Associations of human leukocyte antigen-G with resistance and susceptibility to HIV-1 infection in the Pumwani sex worker cohort
Bibliographic record
Abstract
OBJECTIVE: To determine the association between human leukocyte antigens (HLA)-G genotypes and resistance or susceptibility to HIV-1. DESIGN: A group of sex workers in Pumwani, Kenya can be epidemiologically defined as resistant to HIV-1 infection despite frequent exposure and provide an example of natural protective immunity. HLA class I and II molecules have been shown to be associated with resistance/susceptibility to infection in this cohort. HLA-G is a nonclassical class I allele that is primarily involved in mucosal and inflammatory response, which is of interest in HIV-1 resistance. METHODS: In this study, we used a sequence-based typing method to genotype HLA-G for 667 women enrolled in this cohort and examined the influence of HLA-G genotypes on resistance or susceptibility to HIV-1 infection. RESULTS: The G*01 : 01:01 genotype was significantly enriched in the HIV-1-resistant women [P = 0.002, Odds ratio: 2.11, 95% confidence interval (CI): 0.259-0.976], whereas the G*01 : 04:04 genotype was significantly associated with susceptibility to HIV-1 infection (P = 0.039, OR:0.502, 95% CI:0.259-0.976). Kaplan-Meier survival analysis correlated with these results. G*01 : 01:01 genotype was associated with significantly lower rate of seroconversion (P = 0.001). Whereas, G*01 : 04:04 genotype was significantly associated with an increased rate of seroconversion (P = 0.013). The associations of these HLA-G alleles are independent of other HLA class I and II alleles identified in this population. CONCLUSION: Our study showed that specific HLA-G alleles are associated with resistance or susceptibility to HIV-1 acquisition in this high-risk population. Further studies are needed to understand its functional significance in HIV-1 transmission.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".