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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.

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: 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.

Background: One out of ten newly diagnosed patients in Europe was infected with a virus carrying a drug resistant mutation. We analysed the patterns over time for transmitted drug resistance mutations (TDRM) using data from the European Spread program., Methods: Clinical, epidemiological and virological data from 4317 patients newly diagnosed with HIV-1 infection between 2002 and 2007 were analysed. Patients were enrolled using a pre-defined sampling strategy., Results: The overall prevalence of TDRM in this period was 8.9% (95% CI: 8.1-9.8). Interestingly, significant changes over time in TDRM caused by the different drug classes were found. Whereas nucleoside resistance mutations remained constant at 5%, a significant decline in protease inhibitors resistance mutations was observed, from 3.9% in 2002 to 1.6% in 2007 (p = 0.001). In contrast, resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) doubled from 2.0% in 2002 to 4.1% in 2007 (p = 0.004) with 58% of viral strains carrying a K103N mutation. Phylogenetic analysis showed that these temporal changes could not be explained by large clusters of TDRM., Conclusion: During the years 2002 to 2007 transmitted resistance to NNRTI has doubled to 4% in Europe. The frequent use of NNRTI in first-line regimens and the clinical impact of NNRTI mutations warrants continued monitoring.

Objectives: Despite a decreasing mortality and morbidity in treated HIV-1 patients, highly active antiretroviral treatment (HAART) can still fail due to the development of drug resistance. Especially, multidrug-resistant viruses pose a threat to efficient therapy. We studied the changing prevalence of multidrug resistance (MDR) over time in a cohort of HIV-1-infected patients in Portugal., Patients and Methods: We used data of 8065 HIV-1-infected patients followed from July 2001 up to April 2012 in 22 hospitals located in Portugal. MDR at a specific date of sampling was defined as no more than one fully active drug (excluding integrase and entry inhibitors) at that time authorized by the Portuguese National Authority of Medicines and Health Products (INFARMED), as interpreted with the Rega algorithm version 8.0.2. A generalized linear mixed model was used to study the time trend of the prevalence of MDR., Results: We observed a statistically significant decrease in the prevalence of MDR over the last decade, from 6.9% (95% CI: 5.7-8.4) in 2001-03, 6.0% (95% CI: 4.9-7.2) in 2003-05, 3.7% (95% CI: 2.8-4.8) in 2005-07 and 1.6% (95% CI: 1.1-2.2) in 2007-09 down to 0.6% (95% CI: 0.3-0.9) in 2009-12 [OR=0.80 (95% CI: 0.75-0.86); P<0.001]. In July 2011 the last new case of MDR was seen., Conclusions: The prevalence of multidrug-resistant HIV-1 is decreasing over time in Portugal, reflecting the increasing efficiency of HAART and the availability of new drugs. Therefore, in designing a new drug, safety and practical aspects, e.g. less toxicity and ease of use, may need more attention than focusing mainly on efficacy against resistant strains.

Objectives: The use of tenofovir is highly associated with the emergence of mutation K65R, which confers broad resistance to nucleoside/nucleotide analogue reverse transcriptase inhibitors (NRTIs), especially when tenofovir is combined with other NRTIs also selecting for K65R. Although recent HIV-1 treatment guidelines discouraging these combinations resulted in reduced K65R selection with tenofovir, updated information on the impact of currently recommended regimens on the population selection rate of K65R is presently lacking., Methods: In this study, we evaluated changes over time in the selection rate of resistance mutation K65R in a large population of 2736 HIV-1-infected patients failing combination antiretroviral treatment between 2002 and 2010., Results: The K65R resistance mutation was detected in 144 patients, a prevalence of 5.3%. A large majority of observed K65R cases were explained by the use of tenofovir, reflecting its wide use in clinical practice. However, changing patterns over time in NRTIs accompanying tenofovir resulted in a persistent decreasing probability of K65R selection by tenofovir-based therapy. The currently recommended NRTI combination tenofovir/emtricitabine was associated with a low probability of K65R emergence. For any given dual NRTI combination including tenofovir, higher selection rates of K65R were consistently observed with a non-nucleoside reverse transcriptase inhibitor than with a protease inhibitor as the third agent., Discussion: Our finding of a stable time trend of K65R despite elevated use of tenofovir illustrates increased potency of current HIV-1 therapy including tenofovir.

