Phylogenetic inferences on HIV-1 transmission: implications for the design of prevention and treatment interventions

HIV-1 transmission between MSM and heterosexuals, and increasing proportions of circulating recombinant forms in the Nordic Countries

Increased knowledge about HIV-1 transmission dynamics in different transmission groups and geographical regions is fundamental for assessing and designing prevention efforts against HIV-1 spread. Since the first reported cases of HIV infection during the early 1980s, the HIV-1 epidemic in the Nordic countries has been dominated by HIV-1 subtype B and MSM transmission. HIV-1 pol sequences and clinical data of 51 per cent of all newly diagnosed HIV-1 infections in Sweden, Denmark, and Finland in the period 2000-2012 (N = 3,802) were analysed together with a large reference sequence dataset (N = 4,537) by trend analysis and phylogenetics. Analysis of the eight dominating subtypes and CRFs in the Nordic countries (A, B, C, D, G, CRF01_AE, CRF02_AG, and CRF06_cpx) showed that the subtype B proportion decreased while the CRF proportion increased over the study period. A majority (57 per cent) of the Nordic sequences formed transmission clusters, with evidence of mixing both geographically and between transmission groups. Detailed analyses showed multiple occasions of transmissions from MSM to heterosexuals and that active transmission clusters more often involved single than multiple Nordic countries. The strongest geographical link was between Denmark and Sweden. Finally, Denmark had a larger proportion of heterosexual domestic spread of HIV-1 subtype B (75 per cent) compared with Sweden (49 per cent) and Finland (57 per cent). We describe different HIV-1 transmission patterns between countries and transmission groups in a large geographical region. Our results may have implications for public health interventions in targeting HIV-1 transmission networks and identifying where to introduce such interventions.

Estimating HIV-1 Transmission Routes for Patients With Unknown Risk Histories by Viral Sequence Phylogenetic Analyses

OBJECTIVE

To estimate routes of transmission among HIV-infected persons with unknown-risk histories in China.

DESIGN/METHOD

All newly reported cases of HIV infection between year 1985 and 2009 were obtained from the National Databank of Chinese Center for Disease Control and Prevention (China CDC). A large number of unknown-risk HIV-positive samples were found. To estimate the transmission routes, HIV gag sequences were amplified by reverse transcription polymerase chain reaction and phylogenetically analyzed. The cases with unknown-risk history were compared with those with known-risk histories from the same local region and time period. A statistical model was developed to predict the transmission routes and was validated on known-risk samples, before testing 324 unknown-risk samples collected from 1996 to 2006.

RESULTS

Newly reported cases of HIV infection in China increased steadily between 1985 and 2009, from just a handful of cases to 30,340 in 2009. Injecting drug use (IDU) was the dominant route of transmission among reported cases in the early years and decreased from 83.4% in 1985-2001 to 28.2% in 2009. Conversely, sexual transmission increased from 6.9% in 1985-2001 to 60.9% in 2009. Among the 324 unknown-risk HIV sequences collected from 1996 to 2006, our model identified 100 samples most likely transmitted by blood, 114 by IDU, and 110 by sexual transmission. Our validation samples showed that our model has 90.8%, 94.8%, and 69.6% sensitivity and 87.3%, 87.5%, and 85.5% specificity, for blood, IDU, and sexual transmission, respectively.

CONCLUSIONS

We developed a model to estimate transmission route of unknown-risk HIV-positive samples and found that these unknown-risk patients could be transmitted by blood, IDU, or sex.

