Dataset Information

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.

ABSTRACT: BACKGROUND:Cross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by reducing the likelihood of a false-recent result. METHODS:The data comes from 854 time-points and 42 participants enrolled in a primary HIV-1C infection study in Botswana. Time points after treatment initiation or with evidence of multiplicity of infection were excluded from the final analysis. PwD was calculated from quasispecies generated using single genome amplification and sequencing. We evaluated the ability of PwD to correctly classify HIV infection recency within <130, <180 and <360 days post-seroconversion using Receiver Operator Characteristics (ROC) methods. Following a secondary PwD screening, we quantified the reduction in the relative false-recency rate (rFRR) of the BED and LAg assays while maintaining a sensitivity of either 75, 80, 85 or 90%. RESULTS:The final analytic sample consisted of 758 time-points from 40 participants. The PwD assay was more accurate in classifying infection recency for the 130 and 180-day cut-offs when compared with the recommended LAg and BED thresholds. A higher AUC statistic confirmed the superior predictive performance of the PwD assay for the three cut-offs. When used for combination screening, the PwD assay reduced the rFRR of the LAg assay by 52% and the BED assay by 57.8% while maintaining a 90% sensitivity for the 130 and 180-day cut-offs respectively. CONCLUSION:PwD can accurately determine HIV infection recency. A secondary PwD screening reduces misclassification and increases the accuracy of serologic-based assays.

SUBMITTER: Moyo S

PROVIDER: S-EPMC4994946 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.

Moyo Sikhulile S Vandormael Alain A Wilkinson Eduan E Engelbrecht Susan S Gaseitsiwe Simani S Kotokwe Kenanao P KP Musonda Rosemary R Tanser Frank F Essex Max M Novitsky Vladimir V de Oliveira Tulio T

PloS one 20160823 8

<h4>Background</h4>Cross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by ...[more]

PMID: 27552218

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Project description:BackgroundDetermining patterns of HIV transmission is increasingly important for the most efficient use of modern prevention interventions. HIV phylogeny can provide a better understanding of the mechanisms underlying HIV transmission networks in communities.MethodsTo reconstruct the structure and dynamics of a local HIV/AIDS epidemic, the phylogenetic relatedness of HIV-1 subtype C env sequences obtained from 785 HIV-infected community residents in the northeastern sector of Mochudi, Botswana, during 2010-2013 was estimated. The genotyping coverage was estimated at 44%. Clusters were defined based on relatedness of HIV-1C env sequences and bootstrap support of splits.ResultsThe overall proportion of clustered HIV-1C env sequences was 19.1% (95% CI 17.5% to 20.8%). The proportion of clustered sequences from Mochudi was significantly higher than the proportion of non-Mochudi sequences that clustered, 27.0% vs. 14.7% (p?=?5.8E-12; Fisher exact test). The majority of clustered Mochudi sequences (90.1%; 95% CI 85.1% to 93.6%) were found in the Mochudi-unique clusters. None of the sequences from Mochudi clustered with any of the 1,244 non-Botswana HIV-1C sequences. At least 83 distinct HIV-1C variants, or chains of HIV transmission, in Mochudi were enumerated, and their sequence signatures were reconstructed. Seven of 20 genotyped seroconverters were found in 7 distinct clusters.ConclusionsThe study provides essential characteristics of the HIV transmission network in a community in Botswana, suggests the importance of high sampling coverage, and highlights the need for broad HIV genotyping to determine the spread of community-unique and community-mixed viral variants circulating in local epidemics. The proposed methodology of cluster analysis enumerates circulating HIV variants and can work well for surveillance of HIV transmission networks. HIV genotyping at the community level can help to optimize and balance HIV prevention strategies in trials and combined intervention packages.