Subtype-dependent selection of HIV-1 reverse transcriptase resistance mutation K65R was previously observed in cell culture and small clinical investigations. We compared K65R prevalence across subtypes A, B, C, F, G, and CRF02&#95;AG separately in a cohort of 3,076 patients on combination therapy including tenofovir. K65R selection was significantly higher in HIV-1 subtype C. This could not be explained by clinical and demographic factors in multivariate analysis, suggesting subtype sequence-specific K65R pathways.

Objectives: To investigate mutations selected in viruses from HIV-2-infected patients failing a highly active antiretroviral treatment (HAART) regimen including atazanavir/ritonavir., Methods: Twenty-eight HIV-2-infected patients previously exposed to atazanavir/ritonavir and failing therapy were studied. The protease (PR) gene was amplified and sequenced, and mutations emerging under atazanavir/ritonavir selective pressure were reported., Results: The I50L mutation emerged in 4 out of 28 HIV-2-infected patients failing a HAART regimen including atazanavir/ritonavir. Besides I50L, four PR mutations previously associated with protease inhibitor resistance (I54L, I64V, V71I and I82F) and six PR mutations of unknown impact (V10I, E37D, S43T, K45R, I75V and F85L) in HIV-2 were also identified in this small group of patients., Conclusions: Several mutations were associated with virological failure of a regimen including atazanavir/ritonavir in HIV-2-infected patients, including I50L for the first time. It should be included in HIV-2 algorithms for interpretation of genotypic resistance data, and taken into account when making therapeutic decisions for HIV-2-infected patients.

Background: The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission. While compensatory mutations increase fitness during treatment, their presence may also modulate viral fitness and virulence in absence of therapy and major resistance mutations. We previously designed a modeling technique that quantifies genotypic footprints of in vivo treatment selective pressure, including both drug resistance mutations and polymorphic compensatory mutations, through the quantitative description of a fitness landscape from virus genetic sequences., Results: Genotypic correlates of viral load and CD4 cell count were evaluated in subtype B sequences from recently diagnosed treatment-naive patients enrolled in the SPREAD programme. The association of surveillance drug resistance mutations, reported compensatory mutations and fitness estimated from drug selective pressure fitness landscapes with baseline viral load and CD4 cell count was evaluated using regression techniques. Protease genotypic variability estimated to increase fitness during treatment was associated with higher viral load and lower CD4 cell counts also in treatment-naive patients, which could primarily be attributed to well-known compensatory mutations at highly polymorphic positions. By contrast, treatment-related mutations in reverse transcriptase could not explain viral load or CD4 cell count variability., Conclusions: These results suggest that polymorphic compensatory mutations in protease, reported to be selected during treatment, may improve the replicative capacity of HIV-1 even in absence of drug selective pressure or major resistance mutations. The presence of this polymorphic variation may either reflect a history of drug selective pressure, i.e. transmission from a treated patient, or merely be a result of diversity in wild-type virus. Our findings suggest that transmitted drug resistance has the potential to contribute to faster disease progression in the newly infected host and to shape the HIV-1 epidemic at a population level.

