Haplotype Analysis of Hemochromatosis Gene Polymorphisms in Chronic Hepatitis C Virus Infection: A Case Control Study
Bibliographic record
Abstract
BACKGROUND: Chronic hepatitis C virus (HCV) infection is frequently associated with elevated serum iron markers. Polymorphisms in the hemochromatosis (HFE) genes are responsible for iron accumulation in most cases of hemochromatosis, and may play a role in HCV infection. OBJECTIVES: We aimed to assess the prevalence of HFE gene polymorphisms in a group of Iranian HCV-infected patients, and to explore the association of these polymorphisms with HCV infection. PATIENTS AND METHODS: HFE gene polymorphisms were examined in a total of 69 HCV patients and 69 healthy controls using polymerase chain reaction and restriction fragment length polymorphism techniques. Haplotype and diplotype analyses were performed using PHASE software. RESULTS: In a recessive analysis model of the His63Asp (H63D) locus (HH vs. HD + DD), the HH genotype was more common in patients compared to controls (adjusted P = 0.012; OR = 6.42 [95% CI: 1.51 - 27.33]). Also, in a recessive analysis model of the Cys282Tyr (C282Y) locus (CC vs. CY + YY), the CC genotype was more frequent in patients compared to controls (adjusted P = 0.03; OR = 5.06 [95% CI: 1.13 - 22.06]). In addition, there was a significant association between the HC haplotype and the HCDC diplotype and HCV infection. CONCLUSIONS: Polymorphism in the hemochromatosis gene may confer some degree of risk for HCV infection, and individuals carrying the H and C alleles may be susceptible to this disease; however, a larger sample of HCV patients and healthy individuals may be necessary to further illustrate the role of these polymorphisms in HCV.
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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 | 0.001 | 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) | 0.006 | 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".