A Phylogenetic Analysis of HIV-1 Sequences in Kiev: Findings among Key Populations

BACKGROUND: The HIV epidemic in Ukraine has been driven by a rapid rise among people who inject drugs, but recent studies have shown an increase through sexual transmission. METHODS: Protease and RT sequences from 876 new HIV diagnoses (April 2013 - March 2015) in Kiev were linked to demographic data. We constructed phylogenetic trees for 794 subtype A1 and 64 subtype B sequences and identified factors associated with transmission clustering. Clusters were defined as ≥ 2 sequences, ≥ 80% local branch support and maximum genetic distance of all sequence pairs in the cluster ≤ 2.5%. Recent infection was determined through the LAg avidity EIA assay. Sequences were analysed for transmitted drug resistance (TDR) mutations. RESULTS: 30% of subtype A1 and 66% of subtype B sequences clustered. Large clusters (maximum 11 sequences) contained mixed risk groups. In univariate analysis, clustering was significantly associated with subtype B compared to A1 (OR 4.38 [95% CI 2.56-7.50]), risk group (OR 5.65 [3.27-9.75]) for men who have sex with men compared to heterosexual males, recent, compared to long-standing, infection (OR 2.72 [1.64-4.52]), reported sex work contact (OR 1.93 [1.07-3.47]) and younger age groups compared to age ≥36 (OR 1.83 [1.10-3.05] for age ≤25). Females were associated with lower odds of clustering than heterosexual males (OR 0.49 [0.31-0.77]). In multivariate analysis, risk group, subtype and age group were independently associated with clustering (p<0.001, p=0.007 and p=0.033). 18 sequences (2.1%) indicated evidence of TDR. CONCLUSIONS: Our findings suggest high levels of transmission and bridging between risk groups

Molecular phylodynamics of the heterosexual HIV epidemic in the United Kingdom

The heterosexual risk group has become the largest HIV infected group in the United Kingdom during the last 10 years, but little is known of the network structure and dynamics of viral transmission in this group. The overwhelming majority of UK heterosexual infections are of non-B HIV subtypes, indicating viruses originating among immigrants from sub-Saharan Africa. The high rate of HIV evolution, combined with the availability of a very high density sample of viral sequences from routine clinical care has allowed the phylodynamics of the epidemic to be investigated for the first time. Sequences of the viral protease and partial reverse transcriptase coding regions from 11,071 patients infected with HIV of non-B subtypes were studied. Of these, 2774 were closely linked to at least one other sequence by nucleotide distance. Including the closest sequences from the global HIV database identified 296 individuals that were in UK-based groups of 3 or more individuals. There were a total of 8 UK-based clusters of 10 or more, comprising 143/2774 (5%) individuals, much lower than the figure of 25% obtained earlier for men who have sex with men (MSM). Sample dates were incorporated into relaxed clock phylogenetic analyses to estimate the dates of internal nodes. From the resulting time-resolved phylogenies, the internode lengths, used as estimates of maximum transmission intervals, had a median of 27 months overall, over twice as long as obtained for MSM (14 months), with only 2% of transmissions occurring in the first 6 months after infection. This phylodynamic analysis of non-B subtype HIV sequences representing over 40% of the estimated UK HIV-infected heterosexual population has revealed heterosexual HIV transmission in the UK is clustered, but on average in smaller groups and is transmitted with slower dynamics than among MSM. More effective intervention to restrict the epidemic may therefore be feasible, given effective diagnosis programmes

Transmission of Non-B HIV Subtypes in the United Kingdom Is Increasingly Driven by Large Non-Heterosexual Transmission Clusters

BACKGROUND: The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change. METHODS: Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group. RESULTS: Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P< .0001), cluster size (P< .0001), and subtype (P< .01) were predictive of growth in a generalized linear model. DISCUSSION: Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom

Transmission of non-B HIV subtypes in the UK is increasingly driven by large non-heterosexual clusters