Objectives: The purpose of this study was the qualitative and quantitative assessment of the in vitro effect of HIV-1 protease (PR) mutation 82M on replication capacity and susceptibility to the eight clinically available PR inhibitors (PIs)., Methods: The 82M substitution was introduced by site-directed mutagenesis in wild-type subtype B and G strains, as well as reverted back to wild-type in a therapy-failing strain. The recombinant viruses were evaluated for their replication capacity and susceptibility to PIs., Results: The single 82M mutation within a wild-type subtype B or G background did not result in drug resistance. However, the in vitro effect of single PR mutations on PI susceptibility is not always distinguishable from wild-type virus, and particular background mutations and polymorphisms are required to detect significant differences in the drug susceptibility profile. Consequently, reverting the 82M mutation back to wild-type (82I) in a subtype G isolate from a patient that failed therapy with multiple other PR mutations did result in significant increases in susceptibility towards indinavir and lopinavir and minor increases in susceptibility towards amprenavir and atazanavir. The presence of the 82M mutation also slightly decreased viral replication, whether it was in the genetic background of subtype B or subtype G., Conclusions: Our results suggest that 82M has an impact on PI susceptibility and that this effect is not due to a compensatory effect on the replication capacity. Because 82M is not observed as a polymorphism in any subtype, these observations support the inclusion of 82M in drug resistance interpretation systems and PI mutation lists.

HIV-2 is responsible for a limited epidemic in West Africa. Around 20% of all infected patients will progress to AIDS, and will need antiretroviral therapy. Unfortunately, antiretrovirals were developed to suppress HIV-1 replication; not all of them are active against HIV-2, e.g. all nonnucleoside reverse transcriptase inhibitors or fusion inhibitors. Moreover, only three protease inhibitors have the same activity in HIV-1 and HIV-2: lopinavir, saquinavir and darunavir. Even if all nucleoside and nucleotide reverse transcriptase inhibitors appear to be equally efficient against HIV-2, different resistance pathways and an increased facility of resistance selection make their use much more difficult than in HIV-1. Integrase inhibitors have a potent inhibitory effect on HIV-2 replication, but questions about the best timing for their use remain unanswered, as well as those regarding the use of entry inhibitors in this setting. The lack of reliable monitoring tools adds to the difficulty of treating HIV-2-infected patients, mostly because the viral load is not as useful as it is in HIV-1, and the incomplete knowledge about resistance pathways limits the clinical usefulness of resistance testing. With all these limitations, HIV-2 treatment remains a challenge. Further research is urgently needed, since antiretroviral therapy is now becoming available in countries where the HIV-2 prevalence is significant. The need for appropriate guidelines for HIV-2 treatment has become an emergency., (Copyright © 2012 S. Karger AG, Basel.)

HIV drug resistance is a multifactorial phenomenon and constitutes a major concern as it results in therapy failure. The aim of this study was to assess the impact of an amino acid insertion identified at position 33 of the protease gene, derived from samples from three patients under lopinavir therapy, on viral fitness and protease inhibitor (PI) resistance. Successive samples were available from one of the patients for genotypic and phenotypic testing in order to investigate the role of this insertion. The patient had been pretreated with various antiretroviral drugs and showed poor virological response from the point of the acquisition of the mutation onward. The insertion was acquired in the context of a number of other PI mutations and was stable following acquisition. Phenotypic testing revealed reduced susceptibility to various PIs and a reduction of the replicative capacity (RC) of the virus. In the presence of the insertion alone, a decrease of the RC was observed, which seemed to be compensated by the presence of other mutations. The L33ins might have a potential role in PI resistance pathways but further investigation in a larger number of clinical samples is required in order to elucidate this resistance mechanism.

