Genome-wide association study of REM sleep behavior disorder in Parkinson’s disease
Bibliographic record
Abstract
Abstract Objective REM sleep behavior disorder (RBD) is a prodromal synucleinopathy, reported in a subset of Parkinson’s disease (PD) patients, and associated with neuropsychiatric symptoms in PD. We aimed to compare the genetic background of PD patients with probable RBD (PD+RBD) and PD patients without probable RBD (PD-RBD). Furthermore, we examined genetic correlations and potential causal associations between multiple neuropsychiatric traits and PD+RBD. Methods We performed a genome-wide association study (GWAS) including 5,403 PD+RBD and 13,020 PD-RBD. To test for genetic correlations and potential causal associations between neuropsychiatric traits and PD+RBD, we used linkage disequilibrium score regression and Mendelian randomization. Results The SNCA locus was associated with PD+RBD compared to PD-RBD (rs10005233, OR=1.21, 95% CI=1.16-1.27, p =1.81e-15). Further examination of known genetic loci associated with PD from the most recent PD GWAS in Europeans and Asians identified additional variants associated with reduced risk for PD+RBD: two in the SNCA locus (rs5019538-G, OR=0.85, 95% CI=0.81-0.89, p =2.46E-10; rs356182-G, OR=0.89, 95% CI=0.84-0.95, p =0.0001), and one in the LRRK2 locus (rs34637584, p.G2019S, OR=0.41, 95% CI=0.28-0.61, p =1.04E-5). We found a potential genetic correlation between attention deficit hyperactivity disorder (ADHD) and PD+RBD, which was not statistically significant after correction for multiple comparisons. No causative association emerged between PD and neuropsychiatric traits. Interpretation Genetic variants contribute to the occurrence of RBD in PD, further distinguishing between the PD+RBD and PD-RBD subtypes. Understanding the mechanisms underlying these genetic associations could contribute to the development of subtype-specific treatments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".