Association between miRNA‐146a rs2910164 (G/C) polymorphism with the susceptibility to chronic HBV infection and spontaneous viral clearance in an Iranian population
Bibliographic record
Abstract
Hepatitis B virus (HBV) infection is one of the clinical dilemmas in chronic liver diseases. MicroRNAs (miRNAs) are small noncoding RNA molecules that play an important role in the pathogenesis of liver diseases and single nucleotide polymorphisms (SNPs) in miRNA genes affect the clinical course of HBV infection. Previous studies have shown that miRNA-146a rs2910164 polymorphism can be associated with the pathogenesis of liver diseases such as hepatocellular carcinoma. The present study investigated the association between miRNA-146a rs2910164 polymorphism and susceptibility to HBV infection in an Iranian population. The study comprised 266 patients with chronic HBV infection, 172 patients with spontaneous viral clearance (SVC) after acute HBV infection, and 266 healthy control adjusted for sex and age. The genotyping of the miRNA-146a rs2910164 polymorphism was performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Our data revealed that GG genotype and G allele of miRNA-146a rs2910164 SNP is dominated (P < 0.001) in patients with chronic HBV infection (Odds ratio [OR] = 3.92; 95% confidence interval [CI] = 2.1-7.32). miRNA-146a rs2910164 polymorphism showed a statistically significant association (P < 0.001) between CC genotype and allele C with SVC (OR = 2.92; 95% CI = 1.56-546). Our findings suggest miRNA-146a SNP (C/G) in our population may be associated with the susceptibility to HBV infection and CC genotype is associated with SVC. Also, the GG genotype and G allele at miRNA-146a rs2910164 is associated with chronic HBV infection in our population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".