Gag-Protease-Mediated Replication Capacity in HIV-1 Subtype C Chronic Infection: Associations with HLA Type and Clinical Parameters
Bibliographic record
Abstract
The mechanisms underlying HIV-1 control by protective HLA class I alleles are not fully understood and could involve selection of escape mutations in functionally important Gag epitopes resulting in fitness costs. This study was undertaken to investigate, at the population level, the impact of HLA-mediated immune pressure in Gag on viral fitness and its influence on HIV-1 pathogenesis. Replication capacities of 406 recombinant viruses encoding plasma-derived Gag-protease from patients chronically infected with HIV-1 subtype C were assayed in an HIV-1-inducible green fluorescent protein reporter cell line. Viral replication capacities varied significantly with respect to the specific HLA-B alleles expressed by the patient, and protective HLA-B alleles, most notably HLA-B81, were associated with lower replication capacities. HLA-associated mutations at low-entropy sites, especially the HLA-B81-associated 186S mutation in the TL9 epitope, were associated with lower replication capacities. Most mutations linked to alterations in replication capacity in the conserved p24 region decreased replication capacity, while most in the highly variable p17 region increased replication capacity. Replication capacity also correlated positively with baseline viral load and negatively with baseline CD4 count but did not correlate with the subsequent rate of CD4 decline. In conclusion, there is evidence that protective HLA alleles, in particular HLA-B81, significantly influence Gag-protease function by driving sequence changes in Gag and that conserved regions of Gag should be included in a vaccine aiming to drive HIV-1 toward a less fit state. However, the long-term clinical benefit of immune-driven fitness costs is uncertain given the lack of correlation with longitudinal markers of disease progression.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".