Robert W. Shafer

Human immunodeficiency virus reverse transcriptase and protease sequence database

The HIV RT and Protease Sequence Database is an online relational database that catalogs evolutionary and drug-related human immunodeficiency virus (HIV) reverse transcriptase (RT) and protease sequence variation (http://hivdb.stanford.edu). The database contains a compilation of nearly all published HIV RT and protease sequences including International Collaboration database submissions (e.g., GenBank) and sequences published in journal articles. Sequences are linked to data about the source of the sequence sample and the antiretroviral drug treatment history of the individual from whom the isolate was obtained. The database is curated and sequences are annotated with data from >230 literature references. Users can retrieve additional data and view alignments of sequence sets meeting specific criteria (e.g., treatment history, subtype, presence of a particular mutation). A gene-specific sequence analysis program, new user-defined queries and nearly 2000 additional sequences were added in 1999.

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.

Exogenous Reinfection with Multidrug-Resistant Mycobacterium tuberculosis in Patients with Advanced HIV Infection

BACKGROUND In the United States there have been recent outbreaks of multidrug-resistant tuberculosis. These outbreaks have primarily involved persons infected with the human immunodeficiency virus (HIV). METHODS We collected clinical information on 17 patients seen at a New York City hospital who had repeatedly positive cultures for Mycobacterium tuberculosis. Analysis of restriction-fragment--length polymorphisms (RFLPs) was performed on serial isolates of M. tuberculosis obtained from these patients. RESULTS Six patients had isolates that remained drug-susceptible, and the RFLP patterns of these isolates did not change over time. Eleven patients had isolates that became resistant to antimicrobial agents. The RFLP patterns of the isolates from six of these patients remained essentially unchanged (two strains showed one additional band) despite the development of drug resistance. In five other patients, however, the RFLP patterns of the isolates changed dramatically at the time that drug resistance was detected. The change in the RFLP pattern of the isolate from one patient appeared to be the result of contamination during processing in the laboratory. In the remaining four patients, all of whom had advanced HIV disease, the clinical and microbiologic evidence was consistent with the presence of active tuberculosis caused by a new strain of M. tuberculosis. CONCLUSIONS Resistance to antituberculous drugs can develop not only in the strain that caused the initial disease, but also as a result of reinfection with a new strain of M. tuberculosis that is drug-resistant. Exogenous reinfection with multidrug-resistant M. tuberculosis can occur either during therapy for the original infection or after therapy has been completed.

Web Resources for HIV Type 1 Genotypic-Resistance Test Interpretation

Interpreting the results of plasma human immunodeficiency virus type 1 (HIV-1) genotypic drug-resistance tests is one of the most difficult tasks facing clinicians caring for HIV-1-infected patients. There are many drug-resistance mutations, and they arise in complex patterns that cause varying levels of drug resistance. In addition, HIV-1 exists in vivo as a virus population containing many genomic variants. Genotypic-resistance testing detects the drug-resistance mutations present in the most common plasma virus variants but may not detect drug-resistance mutations present in minor virus variants. Therefore, interpretation systems are necessary to determine the phenotypic and clinical significance of drug-resistance mutations found in a patients plasma virus population. We describe the scientific principles of HIV-1 genotypic-resistance test interpretation and the most commonly used Web-based resources for clinicians ordering genotypic drug-resistance tests.

Genotypic Testing for Human Immunodeficiency Virus Type 1 Drug Resistance

SUMMARY There are 16 approved human immunodeficiency virus type 1 (HIV-1) drugs belonging to three mechanistic classes: protease inhibitors, nucleoside and nucleotide reverse transcriptase (RT) inhibitors, and nonnucleoside RT inhibitors. HIV-1 resistance to these drugs is caused by mutations in the protease and RT enzymes, the molecular targets of these drugs. Drug resistance mutations arise most often in treated individuals, resulting from selective drug pressure in the presence of incompletely suppressed virus replication. HIV-1 isolates with drug resistance mutations, however, may also be transmitted to newly infected individuals. Three expert panels have recommended that HIV-1 protease and RT susceptibility testing should be used to help select HIV drug therapy. Although genotypic testing is more complex than typical antimicrobial susceptibility tests, there is a rich literature supporting the prognostic value of HIV-1 protease and RT mutations. This review describes the genetic mechanisms of HIV-1 drug resistance and summarizes published data linking individual RT and protease mutations to in vitro and in vivo resistance to the currently available HIV drugs.

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.

Extrapulmonary tuberculosis in patients with human immunodeficiency virus infection.

