The Association Between Non-Syndromic Tooth Agenesis and MSX1, AXIN2, WNT10A, EDA, EDAR, and EDARADD Gene Mutations: A Systematic Review
Bibliographic record
Abstract
Background: Tooth development or odontogenesis is a complicated, multi-staged process, regulated by a plethora of genes. Disruptions during the early stages of odontogenesis may cause the complete absence of one or more teeth, known as tooth agenesis (TA). Except for PAX9, alterations in MSX1, AXIN2, WNT10A, and EDA/EDAR/EDARADD have gathered an increasing amount of interest. Objectives: This systematic review aims to investigate whether non-syndromic tooth agenesis (NSTA) is associated with MSX1, AXIN2, WNT10A, and EDA/EDAR/EDARADD mutations and to list the related phenotypic patterns of these alterations with regard to missing teeth. Methods: MEDLINE, Scopus, and Web of Science were the three selected databases. Duplicates were removed using Mendeley, and the records were assessed via the Rayyan platform. The Newcastle–Ottawa Scale was used to evaluate the quality of the evidence. Results: Fifteen case–control studies were eligible for this systematic review. The MSX1 gene was examined in most studies, whereas second premolars and lateral incisors were the most commonly missing teeth among TA cases. In total, 61.29% to 84.9% of the cases included one or two absent teeth. Conclusions: Due to the considerable heterogeneity in reporting results across the included studies, along with the high risk of bias present in most of them, it was not feasible to conduct a meta-analysis of the data. Nonetheless, the findings suggest that the NSTA phenotypes linked to the studied genes are similar to those associated with other forms of TA and share a common pattern of missing teeth. Future research should adopt a more standardized approach in presenting findings by adhering to established terminology and definitions and by utilizing common cut-off points to categorize results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".