A recurrent de novo mutation in TMEM106B causes hypomyelinating leukodystrophy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hypomyelinating leukodystrophies are a heterogeneous group of disorders with a clinical presentation that often includes early-onset nystagmus, ataxia and spasticity and a wide range of severity. Using next-generation sequencing techniques and GeneMatcher, we identified four unrelated patients with brain hypomyelination, all with the same recurrent dominant mutation, c.754G>A p.(Asp252Asn), in TMEM106B. The mutation was confirmed as de novo in three of the cases, and the mildly affected father of the fourth affected individual was confirmed as mosaic for this variant. The protein encoded by TMEM106B is poorly characterized but is reported to have a role in regulation of lysosomal trafficking. Polymorphisms in TMEM106B are thought to modify disease onset in frontotemporal dementia, but its relation to myelination is not understood. Clinical presentation in three of the four patients is remarkably benign compared to other hypomyelinating disorders, with congenital nystagmus and mild motor delay. These findings add TMEM106B to the growing list of genes causing hypomyelinating disorders and emphasize the essential role lysosomes play in myelination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it