Association of miR polymorphisms with coronary artery disease risk: a comprehensive meta-analysis
Bibliographic record
Abstract
Abstract Background Cardiovascular disease (CVD) is the leading cause of mortality worldwide, with coronary artery disease (CAD) being the most prevalent type caused by atherosclerosis. Genetic factors contribute to 40–60% of CAD susceptibility. miRNAs have emerged as potential biomarkers due to their regulatory roles in cardiovascular pathways. miR-146a, miR-149, miR-196a2, and miR-499 are linked to CAD, influencing inflammation, endothelial dysfunction, and lipid metabolism. Additionally, miR-21, miR-126, and miR-155 have been studied in myocardial infarction and heart failure, highlighting their diagnostic relevance. Identifying miRNA polymorphisms associated with CAD may improve prognostic indicators and treatment strategies. Methods This study aimed to investigate the association between miRNA polymorphisms and CAD through a comprehensive meta-analysis using data from PubMed, Scopus, Web of Science, and Embase. Inclusion criteria involved case–control studies with genotyping data on CAD/ Acute Coronary Syndrome (ACS) risk. Heterogeneity was evaluated with the I 2 , tau 2 , Q score and H values, and the Newcastle–Ottawa Scale assessed study quality. For statistical analysis, odds ratio of miRNA SNPs reported in three or more studies were calculated. Results A total of 276 studies were identified, of which 10 met the inclusion criteria for meta-analysis. Among the 13 miRNA SNPs reported, only three (rs2910164, rs11614913, and rs3746444) were included in the meta-analysis, as they were examined in three or more studies. rs2910164 (miR-146a) showed a significant association with CAD risk in the homozygous (OR: 0.79, 95% CI 0.63–1.00), heterozygous (OR: 0.88, 95% CI 0.79–0.99), and dominant models (OR: 0.86, 95% CI 0.75–0.99), suggesting a potential protective role. However, rs11614913 (miR-196a2) and rs3746444 (miR-499) did not show significant associations with CAD risk. Publication bias analysis revealed potential bias in the allele, homozygote, and recessive models of rs11614913. In-silico analysis identified weakly validated common targets among miR-146a, miR-196a, and miR-499, with KEGG pathway analysis highlighting key pathways, including cell cycle regulation and adherens junctions, involved in CAD pathogenesis. Conclusion The results obtained suggests that rs2910164 maybe be associated with increased risk of CAD. Given the limitations listed above, further research with bigger sample sizes are required to definitely identify the connection between miRNA variations and the risk of CAD.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.045 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".