Association of pre-miRNA-146a rs2910164 and pre-miRNA-499 rs3746444 polymorphisms and susceptibility to rheumatoid arthritis
Bibliographic record
Abstract
Single nucleotide polymorphisms in pre‑microRNA (miRNA) may alter miRNA expression levels or processing and contribute to susceptibility in a wide range of diseases. The present study aimed to evaluate the possible association between rs2910164 and rs3746444 of the pre-miRNA (hsa-mir-146a and hsa-mir-499) polymorphisms and susceptibility to rheumatoid arthritis (RA) in an Iranian population. This case-control study was performed on 104 patients with RA and 110 healthy individuals. Tetra amplification refractory mutation system-polymerase chain reaction was used to genotype the hsa-mir-499 rs3746444 and hsa-mir-146a rs2910164 polymorphisms. The hsa-mir-499 rs3746444 polymorphism was a risk factor for predisposition to RA in codominant [TT vs. TC: odds ratio (OR), 2.11; 95% confidence interval (CI), 1.08-4.11; p=0.029; TT vs. CC: OR, 3.88; 95% CI, 1.68-8.98; p=0.002], dominant (TT vs. TC-CC: OR, 2.64; 95% CI, 1.48-4.72; p=0.001) and recessive (TC-CC vs. CC: OR, 3.05; 95% CI, 1.36-6.83; p=0.007) tested inheritance models. In addition, the rs3746444 C allele was a risk factor for RA (OR, 2.49; 95% CI, 1.63-3.81; p<0.0001). No significant difference was found between the groups concerning the rs2910164 polymorphism (χ2=0.348, p=0.841). Our findings demonstrated that the hsa-mir-499 rs3746444, but not mir-146a rs2910164, polymorphism is associated with an increased RA risk in a sample of the Iranian population. Larger studies with different ethnicities are required to validate our findings.
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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) | 0.000 | 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".