Phylodynamic analysis of HIV sub-epidemics in Mochudi, Botswana

Southern Africa continues to be the epicenter of the HIV/AIDS epidemic. This HIV-1 subtype C epidemic has a predominantly heterosexual mode of virus transmission and high (>15%) HIV prevalence among adults. The epidemiological dynamics of the HIV-1C epidemic in southern Africa are still poorly understood. Here, we aim at a better understanding of HIV transmission dynamics by analyzing HIV-1 subtype C sequences from Mochudi, a peri-urban village in Botswana. HIV-1C env gene sequences (gp120 V1C5) were obtained through enhanced household-based HIV testing and counseling in Mochudi. More than 1200 sequences were generated and phylogenetically distinct sub-epidemics within Mochudi identified. The Bayesian birth-death skyline plot was used to estimate the effective reproductive number, R, and the timing of virus transmission, to classify sub-epidemics as "acute" (those with recent viral transmissions) or "historic" (those without recent viral transmissions). We identified two of the 15 sub-epidemics as "acute." The median estimates of R among the clusters ranged from 0.72 to 1.77. The majority of HIV lineages, 11 out of 15 clusters with 5+ members, appear to have been introduced to Mochudi between 1996 and 2002. The median peak duration of viral transmissions was 7.1 years (range 2.9-9.7 years). The median life span of identified HIV sub-epidemics, i.e., the time between the inferred epidemic origin and its most recent sample, was 13.1 years (range 10.2-22.1 years). Most viral transmissions within the sub-epidemics occurred between 1997 and 2007. The time period during which infected people are infectious appears to have decreased since the introduction of the national ART program in Botswana. Real-time HIV genotyping and breaking down local HIV epidemics into phylogenetically distinct sub-epidemics may help to reveal the structure and dynamics of HIV transmission networks in communities, and aid in the design of targeted interventions for members of the acute sub-epidemics that likely fuel local HIV/AIDS epidemics.

Potential impact on HIV incidence of higher HIV testing rates and earlier antiretroviral therapy initiation in MSM

BACKGROUND

Increased rates of testing, with early antiretroviral therapy (ART) initiation, represent a key potential HIV-prevention approach. Currently, in MSM in the United Kingdom, it is estimated that 36% are diagnosed by 1 year from infection, and the ART initiation threshold is at CD4 cell count 350/μl. We investigated what would be required to reduce HIV incidence in MSM to below 1 per 1000 person-years (i.e. <535 new infections per year) by 2030, and whether this is likely to be cost-effective.

METHODS

A dynamic, individual-based simulation model was calibrated to multiple data sources on HIV in MSM in the United Kingdom. Outcomes were projected according to future alternative HIV testing and ART initiation scenarios to 2030, considering also potential changes in levels of condomless sex.

RESULTS

For ART use to result in an incidence of close to 1/1000 person-years requires the proportion of all HIV-positive MSM with viral suppression to increase from below 60% currently to 90%, assuming no rise in levels of condomless sex. Substantial increases in HIV testing, such that over 90% of men are diagnosed within a year of infection, would increase the proportion of HIV-positive men with viral suppression to 80%, and it would be 90%, if ART is initiated at diagnosis. The scenarios required for such a policy to be cost-effective are presented.

CONCLUSION

This analysis provides targets for the proportion of all HIV-positive MSM with viral suppression required to achieve substantial reductions in HIV incidence.

Viral Genetic Linkage Analysis in the Presence of Missing Data

Analyses of viral genetic linkage can provide insight into HIV transmission dynamics and the impact of prevention interventions. For example, such analyses have the potential to determine whether recently-infected individuals have acquired viruses circulating within or outside a given community. In addition, they have the potential to identify characteristics of chronically infected individuals that make their viruses likely to cluster with others circulating within a community. Such clustering can be related to the potential of such individuals to contribute to the spread of the virus, either directly through transmission to their partners or indirectly through further spread of HIV from those partners. Assessment of the extent to which individual (incident or prevalent) viruses are clustered within a community will be biased if only a subset of subjects are observed, especially if that subset is not representative of the entire HIV infected population. To address this concern, we develop a multiple imputation framework in which missing sequences are imputed based on a model for the diversification of viral genomes. The imputation method decreases the bias in clustering that arises from informative missingness. Data from a household survey conducted in a village in Botswana are used to illustrate these methods. We demonstrate that the multiple imputation approach reduces bias in the overall proportion of clustering due to the presence of missing observations.

