<scp>CAMTA1‐related</scp> disorder: Phenotypic and molecular characterization of 26 new individuals and literature review
Bibliographic record
Abstract
Calmodulin-binding transcriptional activator 1 (CAMTA1) is highly expressed in the brain and plays a role in cell cycle regulation, cell differentiation, regulation of long-term memory, and initial development, maturation, and survival of cerebellar neurons. The existence of human neurological phenotypes, including cerebellar dysfunction with variable cognitive and behavioral abnormalities (CECBA), associated with CAMTA1 variants, has further supported its role in brain functions. In this study, we phenotypically and molecularly characterize the largest cohort of individuals (n = 26) with 23 novel CAMTA1 variants (frameshift-7, nonsense-6, splicing-1, initiation codon-1, missense-5, and intragenic deletions-3) and compare the findings with all previously reported cases (total = 53). We show that the most notable phenotypic findings are developmental delay/intellectual disability, unsteady or uncoordinated gait, hypotonia, behavioral problems, and eye abnormalities. In addition, there is a high incidence of dysarthria, dysgraphia, microcephaly, gastrointestinal abnormalities, sleep difficulties, and nonspecific brain MRI findings; a few of which have been under-reported. More than one third of the variants in this cohort were inherited from an asymptomatic or mildly affected parent suggesting reduced penetrance and variable expressivity. Our cohort provides a comprehensive characterization of the spectrum of phenotypes and genotypes among individuals with CECBA and the large data will facilitate counseling and formulating management plans and surveillance recommendations for these individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".