Genetic and epidemiological characterization of restless legs syndrome in Québec
Bibliographic record
Abstract
Currently, a total of 19 genetic loci are associated with the risk for developing RLS. This study aimed to assess these RLS predisposing genetic variants, as well as investigate the epidemiological profile and diagnostic features of individuals with RLS in the Québec population, using an interviewer-administered questionnaire. A total of 18 RLS-associated variants were genotyped in the Québec population-based CARTaGENE cohort. A case-control series consisting of 1,362 RLS cases and 1,379 age-matched unaffected controls was used to conduct a genetic and epidemiological association study that integrated the first four RLS diagnostic features of affected individuals, as well as additional RLS-related questions (e.g. frequency of the symptoms and number of total pregnancies in female). Five RLS-predisposing variants were significantly associated after Bonferroni correction and an additional five variants were nominally associated with RLS (p < 0.05). BTBD9 was the strongest genetic risk factor in our cohort (rs9296249, OR = 1.71, p = 9.57 × 10-10). The patient group that met all four essential diagnostic criteria of RLS provided the most significant genetic findings. These results suggest that employing the questionnaire which included standard diagnostic criteria of RLS could improve the accuracy of the survey-based studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".