Pre-treatment integrase inhibitor resistance is uncommon in antiretroviral therapy-naive individuals with HIV-1 subtype A1 and D infections in Uganda
Bibliographic record
Abstract
OBJECTIVE: Dolutegravir (DTG) is now a preferred component of first-line antiretroviral therapy (ART). However, prevalence data on natural resistance to integrase inhibitors [integrase strand transfer inhibitors (INSTIs)] in circulating non-subtype B HIV-1 in sub-Saharan Africa is scarce. Our objective is to report prevalence of pre-treatment integrase polymorphisms associated with resistance to INSTIs in an ART-naive cohort with diverse HIV-1 subtypes. DESIGN: We retrospectively examined HIV-1 integrase sequences from Uganda. METHODS: Plasma samples were derived from the Uganda AIDS Rural Treatment Outcomes (UARTO) cohort, reflecting enrollment from 2002 to 2010, prior to initiation of ART. HIV-1 integrase was amplified using nested-PCR and Sanger-sequenced (HXB2 4230-5093). Stanford HIVdb v8.8 was used to infer clinically significant INSTI-associated mutations. Human leukocyte antigen (HLA) typing was performed for all study participants. RESULTS: Plasma samples from 511 ART-naive individuals (subtype: 48% A1, 39% D) yielded HIV-1 integrase genotyping results. Six out of 511 participants (1.2%) had any major INSTI-associated mutations. Of these, two had E138T (subtype A1), three had E138E/K (subtype D), and one had T66T/I (subtype D). No participants had mutations traditionally associated with high levels of INSTI resistance. HLA genotypes A∗02:01/05/14, B∗44:15, and C∗04:07 predicted the presence of L74I, a mutation recently observed in association with long-acting INSTI cabotegravir virologic failure. CONCLUSION: We detected no HIV-1 polymorphisms associated with high levels of DTG resistance in Uganda in the pre-DTG era. Our results support widespread implementation of DTG but careful monitoring of patients on INSTI with virologic failure is warranted to determine if unique mutations predict failure for non-B subtypes of HIV-1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".