Subtype-independent near full-length HIV-1 genome sequencing and assembly to be used in large molecular epidemiological studies and clinical management

Introduction

HIV-1 near full-length genome (HIV-NFLG) sequencing from plasma is an attractive multidimensional tool to apply in large-scale population-based molecular epidemiological studies. It also enables genotypic resistance testing (GRT) for all drug target sites allowing effective intervention strategies for control and prevention in high-risk population groups. Thus, the main objective of this study was to develop a simplified subtype-independent, cost- and labour-efficient HIV-NFLG protocol that can be used in clinical management as well as in molecular epidemiological studies.

Methods

Plasma samples (n=30) were obtained from HIV-1B (n=10), HIV-1C (n=10), CRF01_AE (n=5) and CRF01_AG (n=5) infected individuals with minimum viral load >1120 copies/ml. The amplification was performed with two large amplicons of 5.5 kb and 3.7 kb, sequenced with 17 primers to obtain HIV-NFLG. GRT was validated against ViroSeq™ HIV-1 Genotyping System.

Results

After excluding four plasma samples with low-quality RNA, a total of 26 samples were attempted. Among them, NFLG was obtained from 24 (92%) samples with the lowest viral load being 3000 copies/ml. High (>99%) concordance was observed between HIV-NFLG and ViroSeq™ when determining the drug resistance mutations (DRMs). The N384I connection mutation was additionally detected by NFLG in two samples.

Conclusions

Our high efficiency subtype-independent HIV-NFLG is a simple and promising approach to be used in large-scale molecular epidemiological studies. It will facilitate the understanding of the HIV-1 pandemic population dynamics and outline effective intervention strategies. Furthermore, it can potentially be applicable in clinical management of drug resistance by evaluating DRMs against all available antiretrovirals in a single assay.

Epidemiological Surveillance of HIV-1 Transmitted Drug Resistance in Spain in 2004-2012: Relevance of Transmission Clusters in the Propagation of Resistance Mutations

Our objectives were to carry out an epidemiological surveillance study on transmitted drug resistance (TDR) among individuals newly diagnosed of HIV-1 infection during a nine year period in Spain and to assess the role of transmission clusters (TC) in the propagation of resistant strains. An overall of 1614 newly diagnosed individuals were included in the study from January 2004 through December 2012. Individuals come from two different Spanish regions: Galicia and the Basque Country. Resistance mutations to reverse transcriptase inhibitors (RTI) and protease inhibitors (PI) were analyzed according to mutations included in the surveillance drug-resistance mutations list updated in 2009. TC were defined as those comprising viruses from five or more individuals whose sequences clustered in maximum likelihood phylogenetic trees with a bootstrap value ≥90%. The overall prevalence of TDR to any drug was 9.9%: 4.9% to nucleoside RTIs (NRTIs), 3.6% to non-nucleoside RTIs (NNRTIs), and 2.7% to PIs. A significant decrease of TDR to NRTIs over time was observed [from 10% in 2004 to 2% in 2012 (p=0.01)]. Sixty eight (42.2%) of 161 sequences with TDR were included in 25 TC composed of 5 or more individuals. Of them, 9 clusters harbored TDR associated with high level resistance to antiretroviral drugs. T215D revertant mutation was transmitted in a large cluster comprising 25 individuals. The impact of epidemiological networks on TDR frequency may explain its persistence in newly diagnosed individuals. The knowledge of the populations involved in TC would facilitate the design of prevention programs and public health interventions.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

HIV-1 diversity, transmission dynamics and primary drug resistance in Angola

Objectives

To assess HIV-1 diversity, transmission dynamics and prevalence of transmitted drug resistance (TDR) in Angola, five years after ART scale-up.

Methods

Population sequencing of the pol gene was performed on 139 plasma samples collected in 2009 from drug-naive HIV-1 infected individuals living in Luanda. HIV-1 subtypes were determined using phylogenetic analysis. Drug resistance mutations were identified using the Calibrated Population Resistance Tool (CPR). Transmission networks were determined using phylogenetic analysis of all Angolan sequences present in the databases. Evolutionary trends were determined by comparison with a similar survey performed in 2001.

