Genetic Variability of <i>IRF6</i> Polymorphisms in Non-Syndromic Cleft Lip/Palate: A Meta-Analysis Across Diverse Populations
Bibliographic record
Abstract
Background Common congenital malformations known as orofacial clefts include cleft lip, cleft lip and palate, and cleft palate. They present significant public health challenges globally due to their medical, psychological, and socioeconomic impacts. Genetic and environmental factors mostly influence the genesis of nonsyndromic cleft lip with or without cleft palate. Methods A meta-analysis was carried out to evaluate the association between IRF6 polymorphisms (rs2235371, rs2235373, and rs2235375) and NSCL/P. PubMed, Google Scholar, Scopus, and Embase were systematically searched for relevant articles. Studies meeting predefined inclusion criteria included case-control designs, genotype data, and statistical measures (odds ratios, 95% confidence intervals). Seventeen research papers were chosen based on the Newcastle-Ottawa Scale criteria for worth evaluation. Results The meta-analysis included 1809 NSCL/P cases and 3164 controls from diverse populations, including Chinese Han, Brazilian, South Indian, Northeast Chinese, Uyghur, Indonesian, Vietnamese, Mesoamerican, and Iranian groups. However, in our analysis, only specific IRF6 SNPs—rs2235371 and rs2235373—showed significant associations in the allelic and dominant models, respectively, while other SNPs, including rs2235375, showed no significant association. These findings underscore the genetic heterogeneity of NSCL/P across various ethnic groups. Conclusion This meta-analysis emphasizes the complex role of IRF6 polymorphisms in the genetic susceptibility to NSCL/P. While significant associations were identified in several populations, the lack of association in others suggests that genetic factors contributing to NSCL/P vary widely. Further research is needed to elucidate additional genetic determinants and their interfaces with environmental factors in the pathogenesis 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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.046 |
| Bibliometrics | 0.004 | 0.005 |
| 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".