Genetic variants of α‐synuclein are not associated with essential tremor
Bibliographic record
Abstract
BACKGROUND: Given the overlap between Parkinson's disease and essential tremor, we examined genetic variants in α-synuclein (SNCA) as risk determinants for essential tremor. METHODS: Samples from 661 essential tremor subjects and 1316 control subjects from 4 participating North American sites were included in this study. Parkinson's disease samples (n = 427) were compared against controls. Twenty variants were selected for association analysis within the SNCA locus. Individual logistic regression analyses against essential tremor diagnosis were run for each variant and then combined using meta-analysis. RESULTS: Our results do not show a significant association between variants in the SNCA locus and risk of essential tremor, whereas the established association of SNCA variants with Parkinson's disease risk was observed. CONCLUSIONS: Whereas genetic factors are likely to play a large role in essential tremor pathogenesis, our results do not support a role for common SNCA genetic variants in risk for essential tremor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".