APRISMA-compliant systematic review and meta-analysis determining the association of miRNA polymorphisms and risk of congenital heart disease
Bibliographic record
Abstract
PURPOSE: Recent genetic association studies showed conflicting results on the relationship of miRNA single-nucleotide polymorphisms (SNPs) and congenital heart disease (CHD) risk. The purpose of the present systematic review was to collect the current available evidences to evaluate the association between miRNA polymorphisms and CHD risk. METHODS: Four electronic databases including PubMed, EMBASE, ISI Web of Science, and CENTRAL were extensively searched for relevant studies published before February, 2019. Observational studies determining the association between miRNA polymorphisms and risk of CHD were included. Risk of bias was evaluated using the Newcastle-Ottawa Scale by 2 independent researchers. Major characteristics of each study and estimation of effect size of individual locus polymorphism were summarized. In addition, meta-analysis was performed to quantify the associations between miRNA polymorphisms and CHD risk. RESULTS: Nine studies containing 6502 CHD patients and 6969 healthy controls were included in this systematic review. Ten loci in 9 miRNAs were reported. Only rs11614913 in miR-196a2 was determined to have significant associations with CHD susceptibility, which was supported by meta-analysis (CC vs CT+TT: odds ratio 1.54, 95% confidence interval 1.30, 1.82; P < .00001). A strong evidence indicated lack of association between rs2910164 in miR-146a and CHD. Limited or conflicting evidences were found for the associations of the other variants (rs11134527, rs139365823, rs76987351, rs3746444, rs4938723, rs2292832, rs41291957, rs895819) and risk of CHD. CONCLUSIONS: Locus polymorphisms in miRNAs are not generally associated with CHD. Only rs11614913 was found to have significant associations with CHD. Further studies will be needed, using larger populations of different ethnicities, to obtain a better understanding of these associations.
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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 | 0.028 | 0.083 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.027 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".