The association of HLA-G polymorphism with oral and genital HPV infection in men
Bibliographic record
Abstract
The host genetic factors that influence the natural history of human papillomavirus (HPV) infection in men are not well known. Our aim was to evaluate the role of human leukocyte antigen (HLA)-G polymorphism in oral and genital HPV infection in men. Altogether, 130 men from the Finnish Family HPV Study, with a 6-year follow-up, were included in the analyses. HLA-G alleles were tested by direct sequencing. Oral, urethral, and semen samples were collected and analyzed for 24 different HPV genotypes. Unconditional logistic regression was used to determine associations between HLA-G alleles and genotypes with HPV infection and its outcomes. Overall, eight different HLA-G alleles were identified with 15 different HLA-G genotype combinations. The most common HLA-G allele among the men was G*01:01:01 (86.2%, n = 112) followed by G*01:01:02 (36.2%, n = 47). Allele G*01:01:02 showed to be protective against any- and high-risk (HR) oral HPV (OR range of 0.20-0.24, 95% CI range of 0.06-0.85). Men having allele G*01:01:01 showed a reduced risk for incident (OR 0.30, 95% CI 0.11-0.84) and persistent (OR 0.24, 95% CI 0.08-0.69) oral infections. Allele G*01:01:03 was associated with increased risk for urethral HR-HPV infections (OR 4.94, 95% CI 1.34-18.27). Among self-reported demographic data, genotype G*01:01:01/01:01:03 was associated with an increased risk for oral warts (OR 8.00, 95% CI 1.23-51.89) and allele G*01:03:01 increased the risk of pollen and/or animal allergy (OR 13.59, 95% CI 1.57-117.25). To conclude, HLA-G polymorphism in men largely impacts the outcome of an oral HPV infection and seems to associate with self-reported allergies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".