Prenatal phenotyping of fetal tubulinopathies: A multicenter retrospective case series
Bibliographic record
Abstract
OBJECTIVE: Tubulinopathies refer to conditions caused by genetic variants in isotypes of tubulin resulting in defective neuronal migration. Historically, diagnosis was primarily via postnatal imaging. Our objective was to establish the prenatal phenotype/genotype correlations of tubulinopathies identified by fetal imaging. METHODS: A large, multicenter retrospective case series was performed across nine institutions in the Fetal Sequencing Consortium. Demographics, fetal imaging reports, genetic screening and diagnostic testing results, delivery reports, and neonatal imaging reports were extracted for pregnancies with a confirmed molecular diagnosis of a tubulinopathy. RESULTS: Nineteen pregnancies with a fetal tubulinopathy were identified. The most common prenatal imaging findings were cerebral ventriculomegaly (15/19), cerebellar hypoplasia (13/19), absence of the cavum septum pellucidum (6/19), abnormalities of the corpus callosum (6/19), and microcephaly (3/19). Fetal MRI identified additional central nervous system features that were not appreciated on neurosonogram in eight cases. Single gene variants were reported in TUBA1A (13), TUBB (1), TUBB2A (1), TUBB2B (2), and TUBB3 (2). CONCLUSION: The presence of ventriculomegaly with cerebellar abnormalities in conjunction with additional prenatal neurosonographic findings warrants additional evaluation for a tubulinopathy. Conclusive diagnosis can be achieved by molecular sequencing, which may assist in coordination, prognostication, and reproductive planning.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".