Polymorphisms in IRF-1 associated with resistance to HIV-1 infection in highly exposed uninfected Kenyan sex workers
Bibliographic record
Abstract
OBJECTIVE: To determine the correlation between polymorphisms in the IL-4 gene cluster and resistance to HIV-1 infection. DESIGN: : A cross-sectional genetic analysis of polymorphisms within the IL-4 gene cluster was conducted in a well-described female sex worker cohort from Nairobi, Kenya, known to exhibit differential susceptibility to HIV-1 infection. METHODS: Microsatellite genotyping was used to screen six microsatellite markers in the IL-4 gene cluster for associations with HIV-1 resistance. Further analysis of the interferon regulatory factor 1 (IRF-1) gene was conducted by genomic sequencing. Associations between IRF-1 gene polymorphisms and the HIV-1 resistance phenotype were determined using the chi-square test and Kaplan-Meier survival analysis. The functional consequence of IRF-1 polymorphism was conducted by quantitative Western blot. RESULTS: Three polymorphisms in IRF-1, located at 619, the microsatellite region and 6516 of the gene, showed associations with resistance to HIV-1 infection. The 619A, 179 at IRF-1 microsatellite and 6516G alleles were associated with the HIV-1-resistant phenotype and a reduced likelihood of seroconversion. Peripheral blood mononuclear cells from patients with protective IRF-1 genotypes exhibited significantly lower basal IRF-1 expression and reduced responsiveness to exogenous IFN-gamma stimulation. CONCLUSION: Polymorphisms in the IRF-1 gene are associated with resistance to infection by HIV-1 and a lowered level of IRF-1 protein expression. This study adds IRF-1, a transcriptional immunoregulatory gene, to the list of genetic correlates of altered susceptibility to HIV-1. This is the first report suggesting that a viral transcriptional regulator might contribute to resistance to HIV-1. Further functional analysis on the role of IRF-1 polymorphisms and HIV-1 resistance is underway.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".