<i>De Novo</i> variants in <i>EEF2</i> cause a neurodevelopmental disorder with benign external hydrocephalus
Bibliographic record
Abstract
Eukaryotic translation elongation factor 2 (eEF2) is a key regulatory factor in gene expression that catalyzes the elongation stage of translation. A functionally impaired eEF2, due to a heterozygous missense variant in the EEF2 gene, was previously reported in one family with spinocerebellar ataxia-26 (SCA26), an autosomal dominant adult-onset pure cerebellar ataxia. Clinical exome sequencing identified de novo EEF2 variants in three unrelated children presenting with a neurodevelopmental disorder (NDD). Individuals shared a mild phenotype comprising motor delay and relative macrocephaly associated with ventriculomegaly. Populational data and bioinformatic analysis underscored the pathogenicity of all de novo missense variants. The eEF2 yeast model strains demonstrated that patient-derived variants affect cellular growth, sensitivity to translation inhibitors and translational fidelity. Consequently, we propose that pathogenic variants in the EEF2 gene, so far exclusively associated with late-onset SCA26, can cause a broader spectrum of neurologic disorders, including childhood-onset NDDs and benign external hydrocephalus.
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.
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 | 0.001 | 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".