Integrase strand transfer inhibitor (INSTI)-resistance mutations for the surveillance of transmitted HIV-1 drug resistance
Bibliographic record
Abstract
BACKGROUND: Integrase strand transfer inhibitors (INSTIs) are expected to be widely adopted globally, requiring surveillance of resistance emergence and transmission. OBJECTIVES: We therefore sought to develop a standardized list of INSTI-resistance mutations suitable for the surveillance of transmitted INSTI resistance. METHODS: To characterize the suitability of the INSTI-resistance mutations for transmitted HIV-1 drug resistance (TDR) surveillance, we classified them according to their presence on published expert lists, conservation in INSTI-naive persons, frequency in INSTI-treated persons and contribution to reduced in vitro susceptibility. Mutation prevalences were determined using integrase sequences from 17302 INSTI-naive and 2450 INSTI-treated persons; 53.3% of the INSTI-naive sequences and 20.0% of INSTI-treated sequences were from non-B subtypes. Approximately 10% of sequences were from persons who received dolutegravir alone or a first-generation INSTI followed by dolutegravir. RESULTS: Fifty-nine previously recognized (or established) INSTI-resistance mutations were present on one or more of four published expert lists. They were classified into three main non-overlapping groups: 29 relatively common non-polymorphic mutations, occurring in five or more individuals and significantly selected by INSTI treatment; 8 polymorphic mutations; and 22 rare mutations. Among the 29 relatively common INSTI-selected mutations, 24 emerged as candidates for inclusion on a list of INSTI surveillance drug-resistance mutations: T66A/I/K, E92G/Q, G118R, F121Y, E138A/K/T, G140A/C/S, Y143C/H/R/S, S147G, Q148H/R/K, N155H, S230R and R263K. CONCLUSIONS: A set of 24 non-polymorphic INSTI-selected mutations is likely to be useful for quantifying INSTI-associated TDR. This list may require updating as more sequences become available from INSTI-experienced persons infected with HIV-1 non-subtype B viruses and/or receiving dolutegravir.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".