BackgroundThe genetic differences among HIV-1 subtypes may be critical to clinical management and drug resistance surveillance as antiretroviral treatment is expanded to regions of the world where diverse non-subtype-B viruses predominate.Methods and FindingsTo assess the impact of HIV-1 subtype and antiretroviral treatment on the distribution of mutations in protease and reverse transcriptase, a binomial response model using subtype and treatment as explanatory variables was used to analyze a large compiled dataset of non-subtype-B HIV-1 sequences. Non-subtype-B sequences from 3,686 persons with well characterized antiretroviral treatment histories were analyzed in comparison to subtype B sequences from 4,769 persons. The non-subtype-B sequences included 461 with subtype A, 1,185 with C, 331 with D, 245 with F, 293 with G, 513 with CRF01_AE, and 618 with CRF02_AG. Each of the 55 known subtype B drug-resistance mutations occurred in at least one non-B isolate, and 44 (80%) of these mutations were significantly associated with antiretroviral treatment in at least one non-B subtype. Conversely, of 67 mutations found to be associated with antiretroviral therapy in at least one non-B subtype, 61 were also associated with antiretroviral therapy in subtype B isolates.ConclusionGlobal surveillance and genotypic assessment of drug resistance should focus primarily on the known subtype B drug-resistance mutations.

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.

The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V ؉ 63P ؉ 36I/V for subtype C and 82I ؉ 63P ؉ 36I ؉ 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A ؉ 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R ؉ 115 M and 118I ؉ 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtypedependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype.Genotyping for the assessment of anti-human immunodeficiency virus (HIV) drug resistance is often used in the management of individual patient therapy. Currently, it is recommended in European as well as American guidelines (17,38). In several retrospective and prospective studies, genotyping proved beneficial in optimizing treatment for individual patients (5,10,16,23,25,31,37).Although genotyping is commonly used, there are still many uncertainties with respect to the value of genotype in the assignment of a new regimen. The current genotypic assays are not always able to report all drug resistance mutations among non-B subtypes (11,18,19,24). Regardless of subtype, genotyping is not sensitive to mutations that are present as a minor variant in the population (22,40). Genotyping results also differ depending on the laboratory where they are performed. Quality control studies indicate that mutations, even present as a pure variant, are often underestimated (32).However, separate from the quality and sensitivity issues, the interpretation of genotypic results is still not standardized.

Despite improvements in HIV treatment, the prevalence of multidrug resistance and full class resistance is still reported to be increasing. However, to investigate whether current treatment strategies are still selecting for multidrug and full class resistance, the incidence, instead of the prevalence, is more informative. Temporal trends in multidrug resistance (MDR defined as at most 1 drug fully susceptible) and full class resistance (FCR defined as no drug in this class fully susceptible) in Portugal based on 3394 viral isolates genotyped from 2000 to 2006 were examined using the Rega 6.4.1 interpretation system. From July 2001 to July 2006 there was a significant decreasing trend of MDR with 5.7%, 5.2%, 3.8%, 3.4% and 2.7% for the consecutive years (P = 0.003). Multivariate analysis showed that for every consecutive year the odds of having a new MDR case decreased with 20% (P = 0.003). Furthermore, a decline was observed for NRTI-and PI-FCR (both P < 0.001), whereas for NNRTI-FCR a parabolic trend over time was seen (P < 0.001), with a maximum incidence in 2003-'04. Similar trends were obtained when scoring resistance for only one drug within a class or by using another interpretation system. In conclusion, the incidence of multidrug and full class resistance is decreasing over time in Portugal, with the exception of NNRTI full class resistance which showed an initial rise, but subsequently also a decline. This is most probably reflecting the changing drug prescription, the increasing efficiency of HAART and the improved management of HIV drug resistance. This work was presented in part at

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