The annual number of cases of culture-proven extrapulmonary tuberculosis (TB) at our hospital increased from 47 cases in 1983 to 113 cases in 1988. At least 43% (199) of 464 consecutive patients with extrapulmonary TB during this 6-year period were infected with the human immunodeficiency virus (HIV); since HIV serologic testing was not performed routinely the true HIV prevalence is likely to be higher. Of the HIV-infected patients, 59% were intravenous drug users, 31% were Haitian, 3% were homosexual males, 1% were perinatally-infected infants, and 6% did not have a known risk factor for HIV infection. Ninety-eight percent of the HIV-infected patients were black (84%) or hispanic (14%). The HIV-infected patients were more likely than the control patients to have either disseminated, genitourinary, intra-abdominal, mediastinal, or concurrent pulmonary TB. Fever was nearly universal among the HIV-infected patients, but was absent in about one-third of the control patients. Among untreated HIV-infected patients, disease progression was rapid and nearly always fatal. Among HIV-infected patients who received treatment, the response to therapy, as judged by hospital survival and time to defervescence, was similar to that of the control patients. Despite the extensive tuberculous dissemination among the HIV-infected patients, the diagnosis of TB was difficult and often delayed. In addition to the decrease in tuberculin reactivity and the atypical chest radiograph patterns, there was a need to consider other HIV-related infections in the differential diagnosis. Although sputum specimens grew M. tuberculosis in greater than 90% of the HIV-infected patients in whom they were obtained, sputum AFB stains were positive in less than 50%. Blood and urine specimen cultures were positive in 56% and 77% of the HIV-infected patients in whom these specimens were obtained, but did not provide a means of early diagnosis. Cerebrospinal fluid and pleural fluid were abnormal in nearly all patients with involvement of these sites but were rarely AFB-positive and were, therefore, only suggestive of TB. Procedures such as biopsies and aspirates of peripheral lymph nodes, visceral lymph nodes, liver, and bone marrow provided the highest immediate diagnostic yields with rates between 50% and 90%. These procedures must be considered early in the course of illness in HIV-infected patients with suspected extrapulmonary TB due to the rapidly progressive nature of this often fatal but usually treatable infection.

Pharmacogenetics of Long-Term Responses to Antiretroviral Regimens Containing Efavirenz and/or Nelfinavir: An Adult AIDS Clinical Trials Group Study

BACKGROUND Efavirenz and nelfinavir are metabolized by cytochrome P-450 (CYP) 2B6 and CYP2C19, respectively, with some involvement by CYP3A. Nelfinavir is a substrate for P-glycoprotein, which is encoded by MDR1. The present study examined associations between genetic variants and long-term responses to treatment. METHODS Adult AIDS Clinical Trials Group study 384 randomized antiretroviral-naive subjects to receive efavirenz and/or nelfinavir plus 2 nucleoside analogues, with follow-up lasting up to 3 years. Population pharmacokinetics were estimated from a nonlinear mixed-effects model. Polymorphisms in CYP2B6, CYP2C19, CYP3A4, CYP3A5, and MDR1 were characterized. RESULTS The 504 participants in the genetic study included 340 efavirenz recipients and 348 nelfinavir recipients (184 of the 504 participants received both efavirenz and nelfinavir). Of the participants, 49% were white, 31% were black, and 19% were Hispanic. Plasma exposure to efavirenz and nelfinavir in each population was significantly associated with the polymorphisms CYP2B6 516G-->T and CYP2C19 681G-->A, respectively. Among efavirenz recipients, the MDR1 position 3435 TT genotype was associated with decreased likelihood of virologic failure and decreased emergence of efavirenz-resistant virus but not with plasma efavirenz exposure. Among nelfinavir recipients, a trend toward decreased virologic failure was associated with the polymorphism CYP2C19 681G-->A. CONCLUSIONS Genetic variants predict plasma exposure to efavirenz and nelfinavir, and they may predict virologic failure and/or emergence of drug-resistant virus. These associations with treatment responses must be validated in other studies.

HIV-1 genotypic resistance patterns predict response to saquinavir-ritonavir therapy in patients in whom previous protease inhibitor therapy had failed.

