Association Between miR-146a rs2910164 Polymorphism and Breast CancerSusceptibility: An Updated Meta-Analysis of 9545 Cases and 10030Controls
Bibliographic record
Abstract
BACKGROUND: Several studies have reported a possible association of miR-146a rs2910164 polymorphism with Breast Cancer (BC) development. However, the correlation between this polymorphism and susceptibility to BC is under debate. The current meta-analysis was designed and performed to more conclusively evaluate the miR-146a rs2910164 polymorphism and its potential link to BC. METHODS: Our team has selected eligible studies (published up to October 2, 2020) from several electronic databases, including Web of Science, PubMed, Scopus and Google Scholar. A total number of 9,545 BC cases and 10,030 controls extracted from 26 eligible articles were included in this study. We utilized pooled Odds Ratios (ORs) as well as 95% confidence intervals (95% CIs) under five genetic models for quantitative estimation of any possible association between miR-146a rs2910164 polymorphism and BC. RESULTS: Based on this meta-analysis, our findings suggest that there is no significant association between miR-146a rs2910164 polymorphism and BC risk. However, stratified analysis revealed that the rs2910164 polymorphism significantly increased the risk of BC in hospital-based studies using the homozygous genetic model (OR=1.37, 95%CI=1.01-1.86, p=0.043, CC vs. GG). Neither Asian nor Caucasian populations showed any significant association between rs2910164 polymorphism and BC susceptibility. CONCLUSION: In summary, our findings suggest that BC development is not associated with miR-146a rs2910164 polymorphism. However, larger ingenious future investigations might be needed for a more precise estimation of any association between miR-146a rs2910164 polymorphism and BC.
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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) | 0.003 | 0.001 |
| 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 | 0.001 | 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".