Clearance of asymptomatic genital HPV infections in young adult women is shaped by host immune response
Bibliographic record
Abstract
Abstract Persistent infection with high-risk human papillomavirus (HPV) genotypes is an etiological factor in many cancers. The vast majority of HPV infections clear spontaneously within two years but the underlying mechanisms leading to this clearance remain unclear. Building on the PAPCLEAR longitudinal study, which followed young adult women with genital HPV infections, we analysed 100 vaginal swabs from 40 participants using quantitative bulk RNA sequencing to identify potential host transcriptomic signatures associated with infection clearance. Using a Gene Set Enrichment Analysis (GSEA) to detect significantly enriched pathways across infection outcome categories, we find that HPV-positive samples are characterised by a downregulation in both antiviral innate and adaptive immune responses. Independently of the genotype, non-clearing infections stand out by their adaptive immune response activation, which is surprisingly downregulated in persisting infections. This represents one of the rare transcriptomic analyses of asymptomatic HPV infection clearance. It stresses the key role of adaptive immunity, which represents a promising target for future diagnostics or immunotherapies. Author Summary Study motivation Human papillomavirus (HPV) is one of the most prevalent sexually transmitted infections worldwide. Most HPV infections resolve spontaneously within about two years, but the mechanisms that drive natural clearance remain poorly understood. Persistent infection with certain high-risk HPV types can lead to precancerous lesions and, more rarely, cervical and other cancers. Study design and findings We used data from the PAPCLEAR study, a longitudinal cohort of young women with genital HPV infections, and analysed gene expression profiles from vaginal swabs collected from 40 participants. By comparing samples from cleared, persistent, and HPV-negative infections, we found that HPV positivity was associated with reduced expression of antiviral immune defences. Infections that did not clear showed stronger activation of adaptive immune pathways compared with clearing infections. Conclusions HPV-positive infections are associated with weakened antiviral immune responses. Non-clearing infections show activation of adaptive immunity.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".