The European HIV Drug Resistance Guidelines Panel, established to make recommendations to clinicians and virologists, felt that sufficient new information has become available to warrant an update of its recommendations, explained in both pocket guidelines and this full paper. The Panel makes the following recommendations concerning the indications for resistance testing: for HIV-1 (i) test earliest sample for protease and reverse transcriptase drug resistance in drug-naive patients with acute or chronic infection; (ii) test protease and reverse transcriptase drug resistance at virologic failure, and other drug targets (integrase and envelope) if such drugs were part of the failing regimen; (iii) consider testing for CCR5 tropism at virologic failure or when a change of therapy has to be made in absence of detectable viral load, and in the latter case test DNA or last detectable plasma RNA; (iv) consider testing earliest detectable plasma RNA when a successful nonnucleoside reverse transcriptase inhibitor-containing therapy was inappropriately interrupted; (v) genotype source patient when postexposure prophylaxis is considered; for HIV-2, (vi) consider resistance testing where treatment change is needed after treatment failure. The Panel recommends genotyping in most situations, using updated and clinically evaluated interpretation systems. It is mandatory that laboratories performing HIV resistance tests take part regularly in external quality assurance programs, and that they consider storing samples in situations where resistance testing cannot be performed as recommended. Similarly, it is necessary that HIV clinicians and virologists take part in continuous education and discuss problematic clinical cases. Indeed, resistance test results should be used in the context of all other clinically relevant information for predicting therapy response.

A better understanding of human immunodeficiency virus type 1 drug-resistance evolution under the selective pressure of combination treatment is important for the design of long-term effective treatment strategies. We applied Bayesian network learning to sequences from patients treated with the reverse transcriptase inhibitor combination of zidovudine (AZT) and lamivudine (3TC) to identify the role of many treatment-selected mutations in the development of resistance. Based on the Bayesian network structure, an in vivo fitness landscape was built, reflecting the necessary selective pressure under treatment, to evolve naive sequences to sequences obtained from patients treated with the combination. This landscape, combined with an evolutionary model, was used to predict resistance evolution in longitudinal sequence pairs. In our analysis, mutations 41L, 70R, 184V and 215F/Y were identified as major resistance mutations to the combination of AZT and 3TC, as they were associated directly with treatment experience. The network also suggested a possible role in resistance development for a number of novel mutations. Estimated fitness, using the landscape, correlated significantly with in vitro resistance phenotype in genotype-phenotype pairs (R(2)=0.70). Variation in predicted evolution under selective pressure correlated significantly with observed in vivo evolution during AZT plus 3CT treatment. In conclusion, we confirmed current knowledge on resistance development to the combination of AZT and 3CT, but additional novel mutations were identified. Moreover, a model to predict resistance evolution during AZT and 3CT treatment has been built and validated.

Objective: To clarify the role of novel mutations selected by treatment with efavirenz or nevirapine, and investigate the influence of HIV-1 subtype on nonnucleoside reverse transcriptase inhibitor (nNRTI) resistance pathways., Design: By finding direct dependencies between treatment-selected mutations, the involvement of these mutations as minor or major resistance mutations against efavirenz, nevirapine, or coadministrated nucleoside analogue reverse transcriptase inhibitors (NRTIs) is hypothesized. In addition, direct dependencies were investigated between treatment-selected mutations and polymorphisms, some of which are linked with subtype, and between NRTI and nNRTI resistance pathways., Methods: Sequences from a large collaborative database of various subtypes were jointly analyzed to detect mutations selected by treatment. Using Bayesian network learning, direct dependencies were investigated between treatment-selected mutations, NRTI and nNRTI treatment history, and known NRTI resistance mutations., Results: Several novel minor resistance mutations were found: 28K and 196R (for resistance against efavirenz), 101H and 138Q (nevirapine), and 31L (lamivudine). Robust interactions between NRTI mutations (65R, 74V, 75I/M, and 184V) and nNRTI resistance mutations (100I, 181C, 190E and 230L) may affect resistance development to particular treatment combinations. For example, an interaction between 65R and 181C predicts that the nevirapine and tenofovir and lamivudine/emtricitabine combination should be more prone to failure than efavirenz and tenofovir and lamivudine/emtricitabine., Conclusion: Bayesian networks were helpful in untangling the selection of mutations by NRTI versus nNRTI treatment, and in discovering interactions between resistance mutations within and between these two classes of inhibitors.