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The hepatitis C virus (HCV) epidemic in Western countries is primarily perpetuated by the sub-populations of men who have sex with men (MSM) and people who inject drugs (PWID). Understanding the dynamics of transmission in these communities is crucial for removing the remaining hurdles towards HCV elimination. We sequenced 269 annotated HCV plasma samples using probe enrichment and next-generation sequencing, obtaining 224 open reading frames of HCV (OR497849-OR498072). Maximum likelihood phylogenies were generated on the four most prevalent subtypes in this study (HCV1a, 1b, 3a, 4d) with a subsequent transmission cluster analysis. The highest rate of clustering was observed for HCV4d samples (13/17 (76.47%)). The second highest rate of clustering was observed in HCV1a samples (42/78 (53.85%)) with significant association with HIV-positive MSM. HCV1b and HCV3a had very low rates of clustering (2/83 (2.41%) and (0/29)). The spread of the prevalent subtype HCV1b appears to have been largely curtailed, and we demonstrate the onwards transmission of HCV1a and HCV4d in the HIV-positive MSM population across municipal borders. More systematic data collection and sequencing is needed to allow a better understanding of the HCV transmission among the community of PWID and overcome the remaining barriers for HCV elimination in Belgium.

To curb HIV infection rate in Tanzania, antiretroviral therapy (ART) has been scaled up since 2006, and in 2019, the country shifted to regimen including dolutegravir as a default first line. We assessed the success of ART and the contribution of HIV drug resistance (HIVDR) to unsuppressed viral loads. Between February and May 2023 a cross-sectional survey with random sampling was conducted in the six clinics in an urban cohort in Dar es Salaam. Patients with unsuppresed viral loads (local criteria viral load (VL) ≥ 1000 copies/mL) were tested for HIVDR mutations using the WHO adapted protocol for plasma samples. Mutations were interpreted using the Stanford HIVDR database. In total 600 individuals participated in this survey, the majority were female (76.83%), mean age ([Formula: see text] standard deviation) was 44.0 ([Formula: see text] 11.6) years. The median duration on ART (interquartile range) was 6.5 (3.9-10.2) years. Approximately 99% were receiving tenofovir + lamivudine + dolutegravir as a fixed dose combination. VL testing was successful in 99.67% (598/600) of survey patients and only 33 had VL ≥ 1000 copies/mL, resulting in a viral suppression level of 94.48% (565/598, 95% CI 92.34-96.17%). For 23 samples, protease and reverse transcriptase (RT) genotyping were successful, with 13 sequences containing RT inhibitor surveillance drug resistance mutations (SDRMs) (56.5%). No SDRM against protease inhibitors were detected. Thirty samples were successfully genotyped for integrase with 3 sequences (10.08%) containing integrase strand transfer inhibitor (INSTI) SDRMs. In samples successfully genotyped in the three genetic regions, 68.18% (16/22) had a genotypic susceptibility score (GSS) ≥ 2.5 for the concurrent regimen, implying factors beyond drug resistance caused the unsuppressed viral load. For five patients, GSS indicated that HIVDR may have caused the unsuppressed viral load. All three patients with INSTI resistance mutations were highly resistant to dolutegravir and accumulated nucleoside and non-nucleoside RT inhibitor HIVDR mutations. Although in this cohort the last 95 UNAIDS target was almost achieved, HIVDR mutations, including INSTIs resistance mutations were detected in HIV-positive individuals taking ART for at least one year. We recommend the design and implementation of high-impact interventions to prevent the increase of HIVDR, failure of dolutegravir and address the non-resistance factors in the study area., (© 2023. The Author(s).)

• Human immunodeficiency virus (HIV) drug resistance has implications for antiretroviral treatment strategies and for containing the HIV pandemic because the development of HIV drug resistance leads to the requirement for antiretroviral drugs that may be less effective, less well-tolerated, and more expensive than those used in first-line regimens.  • HIV drug resistance studies are designed to determine which HIV mutations are selected by antiretroviral drugs and, in turn, how these mutations affect antiretroviral drug susceptibility and response to future antiretroviral treatment regimens.  • Such studies collectively form a vital knowledge base essential for monitoring global HIV drug resistance trends, interpreting HIV genotypic tests, and updating HIV treatment guidelines.  • Although HIV drug resistance data are collected in many studies, such data are often not publicly shared, prompting the need to recommend best practices to encourage and standardize HIV drug resistance data sharing.  • In contrast to other viruses, sharing HIV sequences from phylogenetic studies of transmission dynamics requires additional precautions as HIV transmission is criminalized in many countries and regions.  • Our recommendations are designed to ensure that the data that contribute to HIV drug resistance knowledge will be available without undue hardship to those publishing HIV drug resistance studies and without risk to people living with HIV., Competing Interests: SJL has received research funding paid to her institution from Gilead Sciences. VC has received travel grants, advisor honorarium and research grant from Merck Sharp & Dohme, ViiV Healthcare and Gilead Sciences. FCS has been a consultant to ViiV Healthcare, Gilead Sciences and Merck Sharp & Dohme, and received research grants paid to her institution from Gilead Sciences. CC has received honoraria and conference travels grants from Merck Sharp & Dohme, Gilead Sciences, and ViiV Healthcare. DD has received honoraria for participation in advisory boards and conference travel grants ViiV Healthcare, Gilead Sciences, Janssen Pharmaceuticals, and Merck Sharp & Dohme. LF has received NIH research grants paid to her institution. RKG has received honoraria for participation on advisory boards from Gilead-Sciences and GlaxoSmithKline. RDK has received research grants from Gilead Sciences paid to his institution. DRK is a consultant to and has received honoraria from AbbVie, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals, Merck, Roche, and ViiV Healthcare. DRK has also received honoraria from Gilead for expert testimony and speaking fees from Gilead Sciences and Janssen Pharmaceuticals and has received research support paid to his institution from Gilead Sciences, Merck, and ViiV Healthcare. AGM received travel grants, honoraria and study grants from Gilead Sciences, Merck Sharp & Dohme, ViiV Healthcare, GlaxoSmithKline, Roche, and Astra Zeneca. RP has received research grants paid to his institution from Merck Sharp & Dohme and ViiV Healthcare and consulting fees from Gilead Sciences, Merck Sharp & Dohme, GlaxoSmithKline, Atea Pharmaceuticals, Roche, and Shinogi Pharmaceuticals. PCS is a co-founder of, shareholder in, and consultant to Sherlock Biosciences and Delve Bio, and a board member of and shareholder in Danaher Corporation. JMS has received research support, honorarium, or consulting fees from the following: Abbvie, Merck, Gilead Sciences, GlaxoSmithKline, Tibotec-Janssen, Teva, Virology Education and ViiV Healthcare. He has received travel support and stipends for advisory work for the World Health Organization. WS has received speaking honoraria from GlaxoSmithKline, ViiV Healthcare, Merck Sharp & Dohme, Pfizer, and Abbott Pharmaceuticals. AMJW has received research support paid to her institution by Gilead Sciences and has consulted for Gilead Sciences and ViiV Healthcare. JOW receives funding from grants and contracts to his institution from NIH and CDC pertaining to work on HIV molecular epidemiology. HFG has received grants paid to his institution from Gilead Sciences, and Roche, and has received consulting fees from Merck, Gilead Sciences, ViiV Healthcare, Janssen Pharmaceuticals, GlaxoSmithKline, Johnson and Johnson, and Novartis. RWS has received honoraria for participation in advisory boards from Gilead Sciences and GlaxoSmithKline and speaking honoraria from Gilead Sciences and ViiV Healthcare., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Introduction: Disease progression, drug resistance mutations, and treatment strategies may vary by HIV-1 subtype. This study determined HIV-1 subtypes circulating in Slovenia, a Central European country with an HIV-1 epidemic driven by men who have sex with men, focusing on molecular epidemiology of non-B subtypes., Methods: A total of 367 HIV-1 sequences were included. Subtype was assigned by employing eight different HIV subtyping tools coupled with maximum likelihood phylogenetic analyses., Results: The subtyping tools COMET, jpHMM, and REGA 3.0 exhibited the best performance on the dataset studied. Phylogenetic analyses showed a 14.7% prevalence of non-B subtypes, with subtype A detected most frequently (4.9%), followed by CRF02_AG (2.4%), subtype C (1.1%), subtypes D, G, and CRF01_AE (0.8% each), and subtypes F and CRF22_01A1 (0.3% each). A subtype could not be assigned to 12 sequences (3.3%), indicating potential unique recombinant forms. Non-B subtypes were significantly associated with a heterosexual route of transmission and infection acquired in Eastern Europe, Africa, or Asia., Conclusion: In a country where subtype B is predominant, non-B subtypes were observed in one out of seven patients, a non-negligible proportion, which underlines the importance of systematic surveillance of HIV subtype diversity and the corresponding molecular epidemiology.

