Analysis of transmitted resistance to raltegravir and selective pressure among HIV-1-infected patients on a failing HAART in Sao Paulo, Brazil

Preliminary report of transmitted drug resistance to integrase strand chain transfer inhibitors in treatment-naïve HIV infected patients

Transmitted Resistance exists in a newly diagnosed person who has not yet started their treatment. Our objective was to obtain a profile of HIV-1 resistance to integrase inhibitors in newly diagnosed treatment-naïve patients. Fifty people newly diagnosed with HIV-1 infection who had never received antiretroviral treatment were recruited. The complete integrase gene was amplified by nested RTPCR and the sequences obtained were analyzed with the ReCall and HIVdb v9.0. The overall prevalence transmitted due to mutations with some impact on integrase strand transfer inhibitors (INSTI) activity during the study period was 8%. The major E138K mutation was detected in only 1 patient and the secondary G163R mutation was detected in the other 3. The transmitted resistance for the first generation INSTI was 8% and for the second generation it was 0%. In Chile the resistance transmitted to INSTI is low and it is in according values detect in other part of the world.

Dolutegravir-associated resistance mutations after first-line treatment failure in Brazil

BACKGROUND

Since January 2017, the recommended first-line antiretroviral regimen in Brazil is the fixed-dose combination of tenofovir plus lamivudine with dolutegravir (TL + D). According to the literature, integrase resistance-associated mutations (INRAMs) are rarely found upon virologic failure to first-line dolutegravir plus two nucleoside reverse transcriptase inhibitors. We evaluated the HIV antiretroviral genotypic resistance profile of patients referred for genotyping in the public health system who failed first-line TL + D after at least six months of therapy on or before December 31, 2018.

METHODS

HIV Sanger sequences of the pol gene were generated from plasma of patients with confirmed virologic failure to first-line TL + D in the Brazilian public health system before December 31, 2018.

RESULTS

One hundred thirteen individuals were included in the analysis. Major INRAMs were detected in seven patients (6.19%), four with R263K, one with G118R, one with E138A, and one with G140R. Four patients with major INRAMs also had the K70E and M184V mutations in the RT gene. Sixteen (14.2%) additional individuals presented minor INRAMs, and five (4,42%) patients had both major and minor INRAMS. Thirteen (11.5%) patients also presented mutations in the RT gene selected by tenofovir and lamivudine, including four with both the K70E and M184V mutations and four with only M184V. The integrase mutations L101I and T124A, which are in the in vitro pathway for integrase inhibitor resistance, were found in 48 and 19 patients, respectively. Mutations not related to TL + D, thus probable transmitted resistance mutations (TDR), were present in 28 patients (24.8%): 25 (22.1%) to nucleoside reverse transcriptase inhibitors, 19 (16.8%) to non-nucleoside reverse transcriptase inhibitors, and 6 (5.31%) to protease inhibitors.

CONCLUSIONS

In marked contrast to previous reports, we report a relatively high frequency of INRAMs among selected patients failing first-line TL + D in the public health system in Brazil. Possible reasons for this discrepancy include delays in detecting virologic failure, patients inadvertently on dolutegravir monotherapy, TDR, and/or infecting subtype.

Novel Approaches for Visualizing and Analyzing Dose-Timing Data from Electronic Drug Monitors, or "How the 'Broken Window' Theory Pertains to ART Adherence"

Adherence to antiretroviral medications is usually expressed in terms of the proportion of doses taken. However, the timing of doses taken may also be an important dimension to overall adherence. Little is known about whether patients who mistime doses are also more likely to skip doses. Using data from the completed Adherence for Life randomized controlled trial, we created visual and statistical models to capture and analyze dose timing data collected longitudinally with electronic drug monitors (EDM). From scatter plots depicting dose time versus calendar date, we identified dominant patterns of dose taking and calculated key features [slope of line over calendar date; residual mean standard error (RMSE)]. Each was assessed for its ability to categorize subjects with 'sub-optimal' (<95 % of doses taken) using area under the receiver operating characteristic (AROC) curve analysis. Sixty eight subjects contributed EDM data, with ~300 to 400 observations/subject. While regression line slopes did not predict 'sub-optimal' adherence (AROC 0.51, 95 % CI 0.26-0.75), the variability in dose timing (RMSE) was strongly predictive (AROC 0.79, 95 % CI 0.62-0.97). Compared with the lowest quartile of RMSE (minimal dose time variability), each successive quartile roughly doubled the odds of 'sub-optimal' adherence (OR 2.1, 95 % CI 1.3-3.4). Patterns of dose timing and mistiming are strongly related to overall adherence behavior. Notably, individuals who skip doses are more likely to mistime doses, with the degree of risk positively correlated with the extent of dose timing variability.

HIV-1 integrase resistance among antiretroviral treatment naive and experienced patients from Northwestern Poland

Background

HIV integrase inhibitor use is limited by low genetic barrier to resistance and possible cross-resistance among representatives of this class of antiretrovirals. The aim of this study was to analyse integrase sequence variability among antiretroviral treatment naive and experienced patients with no prior integrase inhibitor (InI) exposure and investigate development of the InI drug resistance mutations following the virologic failure of the raltegravir containing regimen.

Methods

Sequencing of HIV-1 integrase region from plasma samples of 80 integrase treatment naive patients and serial samples from 12 patients with observed virologic failure on raltegravir containing treatment whenever plasma vireamia exceeded >50 copies/ml was performed. Drug resistance mutations were called with Stanford DB database and grouped into major and minor variants. For subtyping bootstrapped phylogenetic analysis was used; Bayesian Monte Carlo Marcov Chain (MCMC) model was implemented to infer on the phylogenetic relationships between the serial sequences from patients failing on raltegravir.

Results

Majority of the integrase region sequences were classified as subtype B; the remaining ones being subtype D, C, G, as well as CRF01_AE , CRF02_AG and CRF13_cpx recombinants. No major integrase drug resistance mutations have been observed in InI-treatment naive patients. In 30 (38.5%) cases polymorphic variation with predominance of the E157Q mutation was observed. This mutation was more common among subtype B (26 cases, 54.2%) than non-B sequences (5 cases, 16.7%), p=0.00099, OR: 5.91 (95% CI:1.77-22.63)]. Other variants included L68V, L74IL, T97A, E138D, V151I, R263K. Among 12 (26.1%) raltegravir treated patients treatment failure was observed; major InI drug resistance mutations (G140S, Q148H and N155H, V151I, E92EQ, V151I, G163R) were noted in four of these cases (8.3% of the total InI-treated patients). Time to the development of drug resistance ranged from 2.6 to 16.3 months with mean increase of HIV viral load of 4.34 (95% CI:1.86-6.84) log HIV-RNA copies/ml at the time of emergence of the major mutations. Baseline polymorphisms, including E157Q were not associated with the virologic failure on raltegravir.

Conclusions

In InI treatment naive patients polymorphic integrase sequence variation was common, with no major resistance mutants. In the treatment failing patients selection of drug resistance occurred rapidly and followed the typical drug resistance pathways. Preexisting integrase polymorphisms were not associated with the treatment failure.