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Assessment of BED HIV-1 incidence assay in seroconverter cohorts: effect of individuals with long-term infection and importance of stable incidence.

ABSTRACT: BACKGROUND: Performance of the BED assay in estimating HIV-1 incidence has previously been evaluated by using longitudinal specimens from persons with incident HIV infections, but questions remain about its accuracy. We sought to assess its performance in three longitudinal cohorts from Thailand where HIV-1 CRF01_AE and subtype B' dominate the epidemic. DESIGN: BED testing was conducted in two longitudinal cohorts with only incident infections (a military conscript cohort and an injection drug user cohort) and in one longitudinal cohort (an HIV-1 vaccine efficacy trial cohort) that also included long-term infections. METHODS: Incidence estimates were generated conventionally (based on the number of annual serocoversions) and by using BED test results in the three cohorts. Adjusted incidence was calculated where appropriate. RESULTS: For each longitudinal cohort the BED incidence estimates and the conventional incidence estimates were similar when only newly infected persons were tested, whether infected with CRF01_AE or subtype B'. When the analysis included persons with long-term infections (to mimic a true cross-sectional cohort), BED incidence estimates were higher, although not significantly, than the conventional incidence estimates. After adjustment, the BED incidence estimates were closer to the conventional incidence estimates. When the conventional incidence varied over time, as in the early phase of the injection drug user cohort, the difference between the two estimates increased, but not significantly. CONCLUSIONS: Evaluation of the performance of incidence assays requires the inclusion of a substantial number of cohort-derived specimens from individuals with long-term HIV infection and, ideally, the use of cohorts in which incidence remained stable. Appropriate adjustments of the BED incidence estimates generate estimates similar to those generated conventionally.

SUBMITTER: McNicholl JM

PROVIDER: S-EPMC3048863 | biostudies-other | 2011

REPOSITORIES: biostudies-other

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Project description:Human immunodeficiency virus (HIV) incidence is an important measure for monitoring the epidemic and evaluating the efficacy of intervention and prevention trials. This study developed a high-throughput, single-measure incidence assay by implementing a pyrosequencing platform. We devised a signal-masking bioinformatics pipeline, which yielded a process error rate of 5.8 × 10(-4) per base. The pipeline was then applied to analyze 18,434 envelope gene segments (HXB2 7212 to 7601) obtained from 12 incident and 24 chronic patients who had documented HIV-negative and/or -positive tests. The pyrosequencing data were cross-checked by using the single-genome-amplification (SGA) method to independently obtain 302 sequences from 13 patients. Using two genomic biomarkers that probe for the presence of similar sequences, the pyrosequencing platform correctly classified all 12 incident subjects (100% sensitivity) and 23 of 24 chronic subjects (96% specificity). One misclassified subject's chronic infection was correctly classified by conducting the same analysis with SGA data. The biomarkers were statistically associated across the two platforms, suggesting the assay's reproducibility and robustness. Sampling simulations showed that the biomarkers were tolerant of sequencing errors and template resampling, two factors most likely to affect the accuracy of pyrosequencing results. We observed comparable biomarker scores between AIDS and non-AIDS chronic patients (multivariate analysis of variance [MANOVA], P = 0.12), indicating that the stage of HIV disease itself does not affect the classification scheme. The high-throughput genomic HIV incidence marks a significant step toward determining incidence from a single measure in cross-sectional surveys.Annual HIV incidence, the number of newly infected individuals within a year, is the key measure of monitoring the epidemic's rise and decline. Developing reliable assays differentiating recent from chronic infections has been a long-standing quest in the HIV community. Over the past 15 years, these assays have traditionally measured various HIV-specific antibodies, but recent technological advancements have expanded the diversity of proposed accurate, user-friendly, and financially viable tools. Here we designed a high-throughput genomic HIV incidence assay based on the signature imprinted in the HIV gene sequence population. By combining next-generation sequencing techniques with bioinformatics analysis, we demonstrated that genomic fingerprints are capable of distinguishing recently infected patients from chronically infected patients with high precision. Our high-throughput platform is expected to allow us to process many patients' samples from a single experiment, permitting the assay to be cost-effective for routine surveillance.

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Assessment of BED HIV-1 incidence assay in seroconverter cohorts: effect of individuals with long-term infection and importance of stable incidence.

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