Extensive host immune adaptation in a concentrated North American HIV epidemic
Bibliographic record
Abstract
OBJECTIVE: HIV incidence in the Canadian province of Saskatchewan, where Indigenous persons make up 80% of those infected, are among the highest on the continent. Reports of accelerated HIV progression, associated with carriage of certain human leukocyte antigen (HLA) alleles (including the typically protective HLA-B*51) have also emerged from the region. Given that acquisition of HIV preadapted to host HLA negatively impacts clinical outcome, we hypothesized that HIV-host adaptation may be elevated in Saskatchewan. DESIGN: Comparative analysis of population-level HIV sequence datasets from Saskatchewan and elsewhere in Canada/USA. METHODS: We analyzed 1144 HIV subtype B Pol sequences collected in Saskatchewan between 2000 and 2016, comprising ∼65% of cumulative provincial HIV cases, for the presence of 70 HLA-associated Pol mutations. Sequences from British Columbia (N = 6525) and elsewhere in Canada/USA (N = 6517) were used for comparison. HIV adaptation levels to 34 HLA alleles were also computed. Putative HIV transmission clusters were identified, and the prevalence of HLA-associated adaptations within and outside these clusters was investigated. RESULTS: Analyses confirmed significantly elevated and temporally increasing levels of HIV adaptation to commonly expressed HLA alleles, in particular B*51. Notably, HLA-adapted HIV strains were significantly enriched among phylogenetic clusters in Saskatchewan. CONCLUSION: Extensive circulating HIV adaptation to HLA in Saskatchewan provides a plausible explanation for accelerated progression, while enrichment of adapted variants in phylogenetic clusters suggests they are being widely transmitted. Results highlight the utility of Pol sequences, routinely collected for drug resistance monitoring, for surveillance of HIV-host adaptation, and underscore the urgent need to expand HIV prevention and treatment programmes in Saskatchewan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".