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug resistance, however, is a rare event in modern HIV treatment, but can be life-threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that the accumulation of resistance mutations is not acquired simultaneously and randomly across viral genotypes but rather tends to follow a predetermined order. The knowledge of this order might help to elucidate potential mechanisms of multidrug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well-known nucleoside reverse transcriptase (RT) inhibitor-related mutations like K223Q, L228H, and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multidrug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and RT. We followed up with an analysis of the mutation-specific error rates of our model given the data. We identified several mutations with unusual rates (PR: M41L, L33F, IN: G140S). This could imply the existence of previously unknown virus variants in the viral quasispecies. In conclusion, our bioinformatics model supports the analysis and understanding of multidrug resistance., (© 2022 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

Competing Interests: Competing interests: A-MV declares consultancy fees from Gilead.

Background: HIV drug resistance (HIVDR) continues to threaten the effectiveness of worldwide antiretroviral therapy (ART). Emergence and transmission of HIVDR are driven by several interconnected factors. Though much has been done to uncover factors influencing HIVDR, overall interconnectedness between these factors remains unclear and African policy makers encounter difficulties setting priorities combating HIVDR. By viewing HIVDR as a complex adaptive system, through the eyes of multi-disciplinary HIVDR experts, we aimed to make a first attempt to linking different influencing factors and gaining a deeper understanding of the complexity of the system., Methods: We designed a detailed systems map of factors influencing HIVDR based on semi-structured interviews with 15 international HIVDR experts from or with experience in sub-Saharan Africa, from different disciplinary backgrounds and affiliated with different types of institutions. The resulting detailed system map was conceptualized into three main HIVDR feedback loops and further strengthened with literature evidence., Results: Factors influencing HIVDR in sub-Saharan Africa and their interactions were sorted in five categories: biology, individual, social context, healthcare system and 'overarching'. We identified three causal loops cross-cutting these layers, which relate to three interconnected subsystems of mechanisms influencing HIVDR. The 'adherence motivation' subsystem concerns the interplay of factors influencing people living with HIV to alternate between adherence and non-adherence. The 'healthcare burden' subsystem is a reinforcing loop leading to an increase in HIVDR at local population level. The 'ART overreliance' subsystem is a balancing feedback loop leading to complacency among program managers when there is overreliance on ART with a perceived low risk to drug resistance. The three subsystems are interconnected at different levels., Conclusions: Interconnectedness of the three subsystems underlines the need to act on the entire system of factors surrounding HIVDR in sub-Saharan Africa in order to target interventions and to prevent unwanted effects on other parts of the system. The three theories that emerged while studying HIVDR as a complex adaptive system form a starting point for further qualitative and quantitative investigation., (© 2022. The Author(s).)

In the early 1990s, several observational studies determined that genital ulcer disease (GUD), in either the index or the exposed person, facilitates HIV transmission. Several meta-analyses have since presented associated risk ratios (RR) over the baseline per-act transmission probability (PATP) usually in the range of 2-5. Here we review all relevant observational studies and meta-analyses, and show that the estimation of RRs was, in most cases, biased by assuming the presence of GUD at any time during long follow-up periods, while active genital ulcers were present in a small proportion of the time. Only two studies measured the GUD co-factor effect in PATPs focusing on acts in which ulcers were present, and both found much higher RRs (in the range 11-112). We demonstrate that these high RRs can be reconciled with the studies on which currently accepted low RRs were based, if the calculations are restricted to the actual GUD episodes. Our results indicate that the effect of genital ulcers on the PATP of HIV might be much greater than currently accepted. We conclude that the medical community should work on the assumption that HIV risk is very high during active genital ulcers.

To which extent STDs facilitated HIV-1 adaptation to humans, sparking the pandemic, is still unknown. We searched colonial medical records from 1906-1958 for Leopoldville, Belgian Congo, which was the initial epicenter of pandemic HIV-1, compiling counts of treated STD cases in both Africans and Europeans. Almost all Europeans were being treated, while for Africans, generalized treatment started only in 1929. Treated STD counts in Europeans thus reflect STD infection rates more accurately compared to counts in Africans. In Africans, the highest recorded STD treatment incidence was in 1929-1935, declining to low levels in the 1950s. In Europeans, the recorded treatment incidences were highest during the period 1910-1920, far exceeding those in Africans. Europeans were overwhelmingly male and had frequent sexual contact with African females. Consequently, high STD incidence among Europeans must have coincided with high prevalence and incidence in the city's African population. The data strongly suggest the worst STD period was 1910-1920 for both Africans and Europeans, which coincides with the estimated origin of pandemic HIV-1. Given the strong effect of STD coinfections on HIV transmission, these new data support our hypothesis of a causal effect of STDs on the epidemic emergence of HIV-1.

Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a heterosexual population with Herpes simplex virus type-2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé-Cameroon were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. These differences in predictions of an intervention were also observed for two models that agreed in their predictions of the HIV epidemic in the absence of that intervention. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models., (© 2021. The Author(s).)

Introduction: Treatment for All recommendations have allowed access to antiretroviral (ARV) treatment for an increasing number of patients. This minimizes the transmission of infection but can potentiate the risk of transmitted (TDR) and acquired drug resistance (ADR)., Objective: To study the trends of TDR and ADR in patients followed up in Portuguese hospitals between 2001 and 2017., Methods: In total, 11,911 patients of the Portuguese REGA database were included. TDR was defined as the presence of one or more surveillance drug resistance mutation according to the WHO surveillance list. Genotypic resistance to ARV was evaluated with Stanford HIVdb v7.0. Patterns of TDR, ADR and the prevalence of mutations over time were analyzed using logistic regression., Results and Discussion: The prevalence of TDR increased from 7.9% in 2003 to 13.1% in 2017 ( p < 0.001). This was due to a significant increase in both resistance to nucleotide reverse transcriptase inhibitors (NRTIs) and non-nucleotide reverse transcriptase inhibitors (NNRTIs), from 5.6% to 6.7% ( p = 0.002) and 2.9% to 8.9% ( p < 0.001), respectively. TDR was associated with infection with subtype B, and with lower viral load levels ( p < 0.05). The prevalence of ADR declined from 86.6% in 2001 to 51.0% in 2017 ( p < 0.001), caused by decreasing drug resistance to all antiretroviral (ARV) classes ( p < 0.001)., Conclusions: While ADR has been decreasing since 2001, TDR has been increasing, reaching a value of 13.1% by the end of 2017. It is urgently necessary to develop public health programs to monitor the levels and patterns of TDR in newly diagnosed patients., Competing Interests: The authors declare that they have no conflict of interests.

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.

Migration is associated with HIV-1 vulnerability., Objectives: To identify long-term trends in HIV-1 molecular epidemiology and antiretroviral drug resistance (ARV) among migrants followed up in Portugal Methods: 5177 patients were included between 2001 and 2017. Rega, Scuel, Comet, and jPHMM algorithms were used for subtyping. Transmitted drug resistance (TDR) and Acquired drug resistance (ADR) were defined as the presence of surveillance drug resistance mutations (SDRMs) and as mutations of the IAS-USA 2015 algorithm, respectively. Statistical analyses were performed., Results: HIV-1 subtypes infecting migrants were consistent with the ones prevailing in their countries of origin. Over time, overall TDR significantly increased and specifically for Non-nucleoside reverse transcriptase inhibitor (NNRTIs) and Nucleoside reverse transcriptase inhibitor (NRTIs). TDR was higher in patients from Mozambique. Country of origin Mozambique and subtype B were independently associated with TDR. Overall, ADR significantly decreased over time and specifically for NRTIs and Protease Inhibitors (PIs). Age, subtype B, and viral load were independently associated with ADR., Conclusions: HIV-1 molecular epidemiology in migrants suggests high levels of connectivity with their country of origin. The increasing levels of TDR in migrants could indicate an increase also in their countries of origin, where more efficient surveillance should occur.

