Resequencing of 29 Candidate Genes in Patients With Familial and Sporadic Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
OBJECTIVE: To identify novel disease-causing genes for amyotrophic lateral sclerosis (ALS). DESIGN, SETTING, AND PATIENTS: We carried out a systematic mutation screening of the entire coding regions of 29 candidate genes encoding critically important proteins for proper differentiation and development of corticospinal motor neurons in 190 patients with familial and sporadic ALS. MAIN OUTCOME MEASURES: We focused our analysis on coding variants and evaluated the distribution of nonsynonymous and synonymous variants in our cohort of patients with ALS. RESULTS: We identified 40 novel nonsynonymous variants and showed a significant excess of unique nonsynonymous variants in our cohort of patients with ALS, which suggests the presence of ALS-predisposing mutations. CONCLUSIONS: Using a multifaceted approach based on the functional prediction of missense variants, the conservation of the altered amino acid, and the cosegregation of the variants identified in familial cases, we identified several promising novel genes for ALS such as LUM and CRYM. We have also highlighted the analytical challenges of large-scale sequencing screens to detect disease-causing variants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".