Genotypic analysis of the V3 region of HIV from virologic nonresponders to maraviroc-containing regimens reveals distinct patterns of failure.

Changes in HIV tropism from R5 to non-R5 or development of drug resistance is often associated with virologic failure in patients treated with maraviroc, a CCR5 antagonist. We sought to examine changes in HIV envelope sequences and inferred tropism in patients who did not respond to maraviroc-based regimens. We selected 181 patients who experienced early virologic failure on maraviroc-containing therapy in the MOTIVATE trials. All patients had R5 HIV by the original Trofile assay before entry. We used population-based sequencing methods and the geno2pheno algorithm to examine changes in tropism and V3 sequences at the time of failure. Using deep sequencing, we assessed whether V3 sequences observed at failure emerged from preexisting subpopulations. From population genotyping data at failure, 90 patients had R5 results, and 91 had non-R5 results. Of the latter group, the geno2pheno false-positive rate (FPR) value fell from a median of 20 at screening to 1.1 at failure. By deep sequencing, the median percentage of non-R5 variants in these patients rose from 1.4% to 99.5% after a median of 4 weeks on maraviroc. In 70% of cases, deep sequencing could detect a pretreatment CXCR4-using subpopulation, which emerged at failure. Overall, there were two distinct patterns of failure of maraviroc. Patients failing with R5 generally had few V3 substitutions and low non-R5 prevalence by deep sequencing. Patients with non-R5 HIV who were failing developed very-high-prevalence non-R5 HIV (median, 99%) and had very low geno2pheno values.

Correlates of protective cellular immunity revealed by analysis of population-level immune escape pathways in HIV-1.

HLA class I-associated polymorphisms identified at the population level mark viral sites under immune pressure by individual HLA alleles. As such, analysis of their distribution, frequency, location, statistical strength, sequence conservation, and other properties offers a unique perspective from which to identify correlates of protective cellular immunity. We analyzed HLA-associated HIV-1 subtype B polymorphisms in 1,888 treatment-naïve, chronically infected individuals using phylogenetically informed methods and identified characteristics of HLA-associated immune pressures that differentiate protective and nonprotective alleles. Over 2,100 HLA-associated HIV-1 polymorphisms were identified, approximately one-third of which occurred inside or within 3 residues of an optimally defined cytotoxic T-lymphocyte (CTL) epitope. Differential CTL escape patterns between closely related HLA alleles were common and increased with greater evolutionary distance between allele group members. Among 9-mer epitopes, mutations at HLA-specific anchor residues represented the most frequently detected escape type: these occurred nearly 2-fold more frequently than expected by chance and were computationally predicted to reduce peptide-HLA binding nearly 10-fold on average. Characteristics associated with protective HLA alleles (defined using hazard ratios for progression to AIDS from natural history cohorts) included the potential to mount broad immune selection pressures across all HIV-1 proteins except Nef, the tendency to drive multisite and/or anchor residue escape mutations within known CTL epitopes, and the ability to strongly select mutations in conserved regions within HIV's structural and functional proteins. Thus, the factors defining protective cellular immune responses may be more complex than simply targeting conserved viral regions. The results provide new information to guide vaccine design and immunogenicity studies.

Automating HIV drug resistance genotyping with RECall, a freely accessible sequence analysis tool.

Genotypic HIV drug resistance testing is routinely used to guide clinical decisions. While genotyping methods can be standardized, a slow, labor-intensive, and subjective manual sequence interpretation step is required. We therefore performed external validation of our custom software RECall, a fully automated sequence analysis pipeline. HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first interpreted manually by a laboratory technician and subsequently reanalyzed by RECall, without intervention. The relative performances of the two methods were assessed by determination of the concordance of nucleotide base calls, identification of key resistance-associated substitutions, and HIV drug resistance susceptibility scoring by the Stanford Sierra algorithm. RECall is freely available at http://pssm.cfenet.ubc.ca. In total, 875 of 981 sequences were analyzed by both human and RECall interpretation. RECall analysis required minimal hands-on time and resulted in a 25-fold improvement in processing speed (∼150 technician-hours versus ∼6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% agreement for >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures being called by one method but not the other. Similarly, 98.6% of key antiretroviral resistance-associated mutations observed were identified by both methods, resulting in 98.5% concordance of resistance susceptibility interpretations. This automated sequence analysis tool provides both standardization of analysis and a significant improvement in data workflow. The time-consuming, error-prone, and dreadfully boring manual sequence analysis step is replaced with a fully automated system without compromising the accuracy of reported HIV drug resistance data.