Objectives: The study aimed to survey maraviroc use and assess effectiveness and durability of maraviroc-containing antiretroviral treatment (ART) in routine practice across Europe., Methods: Data were retrieved from 26 cohorts in 8 countries comprising adults who started maraviroc in 2005-2016 and had ≥1 follow-up visit. Available V3 sequences were re-analysed centrally for tropism determination by geno2pheno[coreceptor]. Treatment failure (TF) was defined as either virological failure (viral load >50 copies/mL) or maraviroc discontinuation for any reason over 48 weeks. Predictors of TF were explored by logistic regression analysis. Time to maraviroc discontinuation was estimated by Kaplan-Meier survival analysis., Results: At maraviroc initiation (baseline), among 1,381 patients, 67.1% had experienced ≥3 ART classes and 45.6% had a viral load <50 copies/mL. Maraviroc was occasionally added to the existing regimen as a single agent (7.3%) but it was more commonly introduced alongside other new agents, and was often (70.4%) used with protease inhibitors. Accompanying drugs comprised 1 (40.2%), 2 (48.6%) or ≥3 (11.2%) ART classes. Among 1,273 patients with available tropism data, 17.6% showed non-R5 virus. Non-standard maraviroc use also comprised reported once daily dosing (20.0%) and a total daily dose of 150mg (12.1%). Over 48 weeks, 41.4% of patients met the definition of TF, although the 1-year estimated retention on maraviroc was 82.1% (95% confidence interval 79.9-84.2). Among 1,010 subjects on maraviroc at week 48, the viral load was >50 copies/mL in 19.9% and >200 copies/mL in 10.7%. Independent predictors of TF comprised a low nadir CD4 count, a detectable baseline viral load, previous PI experience, non-R5 tropism, having ≥3 active drugs in the accompanying regimen, and a more recent calendar year of maraviroc initiation., Conclusions: This study reports on the largest observation cohort of patients who started maraviroc across 8 European countries. In this overall highly treatment-experienced population, with a small but appreciable subset that received maraviroc outside of standard treatment guidelines, maraviroc was safe and reasonably effective, with relatively low rates of discontinuation over 48 weeks and only 2 cases of serum transaminase elevations reported as reasons for discontinuation., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Dr. Boucher reports personal fees and research grant from ViiV, outside the submitted work. Dr. Geretti reports grants from BMS, grants and personal fees from Gilead Sciences, personal fees from Cepheid, grants and personal fees from Roche Pharma, grants and personal fees from ViiV Healthcare, grants and personal fees from Janssen, outside the submitted work; Dr. Kaiser reports grants from Gilead Sciences and ViiV Healthcare, personal fees from Janssen-Cilag, MSD, ROCHE, ABBVIE, Siemens and ViiV Healthcare, outside the submitted work; Dr. Vandamme received a personal fee from Gilead outside the submitted work; Dr. Zazzi reports grants from Gilead Sciences and ViiV Healthcare, personal fees from Janssen-Cilag and ViiV Healthcare, outside the submitted work; Dr. Incardona reports grants from Gilead Sciences, Janssen and ViiV Healthcare, outside the submitted work; she received salary from InformaPRO, Rome. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Estimation of temporal changes in human immunodeficiency virus (HIV) transmission patterns can help to elucidate the impact of preventive strategies and public health policies., Methods: Portuguese HIV-1 subtype B and G pol genetic sequences were appended to global reference data sets to identify country-specific transmission clades. Bayesian birth-death models were used to estimate subtype-specific effective reproductive numbers (Re). Discrete trait analysis (DTA) was used to quantify mixing among transmission groups., Results: We identified 5 subtype B Portuguese clades (26-79 sequences) and a large monophyletic subtype G Portuguese clade (236 sequences). We estimated that major shifts in HIV-1 transmission occurred around 1999 (95% Bayesian credible interval [BCI], 1998-2000) and 2000 (95% BCI, 1998-2001) for subtypes B and G, respectively. For subtype B, Re dropped from 1.91 (95% BCI, 1.73-2.09) to 0.62 (95% BCI,.52-.72). For subtype G, Re decreased from 1.49 (95% BCI, 1.39-1.59) to 0.72 (95% BCI, .63-.8). The DTA suggests that people who inject drugs (PWID) and heterosexuals were the source of most (>80%) virus lineage transitions for subtypes G and B, respectively., Conclusions: The estimated declines in Re coincide with the introduction of highly active antiretroviral therapy and the scale-up of harm reduction for PWID. Inferred transmission events across transmission groups emphasize the importance of prevention efforts for bridging populations., (© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America.)

Objective: To evaluate the effect of primary resistance and selected polymorphic amino-acid substitutions in HIV reverse transcriptase and protease on the CD4 cell count and viral load set point before the start of antiretroviral treatment., Design: Prospective cohort study., Methods: A total of 6180 individuals with a resistance test prior to starting antiretroviral treatment accessing care in HIV clinics across Europe who had at least one viral load and one CD4+ test available were included in the analysis. The impact of amino-acid substitutions variants on viral load and CD4+ trends was investigated using linear mixed models. Clusters of mutations were studied using principal component analysis., Results: Overall, the detection of any primary resistance was not associated with either the speed of CD4+ cell decline or the viral load set point. However, transmitted nucleoside reverse transcriptase inhibitor and protease inhibitor resistance appeared to be weakly associated with lower viral load set points, as were the polymorphic G16E or Q92K protease mutations. There was some evidence suggesting that these effects varied according to HIV subtype, with the effects of transmitted nucleoside reverse transcriptase inhibitor and protease resistance being particularly marked among individuals with a subtype B virus. A cluster of five polymorphic protease substitutions at position 20, 13, 36, 69 and 89 was associated with less steep CD4+ cell declines and lower viral load set points., Conclusion: Although we found little evidence for an association between primary resistance and CD4+ speed of decline and viral load set point, the potential role of polymorphic protease (alone or in clusters) and their interplay with HIV subtype needs to be further evaluated.

Phylogenetic analysis of pathogens is an increasingly powerful way to reduce the spread of epidemics, including HIV. As a result, phylogenetic approaches are becoming embedded in public health and research programmes, as well as outbreak responses, presenting unique ethical, legal, and social issues that are not adequately addressed by existing bioethics literature. We formed a multidisciplinary working group to explore the ethical issues arising from the design of, conduct in, and use of results from HIV phylogenetic studies, and to propose recommendations to minimise the associated risks to both individuals and groups. We identified eight key ethical domains, within which we highlighted factors that make HIV phylogenetic research unique. In this Review, we endeavoured to provide a framework to assist researchers, public health practitioners, and funding institutions to ensure that HIV phylogenetic studies are designed, done, and disseminated in an ethical manner. Our conclusions also have broader relevance for pathogen phylogenetics., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Introduction: Globally, prosecutions for non-disclosure, exposure or transmission of HIV frequently relate to sexual activity, biting, or spitting. This includes instances in which no harm was intended, HIV transmission did not occur, and HIV transmission was extremely unlikely or not possible. This suggests prosecutions are not always guided by the best available scientific and medical evidence., Discussion: Twenty scientists from regions across the world developed this Expert Consensus Statement to address the use of HIV science by the criminal justice system. A detailed analysis of the best available scientific and medical research data on HIV transmission, treatment effectiveness and forensic phylogenetic evidence was performed and described so it may be better understood in criminal law contexts. Description of the possibility of HIV transmission was limited to acts most often at issue in criminal cases. The possibility of HIV transmission during a single, specific act was positioned along a continuum of risk, noting that the possibility of HIV transmission varies according to a range of intersecting factors including viral load, condom use, and other risk reduction practices. Current evidence suggests the possibility of HIV transmission during a single episode of sex, biting or spitting ranges from no possibility to low possibility. Further research considered the positive health impact of modern antiretroviral therapies that have improved the life expectancy of most people living with HIV to a point similar to their HIV-negative counterparts, transforming HIV infection into a chronic, manageable health condition. Lastly, consideration of the use of scientific evidence in court found that phylogenetic analysis alone cannot prove beyond reasonable doubt that one person infected another although it can be used to exonerate a defendant., Conclusions: The application of up-to-date scientific evidence in criminal cases has the potential to limit unjust prosecutions and convictions. The authors recommend that caution be exercised when considering prosecution, and encourage governments and those working in legal and judicial systems to pay close attention to the significant advances in HIV science that have occurred over the last three decades to ensure current scientific knowledge informs application of the law in cases related to HIV., (© 2018 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.)

Background: Hepatitis C virus (HCV) resistance-associated variants (RAVs) have been shown to adversely affect treatment response of direct-acting antivirals. Identifying pre-existing RAVs and transmission networks among HIV/HCV genotype 1 (G1)-infected patients from Poland will assist in shaping surveillance strategies for HCV., Methods: NS3 and NS5A sequences were obtained from samples of 112 direct-acting antiviral-naive G1 patients (45 G1a and 67 G1b), of which 74 were chronically infected and 38 were diagnosed with acute hepatitis C (AHC). RAVs were identified using geno2pheno, and 98 concatenated NS3/NS5A alignments were constructed to identify transmission clusters using a maximum likelihood approach., Results: G1a was notably more prevalent compared with G1b among men-having-sex-with-men (MSM) (60.0% vs. 31.3%, P = 0.004), AHC cases (46.7% vs. 25.4%, P = 0.019), and patients diagnosed with syphilis (52.2% vs. 24.5%, P = 0.009). The overall NS3/NS5A RAVs frequency was 14.3% with variants occurring more often in G1a compared with G1b (27.5% vs. 5.2%, P = 0.005), mostly for NS3 due to the high prevalence of polymorphism Q80K. NS5A RAVs were only found in 2.9% of sequences. Significant clustering was observed for 73.5% of the Polish sequences, however, more common in G1a MSM compared with G1b (50.0% vs. 25.9%, P = 0.02). The identified clusters contained sequences originating from up to 5 Polish cities, located within a mean distance of 370 km., Conclusions: Close clustering of Polish strains suggests the presence of compartmentalized epidemics of MSM that fuel the spread of G1a variants. Particularly patients with AHC form a national transmission network, including clusters enriched with the NS3 Q80K polymorphism.

