Gray and white matter damage are associated with motor symptoms in Parkinson’s disease
Bibliographic record
Abstract
Abstract Background Previous studies have found associations between atrophy in Substantia Nigra (SN) and White Matter Hyperintensities (WMH) of vascular origin and motor deficits in Parkinson’s disease (PD) patients (Zeighami et al. 2015, Pozorski et al. 2019). Here we assess the relationship between WMHs and SN atrophy and motor symptoms in PD. Method Data included 50 PD patients and 45 age‐matched controls with T1‐weighted and FLAIR scans at baseline, month18, and month36. WMHs were segmented using T1‐weighted and FLAIR images and a random forests classifier (Dadar et al. 2017, Figure 1.a). Deformation‐based morphometry was used to measure atrophy in Substantia Nigra (SN) (Figure 1.b, Ashburner et al 1998). The relationship between MRI features and clinical scores was assessed using mixed‐effects models: where Cohort denotes a categorical variable contrasting PD versus controls, and ID denotes the categorical random effects. The variables of interest were MRI‐Feature (implying an overall association between the MRI feature and clinical score of interest) and the interaction term Cohort:MRI‐Score (implying an additional PD‐specific impact of the MRI‐Feature on the Clinical‐Score). Log‐transformed WMH volumes and mean DBM score in left and right SN were used as MRI features. The motor subscore of Unified Parkinson's Disease Rating Scale (UPDRSIII) was used as the dependent variable of interest, reflecting motor deficits. Result WMH load significantly increased with age in both groups (t=9.95, p<0.0001). We did not find a significant group difference in WMH volumes. However, WMH load was significantly associated with UPDRSIII in PDs (t=2.63, p=0.008), but not in controls (t=0.02, p=0.86), with a marginal interaction (t=1.67, p=0.05, Figure 2). DBM in both left and right SN significantly decreased with age (tLeftSN=‐5.79, tRightSN=‐6.33, p<0.0001), and were significantly different between the cohorts (Figure 3, tLeftSN=‐4.19, tRightSN=‐3.95, p<0.00001). UPDRSIII significantly increased with age (t=4.75, p<0.00001) and decrease in SN DBM (tLeftSN=‐2.02, tRightSN=‐1.88, p<0.05), with a significantly greater impact in PDs (Figure 4, tLeftSN=‐2.10, tRightSN=‐1.73, p<0.04). Conclusion In our sample, both SN atrophy and WMH burden were significantly associated with additional motor deficits in PD, implying an additive contribution of both gray and white matter damage to the motor deficits in PD.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".