Soo-Yon Rhee

Drug Resistance Mutations for Surveillance of Transmitted HIV-1 Drug-Resistance: 2009 Update

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.

HIV-1 protease and reverse transcriptase mutations for drug resistance surveillance

Objectives:Monitoring regional levels of transmitted HIV-1 resistance informs treatment guidelines and provides feedback on the success of HIV-1 prevention efforts. Surveillance programs for estimating the frequency of transmitted resistance are being developed in both industrialized and resource-poor countries. However, such programs will not produce comparable estimates unless a standardized list of drug-resistance mutations is used to define transmitted resistance. Methods:In this paper, we outline considerations for developing a list of drug-resistance mutations for epidemiologic estimates of transmitted resistance. First, the mutations should cause or contribute to drug resistance and should develop in persons receiving antiretroviral therapy. Second, the mutations should not occur as polymorphisms in the absence of therapy. Third, the mutation list should be applicable to all group M subtypes. Fourth, the mutation list should be simple, unambiguous, and parsimonious. Results:Applying these considerations, we developed a list of 31 protease inhibitor-resistance mutations at 14 protease positions, 31 nucleoside reverse transcriptase inhibitor-resistance mutations at 15 reverse transcriptase positions, and 18 non-nucleoside reverse transcriptase inhibitor-resistance mutations at 10 reverse transcriptase positions. Conclusions:This list, which should be updated regularly using the same or similar criteria, can be used for genotypic surveillance of transmitted HIV-1 drug resistance.

Viral Population Estimation Using Pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation–maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.

Genotypic predictors of human immunodeficiency virus type 1 drug resistance

Understanding the genetic basis of HIV-1 drug resistance is essential to developing new antiretroviral drugs and optimizing the use of existing drugs. This understanding, however, is hampered by the large numbers of mutation patterns associated with cross-resistance within each antiretroviral drug class. We used five statistical learning methods (decision trees, neural networks, support vector regression, least-squares regression, and least angle regression) to relate HIV-1 protease and reverse transcriptase mutations to in vitro susceptibility to 16 antiretroviral drugs. Learning methods were trained and tested on a public data set of genotype–phenotype correlations by 5-fold cross-validation. For each learning method, four mutation sets were used as input features: a complete set of all mutations in ≥2 sequences in the data set, the 30 most common data set mutations, an expert panel mutation set, and a set of nonpolymorphic treatment-selected mutations from a public database linking protease and reverse transcriptase sequences to antiretroviral drug exposure. The nonpolymorphic treatment-selected mutations led to the best predictions: 80.1% accuracy at classifying sequences as susceptible, low/intermediate resistant, or highly resistant. Least angle regression predicted susceptibility significantly better than other methods when using the complete set of mutations. The three regression methods provided consistent estimates of the quantitative effect of mutations on drug susceptibility, identifying nearly all previously reported genotype–phenotype associations and providing strong statistical support for many new associations. Mutation regression coefficients showed that, within a drug class, cross-resistance patterns differ for different mutation subsets and that cross-resistance has been underestimated.

HIV-1 integrase inhibitor resistance and its clinical implications.

With the approval in 2007 of the first integrase inhibitor (INI), raltegravir, clinicians became better able to suppress virus replication in patients infected with human immunodeficiency virus type 1 (HIV-1) who were harboring many of the most highly drug-resistant viruses. Raltegravir also provided clinicians with additional options for first-line therapy and for the simplification of regimens in patients with stable virological suppression. Two additional INIs in advanced clinical development—elvitegravir and S/GSK1349572—may prove equally versatile. However, the INIs have a relatively low genetic barrier to resistance in that 1 or 2 mutations are capable of causing marked reductions in susceptibility to raltegravir and elvitegravir, the most well-studied INIs. This perspective reviews the genetic mechanisms of INI resistance and their implications for initial INI therapy, the treatment of antiretroviral-experienced patients, and regimen simplification.