: Because HIV is a fast-evolving virus, HIV genomic sequences of several individuals can be used to investigate whether they belong to a transmission network. Since the infamous 'Florida dentist case' in the beginning of the 1990s, phylogenetic analyses has been recurrently used in court settings as a forensic tool in HIV transmission investigations, for example cases where one or more complainants allege that a defendant has unlawfully infected them with HIV. Such cases can arise both in the context of HIV-specific criminal laws - in countries where transmission of HIV infection is specifically criminalized - or in the context of general laws, for example, by applying physical or sexual assault laws to HIV-related cases. Although phylogenetic analysis as a forensic technique for HIV transmission investigations has become common in several countries, the methodologies have not yet been standardized, sometimes giving rise to unwarranted conclusions. In this literature review, we revisit HIV court case investigations published in the scientific literature, as well as the methodological aspects important for the application and standardization of phylogenetic analyses methods as a forensic tool. Phylogenetic methodologies are improving quickly, such that more recently, phylogenetic relatedness, directionality of transmission and timing of nodes in the tree are used to assess whether the phylogenetic transmission analysis is consistent with or contradicting the charges. We find that there has been a lack of consistency between methods used in court case investigations and that it is essential to define guidelines to be used by phylogenetic forensic experts in HIV transmission cases in court.

The adaptive potential of HIV-1 is a vital mechanism to evade host immune responses and antiviral treatment. However, high evolutionary rates during persistent infection can impair transmission efficiency and alter disease progression in the new host, resulting in a delicate trade-off between within-host virulence and between-host infectiousness. This trade-off is visible in the disparity in evolutionary rates at within-host and between-host levels, and preferential transmission of ancestral donor viruses. Understanding the impact of within-host evolution for epidemiological studies is essential for the design of preventive and therapeutic measures. Herein, we review recent theoretical and experimental work that generated new insights into the complex link between within-host evolution and between-host fitness, revealing temporal and selective processes underlying the structure and dynamics of HIV-1 transmission., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Resistance to antiretroviral therapy (ART) threatens the efficacy of human immunodeficiency virus type 1 (HIV-1) treatment. We present a review of knowledge gaps in the science and technologies of acquired HIV-1 drug resistance (HIVDR) in an effort to facilitate research, scientific exchange, and progress in clinical management. The expert authorship of this review convened to identify data gaps that exist in the field of HIVDR and discuss their clinical implications. A subsequent literature review of trials and current practices was carried out to provide supporting evidence. Several gaps were identified across HIVDR science and technology. A summary of the major gaps is presented, with an expert discussion of their implications within the context of the wider field. Crucial to optimizing the use of ART will be improved understanding of protease inhibitors and, in particular, integrase strand transfer inhibitors (INSTI) in the context of HIVDR. Limited experience with INSTI represents an important knowledge gap in HIV resistance science. Utilizing such knowledge in a clinical setting relies on accurate testing and analysis of resistance-associated mutations. As next-generation sequencing becomes more widely available, a gap in the interpretation of data is the lack of a defined, clinically relevant threshold of minority variants. Further research will provide evidence on where such thresholds lie and how they can be most effectively applied. Expert discussion identified a series of gaps in our knowledge of HIVDR. Addressing prefsuch gaps through further research and characterization will facilitate the optimal use of ART therapies and technologies.

This article is the second of a two-part review aiming to identify gaps in the knowledge and management of human immunodeficiency virus type 1 drug resistance (HIVDR) from global and regional perspectives. Here, we examine the policy and programmatic gaps in HIVDR surveillance, the affected populations and settings, and implications for clinical practice. The expert authorship of this review convened to identify gaps in HIVDR surveillance, with a particular focus on specific regional variations within and between Europe and Asia, to highlight directions for research and implementation. Further, evidence was gathered from a review of published studies, guidelines, and current practices. This review found that despite recent progress in the development, harmonization, and implementation of guidelines on HIVDR reporting and surveillance, programmatic, and policy gaps reflect the regional variability in HIV epidemics, clinical practice, and resources. The need for representative surveillance was identified as a key gap that has the potential to inform management policies. Monitoring must keep up with the evolution of transmission routes to adapt appropriately, and this will be further impacted by migration from areas with increasing levels of resistance. Analysis of the latest clinical data, regional practice, policy, and guidelines has identified a number of gaps in HIVDR population monitoring and surveillance. More efforts are needed to align surveillance platforms with harm reduction and patient education, particularly in vulnerable subgroups. Addressing these gaps will facilitate research into and progress in the management of HIV across a wide range of health-care settings.

Background: Separate transmission networks for human immunodeficiency virus (HIV) coexist. Molecular typing of viral genomes can provide insight in HIV transmission routes in donors for whom risk behavior-based donor selection failed., Study Design and Methods: This study includes all HIV-infected Dutch and Flemish donors in the period 2005 to 2014 (n = 55). Part of the HIV polymerase (pol) gene was amplified, sequenced, and compared with more than 10,000 HIV strains obtained from HIV-infected Dutch and Flemish patients. The most likely transmission route was determined based on HIV phylogeny and the donor's self-reported risk behavior during the exit interview., Results: HIV-infected donors were predominantly male (69%), were repeat donors (73%), were born in the Netherlands or Belgium (95%), and harbored HIV Subtype B (68%). Seventy-five percent of HIV-infected male donors were part of robust phylogenetic clusters linked to male-to-male sex, while only 24% of HIV-infected male donors reported male-to-male sex during posttest counseling. Sex between men and women accounted for 13% of HIV infections in male donors and 93% of HIV infections in female donors based on phylogenetic analysis. Only 40% of HIV-infected female donors had HIV Subtype B; 65% of female donors reported a foreign partner and indeed HIV sequences interspersed with sequences from HIV-endemic areas abroad, in particular sub-Saharan Africa., Conclusion: HIV typing helps to understand HIV transmission routes in donor populations. We found substantial underreporting of male-to-male sex among HIV-infected male donors. Donor education on HIV risk factors and the danger of window-period donations and a donor environment that encourages frank disclosure of sexual behavior will contribute to a decrease of HIV-infected donors., (© 2017 AABB.)

Objective: HIV-1 epidemics among MSM remain unchecked despite advances in treatment and prevention paradigms. This study combined viral phylogenetic and behavioural risk data to better understand underlying factors governing the temporal growth of the HIV epidemic among MSM in Quebec (2002-2015)., Methods: Phylogenetic analysis of pol sequences was used to deduce HIV-1 transmission dynamics (cluster size, size distribution and growth rate) in first genotypes of treatment-naïve MSM (2002-2015, n = 3901). Low sequence diversity of first genotypes (0-0.44% mixed base calls) was used as an indication of early-stage infection. Behavioural risk data were obtained from the Montreal rapid testing site and primary HIV-1-infection cohorts., Results: Phylogenetic analyses uncovered high proportion of clustering of new MSM infections. Overall, 27, 45, 48, 53 and 57% of first genotypes within one (singleton, n = 1359), 2-4 (n = 692), 5-9 (n = 367), 10-19 (n = 405) and 20+ (n = 1277) cluster size groups were early infections (<0.44% diversity). Thirty viruses within large 20+ clusters disproportionately fuelled the epidemic, representing 13, 25 and 42% of infections, first genotyped in 2004-2007 (n = 1314), 2008-2011 (n = 1356) and 2012-2015 (n = 1033), respectively. Of note, 35, 21 and 14% of MSM belonging to 20+, 2-19 and one (singleton) cluster groups were under 30 years of age, respectively. Half of persons seen at the rapid testing site (2009-2011, n = 1781) were untested in the prior year. Poor testing propensity was associated with fewer reported partnerships., Conclusion: Addressing the heterogeneity in transmission dynamics among HIV-1-infected MSM populations may help guide testing, treatment and prevention strategies.

Background: Epidemic HIV-2 (groups A and B) emerged in humans circa 1930-40. Its closest ancestors are SIVsmm infecting sooty mangabeys from southwestern Côte d'Ivoire. The earliest large-scale serological surveys of HIV-2 in West Africa (1985-91) show a patchy spread. Côte d'Ivoire and Guinea-Bissau had the highest prevalence rates by then, and phylogeographical analysis suggests they were the earliest epicenters. Wars and parenteral transmission have been hypothesized to have promoted HIV-2 spread. Male circumcision (MC) is known to correlate negatively with HIV-1 prevalence in Africa, but studies examining this issue for HIV-2 are lacking., Methods: We reviewed published HIV-2 serosurveys for 30 cities of all West African countries and obtained credible estimates of real prevalence through Bayesian estimation. We estimated past MC rates of 218 West African ethnic groups, based on ethnographic literature and fieldwork. We collected demographic tables specifying the ethnic partition in cities. Uncertainty was incorporated by defining plausible ranges of parameters (e.g. timing of introduction, proportion circumcised). We generated 1,000 sets of past MC rates per city using Latin Hypercube Sampling with different parameter combinations, and explored the correlation between HIV-2 prevalence and estimated MC rate (both logit-transformed) in the 1,000 replicates., Results and Conclusions: Our survey reveals that, in the early 20th century, MC was far less common and geographically more variable than nowadays. HIV-2 prevalence in 1985-91 and MC rates in 1950 were negatively correlated (Spearman rho = -0.546, IQR: -0.553--0.546, p≤0.0021). Guinea-Bissau and Côte d'Ivoire cities had markedly lower MC rates. In addition, MC was uncommon in rural southwestern Côte d'Ivoire in 1930.The differential HIV-2 spread in West Africa correlates with different historical MC rates. We suggest HIV-2 only formed early substantial foci in cities with substantial uncircumcised populations. Lack of MC in rural areas exposed to bushmeat may have had a role in successful HIV-2 emergence., Competing Interests: The authors have declared that no competing interests exist.

