Parkinson's Disease, <scp><i>NOTCH3</i></scp> Genetic Variants, and White Matter Hyperintensities
Bibliographic record
Abstract
BACKGROUND: White matter hyperintensities (WMH) on magnetic resonance imaging may influence clinical presentation in patients with Parkinson's disease (PD), although their significance and pathophysiological origins remain unresolved. Studies examining WMH have identified pathogenic variants in NOTCH3 as an underlying cause of inherited forms of cerebral small vessel disease. METHODS: We examined NOTCH3 variants, WMH volumes, and clinical correlates in 139 PD patients in the Ontario Neurodegenerative Disease Research Initiative cohort. RESULTS: We identified 13 PD patients (~9%) with rare (<1% of general population), nonsynonymous NOTCH3 variants. Bayesian linear modeling demonstrated a doubling of WMH between variant negative and positive patients (3.1 vs. 6.9 mL), with large effect sizes for periventricular WMH (d = 0.8) and lacunes (d = 1.2). Negative correlations were observed between WMH and global cognition (r = -0.2). CONCLUSION: The NOTCH3 rare variants in PD may significantly contribute to increased WMH burden, which in turn may negatively influence cognition. © 2020 International Parkinson and Movement Disorder Society.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".