Reassessing GWAS findings for the shared genetic basis of insomnia and restless legs syndrome
Bibliographic record
Abstract
Two genome-wide association studies (GWAS) suggest that insomnia and restless legs syndrome (RLS) share a common genetic basis. While the identified genetic variation in the MEIS1 gene was previously associated with RLS, the two GWAS suggest a novel and independent association with insomnia symptoms. To test the potential pleiotropic effect of MEIS1, we genotyped three MEIS1 variants in 646 chronic insomnia disorder (CID) patients with and without RLS. To confirm our results, we compared the allelic and genotypic distributions of the CID cohort with ethnically matched controls and RLS cases in the French Canadian cohort. The CID cohort was diagnosed by sleep medicine specialists and 26% of the sample received the combined diagnosis of CID+RLS. We find significant differences in allele and genotype distributions between CID-only and CID+RLS groups, suggesting that MEIS1 is only associated with RLS. Genotype distributions and minor allele frequencies of the three MEIS1 SNPs of the CID-only and control groups were similar (rs113851554: 5.3% vs. 5.6%; rs2300478: 25.3% vs. 26.5%; rs12469063: 23.6% vs. 24.4%; all p > 0.05). Likewise, there were no differences between CID+RLS and RLS-only groups (all p > 0.05). In conclusion, our data confirms that MEIS1 is a genetic risk factor for the development of RLS, but it does not support the pleiotropic effect of MEIS1 in CID. While a lack of power precluded us from refuting small pleiotropic effects, our findings emphasize the critical importance of isolating CID from other disorders that can cause sleep difficulties, particularly RLS, for future genetic 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".