Angola borders and has long-term links with Democratic Republic of Congo (DRC) as well as high levels of Human Immunodeficiency Virus (HIV) genetic diversity, indicating a potential role in the initial spread of the HIV-1 pandemic. Herein, we analyze 564 C2V3 and 354 pol publicly available sequences from DRC, Republic of Congo (RC) and Angola to better understand the initial spread of the virus in this region. Phylogeographic analyses were performed with the BEAST software. While our results pinpoint the origin of the pandemic to Kinshasa (DRC) around 1906, the introduction of HIV-1 to Angola could have occurred early between the 1910s and 1940s. Furthermore, most of the HIV-1 migrations out of Kinshasa were directed not only to Lubumbashi and Mbuji-Mayi (DRC), but also to Luanda and Brazzaville. Kinshasa census records corroborate these findings, indicating that the early exportation of the virus to Angola might be related to the high number of Angolans in Kinshasa at that time, originated mostly from the North of Angola. In summary, our results place Angola at the epicenter of the early HIV dissemination, together with DRC and RC., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Human immunodeficiency virus type 1 (HIV-1) was discovered in the early 1980s when the virus had already established a pandemic. For at least three decades the epidemic in the Western World has been dominated by subtype B infections, as part of a sub-epidemic that traveled from Africa through Haiti to United States. However, the pattern of the subsequent spread still remains poorly understood. Here we analyze a large dataset of globally representative HIV-1 subtype B strains to map their spread around the world over the last 50years and describe significant spread patterns. We show that subtype B travelled from North America to Western Europe in different occasions, while Central/Eastern Europe remained isolated for the most part of the early epidemic. Looking with more detail in European countries we see that the United Kingdom, France and Switzerland exchanged viral isolates with non-European countries than with European ones. The observed pattern is likely to mirror geopolitical landmarks in the post-World War II era, namely the rise and the fall of the Iron Curtain and the European colonialism. In conclusion, HIV-1 spread through specific migration routes which are consistent with geopolitical factors that affected human activities during the last 50years, such as migration, tourism and trade. Our findings support the argument that epidemic control policies should be global and incorporate political and socioeconomic factors., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: The latest nonnucleoside reverse transcriptase inhibitor (NNRTI) rilpivirine (RPV) is indicated for human immunodeficiency virus type-1 (HIV-1) patients initiating antiretroviral treatment, but the extent of genotypic RPV resistance in treatment-naive patients outside clinical trials is poorly defined., Study Design: This retrospective observational study of clinical data from Belgium and Portugal evaluates genotypic information from HIV-1 drug-naive patients obtained for the purpose of drug resistance testing. Rilpivirine resistance-associated mutations (RPV-RAMs) were defined based on clinical trials, phenotypic studies, and expert-based resistance algorithms. Viral susceptibility to RPV alone and to the single-tablet regimen was estimated using expert-based resistance algorithms., Results: In 4,631 HIV-1 treatment-naive patients infected with diverse HIV-1 subtypes, major RPV-RAMs were detected in 4.6%, while complete viral susceptibility to RPV was estimated in 95% of patients. Subtype C- and F1-infected patients displayed the highest levels of reduced viral susceptibility at baseline, respectively 13.2% and 9.3%, mainly due to subtype- and geographic-dependent occurrence of RPV-RAMs E138A and A98G as natural polymorphisms. Strikingly, a founder effect in Portugal resulted in a 138A prevalence of 13.2% in local subtype C-infected treatment-naive patients. The presence of transmitted drug resistance did not impact our estimates., Conclusion: RPV is the first HIV-1 inhibitor for which, in the absence of transmitted drug resistance, intermediate or high-level genotypic resistance can be detected in treatment-naive patients. The extent of RPV susceptibility in treatment-naive patients differs depending on the HIV-1 subtype and dynamics of local compartmentalized epidemics. The highest prevalence of reduced susceptibility was found to be 15.7% in Portuguese subtype C-infected treatment-naive patients. In this context, even in the absence of transmitted HIV-1 drug resistance (TDR), drug resistance testing at baseline should be considered extremely important before starting treatment with this NNRTI.

Background: Numerous studies have shown that baseline drug resistance patterns may influence the outcome of antiretroviral therapy. Therefore, guidelines recommend drug resistance testing to guide the choice of initial regimen. In addition to optimizing individual patient management, these baseline resistance data enable transmitted drug resistance (TDR) to be surveyed for public health purposes. The SPREAD program systematically collects data to gain insight into TDR occurring in Europe since 2001., Methods: Demographic, clinical, and virological data from 4140 antiretroviral-naive human immunodeficiency virus (HIV)-infected individuals from 26 countries who were newly diagnosed between 2008 and 2010 were analyzed. Evidence of TDR was defined using the WHO list for surveillance of drug resistance mutations. Prevalence of TDR was assessed over time by comparing the results to SPREAD data from 2002 to 2007. Baseline susceptibility to antiretroviral drugs was predicted using the Stanford HIVdb program version 7.0., Results: The overall prevalence of TDR did not change significantly over time and was 8.3% (95% confidence interval, 7.2%-9.5%) in 2008-2010. The most frequent indicators of TDR were nucleoside reverse transcriptase inhibitor (NRTI) mutations (4.5%), followed by nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations (2.9%) and protease inhibitor mutations (2.0%). Baseline mutations were most predictive of reduced susceptibility to initial NNRTI-based regimens: 4.5% and 6.5% of patient isolates were predicted to have resistance to regimens containing efavirenz or rilpivirine, respectively, independent of current NRTI backbones., Conclusions: Although TDR was highest for NRTIs, the impact of baseline drug resistance patterns on susceptibility was largest for NNRTIs. The prevalence of TDR assessed by epidemiological surveys does not clearly indicate to what degree susceptibility to different drug classes is affected., (© The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America.)

Genetic analyses play a central role in infectious disease research. Massively parallelized "mechanical cloning" and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure--from nucleic acid extraction to sequencing--should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.

Objectives: Surveillance drug resistance mutations (SDRMs) in drug-naive patients are typically used to survey HIV-1-transmitted drug resistance (TDR). We test here how SDRMs in patients failing treatment, the original source of TDR, contribute to assessing TDR, transmissibility and transmission source of SDRMs., Design: This is a retrospective observational study analyzing a Portuguese cohort of HIV-1-infected patients., Methods: The prevalence of SDRMs to protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) in drug-naive and treatment-failing patients was measured for 3554 HIV-1 subtype B patients. Transmission ratio (prevalence in drug-naive/prevalence in treatment-failing patients), average viral load and robust linear regression with outlier detection (prevalence in drug-naive versus in treatment-failing patients) were analyzed and used to interpret transmissibility., Results: Prevalence of SDRMs in drug-naive and treatment-failing patients were linearly correlated, but some SDRMs were classified as outliers - above (PRO: D30N, N88D/S, L90 M, RT: G190A/S/E) or below (RT: M184I/V) expectations. The normalized regression slope was 0.073 for protease inhibitors, 0.084 for NRTIs and 0.116 for NNRTIs. Differences between SDRMs transmission ratios were not associated with differences in viral loads., Conclusion: The significant linear correlation between prevalence of SDRMs in drug-naive and in treatment-failing patients indicates that the prevalence in treatment-failing patients can be useful to predict levels of TDR. The slope is a cohort-dependent estimate of rate of TDR per drug class and outlier detection reveals comparative persistence of SDRMs. Outlier SDRMs with higher transmissibility are more persistent and more likely to have been acquired from drug-naive patients. Those with lower transmissibility have faster reversion dynamics after transmission and are associated with acquisition from treatment-failing patients.

