Novel variant in glycophorin c gene protects against ribavirin-induced anemia during chronic hepatitis C treatment
Bibliographic record
Abstract
The current use of ribavirin in difficult-to-cure chronic hepatitis C patients (HCV) and patients with severe respiratory infections is constrained by the issue of ribavirin-induced hemolytic anemia that affects 30% of treated patients, requiring dosage modification or discontinuation. Though some genetic variants have been identified predicting this adverse effect, known clinical and genetic factors do not entirely explain the risk of ribavirin-induced anemia. We assessed the associations of previously identified variants in inosine triphosphatase (ITPA), solute carrier 28A2 (SLC28A2) and vitamin D receptor (VDR) genes with ribavirin-induced anemia defined as hemoglobin decline of ≥30 g/L on treatment, followed by a staged discovery (n = 114), replication (n = 74), and combined (n = 188) genome-wide association study to uncover potential new predictive variants. We identified a novel association in the gene coding glycophorin C (rs6741425; OR:0.12, 95%CI:0.04–0.34, P = 2.94 × 10-6) that predicts protection against ribavirin-induced anemia. We also replicated the associations of ITPA and VDR genetic variants with the development of ribavirin-induced anemia (rs1127354; OR:0.13, 95%CI:0.04–0.41, P = 8.66 ×10-5; and rs1544410; OR:1.65, 95%CI:1.01–2.70, P = 0.0437). GYPC variation affecting erythrocyte membrane strength is important in predicting risk for developing ribavirin-induced anemia. ITPA and VDR genetic variants are also important predictors of this adverse reaction.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".