Novel LMNA mutations in patients with Emery-Dreifuss muscular dystrophy and functional characterization of four LMNA mutations
Bibliographic record
Abstract
Mutations in LMNA cause a variety of diseases affecting striated muscle including autosomal Emery-Dreifuss muscular dystrophy (EDMD), LMNA-associated congenital muscular dystrophy (L-CMD), and limb-girdle muscular dystrophy type 1B (LGMD1B). Here, we describe novel and recurrent LMNA mutations identified in 50 patients from the United States and Canada, which is the first report of the distribution of LMNA mutations from a large cohort outside Europe. This augments the number of LMNA mutations known to cause EDMD by 16.5%, equating to an increase of 5.9% in the total known LMNA mutations. Eight patients presented with either p.R249W/Q or p.E358K mutations and an early onset EDMD phenotype: two mutations recently associated with L-CMD. Importantly, 15 mutations are novel and include eight missense mutations (p.R189P, p.F206L, p.S268P, p.S295P, p.E361K, p.G449D, p.L454P, and p.W467R), three splice site mutations (c.IVS4 + 1G>A, c.IVS6 - 2A>G, and c.IVS8 + 1G>A), one duplication/in frame insertion (p.R190dup), one deletion (p.Q355del), and two silent mutations (p.R119R and p.K270K). Analysis of 4 of our lamin A mutations showed that some caused nuclear deformations and lamin B redistribution in a mutation specific manner. Together, this study significantly augments the number of EDMD patients on the database and describes 15 novel mutations that underlie EDMD, which will contribute to establishing genotype-phenotype correlations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".