Project description:BackgroundA single viral variant is transmitted in the majority of HIV infections. However, about 20% of heterosexually transmitted HIV infections are caused by multiple viral variants. Detection of transmitted HIV variants is not trivial, as it involves analysis of multiple viral sequences representing intra-host HIV-1 quasispecies.MethodologyWe distinguish two types of multiple virus transmission in HIV infection: (1) HIV transmission from the same source, and (2) transmission from different sources. Viral sequences representing intra-host quasispecies in a longitudinally sampled cohort of 42 individuals with primary HIV-1C infection in Botswana were generated by single-genome amplification and sequencing and spanned the V1C5 region of HIV-1C env gp120. The Maximum Likelihood phylogeny and distribution of pairwise raw distances were assessed at each sampling time point (n = 217; 42 patients; median 5 (IQR: 4-6) time points per patient, range 2-12 time points per patient).ResultsTransmission of multiple viral variants from the same source (likely from the partner with established HIV infection) was found in 9 out of 42 individuals (21%; 95 CI 10-37%). HIV super-infection was identified in 2 patients (5%; 95% CI 1-17%) with an estimated rate of 3.9 per 100 person-years. Transmission of multiple viruses combined with HIV super-infection at a later time point was observed in one individual.ConclusionsMultiple HIV lineages transmitted from the same source produce a monophyletic clade in the inferred phylogenetic tree. Such a clade has transiently distinct sub-clusters in the early stage of HIV infection, and follows a predictable evolutionary pathway. Over time, the gap between initially distinct viral lineages fills in and initially distinct sub-clusters converge. Identification of cases with transmission of multiple viral lineages from the same source needs to be taken into account in cross-sectional estimation of HIV recency in epidemiological and population studies.

Project description:Identifying recent HIV infection cases has important public health and clinical implications. It is essential for estimating incidence rates to monitor epidemic trends and evaluate the effectiveness of interventions. Detecting recent cases is also important for HIV prevention given the crucial role that recently infected individuals play in disease transmission, and because early treatment onset can improve the clinical outlook of patients while reducing transmission risk. Critical to this enterprise is the development and proper assessment of accurate classification assays that, based on cross-sectional samples of viral sequences, help determine infection recency status. In this work we assess some of the biases present in the evaluation of HIV recency classification algorithms that rely on measures of within-host viral diversity. Particularly, we examine how the time since infection (TSI) distribution of the infected subjects from which viral samples are drawn affect performance metrics (e.g., area under the ROC curve, sensitivity, specificity, accuracy and precision), potentially leading to misguided conclusions about the efficacy of classification assays. By comparing the performance of a given HIV recency assay using six different TSI distributions (four simulated TSI distributions representing different epidemic scenarios, and two empirical TSI distributions), we show that conclusions about the overall efficacy of the assay depend critically on properties of the TSI distribution. Moreover, we demonstrate that an assay with high overall classification accuracy, mainly due to properly sorting members of the well-represented groups in the validation dataset, can still perform notoriously poorly when sorting members of the less represented groups. This is an inherent issue of classification and diagnostics procedures that is often underappreciated. Thus, this work underscores the importance of acknowledging and properly addressing evaluation biases when proposing new HIV recency assays.

Project description:We used Affymetrix U133A 2.0 chips to better understand transcriptional changes associated with HIV-1 infection and perinatal transmission in human PBMCS obtained from young adult mothers with infants in Botswana in vivo. HIV seropositive and drug naÃ¯ve samples:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370, GSM94378; HIV seronegative samples:; GSM92590, GSM92788, GSM92789, GSM92790, GSM92791, GSM92792, GSM92793, GSM92794, GSM92795, GSM92796, GSM92797, GSM92798, GSM92799, GSM92800, GSM92801, GSM92802, GSM92803, GSM92804, GSM92805, GSM92806; HIV seropositive transmitter mothers:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94378; HIV seropositive nontransmitter mothers:; GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370 Experiment Overall Design: Total RNA was extracted from peripheral blood and processed for microarray hybridizations that were conducted using U133A 2.0 chips (Affymetrix, Santa Clara, CA). The 22,777 gene-probes were filtered based on presence/absence, resulting in data for 11,705 gene-probes. The array data sets were then analyzed for differential expression based on HIV status (seronegative, seropositive) and transmitter status (transmitter: TR, nontransmitter: NTR) using BADGE version 1.0, a computer program implementing a Bayesian approach to identify differentially expressed genes (Sebastiani et al, Nat.Gen, 2005). Once differentially expressed genes were identified by BADGE, the biologically enriched categories were identified, as recently described (Montano et al, Int Immunol, 2006), by implementing a stand-alone version of the EASE statistical software (Hosack et al, Genome Biol., 2003). Selected genes were validated using realtime reverse transcription PCR.

Dataset Information

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.

Publications

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.

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