Estrogen-related receptor genes underlie sex differences in cortical atrophy associated with isolated REM sleep behavior disorder
Bibliographic record
Abstract
Abstract Isolated REM sleep behavior (iRBD) is a male predominant parasomnia characterized by abnormal dream-enacting movements in REM sleep. It is the prodromal manifestation most strongly associated with the development of synucleinopathies, such as Parkinson’s disease or dementia with Lewy bodies. While individuals with iRBD exhibit significant cortical atrophy shaped by distinct gene expression, sex-specific differences in structural brain changes remain unknown. In this study, we investigate the effect of sex on brain atrophy in iRBD and examine the gene expression underpinning the brain abnormalities in a large international multicentric MRI dataset with polysomnography-confirmed iRBD. T1-weighted scans from 408 individuals with iRBD and 480 healthy controls were acquired. Vertex-based cortical surface reconstruction and segmentation were conducted, and general linear models were used to quantify brain atrophy and assess the sex effect on cortical thickness in iRBD compared to controls. We then used a high resolution parcellation to further characterize the sex differences and conduct imaging transcriptomics analyses. Gene enrichment analyses were performed to identify genes associated with sex differences in cortical atrophy in iRBD. Males with iRBD showed significantly more cortical thinning compared to females with iRBD and controls, despite similar age and clinical features. The gene enrichment analysis revealed that female-specific resilience in cortical atrophy was associated with overexpression of oestrogen-related receptors. These findings provide mechanistic insight of sex-specific neuroprotection in prodromal stages of synucleinopathies, highlighting the critical impact of sex on the progression of neurodegenerative diseases.
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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 | 0.000 | 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".