Brain Microglial Activation Increased in Glucocerebrosidase (<scp><i>GBA</i></scp>) Mutation Carriers without Parkinson's disease
Bibliographic record
Abstract
ABSTRACT Background Glucocerebrosidase gene mutations are a common genetic risk factor for Parkinson's disease. They exhibit incomplete penetrance. The objective of the present study was to measure microglial activation and dopamine integrity in glucocerebrosidase gene mutation carriers without Parkinson's disease compared to controls. Methods We performed PET scans on 9 glucocerebrosidase gene mutation carriers without Parkinson's disease and 29 age‐matched controls. We measured microglial activation as 11C‐(R)‐PK11195 binding potentials, and dopamine terminal integrity with 18F‐dopa influx constants. Results The 11C‐(R)‐PK11195 binding potential was increased in the substantia nigra of glucocerebrosidase gene carriers compared with controls (Student t test; right, t = −4.45, P = 0.0001). Statistical parametric mapping also localized significantly increased 11C‐(R)‐PK11195 binding potential in the occipital and temporal lobes, cerebellum, hippocampus, and mesencephalon. The degree of hyposmia correlated with nigral 11C‐(R)‐PK11195 regional binding potentials (Spearman's rank, P = 0.0066). Mean striatal 18F‐dopa uptake was similar to healthy controls. Conclusions In vivo 11C‐(R)‐PK11195 PET imaging detects neuroinflammation in brain regions susceptible to Lewy pathology in glucocerebrosidase gene mutation carriers without Parkinson's. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".