Objective: To determine how HIV-1 risk groups impact transmitted diversity and the tempo of viral evolution at a population scale., Methods: We investigated a set of previously described transmission chains (n = 70) using a population genetic approach, and tested whether the expected differences in proportions of multivariant transmissions are reflected by varying proportions of transmitted diversity between men having sex with men (MSM) and heterosexual (HET) subpopulations - the largest contributors to HIV spread. To assess evolutionary rate differences among the different risk groups, we compiled risk group datasets for subtypes A1, B and CRF01&#95;AE, and directly compared the absolute substitution rate and its synonymous and non-synonymous components., Results: There was sufficient demographic signal to inform the transmission model in Bayesian evolutionary analysis by sampling trees using env data to compare the transmission bottleneck size between the MSM and HET risk groups. We found no indications for a different proportion of transmitted genetic diversity at the population level between these groups. In the direct rate comparisons between the risk groups, however, we consistently recovered a higher evolutionary rate in the male-dominated risk group compared to the HET datasets., Conclusion: We find that the risk group composition affects the viral evolutionary rate and therefore potentially also the adaptation rate. In particular, risk group-specific sex ratios, and the variation in within-host evolutionary rates between men and women, impose evolutionary rate differences at the epidemic level, but we cannot exclude a role of varying transmission rates.

Background: Human immunodeficiency virus type 1 (HIV-1) subtype CRF01&#95;AE originated in Africa and then passed to Thailand, where it established a major epidemic. Despite the global presence of CRF01&#95;AE, little is known about its subsequent dispersal pattern., Methods: We assembled a global data set of 2736 CRF01&#95;AE sequences by pooling sequences from public databases and patient-cohort studies. We estimated viral dispersal patterns, using statistical phylogeographic analysis run over bootstrap trees estimated by the maximum likelihood method., Results: We show that Thailand has been the source of viral dispersal to most areas worldwide, including 17 of 20 sampled countries in Europe. Japan, Singapore, Vietnam, and other Asian countries have played a secondary role in the viral dissemination. In contrast, China and Taiwan have mainly imported strains from neighboring Asian countries, North America, and Africa without any significant viral exportation., Discussion: The central role of Thailand in the global spread of CRF01&#95;AE can be probably explained by the popularity of Thailand as a vacation destination characterized by sex tourism and by Thai emigration to the Western world. Our study highlights the unique case of CRF01&#95;AE, the only globally distributed non-B clade whose global dispersal did not originate in Africa., (© The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Rilpivirine is a second-generation nonnucleoside reverse-transcriptase inhibitor (NNRTI) currently indicated for first-line therapy, but its clinical benefit for HIV-1 infected patients failing first-generation NNRTIs is largely undefined. This study quantified the extent of genotypic rilpivirine resistance in viral isolates from 1212 patients upon failure of efavirenz- or nevirapine-containing antiretroviral treatment, of whom more than respectively 80% and 90% showed high-level genotypic resistance to the failing NNRTI. Of all study patients, 47% showed a rilpivirine resistance-associated mutation (RPV-RAM), whereas preserved residual rilpivirine activity was predicted in half of the patients by three genotypic drug resistance interpretation algorithms. An NNRTI-dependent impact on rilpivirine resistance was detected. Compared with the use of nevirapine, the use of efavirenz was associated with a 32% lower risk of having a RPV-RAM and a 50% lower risk of predicted reduced rilpivirine susceptibility. Most prevalent RPV-RAMs after nevirapine experience were Y181C and H221Y, whereas L100I+K103N, Y188L and K101E occurred most in efavirenz-experienced patients. Predicted rilpivirine activity was not affected by HIV-1 subtype, although frequency of individual mutations differed across subtypes. In conclusion, this genotypic resistance analysis strongly suggests that the latest NNRTI, rilpivirine, may retain activity in a large proportion of HIV-1 patients in whom resistance failed while they were on an efavirenz- or nevirapine-containing regimen, and may present an attractive option for second-line treatment given its good safety profile and dosing convenience. However, prospective clinical studies assessing the effectiveness of rilpivirine for NNRTI-experienced patients are warranted to validate knowledge derived from genotypic and phenotypic drug resistance studies., (Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Regional and subtype-specific mutational patterns of HIV-1 transmitted drug resistance (TDR) are essential for informing first-line antiretroviral (ARV) therapy guidelines and designing diagnostic assays for use in regions where standard genotypic resistance testing is not affordable. We sought to understand the molecular epidemiology of TDR and to identify the HIV-1 drug-resistance mutations responsible for TDR in different regions and virus subtypes., Methods and Findings: We reviewed all GenBank submissions of HIV-1 reverse transcriptase sequences with or without protease and identified 287 studies published between March 1, 2000, and December 31, 2013, with more than 25 recently or chronically infected ARV-naïve individuals. These studies comprised 50,870 individuals from 111 countries. Each set of study sequences was analyzed for phylogenetic clustering and the presence of 93 surveillance drug-resistance mutations (SDRMs). The median overall TDR prevalence in sub-Saharan Africa (SSA), south/southeast Asia (SSEA), upper-income Asian countries, Latin America/Caribbean, Europe, and North America was 2.8%, 2.9%, 5.6%, 7.6%, 9.4%, and 11.5%, respectively. In SSA, there was a yearly 1.09-fold (95% CI: 1.05-1.14) increase in odds of TDR since national ARV scale-up attributable to an increase in non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance. The odds of NNRTI-associated TDR also increased in Latin America/Caribbean (odds ratio [OR] = 1.16; 95% CI: 1.06-1.25), North America (OR = 1.19; 95% CI: 1.12-1.26), Europe (OR = 1.07; 95% CI: 1.01-1.13), and upper-income Asian countries (OR = 1.33; 95% CI: 1.12-1.55). In SSEA, there was no significant change in the odds of TDR since national ARV scale-up (OR = 0.97; 95% CI: 0.92-1.02). An analysis limited to sequences with mixtures at less than 0.5% of their nucleotide positions—a proxy for recent infection—yielded trends comparable to those obtained using the complete dataset. Four NNRTI SDRMs—K101E, K103N, Y181C, and G190A—accounted for >80% of NNRTI-associated TDR in all regions and subtypes. Sixteen nucleoside reverse transcriptase inhibitor (NRTI) SDRMs accounted for >69% of NRTI-associated TDR in all regions and subtypes. In SSA and SSEA, 89% of NNRTI SDRMs were associated with high-level resistance to nevirapine or efavirenz, whereas only 27% of NRTI SDRMs were associated with high-level resistance to zidovudine, lamivudine, tenofovir, or abacavir. Of 763 viruses with TDR in SSA and SSEA, 725 (95%) were genetically dissimilar; 38 (5%) formed 19 sequence pairs. Inherent limitations of this study are that some cohorts may not represent the broader regional population and that studies were heterogeneous with respect to duration of infection prior to sampling., Conclusions: Most TDR strains in SSA and SSEA arose independently, suggesting that ARV regimens with a high genetic barrier to resistance combined with improved patient adherence may mitigate TDR increases by reducing the generation of new ARV-resistant strains. A small number of NNRTI-resistance mutations were responsible for most cases of high-level resistance, suggesting that inexpensive point-mutation assays to detect these mutations may be useful for pre-therapy screening in regions with high levels of TDR. In the context of a public health approach to ARV therapy, a reliable point-of-care genotypic resistance test could identify which patients should receive standard first-line therapy and which should receive a protease-inhibitor-containing regimen.

Background: The HIV-1 epidemic in Slovenia, a small Central European country, has some characteristics that make it an ideal model to study HIV-1 transmission. The epidemic is predominantly affecting men who have sex with men infected with subtype B (89% of all patients), has a low prevalence (less than 1/1000) and is growing slowly. The aim of the present study was to analyze in detail the evolutionary history and the determinants of transmission., Methods: A total of 223 partial pol gene sequences from therapy naïve individuals were included, representing 52% of all patients newly diagnosed in 13 years (2000-2012) and analyzed together with genetically similar worldwide sequences, selected in a BLAST search., Results: Combined analysis (maximum likelihood and Bayesian) of HIV-1 transmission chains revealed 8 major clusters (n ≥ 10 patients), 1 group of 4 patients, 2 trios and 12 transmission pairs, thus leaving only 43 (19.3%) Slovenian patients infected with subtype B without a local epidemiological link, indicating a predominance of local transmission of HIV-1 infection. Bayesian analysis performed on a full set of sequences estimated several introductions of HIV-1 into Slovenia, with the most recent common ancestor (tMRCA) of the earliest Slovenian cluster dated to the late 1980s, although tMRCAs obtained from separate independent analysis of each cluster showed considerably more recent estimates. These findings indicate inconsistencies in molecular clock estimation, which we further explored. We hypothesize that these inconsistent dating estimates across the tree could be caused by an evolutionary rate acceleration of HIV-1 after entering the Slovenia epidemic that is not taken into account by the molecular clock model. It could be caused by a lower transmission rate in this setting, as demonstrated by the low epidemic growth rate estimated by Bayesian skyline plot analysis., Conclusions: HIV-1 subtype B was introduced into Slovenia at several time points from the late 80s onward. The majority of patients had a local transmission link, indicating a closed HIV community. The observed slower epidemic rate suggests that individuals with a long-lasting infection are the driving force of the epidemic in this region.

