A systematic investigation of the contribution of genetic variation within the MHC region to HPV seropositivity
Bibliographic record
Abstract
High-risk mucosal types of human papillomavirus (HPV) cause anogenital and oropharyngeal cancers, whereas cutaneous types (e.g. HPV8 and 77) are suspected to be involved in non-melanoma skin cancer. The antibody response to HPVs is a key determinant of protective immunity, but not all infected individuals seroconvert. Genetic variability of the host may have large impact on seroconversion. A previous genome-wide association study (GWAS) has identified a susceptibility locus (rs41270488) for HPV8 seropositivity within the major histocompatibility complex (MHC) region. To further study this locus, we imputed alleles at classical leukocyte antigen (HLA) loci using HLA*IMP:02 with a reference panel from the HapMap Project and the 1958 Birth Cohort, and conducted an integrated analysis among 4811 central European subjects to assess the contribution of classical HLA alleles and gene copy number variation (CNV) at the hypervariable DRB locus within the MHC region to HPV seropositivity at both the individual HPV type level and the phylogenetic species level. Our study provides evidence that the association noted between rs41270488 and HPV8 seropositivity is driven by two independent variants, namely DQB1*0301 [odds ratio (OR) = 1.51, 95% confidence interval (CI) = 1.36-1.68, P = 1.0 × 10(-14)] and DRB1*1101 (OR = 1.89, 95%CI = 1.57-2.28, P = 1.5 × 10(-11)) within the HLA class II region. Additionally, we identified two correlated alleles DRB1*0701 (OR = 1.67, 95%CI = 1.41-1.98, P = 2.6 × 10(-9)) and DQA1*0201 (OR = 1.67, 95%CI = 1.38-1.93, P = 1.7 × 10(-8)), to be associated with HPV77 seropositivity. Comparable results were observed through imputation using SNP2HLA with another reference panel from the Type 1 diabetes Genetics Consortium. This study provides support for an important role of HLA class II alleles in antibody response to HPV infection.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".