Parkinson disease phenotype in Ashkenazi jews with and without <i>LRRK2</i> G2019S mutations
Bibliographic record
Abstract
The phenotype of Parkinson's disease (PD) in patients with and without leucine-rich repeat kinase 2 (LRRK2) G2019S mutations reportedly is similar; however, large, uniformly evaluated series are lacking. The objective of this study was to characterize the clinical phenotype of Ashkenazi Jewish (AJ) PD carriers of the LRRK2 G2019S mutation. We studied 553 AJ PD patients, including 65 patients who were previously reported, from three sites (two in New York and one in Tel-Aviv). Glucocerebrosidase (GBA) mutation carriers were excluded. Evaluations included the Montreal Cognitive Assessment (MoCA), the Unified Parkinson's Disease Rating Scale (UPDRS), the Geriatric Depression Scale (GDS) and the Non-Motor Symptoms (NMS) questionnaire. Regression models were constructed to test the association between clinical and demographic features and LRRK2 status (outcome) in 488 newly recruited participants. LRRK2 G2019S carriers (n = 97) and non-carriers (n = 391) were similar in age and age at onset of PD. Carriers had longer disease duration (8.6 years vs. 6.1 years; P < 0.001), were more likely to be women (51.5% vs. 37.9%; P = 0.015), and more often reported first symptoms in the lower extremities (40.0% vs. 19.2%; P < 0.001). In logistic models that were adjusted for age, disease duration, sex, education, and site, carriers were more likely to have lower extremity onset (P < 0.001), postural instability and gait difficulty (PIGD) (P = 0.043), and a persistent levodopa response for >5 years (P = 0.042). Performance on the UPDRS, MoCA, GDS, and NMS did not differ by mutation status. PD in AJ LRRK2 G2019S mutation carriers is similar to idiopathic PD but is characterized by more frequent lower extremity involvement at onset and PIGD without the associated cognitive impairment.
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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 | 0.001 |
| 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) | 0.001 | 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".