Subtype diversity associated with the development of HIV‐1 resistance to integrase inhibitors
Bibliographic record
Abstract
We used genotypic and phylogenetic analysis to determine integrase diversity among subtypes, and studied natural polymorphisms and mutations implicated in resistance to integrase inhibitors (INI) in treatment-naïve persons (n = 220) and -experienced individuals (n = 24). Phylogenetics revealed 7 and 10% inter-subtype diversity in the integrase and reverse transcriptase (RT)/protease regions, respectively. Integrase sequencing identified a novel A/B recombinant in which all viruses in a male-sex-male (MSM) transmission cluster (n = 12) appeared to possess subtype B in integrase and subtype A in the remainder of the pol region. Natural variations and signature polymorphisms were observed at codon positions 140, 148, 151, 157, and 160 among HIV subtypes. These variations predicted higher genetic barriers to G140S and G140C in subtypes C, CRF02_AG, and A/CRF01_AE, as well as higher genetic barriers toward acquisition of V151I in subtypes CRF02_AG and A/CRF01_AE. The E157Q and E160Q mutational motif was observed in 35% of INI-naïve patients harboring subtype C infections, indicating intra-subtype variations. Thirteen patients failed raltegravir (RAL)-containing regimens within 8 ± 1 months, in association with the major Q148K/R/H and G140A/S (n = 8/24) or N155H (n = 5/24) mutational pathways. Of note, the remaining patients on RAL regimens for 14 ± 3 months harbored no or only minor integrase mutations/polymorphisms (T66I, T97A, H114P, S119P, A124S, G163R, I203M, R263K). These results demonstrate the importance of understanding subtype variability in the development of resistance to INIs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".