Combination antiretroviral therapy for HIV-1 infection has resulted in profound control of HIV replication in vivo, improved immune function, and significant decreases in AIDS-related morbidity and mortality (1-9). For many persons, however, this therapy does not provide sustained viral suppression or durable clinical benefit (10, 11). Potential reasons for the loss of viral suppression include host immune defects, poor adherence to therapy, pharmacologic factors, and drug resistance (10-17). However, HIV-1 resistance to drug therapy is probably the central factor in the loss of viral suppression (18-22). Mutations that result in reduced drug susceptibility have been demonstrated in vitro for all currently available antiretroviral agents, and some of these mutations have been associated with increasing plasma HIV-1 RNA levels and disease progression in clinical trials (19-30). Genotypic and phenotypic methods of measuring drug resistance are increasingly available to clinicians (31-37). However, the role of these tests in clinical practice has not been fully assessed. Many experts have been skeptical of resistance testing, although a recent consensus statement provides cautious support for testing in certain clinical circumstances (38-42). Our objective was to determine the genotypic predictors of virologic response to saquinavirritonavir combination therapy in patients in whom therapy with at least one protease inhibitor-containing antiretroviral regimen had failed. We investigated whether HIV-1 reverse transcriptase and protease genotype predicts virologic response to saquinavirritonavir by week 12 and week 26 and compared those data with predictors from clinical and antiretroviral treatment history. Methods Patients Two of the investigators treated patients in a university-based clinic that provides primary care for 500 HIV-infected adults. We identified 54 patients who received saquinavirritonavir between October 1996 and February 1998 after therapy with at least one protease inhibitor-containing antiretroviral regimen had failed. Treatment failure was defined as a greater than 0.5 log10 copies/mL (more than threefold) increase in plasma HIV RNA level from a nadir value, an HIV RNA level greater than 10 000 copies/mL, or detectable HIV RNA after the level had been below the threshold of detection (<500 copies/mL) during a therapeutic regimen for more than 12 weeks. Study patients received 400 to 600 mg of saquinavir in a hard-gel formulation (Invirase, Roche Laboratories, Nutley, New Jersey) and 300 to 400 mg of ritonavir in capsule form (Norvir, Abbott Laboratories, Abbott Park, Illinois) twice daily. In addition to the two protease inhibitors, 47 patients (87%) received two nucleoside reverse transcriptase inhibitors, 4 received three nucleoside reverse transcriptase inhibitors, 2 received two nucleoside reverse transcriptase inhibitors and either nevirapine or delavirdine, and one patient received lamivudine. Clinical and demographic variables were abstracted from the medical records. Adherence, as recorded in the patients record, was categorized by the self-reported number of missed doses in the month before evaluation and was classified as none, one to two, three to seven, or eight or more. Plasma levels of HIV-1 RNA were monitored on average every 4 to 6 weeks, and samples were stored at 70 C. The Stanford University Panel on Medical Human Subjects approved this study (#M1272). HIV Genotyping Baseline HIV-1 genotype was evaluated in plasma specimens that were stored within 1 month before initiation of saquinavirritonavir therapy and were obtained while patients were still receiving an ineffective antiretroviral regimen. Plasma HIV-1 RNA was extracted, and nested polymerase chain reaction (PCR) amplification generated a 1.3-kb fragment encompassing protease and the first 750 nucleotides of reverse transcriptase (43, 44). Direct bidirectional dideoxynucleotide terminator cycle sequencing of the PCR product was performed as described elsewhere (44). Sequencing reactions were analyzed by using an ABI 377 instrument (Perkin-Elmer, Foster City, California) and were manually proofread and edited. Sequences were compared to the HIV-1 clade B consensus sequence (Los Alamos database), and differences in amino acid sequence, including positions that contained a mixture of wild-type and mutant residues, were classified as mutations (45). Phylogenetic analysis of HIV-1 RNA sequence verified lack of cross-contamination (data not shown). A priori, we decided to assess reverse transcriptase codons 41, 67, 69, 70, 74, 75, 151, 184, 210, 215, and 219 as predictors of virologic response. Mutations at these codons are known to be associated with resistance to one of the nucleoside reverse transcriptase inhibitors (25, 45). In the protease gene, mutations at codons 30, 46, 48, 54, 82, 84, and 90 were evaluated as potential predictors. We chose these major mutations a priori because they are associated with in vitro resistance to a protease inhibitor or occur commonly in patients in whom therapy with currently licensed protease inhibitors is failing. We also evaluated all other protease codons as predictors of response. Virologic Outcomes Virologic response to saquinavirritonavir was measured at two time points between 3 and 18 weeks and again around week 24 (range, 22 to 36 weeks); the median time points of the three follow-up evaluations were 4, 12, and 26 weeks. Levels of HIV-1 RNA were measured by using the Amplicor HIV Monitor Assay (Roche Molecular