HIV-1 resistance against dolutegravir fluctuates rapidly alongside erratic treatment adherence: a case report
Bibliographic record
Abstract
OBJECTIVES: We report a case of incomplete HIV-1 suppression on a dolutegravir, lamivudine, and abacavir single-tablet regimen with the emergence of the H51Y and G118R integrase resistance mutations. METHODS: Integrase sequencing was performed retrospectively by Sanger and next-generation sequencing. Rates of emergence and decline of resistance mutations were calculated using next-generation sequencing data. Dolutegravir plasma concentrations were measured by ultra-performance liquid chromatography-tandem mass spectrometry. The effects of H51Y and G118R on infectivity, fitness, and susceptibility to dolutegravir were quantified using cell-based assays. RESULTS: During periods of non-adherence to treatment, mutations were retrospectively documented only by next-generation sequencing. Misdiagnosis by Sanger sequencing was caused by the rapid decline of mutant strains within the retroviral population. This observation was also true for a M184V lamivudine-resistant reverse transcriptase mutation found in association with integrase mutations on single HIV genomes. Resistance rebound upon treatment re-initiation was swift (>8000 copies per day). Next-generation sequencing indicated cumulative adherence to treatment. Compared to WT HIV-1, relative infectivity was 73%, 38%, and 43%; relative fitness was 100%, 35%, and 10% for H51Y, G118R, and H51Y+G118R viruses, respectively. H51Y did not change the susceptibility to dolutegravir, but G188R and H51Y+G118R conferred 7- and 28-fold resistance, respectively. CONCLUSION: This case illustrates how poorly-fit drug-resistant viruses wax and wane alongside erratic treatment adherence and are easily misdiagnosed by Sanger sequencing. We recommend next-generation sequencing to improve the clinical management of incomplete virological suppression with dolutegravir.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".