Neutralizing antibodies to interferon alfa arising during peginterferon therapy of chronic hepatitis B in children and adults: Results from the HBRN Trials
Bibliographic record
Abstract
BACKGROUND AIMS: Pegylated interferon-α (PegIFNα) is of limited utility during immunotolerant or immune active phases of chronic hepatitis B infection but is being explored as part of new cure regimens. Low/absent levels of IFNα found in some patients receiving treatment are associated with limited/no virological responses. The study aimed to determine if sera from participants inhibit IFNα activity and/or contain therapy-induced anti-IFNα antibodies. APPROACH RESULTS: Pre-treatment, on-treatment, and post-treatment sera from 61 immunotolerant trial participants on PegIFNα/entecavir therapy and 88 immune active trial participants on PegIFNα/tenofovir therapy were screened for anti-IFNα antibodies by indirect ELISA. The neutralization capacity of antibodies was measured by preincubation of sera±recombinant human IFNα added to Huh7 cells with the measurement of interferon-stimulated gene (ISG)-induction by qPCR. Correlations between serum-induced ISG inhibition, presence, and titer of anti-IFNα antibodies and virological responses were evaluated. Preincubation of on-treatment serum from 26 immunotolerant (43%) and 13 immune active (15%) participants with recombinant-human IFNα markedly blunted ISG-induction in Huh7 cells. The degree of ISG inhibition correlated with IFNα antibody titer ( p < 0.0001; r = 0.87). On-treatment development of anti-IFNα neutralizing antibodies (nAbs) was associated with reduced quantitative HBsAg and qHBeAg declines ( p < 0.05) and inhibited IFNα bioactivity to 240 weeks after PegIFNα cessation. Children developed anti-IFNα nAbs more frequently than adults ( p = 0.004) but nAbs in children had less impact on virological responses. CONCLUSIONS: The development of anti-IFNα nAbs during PegIFNα treatment diminishes responses to antiviral therapy. Understanding how and why anti-IFNα antibodies develop may allow for the optimization of IFN-based therapy, which is critical given its renewed use in HBV-cure strategies.
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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 | 0.001 | 0.001 |
| 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".