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Europe is currently observing a significant rise in non-B subtypes. Consequently, the effect of genetic variability on therapy response or genotypic resistance interpretation algorithms is an emerging concern. The purpose of this study is to investigate the amino acid substitutions selected under drug pressure in the protease of human immunodeficiency virus type 1 (HIV-1) subtypes B and G, and determine if there are any significant differences. We investigated therapy-related and subtype-related substitutions in the protease, considering subtype, overall protease inhibitor treatment and individual drug exposure. Many mutations were significantly related to protease inhibitor (PI) therapy, with mutations exclusive to subtype B or subtype G. Some mutations are at positions related to resistance in both subtypes, but the amino acid substitution is different. Other mutations were significantly associated with subtype and PI selective pressure (p<0.05), pointing towards a differential selective pressure in both subtypes. We confirmed previous reports on the subtype-dependent selection of D30N and 89I, and identified a new mutation with such differential selective pressure: 37D was preferentially selected by lopinavir in subtype B. Other novel mutations found under therapy pressure were 13A, 35N, K55R, I66F, I72L/T, T74S, 82M and 89I/V. Our study indicates that even though in general, drug selective pressure and resistance pathways are relatively similar between subtypes B and G, some differences do occur, leading to subtype-dependent substitutions., (2009 Elsevier B.V. All rights reserved.)

The SPREAD Programme investigated prospectively the time trend from September 2002 through December 2005 of transmitted drug resistance (TDR) among 2793 patients in 20 European countries and in Israel with newly diagnosed human immunodeficiency virus type 1 (HIV-1) infection. The overall prevalence of TDR was 8.4% (225 of 2687 patients; 95% confidence interval [CI], 7.4%-9.5%), the prevalence of nucleoside reverse-transcriptase inhibitor (NRTI) resistance was 4.7% (125 of 2687 patients; 95% CI, 3.9%-5.5%), the prevalence of nonucleoside reverse-transcriptase inhibitor (NNRTI) resistance was 2.3% (62 of 2687 patients; 95% CI, 1.8%-2.9%), and the prevalence of protease inhibitor (PI) resistance was 2.9% (79 of 2687 patients; 95% CI, 2.4%-3.6%). There was no time trend in the overall TDR or in NRTI resistance, but there was a statistically significant decrease in PI resistance (P = .04) and in NNRTI resistance after an initial increase (P = .02). We found that TDR appears to be stabilizing in Europe, consistent with recent reports of decreasing drug resistance and improved viral suppression in patients treated for HIV-1 infection.

Objectives: HIV-1 group M is classified into nine different subtypes. Most antiretroviral (ARV) drugs have been developed for subtype B, and the response of non-B subtypes in terms of susceptibility and the acquisition of drug resistance when facing those drugs is largely unknown. In this study, we aimed to address differences in the impact of protease inhibitor (PI)-selected mutations on subtypes B and G., Patients and Methods: ARV-treated, HIV-positive patients regularly monitored at the Hospital de Egas Moniz, in Lisbon, Portugal, were examined for the presence of PI-associated primary mutations (301 subtype B and 184 subtype G), and for the selection of those mutations over the time of PI exposure. Forty-three subtype G patients were phenotyped for susceptibility to all available PIs through VIRCO's Antivirogram, and compared with a similar dataset of subtype B patients., Results: Mutation I54V/L was selected by nelfinavir in subtype G isolates, a mutation not previously described for this drug in subtype B. L90M was associated with a lower reduction in the susceptibility of subtype G to nelfinavir when compared with subtype B, and with no reduced susceptibility to saquinavir. This was compensated for by the acquisition of M89I in subtype G. L90M did not reduce the susceptibility of subtype G to saquinavir, in contrast to subtype B. Likewise, the pattern I54V/L-L90M did not reduce the susceptibility of subtype G to indinavir and saquinavir. Indinavir-associated mutations M46I/L, I84V and V82A/F/T developed earlier in subtype B across the time of exposure to that drug when compared with subtype G counterparts., Conclusions: Our results provide proof of principle and support the growing evidence that subtype-specific responses to ARVs exist. Data presented here highlight inconsistencies in current genotyping interpretation algorithms inadequately applied to all HIV-1 subtypes.

Programs that monitor local, national, and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programs. To accurately compare transmitted drug resistance rates across geographic regions and times, the World Health Organization has recommended the adoption of a consensus genotypic definition of transmitted HIV-1 drug resistance. In January 2007, we outlined criteria for developing a list of mutations for drug-resistance surveillance and compiled a list of 80 RT and protease mutations meeting these criteria (surveillance drug resistance mutations; SDRMs). Since January 2007, several new drugs have been approved and several new drug-resistance mutations have been identified. In this paper, we follow the same procedures described previously to develop an updated list of SDRMs that are likely to be useful for ongoing and future studies of transmitted drug resistance. The updated SDRM list has 93 mutations including 34 NRTI-resistance mutations at 15 RT positions, 19 NNRTI-resistance mutations at 10 RT positions, and 40 PI-resistance mutations at 18 protease positions.

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.

