Evidence of synergism among three genetic variants in a patient with LMNA-related lipodystrophy and amyotrophic lateral sclerosis leading to a remarkable nuclear phenotype
Bibliographic record
Abstract
Neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), can be clinically heterogeneous which may be explained by the co-inheritance of multiple genetic variants that modify the clinical course. In this study we examine variants in three genes in a family with one individual presenting with ALS and lipodystrophy. Sequencing revealed a p.Gly602Ser variant in LMNA, and two additional variants, one each in SETX (g.intron10-13delCTT) and FUS (p.Gly167_Gly168del). These latter genes have been linked to ALS. All family members were genotyped and each variant, and each combination of variants detected, were functionally evaluated in vitro regarding effects on cell survival, expression patterns and cellular phenotype. Muscle biopsy retrieved from the individual with ALS showed leakage of chromatin from the nucleus, a phenotype that was recapitulated in vitro with expression of all three variants simultaneously. Individually expressed variants gave cellular phenotypes there were unremarkable. Interestingly the FUS variant appears to be protective against the effects of the SETX and the LMNA variants on cell viability and may indicate loss of interaction of FUS with SETX and/or R-loops. We conclude that these findings support genetic modifications as an explanation of the clinical heterogeneity observed in human disease.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".