Results

47.1% of the viruses were pure subtypes (all except B), 47.1% were recombinants and 5.8% were untypable. The prevalence of subtype A decreased significantly from 2001 to 2009 (40.0% to 10.8%, P = 0.0019) while the prevalence of unique recombinant forms (URFs) increased>2-fold (40.0% to 83.1%, P<0.0001). The most frequent URFs comprised untypable sequences with subtypes H (U/H, n = 7, 10.8%), A (U/A, n = 6, 9.2%) and G (G/U, n = 4, 6.2%). Newly identified U/H recombinants formed a highly supported monophyletic cluster suggesting a local and common origin. TDR mutation K103N was found in one (0.7%) patient (1.6% in 2001). Out of the 364 sequences sampled for transmission network analysis, 130 (35.7%) were part of a transmission network. Forty eight transmission clusters were identified; the majority (56.3%) comprised sequences sampled in 2008–2010 in Luanda which is consistent with a locally fuelled epidemic. Very low genetic distance was found in 27 transmission pairs sampled in the same year, suggesting recent transmission events.

Conclusions

Transmission of drug resistant strains was still negligible in Luanda in 2009, five years after the scale-up of ART. The dominance of small and recent transmission clusters and the emergence of new URFs are consistent with a rising HIV-1 epidemics mainly driven by heterosexual transmission.

Impact of sampling density on the extent of HIV clustering

Identifying and monitoring HIV clusters could be useful in tracking the leading edge of HIV transmission in epidemics. Currently, greater specificity in the definition of HIV clusters is needed to reduce confusion in the interpretation of HIV clustering results. We address sampling density as one of the key aspects of HIV cluster analysis. The proportion of viral sequences in clusters was estimated at sampling densities from 1.0% to 70%. A set of 1,248 HIV-1C env gp120 V1C5 sequences from a single community in Botswana was utilized in simulation studies. Matching numbers of HIV-1C V1C5 sequences from the LANL HIV Database were used as comparators. HIV clusters were identified by phylogenetic inference under bootstrapped maximum likelihood and pairwise distance cut-offs. Sampling density below 10% was associated with stochastic HIV clustering with broad confidence intervals. HIV clustering increased linearly at sampling density >10%, and was accompanied by narrowing confidence intervals. Patterns of HIV clustering were similar at bootstrap thresholds 0.7 to 1.0, but the extent of HIV clustering decreased with higher bootstrap thresholds. The origin of sampling (local concentrated vs. scattered global) had a substantial impact on HIV clustering at sampling densities ≥10%. Pairwise distances at 10% were estimated as a threshold for cluster analysis of HIV-1 V1C5 sequences. The node bootstrap support distribution provided additional evidence for 10% sampling density as the threshold for HIV cluster analysis. The detectability of HIV clusters is substantially affected by sampling density. A minimal genotyping density of 10% and sampling density of 50-70% are suggested for HIV-1 V1C5 cluster analysis.

Infection with the frequently transmitted HIV-1 M41L variant has no influence on selection of tenofovir resistance

OBJECTIVES

In ∼10% of newly diagnosed HIV-1 patients, drug-resistant viral variants are detected. In such transmitted HIV-1 variants, the thymidine analogue mutation (TAM) M41L is frequently observed as a single resistance mutation and these viral variants often belong to phylogenetic transmission clusters. The presence of at least three TAMs, in particular patterns with M41L/L210W, impairs the efficacy of the extensively used drug tenofovir. We investigated whether the presence of a single M41L mutation at baseline influences the selection of resistance to tenofovir and emtricitabine in vitro and in vivo.

METHODS

The impact of M41L on the development of drug resistance to tenofovir and emtricitabine was determined by extensive in vitro selection experiments and investigation of the virological outcome of patients on a first-line regimen.

RESULTS

The presence of a single M41L mutation did not influence the selected mutational profile or the genetic barrier to resistance to tenofovir and/or emtricitabine during long-term in vitro selection experiments. In vivo, virological outcome of first-line regimens containing tenofovir and emtricitabine was comparable between patients diagnosed with HIV-1 harbouring M41L (n=17, 16 were part of one transmission cluster) and WT virus (n=248).

