching incidence targets for eliminating transmission, but variation in assay performance across genotype should be recognized.

Age- and time-dependent prevalence and incidence of hepatitis C virus infection in drug users in France, 2004-2011: model-based estimation from two national cross-sectional serosurveys

Hepatitis C virus (HCV) infection is a public health issue worldwide. Injecting drug use remains the major mode of transmission in developed countries. Monitoring the HCV transmission dynamic over time is crucial, especially to assess the effect of harm reduction measures in drug users (DU). Our objective was to estimate the prevalence and incidence of HCV infection in DU in France using data from a repeated cross-sectional survey conducted in 2004 and 2011. Age- and time-dependent HCV prevalence was estimated through logistic regression models adjusted for HIV serostatus or injecting practices. HCV incidence was estimated from a mathematical model linking prevalence and incidence. HCV prevalence decreased from 58·2% [95% confidence interval (CI) 49·7-66·8] in 2004 to 43·2% (95% CI 38·8-47·7) in 2011. HCV incidence decreased from 7·9/100 person-years (95% CI 6·4-9·4) in 2004 to 4·4/100 person-years (95% CI 3·3-5·9) in 2011. HCV prevalence and incidence were significantly associated with age, calendar time, HIV serostatus and injecting practices. In 2011, the highest estimated incidence was in active injecting DU (11·2/100 person-years). Given the forthcoming objective of generalizing access to new direct antiviral agents for HCV infection, our results contribute to decision-making and policy development regarding treatment scale-up and disease prevention in the DU population.