<i>MSX1</i> gene polymorphisms and non‐syndromic cleft lip with or without palate (NSCL/P): A meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: Non-syndromic cleft lip, with or without cleft palate (NSCL/P), is a common craniofacial birth defect, the risk of which is influenced from multiple genetic loci. Association study outcomes between single nucleotide polymorphisms (SNPs) near the muscle segment homeobox gene 1 (MSX1) and NSCL/P have been inconsistent. This compels a meta-analysis to obtain more precise estimates. METHODS: From 15 publications, we examined 12 SNPs under six groups (SG), based on linkage disequilibrium. Pooled odds ratios and 95% confidence intervals were calculated under the standard genetic models. The pooled effects were subjected to subgroup, outlier, sensitivity, and funnel plot (publication bias) analyses. RESULTS: Three of the six SGs showed significant associations. SG1 and SG4 effects indicated reduced risks. SG1 outcomes were attributed to outlier treatment, which the Asian outcomes validated. In contrast, increased risks were observed in SG3. All these significant outcomes were deemed robust by sensitivity analysis with no evidence of publication bias. CONCLUSIONS: Our study shows eight MSX1 SNPs associated with risk of NSCL/P. SG1 and SG4 carriers are protected (up to 23%), but SG3 carriers are 1.3-fold susceptible. Outlier treatment unmasked the significant associations in SG1. Non-heterogeneity and robustness helped elevate the level of evidence in our significant findings.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.041 |
| Bibliometrics | 0.003 | 0.004 |
| 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) | 0.004 | 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".