Association of the <i>WNT3</i> polymorphisms and non-syndromic cleft lip with or without cleft palate: evidence from a meta-analysis
Bibliographic record
Abstract
Objective: This meta-analysis was conducted with the aim of investigating the association between WNT3 gene polymorphisms and non-syndromic cleft lip (CL) with or without cleft palate (NSCL/P) predisposition. Methods: A comprehensive literature search was performed in six online databases including PubMed, Embase, ISI Web of Science, CENTRAL, CNKI, and Wanfang from inception up to June 2018 without language restriction. Pooled odds ratios (ORs) and corresponding 95% confidence intervals (95%CIs) were calculated under allele model of inheritance to indicate the association between WNT3 polymorphisms and NSCL/P. Risk of bias was assessed through the Newcastle–Ottawa scale (NOS). Predetermined stratified and sensitivity analyses were performed using the RevMan 5.3 software, publication bias were evaluated by Egger’s and Begg’s tests. Results: Seven case–control studies comprising 1617 NSCL/P patients and 2143 healthy controls were identified and included in the present study, a total of eight loci were investigated in the present study: rs3809857 was significantly associated with NSCL/P vulnerability (G compared with T, OR = 1.34, 95%CI: 1.15–1.56, P=0.0001), a significant association between rs9890413 polymorphism and NSCL/P susceptibility (A compared with G, OR = 1.25, 95%CI: 1.06–1.47, P=0.007) was detected as well. Since only few studies reported detailed data about the association between rs142167, rs7207916, rs199498, rs111769, rs12452064, rs11653738, and NSCL/P risk, these results were not combined using meta-analysis. Conclusion: Based on the findings of our current study, the rs3809857 and rs9890413 polymorphisms of WNT3 appeared to be associated with NSCL/P. Limited evidence is found to support the association between other WNT3 polymorphisms and risk of NSCL/P.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.044 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".