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

Potential role of doravirine for the treatment of HIV-1-infected persons with transmitted drug resistance

Background: Doravirine has a unique resistance profile but how this profile might increase its usefulness beyond first-line therapy in persons with susceptible viruses has not been well studied. We sought to determine scenarios in which doravirine would retain activity against isolates from ART-naïve persons with transmitted drug resistance (TDR) and to identify gaps in available doravirine susceptibility data. Methods: We analyzed published in vitro doravirine susceptibility data and applied the results to 42,535 RT sequences from ART-naïve persons published between 2017 and 2021. NNRTI drug resistance mutations (DRMs) were defined as those with a Stanford HIV Drug Resistance Database doravirine penalty score either alone or in combination with other mutations. Results: V106A, Y188L, F227C/L, M230L, and Y318F were associated with the greatest reductions in doravirine susceptibility. However, several NNRTI DRMs and DRM combinations lacking these canonical resistance mutations had > tenfold reduced susceptibility including G190E, one isolate with G190S, three isolates with L100I + K103N, one isolate with K103N + P225H, and isolates with L100I + K103N + V108I and K101E + Y181C + G190A. Of the 42,535 ART-naïve sequences, 3,374 (7.9%) contained a NNRTI DRM of which 2,788 (82.6%) contained 1 DRM (n = 33 distinct mutations), 426 (12.6%) contained 2 DRMs (79 distinct pairs of mutations), and 143 (4.2%) contained ≥ 3 DRMs (86 distinct mutation patterns). Among the 2,788 sequences with one DRM, 112 (4.0%) were associated with ≥ 3.0-fold reduced doravirine susceptibility while 2,625 (94.2%) were associated with < 3.0-fold reduced susceptibility. Data were not available for individual NNRTI DRMs in 51 sequences (1.8%). Among the 426 sequences with two NNRTI DRMs, 180 (42.3%) were associated with ≥ 3.0 fold reduced doravirine susceptibility while just 32 (7.5%) had < 3.0 fold reduced susceptibility. Data were not available for 214 (50.2%) sequences containing two NNRTI DRMs. Conclusions: First-line therapy containing doravirine plus two NRTIs is expected to be effective in treating most persons with TDR as more than 80% of TDR sequences had a single NNRTI DRM and as more than 90% with a single DRM were expected to be susceptible to doravirine. However, caution is required for the use of doravirine in persons with more than one NNRTI DRM even if none of the DRMs are canonical doravirine-resistance mutations. © 2023, The Author(s)

Multiple independent origins of a protease inhibitor resistance mutation in salvage therapy patients

<p>Abstract</p> <p>Background</p> <p>Combination anti-viral therapies have reduced treatment failure rates by requiring multiple specific mutations to be selected on the same viral genome to impart high-level drug resistance. To determine if the common protease inhibitor resistance mutation L90M is only selected once or repeatedly on different HIV genetic backbones during the course of failed anti-viral therapies we analyzed a linked region of the viral genome during the evolution of multi-drug resistance.</p> <p>Results</p> <p>Using L90M allele specific PCR we amplified and sequenced gag-pro regions linked to very early L90M containing HIV variants prior to their emergence and detection as dominant viruses in 15 failed salvage therapy patients. The early minority L90M linked sequences were then compared to those of the later L90M viruses that came to dominate the plasma quasispecies. Using Bayesian evolutionary analysis sampling trees the emergence of L90M containing viruses was seen to take place on multiple occasion in 5 patients, only once for 2 patients and an undetermined number of time for the remaining 8 patients.</p> <p>Conclusion</p> <p>These results indicate that early L90M mutants can frequently be displaced by viruses carrying independently selected L90M mutations rather than by descendents of the earlier mutants.</p

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 Shannon's 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%