Background: A method has been developed to estimate a fitness landscape experienced by HIV-1 under treatment selective pressure as a function of the genotypic sequence thereby also estimating the genetic barrier to resistance., Methods: We evaluated the performance of two estimated fitness landscapes (nelfinavir [NFV] and zidovudine [AZT] plus lamivudine [3TC]) to predict week 12 viral load (VL) change for 176 treatment change episodes (TCEs) and probability of week 48 virological failure for 90 TCEs, in treatment experienced patients starting these drugs in combination., Results: A higher genetic barrier for AZT plus 3TC, (quantified per additional mutation required to develop resistance against these drugs) was associated with a 0.54 (95% confidence interval [CI] 0.30-0.77) larger log10 VL reduction at 12 weeks (P < 0.0001) and a 0.39 (95%/ CI 0.23-0.66) lower odds of virological failure at 48 weeks (P = 0.0005), in analyses adjusting for the pre-TCE VL and the exact time-lag between the TCE and the date of determining response VL. The strength of these associations was comparable with those seen with expert interpretation systems (Rega, ANRS and HIVDB). A higher genetic barrier to NFV resistance was the only genotypic predictor that tended to be associated with a 0.19 (95% CI 0-0.39) higher log10 VL reduction at 12 weeks (P = 0.05) and a 0.63 (95% CI 0.36-1.09) lower odds of virological failure at 48 weeks ( P = 0.10) per additional mutation., Conclusions: These results suggest that an estimated genetic barrier derived from fitness landscapes may contribute to an improvement of predicted treatment outcome for NFV and this approach should be explored for other drugs.

Purpose of Review: This review summarizes our knowledge of HIV-1 subtype-related differences associated with antiretroviral drug resistance and its interpretation, and with clinical, immunological and virological therapy outcomes. It also addresses the problem that subtypes are only a crude classification of the genetic diversity relevant to these topics., Recent Findings: Subtype-related variability is responsible for differences in drug resistance. Baseline drug susceptibility and resistance pathways vary between subtypes; such variation is mainly related to differences in the prevalence of specific polymorphisms. The clinical impact of these findings is rather limited, but with the increasing genetic diversity of HIV-1, they have the potential to impact the accuracy of the 'algorithm' concept for genotypic drug resistance test interpretation negatively., Summary: Severe limitations exist in the data describing the association of HIV-1 subtypes with resistance and treatment outcomes, because most data are the result of retrospective observational studies. Even with these limitations, the knowledge gathered allows us to assume that differences in the short-term response to treatment in different subtypes should not greatly affect treatment strategies. As for the interpretation of genotypic resistance testing, new tools are needed, taking into account the entire genomic context and thus overcoming the problem of genetic diversity.

Objective: To compare baseline susceptibility to protease inhibitors among HIV-1 isolates of subtypes C, F, G and CRF02&#95;AG, and to identify polymorphisms that determine the differences in susceptibility., Methods: A total of 42 samples of drug-naive patients infected with subtypes G (n=19), CRF02&#95;AG (n = 10), F (n = 6) and C (n = 7) were phenotyped and genotyped with the Antivirogram and the ViroSeq 2.0 genotyping system, respectively. A Bayesian network approach was used for a preliminary analysis of the collected data and the dependencies indicated by the network were statistically confirmed., Results: CRF02&#95;AG samples were found to be more susceptible to nelfinavir and ritonavir than other subtypes. Hypersusceptibility to these drugs was associated with the 70R polymorphism. 37D/S/T was associated with reduced susceptibility to indinavir and 89M with reduced susceptibility to lopinavir. Susceptibility to tipranavir was the lowest among the subtype F samples and the highest for subtype G samples, with samples carrying 57R being more susceptible than samples carrying 57K., Conclusions: Our study suggests that there are baseline susceptibility differences between subtypes and these differences are due to naturally occurring polymorphisms in these subtypes. The predictive value for phenotype of these polymorphisms was even valid in subtypes where these polymorphisms are less prevalent. Taking into account such polymorphisms should improve current algorithms for interpretation of genotyping results in a subtype-independent way.

Objective: To investigate whether and how mutations at position 89 of HIV-1 protease were associated with protease inhibitor (PI) failure, and what is the impact of the HIV-1 subtype., Methods: In a database containing pol nucleotide sequences and treatment history, the correlation between PI experience and mutations at codon 89 was determined separately for subtype B and several non-B subtypes. A Bayesian network model was used to map the resistance pathways in which M89I/V is involved for subtype G. The phenotypic effect of M89I/V for several PIs was also measured., Results: The analysis showed that for the subtypes C, F and G in which the wild-type codon at 89 was M compared to L for subtype B, M89I/V was significantly more frequently observed in PI-treated patients displaying major resistance mutations to PIs than in drug-naive patients. M89I/V was strongly associated with PI resistance mutations at codons 71, 74 and 90. Phenotypically, M89I/V alone did not confer a reduced susceptibility to PIs. However, when combined with L90M, a significantly reduced susceptibility to nelfinavir was observed (P < 0.05) in comparison with strains with L90M alone., Conclusions: The results of the present study show that M89I/V is associated with PI experience in subtypes C, F and G but not in subtype B. M89I/V should be considered a secondary PI mutation with an important effect on nelfinavir susceptibility in the presence of L90M.