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Differences in resistance mutations among HIV-1 non-subtype B infections: a systematic review of evidence (1996-2008).

ABSTRACT: Ninety percent of HIV-1-infected people worldwide harbour non-subtype B variants of HIV-1. Yet knowledge of resistance mutations in non-B HIV-1 and their clinical relevance is limited. Although a few reviews, editorials and perspectives have been published alluding to this lack of data among non-B subtypes, no systematic review has been performed to date.With this in mind, we conducted a systematic review (1996-2008) of all published studies performed on the basis of non-subtype B HIV-1 infections treated with antiretroviral drugs that reported genotype resistance tests. Using an established search string, 50 studies were deemed relevant for this review.These studies reported genotyping data from non-B HIV-1 infections that had been treated with either reverse transcriptase inhibitors or protease inhibitors. While most major resistance mutations in subtype B were also found in non-B subtypes, a few novel mutations in non-B subtypes were recognized. The main differences are reflected in the discoveries that: (i) the non-nucleoside reverse transcriptase inhibitor resistance mutation, V106M, has been seen in subtype C and CRF01_AE, but not in subtype B, (ii) the protease inhibitor mutations L89I/V have been reported in C, F and G subtypes, but not in B, (iii) a nelfinavir selected non-D30N containing pathway predominated in CRF01_AE and CRF02_AG, while the emergence of D30N is favoured in subtypes B and D, (iv) studies on thymidine analog-treated subtype C infections from South Africa, Botswana and Malawi have reported a higher frequency of the K65R resistance mutation than that typically seen with subtype B.Additionally, some substitutions that seem to impact non-B viruses differentially are: reverse transcriptase mutations G196E, A98G/S, and V75M; and protease mutations M89I/V and I93L.Polymorphisms that were common in non-B subtypes and that may contribute to resistance tended to persist or become more frequent after drug exposure. Some, but not all, are recognized as minor resistance mutations in B subtypes. These observed differences in resistance pathways may impact cross-resistance and the selection of second-line regimens with protease inhibitors. Attention to newer drug combinations, as well as baseline genotyping of non-B isolates, in well-designed longitudinal studies with long duration of follow up are needed.

SUBMITTER: Martinez-Cajas JL

PROVIDER: S-EPMC2713201 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Differences in resistance mutations among HIV-1 non-subtype B infections: a systematic review of evidence (1996-2008).

Martinez-Cajas Jorge L JL Pai Nitika P NP Klein Marina B MB Wainberg Mark A MA

Journal of the International AIDS Society 20090630

Ninety percent of HIV-1-infected people worldwide harbour non-subtype B variants of HIV-1. Yet knowledge of resistance mutations in non-B HIV-1 and their clinical relevance is limited. Although a few reviews, editorials and perspectives have been published alluding to this lack of data among non-B subtypes, no systematic review has been performed to date.With this in mind, we conducted a systematic review (1996-2008) of all published studies performed on the basis of non-subtype B HIV-1 infectio ...[more]

PMID: 19566959

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Project description:UnlabelledThe effect of antiretroviral drug resistance mutations on cytotoxic T lymphocyte (CTL) recognition has been analyzed in HIV-1 subtype B infections, but it remains unclear in infections by other HIV-1 subtypes that are epidemic in countries where antiretroviral drugs are not effectively used. We investigated the effect of nonnucleoside reverse transcriptase (RT) inhibitor (NNRTI)-resistance mutations (Y181C, Y181I, and Y181V) on epitope recognition by CTLs specific for 3 different HIV-1 epitopes (HLA-A*02:01-restricted IV10, HLA-B*35:01-restricted NY9, and HLA-C*12:02-restricted KY9) in subtype B and subtype A/E infections and the accumulation of these mutations in treatment-naive Japanese and Vietnamese. These NNRTI-resistance mutations critically affected NY9-specific and KY9-specific T cell responses in the subtype B infections, whereas they showed a different effect on IV10-specific T cell responses among the subtype B-infected individuals. These mutations affected IV10-specific T cell responses but weakly affected NY9-specific T cell responses in the subtype A/E infections. The substitution at position 3 of NY9 epitope which was found in the subtype A/E virus differently influenced the peptide binding to HLA-B*35:01, suggesting that the differences in peptide binding may result in the differences in T cell recognition between the subtype B virus and A/E virus infections. The Y181C mutation was found to be accumulating in treatment-naive Vietnamese infected with the subtype A/E virus. The present study demonstrated different effects of NNRTI-resistance RT181 mutations on CTL responses between the 2 subtype infections. The Y181C mutation may influence HIV-1 control by the CTLs in Vietnam, since this mutation has been accumulating in treatment-naive Vietnamese.ImportanceAntiretroviral therapy leads to the emergence of drug-resistant HIV-1, resulting in virological and clinical failures. Though HIV-1-specific CTLs play a critical role in HIV-1 infection, some of drug resistance mutations located in CTL epitopes are known to affect HIV-1-specific CTL responses. Nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistance RT181 mutations are frequently observed in patients treated with NNRTIs. Such drug resistance mutations may have an influence on immune control by HIV-1-specific CTLs, especially in countries where antiretroviral drugs are not effectively used. We here investigated the effect of three NNRTI-resistance RT181 mutations on immune responses by HIV-1-specific CTLs and the recent accumulation of these mutations in treatment-naive Vietnamese infected with HIV-1 subtype A/E virus. RT181 mutations affected CTL recognition in both subtype A/E and B infections, while the RT Y181C mutation has been accumulating in treatment-naive Vietnamese. The results suggest that the Y181C mutation may influence HIV-1 control by CTLs in Vietnam.

