Parkinson’s Disease Progression and Statins: Hydrophobicity Matters
Bibliographic record
Abstract
BACKGROUND: Recent randomized clinical trials using hydrophobic statins reported no influence on Parkinson's disease (PD) clinical progression. Hydrophobicity is a key determinant for blood-brain barrier penetrance. OBJECTIVE: Investigate a potential effect of statins on PD progression. METHODS: Statin use was determined at baseline and subtyped according to hydrophobicity in 125 PD patients participating in the PD Biomarker Program (PDBP, 2012-2015) at our site. Clinical (N = 125) and susceptibility MRI (N = 86) data were obtained at baseline and 18-months. Movement Disorders Society-Unified PD Rating Scales were used to track progression of non-motor (MDS-UPDRS-I) and motor (MDS-UPDRS-II) symptoms, and rater-based scores (MDS-UPDRS-III) of patients in the "on" drug state. R2* values were used to capture pathological progression in the substantia nigra. Associations between statin use, its subtypes, and PD progression were evaluated with linear mixed effect regressions. RESULTS: Compared to statin non-users, overall statin or lipophilic statin use did not significantly influence PD clinical or imaging progression. Hydrophilic statin users, however, demonstrated faster clinical progression of non-motor symptoms [MDS-UPDRS-I (β= 4.8, p = 0.010)] and nigral R2* (β= 3.7, p = 0.043). A similar trend was found for MDS-UPDRS-II (β= 3.9, p = 0.10), but an opposite trend was observed for rater-based MDS-UPDRS-III (β= -7.3, p = 0.10). Compared to lipophilic statin users, hydrophilic statin users also showed significantly faster clinical progression of non-motor symptoms [MDS-UPDRS-I (β= 5.0, p = 0.020)], but R2* did not reach statistical significance (β= 2.5, p = 0.24). CONCLUSION: This study suggests that hydrophilic, but not lipophilic, statins may be associated with faster PD progression. Future studies may have clinical and scientific implications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".