No rare deleterious variants from <i>STK32B</i> , <i>PPARGC1A</i> , and <i>CTNNA3</i> are associated with essential tremor
Bibliographic record
Abstract
OBJECTIVE: as essential tremor (ET) predisposing factors following their association in a 2-stage genome-wide association study (GWAS). METHODS: The coding regions of these genes was examined for the presence of rare variants using two approaches: (1) Looking at whole-exome and whole-genome sequencing data of 14 autosomal dominant multiplex ET families. (2) Conducting a targeted massive parallel sequencing to examine the three genes in cohorts of 269 ET cases and 287 control individuals. The cumulative impact of rare variants was assessed using SKAT-O analyses using (1) all variants, (2) only rare variants, and (3) only the rare variants altering the mRNA. RESULTS: Thirty-four variants were identified. No difference emerged regarding the distributions of individual variants (or gene) between cases and controls. CONCLUSION: No rare exonic variants further validated one of these genes as a risk factor for ET. The recent GWAS offers promising avenues, but the genetic heterogeneity of ET is nonetheless challenging for the validation of risk factors, and ultimately larger cohorts of cases should help to overcome this task.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".