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.</p

HIV-1 Protease, Reverse Transcriptase, and Integrase Variation

ABSTRACT HIV-1 protease (PR), reverse transcriptase (RT), and integrase (IN) variability presents a challenge to laboratories performing genotypic resistance testing. This challenge will grow with increased sequencing of samples enriched for proviral DNA such as dried blood spots and increased use of next-generation sequencing (NGS) to detect low-abundance HIV-1 variants. We analyzed PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to characterize variation at each amino acid position, identify mutations indicating APOBEC-mediated G-to-A editing, and identify mutations resulting from selective drug pressure. Forty-seven percent of PR, 37% of RT, and 34% of IN positions had one or more amino acid variants with a prevalence of ≥1%. Seventy percent of PR, 60% of RT, and 60% of IN positions had one or more variants with a prevalence of ≥0.1%. Overall 201 PR, 636 RT, and 346 IN variants had a prevalence of ≥0.1%. The median intersubtype prevalence ratios were 2.9-, 2.1-, and 1.9-fold for these PR, RT, and IN variants, respectively. Only 5.0% of PR, 3.7% of RT, and 2.0% of IN variants had a median intersubtype prevalence ratio of ≥10-fold. Variants at lower prevalences were more likely to differ biochemically and to be part of an electrophoretic mixture compared to high-prevalence variants. There were 209 mutations indicative of APOBEC-mediated G-to-A editing and 326 mutations nonpolymorphic treatment selected. Identification of viruses with a high number of APOBEC-associated mutations will facilitate the quality control of dried blood spot sequencing. Identifying sequences with a high proportion of rare mutations will facilitate the quality control of NGS. IMPORTANCE Most antiretroviral drugs target three HIV-1 proteins: PR, RT, and IN. These proteins are highly variable: many different amino acids can be present at the same position in viruses from different individuals. Some of the amino acid variants cause drug resistance and occur mainly in individuals receiving antiretroviral drugs. Some variants result from a human cellular defense mechanism called APOBEC-mediated hypermutation. Many variants result from naturally occurring mutation. Some variants may represent technical artifacts. We studied PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to quantify variation at each amino acid position in these three HIV-1 proteins. We performed analyses to determine which amino acid variants resulted from antiretroviral drug selection pressure, APOBEC-mediated editing, and naturally occurring variation. Our results provide information essential to clinical, research, and public health laboratories performing genotypic resistance testing by sequencing HIV-1 PR, RT, and IN

Predicting the Response to Combination Antiretroviral Therapy: Retrospective Validation of geno2pheno-THEO on a Large Clinical Database

BackgroundExpert-based genotypic interpretation systems are standard methods for guiding treatment selection for patients infected with human immunodeficiency virus type 1. We previously introduced the software pipeline geno2pheno-THEO (g2p-THEO), which on the basis of viral sequence predicts the response to treatment with a combination of antiretroviral compounds by applying methods from statistical learning and the estimated potential of the virus to escape from drug pressure MethodsWe retrospectively validated the statistical model used by g2p-THEO in ∼7600 independent treatment-sequence pairs extracted from the EuResist integrated database, ranging from 1990 to 2007. Results were compared with the 3 most widely used expert-based interpretation systems: Stanford HIVdb, ANRS, and Rega ResultsThe difference in receiver operating characteristic curves between g2p-THEO and expert-based approaches was significant (P<.001; paired Wilcoxon test). Indeed, at 80% specificity, g2p-THEO found 16.2%-19.8% more successful regimens than did the expert-based approaches. The increased performance of g2p-THEO was confirmed in a 2001-2007 data set from which most obsolete therapies had been removed ConclusionFinding drug combinations that increase the chances of therapeutic success is the main reason for using decision support systems. The present analysis of a large data set derived from clinical practice demonstrates that g2p-THEO solves this task significantly better than state-of-the-art expert-based systems. The tool is available at http://www.geno2pheno.or

Constrained patterns of covariation and clustering of HIV-1 non-nucleoside reverse transcriptase inhibitor resistance mutations