Background: The HIV pandemic is characterized by extensive genetic variability, which has challenged the development of HIV drugs and vaccines. Although HIV genomes have been classified into different types, groups, subtypes and recombinants, a comprehensive study that maps HIV genome-wide diversity at the population level is still lacking to date. This study aims to characterize HIV genomic diversity in large-scale sequence populations, and to identify driving factors that shape HIV genome diversity., Results: A total of 2996 full-length genomic sequences from 1705 patients infected with 16 major HIV groups, subtypes and circulating recombinant forms (CRFs) were analyzed along with structural, immunological and peptide inhibitor information. Average nucleotide diversity of HIV genomes was almost 50% between HIV-1 and HIV-2 types, 37.5% between HIV-1 groups, 14.7% between HIV-1 subtypes, 8.2% within individual HIV-1 subtypes and less than 1% within single patients. Along the HIV genome, diversity patterns and compositions of nucleotides and amino acids were highly similar across different groups, subtypes and CRFs. Current HIV-derived peptide inhibitors were predominantly derived from conserved, solvent accessible and intrinsically ordered structures in the HIV-1 subtype B genome. We identified these conserved regions in Capsid, Nucleocapsid, Protease, Integrase, Reverse transcriptase, Vpr and the GP41 N terminus as potential drug targets. In the analysis of factors that impact HIV-1 genomic diversity, we focused on protein multimerization, immunological constraints and HIV-human protein interactions. We found that amino acid diversity in monomeric proteins was higher than in multimeric proteins, and diversified positions were preferably located within human CD4 T cell and antibody epitopes. Moreover, intrinsic disorder regions in HIV-1 proteins coincided with high levels of amino acid diversity, facilitating a large number of interactions between HIV-1 and human proteins., Conclusions: This first large-scale analysis provided a detailed mapping of HIV genomic diversity and highlighted drug-target regions conserved across different groups, subtypes and CRFs. Our findings suggest that, in addition to the impact of protein multimerization and immune selective pressure on HIV-1 diversity, HIV-human protein interactions are facilitated by high variability within intrinsically disordered structures.

Background: Optimal adherence to antiretroviral therapy is critical to prevent HIV drug resistance (HIVDR) epidemic. The objective of the study was to investigate the best performing adherence assessment method for predicting virological failure in resource-limited settings (RLS)., Method: This study was a single-centre prospective cohort, enrolling 220 HIV-infected adult patients attending an HIV/AIDS Care and Treatment Centre in Dar es Salaam, Tanzania, in 2010. Pharmacy refill, self-report (via visual analog scale [VAS] and the Swiss HIV Cohort study-adherence questionnaire), pill count, and appointment keeping adherence measurements were taken. Univariate logistic regression (LR) was done to explore a cut-off that gives a better trade-off between sensitivity and specificity, and a higher area under the curve (AUC) based on receiver operating characteristic curve in predicting virological failure. Additionally, the adherence models were evaluated by fitting multivariate LR with stepwise functions, decision trees, and random forests models, assessing 10-fold multiple cross validation (MCV). Patient factors associated with virological failure were determined using LR., Results: Viral load measurements at baseline and one year after recruitment were available for 162 patients, of whom 55 (34%) had detectable viral load and 17 (10.5%) had immunological failure at one year after recruitment. The optimal cut-off points significantly predictive of virological failure were 95%, 80%, 95% and 90% for VAS, appointment keeping, pharmacy refill, and pill count adherence respectively. The AUC for these methods ranged from 0.52 to 0.61, with pharmacy refill giving the best performance at AUC 0.61. Multivariate logistic regression with boost stepwise MCV had higher AUC (0.64) compared to all univariate adherence models, except pharmacy refill adherence univariate model, which was comparable to the multivariate model (AUC = 0.64). Decision trees and random forests models were inferior to boost stepwise model. Pharmacy refill adherence (<95%) emerged as the best method for predicting virological failure. Other significant predictors in multivariate LR were having a baseline CD4 T lymphocytes count < 200 cells/μl, being unable to recall the diagnosis date, and a higher weight., Conclusion: Pharmacy refill has the potential to predict virological failure and to identify patients to be considered for viral load monitoring and HIVDR testing in RLS.

HIV-1 Gag amino acid substitutions associated with protease inhibitor (PI) treatment have mainly been reported in subtype B, while information on other subtypes is scarce. Using sequences from 11613 patients infected with different HIV-1 subtypes, we evaluated the prevalence of 93 Gag amino acid substitutions and their association with genotypic PI resistance. A significant association was found for 13 Gag substitutions, including A431V in both subtype B and CRF01&#95;AE. K415R in subtype C and S451G in subtype B were newly identified. Most PI-associated Gag substitutions are located in the flexible C-terminal domain, revealing the key role this region plays in PI resistance.

Introduction: In Tanzania, the follow-up on antiretroviral therapy (ART) response is based on clinical outcomes. We investigated virological response and ARV resistance mutations in relation to clinical response in ARV-treated patients., Methodology: A cross-sectional study of a cohort of 150 patients taking first-line ART in Dar-es-Salaam was conducted. Data were collected using standardized questionnaires and patients' blood samples. HIV viral load testing and genotyping was performed on all viremic samples. Statistical analyses compared clinical responders and non-responders., Results: The median time on ART was 20 months; 71 (47%) patients were ART clinical responders. Clinical non-responders were more likely to have started ART with advanced disease with significantly lower median percentage weight gain (6% versus 20%) with respect to pre-treatment levels. Sixty-one (86%) and 64 (81%) of clinical responders and non-responders, respectively, had undetectable viral loads. Genotyping was successful in 24 (96%) virologically failing patients, among whom 83% had resistance mutations; 67% had dual nucleoside reverse transcriptase inhibitor (NRTI)/non-NRTI (NNRTI) resistance mutations. Seventeen (71%) and 19 (79%) patients had NRTI and NNRTI resistance mutations, respectively, which were related to the ART in use, with no difference between clinical responders and non-responders. The most prevalent subtypes were A and C, found in 9 (38%) and 7 (29%) patients, respectively., Conclusions: The observed virological response was high and did not correlate with clinical response. The prevalence of ARV resistance mutations was high in viraemic patients and was related to the ARV prescribed. We recommend use of viral load monitoring during ART in Tanzania.

We aimed to study epidemic trends and predictors for transmitted drug resistance (TDR) in our region, its clinical impact and its association with transmission clusters. We included 778 patients from the AIDS Reference Center in Leuven (Belgium) diagnosed from 1998 to 2012. Resistance testing was performed using population-based sequencing and TDR was estimated using the WHO-2009 surveillance list. Phylogenetic analysis was performed using maximum likelihood and Bayesian techniques. The cohort was predominantly Belgian (58.4%), men who have sex with men (MSM) (42.8%), and chronically infected (86.5%). The overall TDR prevalence was 9.6% (95% confidence interval (CI): 7.7-11.9), 6.5% (CI: 5.0-8.5) for nucleoside reverse transcriptase inhibitors (NRTI), 2.2% (CI: 1.4-3.5) for non-NRTI (NNRTI), and 2.2% (CI: 1.4-3.5) for protease inhibitors. A significant parabolic trend of NNRTI-TDR was found (p = 0.019). Factors significantly associated with TDR in univariate analysis were male gender, Belgian origin, MSM, recent infection, transmission clusters and subtype B, while multivariate and Bayesian network analysis singled out subtype B as the most predictive factor of TDR. Subtype B was related with transmission clusters with TDR that included 42.6% of the TDR patients. Thanks to resistance testing, 83% of the patients with TDR who started therapy had undetectable viral load whereas half of the patients would likely have received a suboptimal therapy without this test. In conclusion, TDR remained stable and a NNRTI up-and-down trend was observed. While the presence of clusters with TDR is worrying, we could not identify an independent, non-sequence based predictor for TDR or transmission clusters with TDR that could help with guidelines or public health measures.

Background: In Europe, a continuous programme (SPREAD) has been in place for ten years to study transmission of drug resistant HIV. We analysed time trends of transmitted drug resistance mutations (TDRM) in relation to the risk behaviour reported., Methods: HIV-1 patients newly diagnosed in 27 countries from 2002 through 2007 were included. Inclusion was representative for risk group and geographical distribution in the participating countries in Europe. Trends over time were calculated by logistic regression., Results: From the 4317 patients included, the majority was men-having-sex-with-men -MSM (2084, 48%), followed by heterosexuals (1501, 35%) and injection drug users (IDU) (355, 8%). MSM were more often from Western Europe origin, infected with subtype B virus, and recently infected (<1 year) (p<0.001). The prevalence of TDRM was highest in MSM (prevalence of 11.1%), followed by heterosexuals (6.6%) and IDU (5.1%, p<0.001). TDRM was predominantly ascribed to nucleoside reverse transcriptase inhibitors (NRTI) with a prevalence of 6.6% in MSM, 3.3% in heterosexuals and 2.0% in IDU (p = 0.001). A significant increase in resistance to non- nucleoside reverse transcriptase inhibitors (NNRTIs) and a decrease in resistance to protease inhibitors was observed in MSM (p = 0.008 and p = 0.006, respectively), but not in heterosexual patients (p = 0.68 and p = 0.14, respectively)., Conclusions: MSM showed to have significantly higher TDRM prevalence compared to heterosexuals and IDU. The increasing NNRTI resistance in MSM is likely to negatively influence the therapy response of first-line therapy, as most include NNRTI drugs.

Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the 'store and retrieve' hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation.

Background: Superinfection with drug resistant HIV strains could potentially contribute to compromised therapy in patients initially infected with drug-sensitive virus and receiving antiretroviral therapy. To investigate the importance of this potential route to drug resistance, we developed a bioinformatics pipeline to detect superinfection from routinely collected genotyping data, and assessed whether superinfection contributed to increased drug resistance in a large European cohort of viremic, drug treated patients., Methods: We used sequence data from routine genotypic tests spanning the protease and partial reverse transcriptase regions in the Virolab and EuResist databases that collated data from five European countries. Superinfection was indicated when sequences of a patient failed to cluster together in phylogenetic trees constructed with selected sets of control sequences. A subset of the indicated cases was validated by re-sequencing pol and env regions from the original samples., Results: 4425 patients had at least two sequences in the database, with a total of 13816 distinct sequence entries (of which 86% belonged to subtype B). We identified 107 patients with phylogenetic evidence for superinfection. In 14 of these cases, we analyzed newly amplified sequences from the original samples for validation purposes: only 2 cases were verified as superinfections in the repeated analyses, the other 12 cases turned out to involve sample or sequence misidentification. Resistance to drugs used at the time of strain replacement did not change in these two patients. A third case could not be validated by re-sequencing, but was supported as superinfection by an intermediate sequence with high degenerate base pair count within the time frame of strain switching. Drug resistance increased in this single patient., Conclusions: Routine genotyping data are informative for the detection of HIV superinfection; however, most cases of non-monophyletic clustering in patient phylogenies arise from sample or sequence mix-up rather than from superinfection, which emphasizes the importance of validation. Non-transient superinfection was rare in our mainly treatment experienced cohort, and we found a single case of possible transmitted drug resistance by this route. We therefore conclude that in our large cohort, superinfection with drug resistant HIV did not compromise the efficiency of antiretroviral treatment.

Background: HIV-1 replication can be successfully blocked by targeting gag gene products, offering a promising strategy for new drug classes that complement current HIV-1 treatment options. However, naturally occurring polymorphisms at drug binding sites can severely compromise HIV-1 susceptibility to gag inhibitors in clinical and experimental studies. Therefore, a comprehensive understanding of gag natural diversity is needed., Findings: We analyzed the degree of functional conservation in 10862 full-length gag sequences across 8 major HIV-1 subtypes and identified the impact of natural variation on known drug binding positions targeted by more than 20 gag inhibitors published to date. Complete conservation across all subtypes was detected in 147 (29%) out of 500 gag positions, with the highest level of conservation observed in capsid protein. Almost half (41%) of the 136 known drug binding positions were completely conserved, but all inhibitors were confronted with naturally occurring polymorphisms in their binding sites, some of which correlated with HIV-1 subtype. Integration of sequence and structural information revealed one drug binding pocket with minimal genetic variability, which is situated at the N-terminal domain of the capsid protein., Conclusions: This first large-scale analysis of full-length HIV-1 gag provided a detailed mapping of natural diversity across major subtypes and highlighted the considerable variation in current drug binding sites. Our results contribute to the optimization of gag inhibitors in rational drug design, given that drug binding sites should ideally be conserved across all HIV-1 subtypes.

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations. Epistatic interactions were learned from three different cross-sectional BNs, trained with sequence from patients experienced with indinavir (BNT), all protease inhibitors (PIs) (BNP) or all PI except indinavir (BND). Scaling the fitness landscape was done using cross-sectional data from drug naïve and indinavir experienced patients (Fcross using BNT) and using longitudinal sequences from patients failing indinavir (FlongT using BNT, FlongP using BNP, FlongD using BND). Evaluation to predict the failing sequence and therapy outcome was performed on independent sequences of patients on indinavir. Parameters included estimated fitness (LogF), the number of generations (GF) or mutations (MF) to reach the fitness threshold (average fitness when a major resistance mutation appeared), the number of generations (GR) or mutations (MR) to reach a major resistance mutation and compared to genotypic susceptibility score (GSS) from Rega and HIVdb algorithms. In pairwise FL comparisons we found significant correlation between fitness values for individual sequences, and this correlation improved after correcting for the subtype. Furthermore, FLs could predict the failing sequence under indinavir-containing combinations. At 12 and 48 weeks, all parameters from all FLs and indinavir GSS (both for Rega and HIVdb) were predictive of therapy outcome, except MR for FlongT and FlongP. The fitness landscapes have similar predictive power for treatment response under indinavir-containing regimen as standard rules-based algorithms, and additionally allow predicting genetic evolution under indinavir selective pressure., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Background: To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3)., Methodology: HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region., Results: The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01&#95;AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02&#95;AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01&#95;AE and CRF02&#95;AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%)., Conclusions: REGAv3 had an improved performance for subtype B and CRF02&#95;AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences., (Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: This study evaluates the impact of specific HIV-1 protease-compensatory mutations (wild-type amino acids in non-B subtypes) on virological response to a first-line lopinavir/ritonavir-containing regimen in an HIV-1 subtype B-infected population., Patients and Methods: The prevalence of protease-compensatory mutations from 1997 to 2011 was calculated in 3063 drug-naive HIV-1 B-infected patients. The role of these mutations on virological outcome is estimated in a subgroup of 201 patients starting their first lopinavir/ritonavir-containing regimen by covariation and docking analyses., Results: The number of HIV-1 B-infected patients with at least one protease-compensatory mutation increased over time (from 86.4% prior to 2001 to 92.6% after 2009, P = 0.02). Analysing 201 patients starting first-line lopinavir/ritonavir, the median time to virological failure was shorter in patients with at least one protease-compensatory mutation than in patients with no protease-compensatory mutations. By covariation and docking analyses, specific mutations were found to affect lopinavir affinity for HIV-1 protease and to impact virological failure. Specifically, the L10V + I13V + L63P + I93L cluster, related to fast virological failure, correlated with a decreased drug affinity for the enzyme in comparison with wild-type (ΔGmut = -30.0 kcal/mol versus ΔGwt = -42.3 kcal/mol)., Conclusions: Our study shows an increased prevalence of specific protease-compensatory mutations in an HIV-1 B-infected population and confirms that their copresence can affect the virological outcome in patients starting a lopinavir/ritonavir-containing regimen.

In Cuba, antiretroviral therapy rollout started in 2001 and antiretroviral therapy coverage has reached almost 40% since then. The objectives of this study were therefore to analyze subtype distribution, and level and patterns of drug resistance in therapy-naive HIV-1 patients. Four hundred and one plasma samples were collected from HIV-1 therapy-naive patients in 2003 and in 2007-2011. HIV-1 drug resistance genotyping was performed in the pol gene and drug resistance was interpreted according to the WHO surveillance drug-resistance mutations list, version 2009. Potential impact on first-line therapy response was estimated using genotypic drug resistance interpretation systems HIVdb version 6.2.0 and Rega version 8.0.2. Phylogenetic analysis was performed using Neighbor-Joining. The majority of patients were male (84.5%), men who have sex with men (78.1%) and from Havana City (73.6%). Subtype B was the most prevalent subtype (39.3%), followed by CRF20-23-24&#95;BG (19.5%), CRF19&#95;cpx (18.0%) and CRF18&#95;cpx (10.3%). Overall, 29 patients (7.2%) had evidence of drug resistance, with 4.0% (CI 1.6%-4.8%) in 2003 versus 12.5% (CI 7.2%-14.5%) in 2007-2011. A significant increase in drug resistance was observed in recently HIV-1 diagnosed patients, i.e. 14.8% (CI 8.0%-17.0%) in 2007-2011 versus 3.8% (CI 0.9%-4.7%) in 2003 (OR 3.9, CI 1.5-17.0, p=0.02). The majority of drug resistance was restricted to a single drug class (75.8%), with 55.2% patients displaying nucleoside reverse transcriptase inhibitor (NRTI), 10.3% non-NRTI (NNRTI) and 10.3% protease inhibitor (PI) resistance mutations. Respectively, 20.7% and 3.4% patients carried viruses containing drug resistance mutations against NRTI+NNRTI and NRTI+NNRTI+PI. The first cases of resistance towards other drug classes than NRTI were only detected from 2008 onwards. The most frequent resistance mutations were T215Y/rev (44.8%), M41L (31.0%), M184V (17.2%) and K103N (13.8%). The median genotypic susceptibility score for the commonly prescribed first-line therapies was 2.5. This analysis emphasizes the need to perform additional surveillance studies to accurately assess the level of transmitted drug resistance in Cuba, as the extent of drug resistance might jeopardize effectiveness of first-line regimens prescribed in Cuba and might necessitate the implementation of baseline drug resistance testing., (Copyright © 2013 Elsevier B.V. All rights reserved.)