Motor and nonmotor heterogeneity of <i>LRRK2</i>‐related and idiopathic Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) associated with LRRK2 mutations has been described as similar to idiopathic PD with minor clinical differences. No study has compared the clinical features of LRRK2-associated PD due to different mutations. The objective of this study was to compare LRRK2-associated PD due to G2019S and G2385R mutations and to compare each to idiopathic PD. METHODS: Sites within the international LRRK2 Cohort Consortium undertook family-based, community-based, or clinic-based studies to gather clinical data on manifesting carriers and patients with idiopathic PD. RESULTS: Five hundred sixteen PD patients with the G2019S mutation, 199 with the G2385R mutation, and 790 patients with idiopathic PD were included in the data set. Adjusted for age, sex, disease duration, and levodopa-equivalent daily dose, mean MDS-UPDRS part II or III scores and the frequency of motor fluctuations were higher in the G2385R mutation carriers than in either the G2019S mutation carriers or idiopathic PD patients. G2019S mutation carriers had significantly lower UPDRS part III scores than idiopathic PD patients. Both G2019S and G2385R mutation carriers had a higher proportion of the postural instability gait disorder phenotype compared with idiopathic PD patients. LRRK2 G2019S PD patients had better UPSIT scores and lower Geriatric Depression Scale scores than idiopathic PD patients in adjusted analyses. CONCLUSIONS: G2385R and G2019S PD appear to have motor differences that may be explained by contrasting local treatment or measurement practices or differences in the biology of the disease. Longitudinal studies should evaluate whether progression is faster in G2385R mutation carriers compared with G2019S PD or idiopathic PD. © 2016 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 | 0.000 | 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) | 0.002 | 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".