Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections

Chalmet, Kristen; Staelens, Delfien; Blot, Stijn; Dinakis, Sylvie; Pelgrom, Jolanda; Plum, Jean; Vogelaers, Dirk; Vandekerckhove, Linos; Verhofstede, Chris

doi:10.1186/1471-2334-10-262

Cited by 89 publications

(86 citation statements)

References 34 publications

(38 reference statements)

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“…The identification of transmission clusters was based on the maximum likelihood tree, selecting the clusters from at least three individuals, with a bootstrap support of Ն95% and an average genetic distance of Յ0.03 substitutions per site (29,41). We also used Bayesian inference, and all identified clusters showed a posterior probability equal to 1 (42).…”

Section: Methodsmentioning

confidence: 99%

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

et al. 2015

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The existing data support Portugal as the western European country with the highest HIV-1 subtype diversity. However, detailed phylogenetic studies of Portuguese HIV-1 epidemics are still scarce. Thus, our main goal was to analyze the phylodynamics of a local HIV-1 infection in the Portuguese region of Minho. Molecular epidemiological analysis was applied to data from 289 HIV-1-infected individuals followed at the reference hospital of the province of Minho, Portugal, at which isolated viruses had been sequenced between 2000 and 2012. Viruses of the G (29.1%) and B (27.0%) subtypes were the most frequent, followed by recombinant forms (17.6%) and the C (14.5%), F1 (7.3%), and A1 (4.2%) subtypes. Multinomial logistic regression revealed that the odds of being infected with the A1 and F1 subtypes increased over the years compared with those with B, G, or C subtypes or recombinant viruses. As expected, polyphyletic patterns suggesting multiple and old introductions of the B and G subtypes were found. However, transmission clusters of non-B and non-G viruses among native individuals were also found, with the dates of the most recent common ancestor estimated to be in the early 2000s. Our study supports that the HIV-1 subtype diversity in the Portuguese region of Minho is high and has been increasing in a manner that is apparently driven by factors other than immigration and international travel. Infections with A1 and F1 viruses in the region of Minho are becoming established and are mainly found in sexually transmitted clusters, reinforcing the need for more efficacious control measures targeting this infection route.

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Section: Methodsmentioning

confidence: 99%

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

et al. 2015

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“…Sequence interrelationships were first deduced by the NJ method as described below. In order to use stringent criteria, only clusters with a bootstrap value higher than 90 and an average genetic distance of Ͻ0.015 were selected (30). Clusters including sequences amplified in the same run were excluded from the study to avoid any possibility of contamination.…”

Section: Methodsmentioning

confidence: 99%

Characteristics of Patients Recently Infected with HIV-1 Non-B Subtypes in France: a Nested Study within the Mandatory Notification System for New HIV Diagnoses

et al. 2014

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The presence of HIV-1 non-B subtypes in Western Europe is commonly attributed to migration of individuals from non-European countries, but the possible role of domestic infections with non-B subtypes is not well investigated. The French mandatory anonymous reporting system for HIV is linked to a virological surveillance using assays for recent infection (<6 months) and serotyping. During the first semester of years 2007 to 2010, any sample corresponding to a non-B recent infection was analyzed by sequencing a 415-bp env region, followed by phylogenetic analysis and search for transmission clusters. Two hundred thirtythree recent HIV-1 infections with non-B variants were identified. They involved 5 subtypes and 7 circulating recombinant forms (CRFs). Ninety-two cases (39.5%) were due to heterosexual transmissions, of which 39 occurred in patients born in France. Eighty-five cases (36.5%) were identified in men having sex with men (MSM). Forty-three recent non-B infections (18.5%) segregated into 14 clusters, MSM being involved in 11 of them. Clustered transmission events included 2 to 7 cases per cluster. The largest cluster involved MSM infected by a CRF02_AG variant. In conclusion, we found that the spread of non-B subtypes in France occurs in individuals of French origin and that MSM are particularly involved in this dynamic.

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“…On the other hand, pol and env have been shown to produce identical phylogenetic clustering patterns with similar statistical support, 1,25 suggesting that branch support thresholds are consistent across genes. Our data were collected from stable epidemic in Uganda in which genetic diversity has accumulated over time, whereas other clustering studies have examined more recent and localized HIV outbreaks 6,26,27 or epidemics 10 in which less diversity is present. Yet, this study clearly demonstrates the value of investigating datasetappropriate thresholds and using multiple approaches to determine linkage.…”

Section: Identifying Transmission Clustersmentioning

confidence: 99%

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Rose¹,

Lamers²,

Dollar³

et al. 2017

AIDS Research and Human Retroviruses

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We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

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Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections

Cited by 89 publications

References 34 publications

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

Characteristics of Patients Recently Infected with HIV-1 Non-B Subtypes in France: a Nested Study within the Mandatory Notification System for New HIV Diagnoses

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

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