The calibrated population resistance tool

Summary: The calibrated population resistance (CPR) tool is a web-accessible program for performing standardized genotypic estimation of transmitted HIV-1 drug resistance. The program is linked to the Stanford HIV drug resistance database and can additionally perform viral genotyping and algorithmic estimation of resistance to specific antiretroviral drugs. Availability: http://cpr.stanford.edu/cpr/index.html Contact: robjgiff@gmail.com

HIV-1 Protease Mutations and Protease Inhibitor Cross-Resistance

ABSTRACT The effects of many protease inhibitor (PI)-selected mutations on the susceptibility to individual PIs are unknown. We analyzed in vitro susceptibility test results on 2,725 HIV-1 protease isolates. More than 2,400 isolates had been tested for susceptibility to fosamprenavir, indinavir, nelfinavir, and saquinavir; 2,130 isolates had been tested for susceptibility to lopinavir; 1,644 isolates had been tested for susceptibility to atazanavir; 1,265 isolates had been tested for susceptibility to tipranavir; and 642 isolates had been tested for susceptibility to darunavir. We applied least-angle regression (LARS) to the 200 most common mutations in the data set and identified a set of 46 mutations associated with decreased PI susceptibility of which 40 were not polymorphic in the eight most common HIV-1 group M subtypes. We then used least-squares regression to ascertain the relative contribution of each of these 46 mutations. The median number of mutations associated with decreased susceptibility to each PI was 28 (range, 19 to 32), and the median number of mutations associated with increased susceptibility to each PI was 2.5 (range, 1 to 8). Of the mutations with the greatest effect on PI susceptibility, I84AV was associated with decreased susceptibility to eight PIs; V32I, G48V, I54ALMSTV, V82F, and L90M were associated with decreased susceptibility to six to seven PIs; I47A, G48M, I50V, L76V, V82ST, and N88S were associated with decreased susceptibility to four to five PIs; and D30N, I50L, and V82AL were associated with decreased susceptibility to fewer than four PIs. This study underscores the greater impact of nonpolymorphic mutations compared with polymorphic mutations on decreased PI susceptibility and provides a comprehensive quantitative assessment of the effects of individual mutations on susceptibility to the eight clinically available PIs.

HIV-1 Protease and Reverse-Transcriptase Mutations: Correlations with Antiretroviral Therapy in Subtype B Isolates and Implications for Drug-Resistance Surveillance

Background. It is important, for drug-resistance surveillance, to identify human immunodeficiency virus type 1 (HIV-1) strains that have undergone antiretroviral drug selection.Methods. We compared the prevalence of protease and reverse-transcriptase (RT) mutations in HIV-1 sequences from persons with and without previous treatment with protease inhibitors (PIs), nucleoside RT inhibitors (NRTIs), and nonnucleoside RT inhibitors (NNRTIs). Treatment-associated mutations in protease isolates from 5867 persons and RT isolates from 6247 persons were categorized by whether they were polymorphic (prevalence, >0.5%) in untreated individuals and whether they were established drug-resistance mutations. New methods were introduced to minimize misclassification from transmitted resistance, population stratification, sequencing artifacts, and multiple hypothesis testing.Results. Some 36 established and 24 additional nonpolymorphic protease mutations at 34 positions were related to PI treatment, 21 established and 22 additional nonpolymorphic RT mutations at 24 positions with NRTI treatment, and 15 established and 11 additional nonpolymorphic RT mutations at 15 positions with NNRTI treatment. In addition, 11 PI-associated and 1 NRTI-associated established mutations were polymorphic in viruses from untreated persons.Conclusions. Established drug-resistance mutations encompass only a subset of treatment-associated mutations; some of these are polymorphic in untreated persons. In contrast, nonpolymorphic treatment-associated mutations may be more sensitive and specific markers of transmitted HIV-1 drug resistance.

Natural variation of HIV-1 group M integrase: Implications for a new class of antiretroviral inhibitors

HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete pol gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannons entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q – which was present in 1.1% of sequences – were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%.

Lack of Detectable Human Immunodeficiency Virus Type 1 Superinfection during 1072 Person-Years of Observation

We examined consecutive protease (PR) and reverse transcriptase (RT) sequences from human immunodeficiency virus (HIV) type 1-infected individuals, to distinguish changes resulting from sequence evolution due to possible superinfection. Between July 1997 and December 2001, >/=2 PR and RT samples from 718 persons were sequenced at Stanford University Hospital. Thirty-seven persons had highly divergent sequence pairs characterized by a nucleotide distance of >4.5% in PR or >3.0% in RT. In 16 of 37 sequence pairs, divergence resulted from the loss of mutations during a treatment interruption or from the gain of mutations with reinstitution of treatment. tat and/or gag sequencing of HIV-1 from cryopreserved plasma samples could be performed on 15 of the 21 divergent isolate pairs from persons without a treatment interruption. The sequences of these genes, unaffected by selective drug pressure, were monophyletic. Although HIV-1 PR and RT genes from treated persons may become highly divergent, these changes usually are the result of sequence evolution, rather than superinfection.