C9orf72 intermediate expansions of 24–30 repeats are associated with ALS
Bibliographic record
Abstract
The expansion of a hexanucleotide repeat GGGGCC in C9orf72 is the most common known cause of ALS accounting for ~ 40% familial cases and ~ 7% sporadic cases in the European population. In most people, the repeat length is 2, but in people with ALS, hundreds to thousands of repeats may be observed. A small proportion of people have an intermediate expansion, of the order of 20 to 30 repeats in size, and it remains unknown whether intermediate expansions confer risk of ALS in the same way that massive expansions do. We investigated the association of this intermediate repeat with ALS by performing a meta-analysis of four previously published studies and a new British/Alzheimer’s Disease Neuroimaging Initiative dataset of 1295 cases and 613 controls. The final dataset comprised 5071 cases and 3747 controls. Our meta-analysis showed association between ALS and intermediate C9orf72 repeats of 24 to 30 repeats in size (random-effects model OR = 4.2, 95% CI = 1.23–14.35, p -value = 0.02). Furthermore, we showed a different frequency of the repeat between the northern and southern European populations (Fisher’s exact test p -value = 5 × 10 − 3 ). Our findings provide evidence for the association between intermediate repeats and ALS ( p -value = 2 × 10 − 4 ) with direct relevance for research and clinical practice by showing that an expansion of 24 or more repeats should be considered pathogenic.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.013 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".