30 research outputs found

    Performance of a Limiting-Antigen Avidity Enzyme Immunoassay for Cross-Sectional Estimation of HIV Incidence in the United States

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    Background: A limiting antigen avidity enzyme immunoassay (HIV-1 LAg-Avidity assay) was recently developed for cross-sectional HIV incidence estimation. We evaluated the performance of the LAg-Avidity assay alone and in multi-assay algorithms (MAAs) that included other biomarkers. Methods and Findings: Performance of testing algorithms was evaluated using 2,282 samples from individuals in the United States collected 1 month to >8 years after HIV seroconversion. The capacity of selected testing algorithms to accurately estimate incidence was evaluated in three longitudinal cohorts. When used in a single-assay format, the LAg-Avidity assay classified some individuals infected >5 years as assay positive and failed to provide reliable incidence estimates in cohorts that included individuals with long-term infections. We evaluated >500,000 testing algorithms, that included the LAg-Avidity assay alone and MAAs with other biomarkers (BED capture immunoassay [BED-CEIA], BioRad-Avidity assay, HIV viral load, CD4 cell count), varying the assays and assay cutoffs. We identified an optimized 2-assay MAA that included the LAg-Avidity and BioRad-Avidity assays, and an optimized 4-assay MAA that included those assays, as well as HIV viral load and CD4 cell count. The two optimized MAAs classified all 845 samples from individuals infected >5 years as MAA negative and estimated incidence within a year of sample collection. These two MAAs produced incidence estimates that were consistent with those from longitudinal follow-up of cohorts. A comparison of the laboratory assay costs of the MAAs was also performed, and we found that the costs associated with the optimal two assay MAA were substantially less than with the four assay MAA. Conclusions: The LAg-Avidity assay did not perform well in a single-assay format, regardless of the assay cutoff. MAAs that include the LAg-Avidity and BioRad-Avidity assays, with or without viral load and CD4 cell count, provide accurate incidence estimates

    A Comparison of Two Measures of HIV Diversity in Multi-Assay Algorithms for HIV Incidence Estimation

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    Background: Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence. Methods: Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies. Results: The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion. Conclusions: MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation

    Characterization of the Neutralizing Antibody Response in a Case of Genetically Linked HIV Superinfection.

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    This report describes the identification of a genetically confirmed linked heterosexual human immunodeficiency virus (HIV) superinfection (HIV-SI) in a woman with chronic HIV infection who acquired a second strain of the virus from her husband. Serum neutralizing antibody (NAb) responses against their homologous and heterologous viruses, including the superinfecting strain, in the woman and her husband were examined before and after onset of HIV-SI. The woman displayed a moderately potent and broad anti-HIV NAb response prior to superinfection but did not possess NAb activity against the superinfecting strain. This case highlights the unique potential of linked HIV-SI studies to examine natural protection from HIV infection

    Inter-laboratory assessment of a prototype multiplex kit for determination of recent HIV-1 infection.

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    BACKGROUND:Accurate and reliable laboratory-based assays are needed for estimating HIV-1 incidence from cross-sectional samples. We recently described the development of a customized, HIV-1-specific Bio-Plex assay that allows for the measurement of HIV-specific antibody levels and avidity to multiple analytes for improved HIV-1 incidence estimates. METHODS:To assess intra- and inter-laboratory assay performance, prototype multiplex kits were developed and evaluated by three distinct laboratories. Longitudinal seroconversion specimens were tested in parallel by each laboratory and kit performance was compared to that of an in-house assay. Additionally, the ability of the kit to distinguish recent from long-term HIV-1 infection, as compared to the in-house assay, was determined by comparing the reactivity of known recent (infected 12 months) drug naïve specimens. RESULTS:Although the range of reactivity for each analyte varied between the prototype kit and in-house assay, a measurable distinction in reactivity between recent and long-term specimens was observed with both assays in all three laboratories. Additionally, kit performance was consistent between all three laboratories. The intra-assay coefficient of variation (CV), between sample replicates for all laboratories, ranged from 0.5% to 6.1%. The inter-laboratory CVs ranged from 8.5% to 21.3% for gp160-avidity index (a) and gp120-normalized mean fluorescent intensity (MFI) value (n), respectively. CONCLUSION:We demonstrate the feasibility of producing a multiplex kit for measuring HIV antibody levels and avidity, with the potential for improved incidence estimates based on multi-analyte algorithms. The availability of a commercial kit will facilitate the transfer of technology among diverse laboratories for widespread assay use

    Performance of in-house assay versus prototype kit.

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    <p>The normalized MFI values (n) and avidity index (a) for the in-house assay and kit were compared for drug naïve, known recent (infected <6 months) and long-term (infected >1 year) specimens. The boxes represent the 25<sup>th</sup> to 75<sup>th</sup> percentile of reactivity, while the middle lines represent the median values. Black dots indicate the 5<sup>th</sup> to 95<sup>th</sup> percentile of reactivity. </p

    Inter-laboratory kit performance.

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    <p>The normalized MFI values (n) and avidity index (a) of known recent and long-term specimens, as measured by the prototype kits, were compared for each laboratory. </p

    Evolution of HIV-1 within untreated individuals and at the population scale in Uganda.

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    HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important
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