Analysis of Hepatitis B Virus Haplotype Diversity Detects Striking Sequence Conservation Across Genotypes and Chronic Disease Phase
Bibliographic record
Abstract
BACKGROUND AND AIMS: We conducted haplotype analysis of complete hepatitis B virus (HBV) genomes following deep sequencing from 368 patients across multiple phases of chronic hepatitis B (CHB) infection from four major genotypes (A-D), analyzing 4,110 haplotypes to identify viral variants associated with treatment outcome and disease progression. APPROACH AND RESULTS: Between 18.2% and 41.8% of nucleotides and between 5.9% and 34.3% of amino acids were 100% conserved in all genotypes and phases examined, depending on the region analyzed. Hepatitis B e antigen (HBeAg) loss by week 192 was associated with different haplotype populations at baseline. Haplotype populations differed across the HBV genome and CHB history, this being most pronounced in the precore/core gene. Mean number of haplotypes (frequency) per patient was higher in immune-active, HBeAg-positive chronic hepatitis phase 2 (11.8) and HBeAg-negative chronic hepatitis phase 4 (16.2) compared to subjects in the "immune-tolerant," HBeAg-positive chronic infection phase 1 (4.3, P< 0.0001). Haplotype frequency was lowest in genotype B (6.2, P< 0.0001) compared to the other genotypes (A = 11.8, C = 11.8, D = 13.6). Haplotype genetic diversity increased over the course of CHB history, being lowest in phase 1, increasing in phase 2, and highest in phase 4 in all genotypes except genotype C. HBeAg loss by week 192 of tenofovir therapy was associated with different haplotype populations at baseline. CONCLUSIONS: Despite a degree of HBV haplotype diversity and heterogeneity across the phases of CHB natural history, highly conserved sequences in key genes and regulatory regions were identified in multiple HBV genotypes that should be further investigated as targets for antiviral therapies and predictors of treatment response.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".