Uncovering Phenotypic Expansion in AXIN2-Related Disorders through Precision Animal Modeling
Bibliographic record
Abstract
Abstract Heterozygous pathogenic variants in AXIN2 are associated with oligodontia-colorectal cancer syndrome (ODCRCS), a disorder characterized by oligodontia, colorectal cancer, and in some cases, sparse hair and eyebrows. We have identified four individuals with one of two de novo , heterozygous variants (NM_004655.4:c.196G>A, p.(Glu66Lys) and c.199G>A, p.(Gly67Arg)) in AXIN2 whose presentations expand the phenotype of AXIN2-related disorders. In addition to ODCRCS features, these individuals have global developmental delay, microcephaly, and limb, ophthalmologic, and renal abnormalities. Structural modeling of these variants suggests that they disrupt AXIN2 binding to tankyrase, which regulates AXIN2 levels through PARsylation and subsequent proteasomal degradation. To test whether these variants produce a phenotype in vivo , we utilized an innovative prime editing N1 screen to phenotype heterozygous (p.E66K) mouse embryos, which were perinatal lethal with short palate and skeletal abnormalities, contrary to published viable Axin2 null mouse models. Modeling of the p.E66K variant in the Drosophila wing revealed gain-of-function activity compared to reference AXIN2. However, the variant showed loss-of-function activity in the fly eye compared to reference AXIN2, suggesting that the mechanism by which p.E66K affects AXIN2 function is cell context-dependent. Together, our studies in humans, mice, and flies demonstrate that specific variants in the tankyrase-binding domain of AXIN2 are pathogenic, leading to phenotypic expansion with context-dependent effects on AXIN2 function and WNT signaling. Moreover, the modeling strategies used to demonstrate variant pathogenicity may be beneficial for the resolution of other de novo heterozygous variants of uncertain significance associated with congenital anomalies in humans.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".