CONCLUSIONS

Detection of a single M41L reverse transcriptase mutation at baseline did not influence the development of resistance in vitro or virological outcome on tenofovir-containing regimens in patients belonging to a large transmission cluster. Our results indicate that a high genetic barrier regimen may not be required when patients are diagnosed with HIV variants containing a single M41L mutation in reverse transcriptase.

Molecular tools for studying HIV transmission in sexual networks

PURPOSE OF REVIEW

Phylogenetics is frequently used for studies of population-based HIV transmission. The purpose of this review is to highlight the current utilities and limitations of phylogenetics in HIV epidemiological research from sample collection through to data analysis.

RECENT FINDINGS

Studies of HIV phylogenies can provide critical information about HIV epidemics that are otherwise difficult to obtain through traditional study design such as transmission of drug-resistant virus, mixing between demographic groups, and rapidity of viral spread within populations. However, recent results from empirical and theoretical studies of HIV phylogenies challenge some of the key assumptions and interpretations from phylogenetic studies. Recent findings include lack of transmission bottlenecks in MSM and injection drug use epidemics, evidence for preferential transmission of HIV virus in heterosexual epidemics, and limited evidence that tree topologies correlate directly with underlying network structures. Other challenges include a lack of a standardized definition for a phylogenetic transmission cluster and biased or sparse sampling of HIV transmission networks.

SUMMARY

Phylogenetics is an important tool for HIV research, and offers opportunities to understand critical aspects of the HIV epidemic. Like all epidemiological research, the methods used and interpretation of results from phylogenetic studies should be made cautiously with careful consideration.

Toward an endgame: finding and engaging people unaware of their HIV-1 infection in treatment and prevention

Epidemic modeling suggests that a major scale-up in HIV treatment could have a dramatic impact on HIV incidence. This has led both researchers and policymakers to set a goal of an "AIDS-Free Generation." One of the greatest obstacles to achieving this objective is the number of people with undiagnosed HIV infection. Despite recent innovations, new research strategies are needed to identify, engage, and successfully treat people who are unaware of their infection.

Linkage of viral sequences among HIV-infected village residents in Botswana: estimation of linkage rates in the presence of missing data

Linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them, but estimates of probabilities of linkage between infected people from observed data can be biased downward when missingness is informative. We investigate variation in the rates at which subjects' viral genotypes link across groups defined by viral load (low/high) and antiretroviral treatment (ART) status using blood samples from household surveys in the Northeast sector of Mochudi, Botswana. The probability of obtaining a sequence from a sample varies with viral load; samples with low viral load are harder to amplify. Pairwise genetic distances were estimated from aligned nucleotide sequences of HIV-1C env gp120. It is first shown that the probability that randomly selected sequences are linked can be estimated consistently from observed data. This is then used to develop estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across pairs. Furthermore, a resampling approach is developed that accounts for the presence of correlation across pairs, with diagnostics for assessing the reliability of the method. Sequences were obtained for 65% of subjects with high viral load (HVL, n = 117), 54% of subjects with low viral load but not on ART (LVL, n = 180), and 45% of subjects on ART (ART, n = 126). The probability of linkage between two individuals is highest if both have HVL, and lowest if one has LVL and the other has LVL or is on ART. Linkage across groups is high for HVL and lower for LVL and ART. Adjustment for missing data increases the group-wise linkage rates by 40–100%, and changes the relative rates between groups. Bias in inferences regarding HIV viral linkage that arise from differential ability to genotype samples can be reduced by appropriate methods for accommodating missing data.

The analysis of viral genomes has great potential for investigating transmission of disease, including the identification of risk factors and transmission clusters, and can thereby aid in targeting interventions. To make use of genetic data in this way, it is necessary to make inferences about population-level patterns of viral linkage. As with any rigorous statistical inference from sampled data to a population, it is important to consider the effect of the sampling strategy and the occurrence of missing data on the final inferences made. In this paper we highlight the effects of missing data on the resulting estimates of population level linkage rates and develop methods for adjusting for the presence of missing data. As an example, we consider comparing the rates of linkage of HIV sequences from subjects with high viral load, low viral load, or on antiretroviral treatment, and show that comparative inferences are compromised when adjustment is not made for missing sequences and bias in inferences can be reduced with proper adjustment.