Objectives:We characterized pairwise and higher order patterns of non-nucleoside reverse transcriptase inhibi-tor (NNRTI)-selected mutations because multiple mutations are usually required for clinically significant resist-ance to second-generation NNRTIs. Patients and methods: We analysed viruses from 13039 individuals with sequences containing at least one of 52 published NNRTI-selected mutations, including 1133 viruses from individuals who received efavirenz but no other NNRTI and 1510 viruses from individuals who received nevirapine but no other NNRTI. Of the 17 reported etravirine resistance-associated mutations (RAMs), Y181C/I/V, L100I, K101P and M230L were considered major based on published in vitro susceptibility data

Predictors of first-line antiretroviral therapy failure among adults and adolescents living with HIV/AIDS in a large prevention and treatment program in Nigeria.

BACKGROUND: A substantial number of persons living with HIV (PLWH) in Nigeria do not experience durable viral suppression on first-line antiretroviral therapy (ART). Understanding risk factors for first-line treatment failure informs patient monitoring practices and distribution of limited resources for second-line regimens. We determined predictors of immunologic and virologic failures in a large ART delivery program in Abuja, Nigeria. METHODS: A retrospective cohort study was conducted at the University of Abuja Teaching Hospital, a tertiary health care facility, using data from February 2005 to December 2014 in Abuja, Nigeria. All PLWH aged ≥ 15 years who initiated ART with at least 6-month follow-up and one CD4 measurement were included. Immunologic failure was defined as a CD4 decrease to or below pre-ART level or persistent CD4  1000 copies/mL after at least 6 months of ART and enhanced adherence counselling. HIV drug resistance (Sanger sequences) was analyzed using the Stanford HIV database algorithm and scored for resistance to common nucleoside reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs). Univariate and multivariate log binomial regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CIs). RESULTS: Of 12,452 patients followed, a total of 5928 initiated ART with at least 6 months of follow-up and one CD4 measurement. The entry point for 3924 (66.2%) was through the program's own voluntary counseling and testing (VCT) center, while 1310 (22.1%) were referred from an outside clinic/program, 332 (5.6%) in-patients, and 373 (6.3%) through other entry points including prevention of mother to child transmission (PMTCT) and transferred from other programs. The mean CD4 at enrollment in care was 268 ± 23.7 cells per mm3, and the mean HIV-1 RNA was 3.3 ± 1.3.log10 copies/mL. A total of 3468 (80.5%) received nevirapine (NVP) and 2260 (19.5%) received efavirenz (EFV)-based regimens. A total of 2140 (36.1%) received tenofovir (TDF); 2662 (44.9%) zidovudine (AZT); and 1126 (19.0%) stavudine (d4T). Among those receiving TDF, 45.0% also received emtricitabine (FTC). In a multivariate model, immunologic failure was more common among PLWH with female gender as compared to male [RR (95% CI) 1.22 (1.07-1.40)] and less common among those who entered care at the program's VCT center as compared to other entry points [0.79 (0.64-0.91)], WHO stage 3/4 as compared to 1/2 [0.19 (0.16-0.22)], or CD4 200 + cells per mm3 as compared to lower [0.19 (0.16-0.22)]. Virologic failure was more common among PLWH who entered care at the program's VCT center as compared to other entry points [RR (95% CI) 1.45 (1.11-1.91) and those with CD4 < 200 cells per mm3 at entry into care as compared to higher [1.71 (1.36-2.16)]. Of 198 patient-derived samples sequenced during virologic failure, 42 (21%) were wild-type; 145 (73%) carried NNRTI drug resistance mutations; 151 (76.3%) M184I/V; 29 (14.6%) had ≥ 3 TAMs, and 37 (18.7%) had K65R, of whom all were on TDF-containing first-line regimens. CONCLUSIONS: In this cohort of Nigerian PLWH followed for a period of 9 years, immunologic criteria poorly predicted virologic failure. Furthermore, a subset of samples showed that patients failing ART for extended periods of time had HIV-1 strains harboring drug resistance mutations

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 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.Comment: 23 pages, 13 figure