Project description:OBJECTIVE:Digital innovations with internet/mobile phones offer a potential cost-saving solution for overburdened health systems with high service delivery costs to improve efficiency of HIV/STI (sexually transmitted infections) control initiatives. However, their overall evidence has not yet been appraised. We evaluated the feasibility and impact of all digital innovations for all HIV/STIs. DESIGN:Systematic review. SETTING/PARTICIPANTS:All settings/all participants. INTERVENTION:We classified digital innovations into (1) mobile health-based (mHealth: SMS (short message service)/phone calls), (2) internet-based mobile and/or electronic health (mHealth/eHealth: social media, avatar-guided computer programs, websites, mobile applications, streamed soap opera videos) and (3) combined innovations (included both SMS/phone calls and internet-based mHealth/eHealth). PRIMARY AND SECONDARY OUTCOME MEASURES:Feasibility, acceptability, impact. METHODS:We searched databases MEDLINE via PubMed, Embase, Cochrane CENTRAL and Web of Science, abstracted data, explored heterogeneity, performed a random effects subgroup analysis. RESULTS:We reviewed 99 studies, 63 (64%) were from America/Europe, 36 (36%) from Africa/Asia; 79% (79/99) were clinical trials; 84% (83/99) evaluated impact. Of innovations, mHealth based: 70% (69/99); internet based: 21% (21/99); combined: 9% (9/99).All digital innovations were highly accepted (26/31; 84%), and feasible (20/31; 65%). Regarding impacted measures, mHealth-based innovations (SMS) significantly improved antiretroviral therapy (ART) adherence (pooled OR=2.15(95%CI: 1.18 to 3.91)) and clinic attendance rates (pooled OR=1.76(95%CI: 1.28, 2.42)); internet-based innovations improved clinic attendance (6/6), ART adherence (4/4), self-care (1/1), while reducing risk (5/5); combined innovations increased clinic attendance, ART adherence, partner notifications and self-care. Confounding (68%) and selection bias (66%) were observed in observational studies and attrition bias in 31% of clinical trials. CONCLUSION:Digital innovations were acceptable, feasible and generated impact. A trend towards the use of internet-based and combined (internet and mobile) innovations was noted. Large scale-up studies of high quality, with new integrated impact metrics, and cost-effectiveness are needed. Findings will appeal to all stakeholders in the HIV/STI global initiatives space.

Project description:The reaction of HIV protease to inhibitor therapy is characterized by the emergence of complex mutational patterns which confer drug resistance. The response of HIV protease to drugs often involves both primary mutations that directly inhibit the action of the drug, and a host of accessory resistance mutations that may occur far from the active site but may contribute to restoring the fitness or stability of the enzyme. Here we develop a probabilistic approach based on connected information that allows us to study residue, pair level and higher-order correlations within the same framework.We apply our methodology to a database of approximately 13,000 sequences which have been annotated by the treatment history of the patients from which the samples were obtained. We show that including pair interactions is essential for agreement with the mutational data, since neglect of these interactions results in order-of-magnitude errors in the probabilities of the simultaneous occurence of many mutations. The magnitude of these pair correlations changes dramatically between sequences obtained from patients that were or were not exposed to drugs. Higher-order effects make a contribution of as much as 10% for residues taken three at a time, but increase to more than twice that for 10 to 15-residue groups. The sequence data is insufficient to determine the higher-order effects for larger groups. We find that higher-order interactions have a significant effect on the predicted frequencies of sequences with large numbers of mutations. While relatively rare, such sequences are more prevalent after multi-drug therapy. The relative importance of these higher-order interactions increases with the number of drugs the patient had been exposed to.Correlations are critical for the understanding of mutation patterns in HIV protease. Pair interactions have substantial qualitative effects, while higher-order interactions are individually smaller but may have a collective effect. Together they lead to correlations which could have an important impact on the dynamics of the evolution of cross-resistance, by allowing the virus to pass through otherwise unlikely mutational states. These findings also indicate that pairwise and possibly higher-order effects should be included in the models of protein evolution, instead of assuming that all residues mutate independently of one another.

Dataset Information

Differences in resistance mutations among HIV-1 non-subtype B infections: a systematic review of evidence (1996-2008).

Publications

Differences in resistance mutations among HIV-1 non-subtype B infections: a systematic review of evidence (1996-2008).

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