Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorder
Bibliographic record
Abstract
Abstract Background Synucleinopathies manifest as a spectrum of disorders that vary in features and severity, including idiopathic/isolated REM sleep behaviour disorder (iRBD) and dementia with Lewy bodies. Patterns of brain atrophy in iRBD are already reminiscent of what is later seen in overt disease and are related to cognitive impairment, being associated with the development of dementia with Lewy bodies. However, how brain atrophy begins and progresses remains unclear. Methods A multicentric cohort of 1,134 participants, including 538 patients with synucleinopathies (451 with polysomnography-confirmed iRBD and 87 with dementia with Lewy bodies) and 596 healthy controls, was recruited from 11 international study centres and underwent T1-weighted MRI imaging and longitudinal clinical assessment. Scans underwent vertex-based cortical surface reconstruction and volumetric segmentation to quantify brain atrophy, followed by parcellation, ComBAT scan harmonization, and piecewise linear z-scoring for age and sex. We applied the unsupervised machine learning algorithm, Subtype and Stage Inference (SuStaIn), to reconstruct spatiotemporal patterns of brain atrophy progression and correlated the distinct subtypes with clinical markers of disease progression. Results SuStaIn identified two unique subtypes of brain atrophy progression: 1) a “cortical-first” progression subtype characterized by atrophy beginning in the frontal lobes followed by the temporal and parietal areas and remaining cortical areas, with the involvement of subcortical structures at later stages; and 2) a “subcortical-first” progression subtype, which involved atrophy beginning in the limbic areas, then basal ganglia, and only involving cortical structures at late stages. Patients classified to either subtype had higher motor and cognitive disease burden and were more likely to phenoconvert to overt disease compared with those that were not classifiable. Of the 84 iRBD patients who developed overt disease during follow-up, those with a subcortical-first pattern of atrophy were more likely to phenoconvert at earlier SuStaIn stages, particularly to a parkinsonism phenotype. Conversely, later disease stages in both subtypes were associated with more imminent phenoconversion to a dementia phenotype. Conclusions Patients with synucleinopathy can be classified into distinct patterns of atrophy that correlate with disease burden. This demonstrates insights into underlying disease biology and the potential value of categorizing patients in clinical trials.
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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 | 0.001 | 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) | 0.002 | 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".