Systems, Alameda, California). Specimens with HIV RNA below the level of detection (<500 copies/mL) on this assay were retested by using the ultrasensitive modification with a lower limit of detection of less than 50 copies/mL (43). Virologic response to saquinavirritonavir therapy was categorized on the basis of the larger response from baseline to the first or second evaluation [median, 4 and 12 weeks]. The ordinal categories were 1) complete response if the plasma HIV-1 RNA level was less than 500 copies/mL, 2) partial response if the reduction from baseline RNA level was 0.5 log10 copies/mL or more but was not less than 500 copies/mL, and 3) nonresponse if reduction from baseline values was less than 0.5 log10 copies/mL. Statistical Analysis Demographic, clinical, and genotypic variables were analyzed as potential predictors of virologic response by using bivariate linear regression and multivariable linear regression. In the multivariable models, we included a subset of the reverse transcriptase mutations (listed above) identified through stepwise regression as significant (P<0.05) predictors. This subset of mutations was included in the model as a signed-sum variable. For the protease mutations, we included the signed sum of the seven major mutations listed above and the signed sum of three additional mutations at codons 10, 19, and 71, which were found to be statistically significant bivariate predictors. The signed-sum variable is derived by a summation of the relevant mutations identified in the baseline sequence. A separate sum is derived from the seven major protease mutations, the three additional protease mutations, and the subset of statistically significant reverse transcriptase mutations (codons 69 and 210). In the signed-sum variable, mutations that are positively associated with virologic outcome (such as protease mutation D30N) are assigned a positive sign (+1) and mutations negatively associated with outcome are assigned a negative sign (1). We used the Cook distance to assess skewing of the ordinal outcome variable in the final multivariable model (model 5, Table 3). The value of 0.11 indicated no significant skewing; this result supports the use of linear regression models (46). We also evaluated the multivariate models for bias that would result from overfitting of the data. We used a bootstrap technique to estimate bias (optimism) in the explained variance values (R 2) for the models presented and found minimal upward bias; for example, model 3 in Table 3 has a bias of approximately one fifth of the SE (data for other models not shown) (47). A bootstrap technique was used to provide the 95% CI estimates for the R 2 values in Table 3. We selected 25 bootstrap samples of 54 with replacement from the original 54 patients to estimate the 95% CIs. The Wilcoxon rank test was used for comparisons between specific previous protease inhibitors in Table 1, and the F test was used for comparisons between models in Table 3. Two-sided P values are reported for all analyses. All analyses were conducted by using S-PLUS, version 4.0 (MathSoft, Seattle, Washington). Table 1. Baseline Demographics, Clinical Characteristics, and Antiretroviral Treatment History as Predictors of Virologic Response to saquinavirritonavir Therapy Table 2. Protease Mutation Patterns at Baseline and Response to saquinavirritonavir Combination Therapy Table 3. Multivariable Linear Regression Models of Clinical, Antiretroviral Treatment History, and HIV-1 Genotypic Predictors of Virologic Response by Week 12 of saquinavirritonavir Therapy Results Virologic Response to saquinavirritonavir Therapy Of the 54 study patients, 22 (41%) achieved a complete response, with plasma HIV-1 RNA levels less than 500 copies/mL by the second follow-up evaluation (at a median of 12 weeks). Of these 22 patients, 10 (18.5% of the entire cohort) achieved a plasma HIV-1 RNA level less than 50 copies/mL. Fourteen patients (26%) had a partial response to saquinavirritonavir, and 18 (33%) were nonresponders (Table 1). The virologic response to saquinavirritonavir is shown by initial response category in Figure 1. The response waned somewhat in the partial and complete response groups by week 26: The HIV RNA level remained below 500 copies/mL in 15 patients (28%) and below 50 copies/mL in 10 patients (19%). Figure 1. Virologic response to saquinavir plus ritonavir through week 26 based on response by week 12. Pred

Rationale and Uses of a Public HIV Drug‐Resistance Database

Knowledge regarding the drug resistance of human immunodeficiency virus (HIV) is critical for surveillance of drug resistance, development of antiretroviral drugs, and management of infections with drug-resistant viruses. Such knowledge is derived from studies that correlate genetic variation in the targets of therapy with the antiretroviral treatments received by persons from whom the variant was obtained (genotype-treatment), with drug-susceptibility data on genetic variants (genotype-phenotype), and with virological and clinical response to a new treatment regimen (genotype-outcome). An HIV drug-resistance database is required to represent, store, and analyze the diverse forms of data underlying our knowledge of drug resistance and to make these data available to the broad community of researchers studying drug resistance in HIV and clinicians using HIV drug-resistance tests. Such genotype-treatment, genotype-phenotype, and genotype-outcome correlations are contained in the Stanford HIV RT and Protease Sequence Database and have specific usefulness.