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Effect of primer selection on estimates of GB virus C (GBV-C) prevalence and response to antiretroviral therapy for optimal testing for GBV-C viremia.

ABSTRACT: GB virus C (GBV-C; also called hepatitis G virus) is a common cause of infection associated with prolonged survival among HIV-infected individuals. The prevalences of GBV-C viremia vary widely in different studies, and there has been poor agreement among different laboratories performing GBV-C RNA detection in quality control studies. To determine the optimal method of measuring GBV-C RNA in clinical samples, samples obtained from 939 HIV-infected subjects were studied using reverse transcription (RT)-PCR methods amplifying four separate regions of the GBV-C genome. Primers amplifying the E2 coding region were 100% specific; however, their sensitivity was only 76.6%. In contrast, primers amplifying three additional conserved regions of the GBV-C genome (the 5' nontranslated region and the nonstructural protein-coding regions 3 and 5A) were more sensitive but produced higher rates of false-positive results. Using low-specificity primer sets influenced the significance of association between GBV-C viremia and response to antiretroviral therapy. Using a quantitative GBV-C RNA method, the GBV-C RNA concentration did not correlate with baseline or set point HIV RNA levels; however, a correlation between negative, low, and high GBV-C RNA levels and increasing reduction in HIV RNA following antiretroviral therapy was observed. Subjects with both GBV-C E2 antibody and viremia had significantly lower GBV-C RNA levels than did viremic subjects without E2 antibody. These studies demonstrate that accurate detection of GBV-C RNA by nested RT-PCR requires the use of primers representing multiple genome regions. Analyses based on testing with single primers do not lead to reliable conclusions about the association between GBV-C infection and clinical outcomes.

SUBMITTER: Souza IE

PROVIDER: S-EPMC1594694 | biostudies-literature | 2006 Sep

REPOSITORIES: biostudies-literature

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Effect of primer selection on estimates of GB virus C (GBV-C) prevalence and response to antiretroviral therapy for optimal testing for GBV-C viremia.

Souza I E IE Allen J B JB Xiang J J Klinzman D D Diaz R R Zhang S S Chaloner K K Zdunek D D Hess G G Williams C F CF Benning L L Stapleton J T JT

Journal of clinical microbiology 20060901 9

GB virus C (GBV-C; also called hepatitis G virus) is a common cause of infection associated with prolonged survival among HIV-infected individuals. The prevalences of GBV-C viremia vary widely in different studies, and there has been poor agreement among different laboratories performing GBV-C RNA detection in quality control studies. To determine the optimal method of measuring GBV-C RNA in clinical samples, samples obtained from 939 HIV-infected subjects were studied using reverse transcriptio ...[more]

PMID: 16954234

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Project description:BackgroundSelection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results.MethodsThe identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated.ResultsUsing nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% - 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive.ConclusionsOur approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

Project description:During antiretroviral therapy (ART) that suppresses HIV replication to below the limit-of-quantification, virions produced during ART can be detected at low frequencies in the plasma, termed residual viremia (RV). We hypothesized that a reservoir of HIV-infected cells actively produce and release virions during ART that are potentially infectious, and that following ART-interruption, these virions can complete full-cycles of replication and contribute to rebound viremia. Therefore, we studied the dynamics of RV sequence variants in 3 participants who initiated ART after ~3 years of infection and were ART-suppressed for >6 years prior to self-initiated ART-interruptions. Longitudinal RV C2V5env sequences were compared to sequences from pre-ART plasma, supernatants of quantitative viral outgrowth assays (QVOA) of cells collected during ART, post-ART-interruption plasma, and ART-re-suppression plasma. Identical, "putatively clonal," RV sequences comprised 8-84% of sequences from each timepoint. The majority of RV sequences were genetically similar to those from plasma collected just prior to ART-initiation, but as the duration of ART-suppression increased, an increasing proportion of RV variants were similar to sequences from earlier in infection. Identical sequences were detected in RV over a median of 3 years (range: 0.3-8.2) of ART-suppression. RV sequences were identical to pre-ART plasma viruses (5%), infectious viruses induced in QVOA (4%) and rebound viruses (5%) (total n = 21/154 (14%) across the 3 participants). RV sequences identical to ART-interruption "rebound" sequences were detected 0.1-7.4 years prior to ART-interruption. RV variant prevalence and persistence were not associated with detection of the variant among rebound sequences. Shortly after ART-re-suppression, variants that had been replicating during ART-interruptions were detected as RV (n = 5). These studies show a dynamic, virion-producing HIV reservoir that contributes to rekindling infection upon ART-interruption. The persistence of identical RV variants over years suggests that a subpopulation of HIV-infected clones frequently or continuously produce virions that may resist immune clearance; this suggests that cure strategies should target this active as well as latent reservoirs.

Dataset Information

Effect of primer selection on estimates of GB virus C (GBV-C) prevalence and response to antiretroviral therapy for optimal testing for GBV-C viremia.

Publications

Effect of primer selection on estimates of GB virus C (GBV-C) prevalence and response to antiretroviral therapy for optimal testing for GBV-C viremia.

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