Favourable IFNL3 Genotypes Are Associated with Spontaneous Clearance and Are Differentially Distributed in Aboriginals in Canadian HIV-Hepatitis C Co-Infected Individuals
Bibliographic record
Abstract
Canadian Aboriginals are reported to clear Hepatitis C (HCV) more frequently. We tested the association of spontaneous clearance and three single nucleotide polymorphisms (SNPs) near the Interferon-lambda 3 (IFNL3) gene (rs12979860, rs8099917, functional variant rs8103142) and compared the SNP frequencies between HIV-HCV co-infected whites and Aboriginals from the Canadian Co-infection Cohort. HCV treatment-naïve individuals with at least two HCV RNA tests were included (n = 538). A spontaneous clearance case was defined as someone with two consecutive HCV RNA-negative tests, at least six months apart. Data were analyzed using Cox proportional hazards adjusted for sex and ethnicity. Advantageous variants and haplotypes were more common in Aboriginals than Caucasians: 57% vs. 46% had the rs12979860 CC genotype, respectively; 58% vs. 48%, rs8103142 TT; 74% vs. 67%, the rs12979860 C allele; and 67% vs. 64% the TCT haplotype with three favourable alleles. The adjusted Hazard Ratios (95% CI) for spontaneous clearance were: rs12979860: 3.80 (2.20, 6.54); rs8099917: 5.14 (2.46, 10.72); and rs8103142: 4.36 (2.49, 7.62). Even after adjusting for rs12979860, Aboriginals and females cleared HCV more often, HR (95% CI) = 1.53 (0.89, 2.61) and 1.42 (0.79, 2.53), respectively. Our results suggest that favourable IFNL3 genotypes are more common among Aboriginals than Caucasians, and may partly explain the higher HCV clearance rates seen among Aboriginals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".