The relationship between resistance and adherence in drug-naive individuals initiating HAART is specific to individual drug classes.

OBJECTIVE: To investigate the relationship between HIV-1 drug resistance and adherence and the accumulation rate of resistance mutations in 1191 HIV-infected, antiretroviral-naive adults initiating highly active antiretroviral therapy in British Columbia, Canada. METHODS: Plasma samples with plasma viral load >1,000 copies per milliliter collected within 30 months of follow-up were genotyped for drug resistance. Adherence was estimated using prescription refills and plasma drug levels. The primary outcome measure was time to detection of drug resistance. Cox proportional hazard regression was used to calculate hazard ratios (HRs) associated with baseline variables. RESULTS: The accumulation rates of multiple primary and secondary mutations were similar in patients initiating highly active antiretroviral therapy with protease inhibitor versus nonnucleoside reverse transcriptase inhibitor (NNRTI). Rates decreased approximately 50% per additional mutation. At 80%-90% adherence based on refills, there was greater risk of detecting lamivudine (3TC) [HR 3.0, 95% confidence interval (CI): 1.9 to 4.7; P < 0.0001] and NNRTI mutations (HR 6.0, 95% CI: 3.3 to 10.9; P < 0.0001) compared with the >or=95% refill reference group. In a multivariate model, individuals with <95% refills and consistently detectable plasma drug levels were at increased risk for 3TC (HR 4.5, 95% CI: 2.6 to 7.9; P = 0.0001) and NNRTI resistance (HR 7.0, 95% CI: 3.4 to 14.5; P = 0.0001) compared with the reference group of >or=95% refills with consistently detectable drug levels. Adherence-resistance relationships were much weaker for protease inhibitors and nucleoside reverse transcriptase inhibitors as there was little variance in HRs among the different adherence strata compared with 3TC and NNRTIs. CONCLUSION: The relationships between resistance, adherence, and mutation accumulation differ between HIV drug classes.

A simple screening approach to reduce B*5701-associated abacavir hypersensitivity on the basis of sequence variation in HIV reverse transcriptase.

BACKGROUND: Abacavir hypersensitivity is strongly associated with the human leukocyte antigen (HLA)-B*5701 allele; however, the cost of routine high-resolution HLA typing before initiation of therapy remains prohibitive. We propose a simple approach to reduce B*5701-associated abacavir hypersensitivity based on the screening of human immunodeficiency virus (HIV) reverse transcriptase (RT) for a signature B*5701-associated cytotoxic T lymphocyte escape mutation at RT codon 245. METHODS: The correlation between HLA-B*5701 and RT codon 245 variation was investigated in 392 HIV-infected, antiretroviral-naive adults who were initiating highly active antiretroviral therapy. The relationship between codon 245 variation and premature abacavir discontinuation was investigated in a larger cohort of treated individuals (n=982). Associations between HLA-B*5701 and codon 245 variants were determined using Fisher's exact test or the chi (2) test. RESULTS: A very strong association between HLA-B*5701 and RT codon 245 variation was observed. Only 1 (4.2%) of 24 subjects with B*5701 harbored virus with the clade B "wild-type" amino acid 245V, compared with 278 (75.5%) of 368 who did not have B*5701 (P<.001). The sensitivity and specificity of codon 245 substitutions for predicting HLA-B*5701 were 96% and 75%, respectively, and the positive and negative predictive values were 20% and 99.6%, respectively. This association remained robust even after antiretroviral treatment was administered (negative predictive value, 100%; n=269). In abacavir-treated individuals (n=982), codon 245 substitutions were predictive of premature abacavir discontinuation (P=.02). CONCLUSIONS: As HIV RT sequence is incidentally obtained as a part of routine drug-resistance testing, the examination of sequence variation at RT codon 245 could be adopted as a simple, low-cost screening method to identify individuals who could be safely treated with abacavir and/or who could benefit from HLA characterization.