Post-traumatic stress disorder and REM-sleep behavior disorder: exploring genetic associations and causal links
Bibliographic record
Abstract
Abstract Objective To explore potential genetic and/or causal associations between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder. Methods We conducted polygenic risk score, genetic correlation, and Mendelian randomization analyses using the latest genome-wide association studies summary statistics and individual genotyping data. Next, a blinded observer examined dopamine transporter imaging binding status—a marker of neurodegeneration—in patients with isolated/idiopathic rapid-eye movement sleep behavior disorder, with (N = 6) and without Post-Traumatic Stress Disorder (N = 32). Results Polygenic risk scores for Post-Traumatic Stress Disorder were associated with isolated/idiopathic rapid-eye-movement sleep behavior disorder, with each standard deviation increase linked to 14.7% higher odds (odds ratio = 1.15, 95% confidence interval: 1.04 to 1.26, p = 0.005). However, genetic correlation was weak, and Mendelian randomization did not support a potential causal relationship. The proportion of individuals with abnormal dopamine transporter imaging binding status was significantly higher in the Post-Traumatic Stress Disorder group compared to those without the disorder (p=0.01, X 2 = 6.62). Interpretation Polygenic risk scores analysis identified an association between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder, consistent with the result from the small exploratory substudy. The lack of strong genetic correlation or causation may reflect limited sample size. Further research with larger and more diverse cohorts is crucial to clarify the genetic, biological and physiological mechanisms underlying this association.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".