Questioning the Association of the <i>STMN2</i> Dinucleotide Repeat With Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Objectives Recently, the number of dinucleotide CA repeats in an intron of the STMN2 gene was reported to be associated with an increased risk for amyotrophic lateral sclerosis (ALS). Therefore, we sought to replicate this observation in an independent group of ALS patients and a much larger control group. Methods Here, we used whole-genome sequencing and tested the STMN2 CA repeat in a case-control cohort of the European genetic background and in genomes from various populations in the gnomAD cohort to attempt to replicate this proposed association. Results We find that repeats well above the previously reported pathogenic threshold of 19 are commonly observed in unaffected individuals across different populations. Furthermore, we did not observe an association between longer STMN2 CA repeats and ALS phenotype. Discussion In summary, our results do not support a role of STMN2 CA repeats toward ALS risk. As TDP-43 aggregation is central to ALS pathogenesis, lowered expression of STMN2 could be used as a biomarker for ALS. Therefore, a variant associated both with the risk for ALS and the level of STMN2 expression would be clinically useful. However, for a variant to be actionable, it must be strongly replicated in independent cohorts and exceed the rigorous statistical thresholds applied.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".