<i>NUBP2</i> deficiency disrupts the centrosome-check point in the brain and causes primary microcephaly
Bibliographic record
Abstract
Abstract Microcephaly affects 1 in 2,500 babies per year. Primary microcephaly results from aberrant neurogenesis leading to a small brain at birth. This is due to altered patterns of proliferation and/or early differentiation of neurons. Premature differentiation of neurons is associated with defects in the centrosome and/or primary cilia. In this study, we report on the first patients identified with NUBP2 -deficiency and utilize a conditional mouse model to ascertain the molecular mechanisms associated with NUBP2 -deficient primary microcephaly. We identified homozygous NUBP2 variants in these patients who displayed profound primary microcephaly in addition to intrauterine growth restriction, cervical kyphosis, severe contractures of joints, and facial dysmorphia. We then generated a mouse model using Emx1-Cre to ablate Nubp2 from the forebrain. The mice presented with severe microcephaly starting at E18.5. Neurospheres generated from the forebrain of Emx1-Cre; Nubp2 flox/flox conditional deletion mice were used to support the pathogenicity of the patient variants. We show that loss of Nubp2 increases both canonical and non-canonical cell death, but that loss of p53 fails to rescue microcephaly in the mouse model. Examination of neurogenesis in Emx1-Cre; Nubp2 flox/flox mice revealed distinct alterations in proliferation and cellular migration accompanied by supernumerary centrosomes and cilia. We therefore propose that NUBP2 is a novel primary microcephaly-related gene and that the role of Nubp2 in centrosome and cilia regulation is crucial for proper neurogenesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".