BACKGROUND: The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change. METHODS: Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group. RESULTS: Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P< .0001), cluster size (P< .0001), and subtype (P< .01) were predictive of growth in a generalized linear model. DISCUSSION: Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom

HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK

\ua9 The Author 2016. Background: Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings. Objectives: We examined darunavir DRMs emerging in clinical practice in the UK. Patients and methods: Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PInaive controls. Results: Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group. Conclusions: Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility

Virological failure and development of new resistance mutations according to CD4 count at combination antiretroviral therapy initiation

Objectives: No randomized controlled trials have yet reported an individual patient benefit of initiating combination antiretroviral therapy (cART) at CD4 counts > 350 cells/μL. It is hypothesized that earlier initiation of cART in asymptomatic and otherwise healthy individuals may lead to poorer adherence and subsequently higher rates of resistance development. Methods: In a large cohort of HIV-positive individuals, we investigated the emergence of new resistance mutations upon virological treatment failure according to the CD4 count at the initiation of cART. Results: Of 7918 included individuals, 6514 (82.3%), 996 (12.6%) and 408 (5.2%) started cART with a CD4 count ≤ 350, 351-499 and ≥ 500 cells/μL, respectively. Virological rebound occurred while on cART in 488 (7.5%), 46 (4.6%) and 30 (7.4%) with a baseline CD4 count ≤ 350, 351-499 and ≥ 500 cells/μL, respectively. Only four (13.0%) individuals with a baseline CD4 count > 350 cells/μL in receipt of a resistance test at viral load rebound were found to have developed new resistance mutations. This compared to 107 (41.2%) of those with virological failure who had initiated cART with a CD4 count < 350 cells/μL. Conclusions: We found no evidence of increased rates of resistance development when cART was initiated at CD4 counts above 350 cells/μL. HIV Medicin

Automated analysis of phylogenetic clusters

BACKGROUND: As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker. RESULTS: We explore the effect of different bootstrap and genetic distance thresholds on clusters identified in a data set of publicly available HIV sequences, and compare these results to those of a previously published tool for cluster identification. To demonstrate their utility, we then use the Cluster Picker and Cluster Matcher together to investigate how clusters in the data set changed over time. We find that clusters containing sequences from more than one UK location at the first time point (multiple origin) were significantly more likely to grow than those representing only a single location. CONCLUSIONS: The Cluster Picker and Cluster Matcher can rapidly process phylogenetic trees containing tens of thousands of sequences. Together these tools will facilitate comparisons of pathogen transmission dynamics between studies and countries

The changing epidemiological profile of HIV-1 subtype B epidemic in Ukraine

Background While HIV‐1 subtype B has caused a large epidemic in the western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV‐1 subtype B viruses circulating in Ukraine, characterized transmission group structure, and estimated key evolutionary and epidemiological parameters. Methods We analysed 120 HIV‐1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002‐2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and to date the most recent common ancestors of identified clades. A phylodynamic birth‐death model was used to estimate the effective reproductive number (Re) of these clades. Results We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV‐1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV‐1 subtype A into Ukraine. Re for Clade 1 was estimated to be 1.42 (95% HPD 1.26‐1.56) and 1.69 (95% HPD 1.49‐1.84) for Clade 2. Discussion The subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV‐1 subtype B.</p

The changing epidemiological profile of HIV-1 subtype B epidemic in Ukraine

Background While HIV‐1 subtype B has caused a large epidemic in the western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV‐1 subtype B viruses circulating in Ukraine, characterized transmission group structure, and estimated key evolutionary and epidemiological parameters. Methods We analysed 120 HIV‐1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002‐2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and to date the most recent common ancestors of identified clades. A phylodynamic birth‐death model was used to estimate the effective reproductive number (Re) of these clades. Results We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV‐1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV‐1 subtype A into Ukraine. Re for Clade 1 was estimated to be 1.42 (95% HPD 1.26‐1.56) and 1.69 (95% HPD 1.49‐1.84) for Clade 2. Discussion The subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV‐1 subtype B.</p