Serotonin, β‐amyloid, and cognition in Parkinson disease
Bibliographic record
Abstract
Objective Serotoninergic neurotransmission may modulate β‐amyloid peptide (Aβ) metabolism through upregulation of α‐secretase. Early Parkinson disease (PD) shows variable serotoninergic denervation, which may impact Aβ deposition. Methods We conducted 3 analyses to explore associations between serotoninergic neurotransmission and cerebral Aβ burden in PD. The first was a cross‐sectional imaging study of PD subjects (n = 23) using the serotoninergic transporter positron emission tomography (PET) ligand [11C]3‐amino‐4‐(2‐dimethylaminomethyl‐phenylsulfaryl)‐benzonitrile (DASB) and amyloid PET Pittsburgh compound B ([11C]PiB). The second was a baseline study of Parkinson's Progression Markers Initiative (PPMI) subjects exploring the influence of serotoninergic medications on cerebrospinal fluid (CSF) Aβ‐42 levels (n = 389), controlling for age, sex, Geriatric Depression Scale, disease duration, and education. Third, we fit an interval censored proportional hazard model with longitudinal PPMI data (n = 367) to test whether serotoninergic medication use associates with reduced risk of PD cognitive decline, defined as time to reach a Montreal Cognitive Assessment score ≤ 20, adjusting for baseline caudate dopamine transporter [123I]ioflupane single photon emission computed tomography and CSF Aβ‐42 levels. Results Serotoninergic DASB distribution volume ratio (DVR) inversely associated with PiB DVR in the cerebral cortex (Pearson r = −0.478, p = 0.021) but not the striatum (r = −0.264, p = 0.224). In the baseline PPMI analysis, serotoninergic medication use for ≥6 months associated with a lower level of CSF Aβ‐42 (t = −2.20, p = 0.029). In the longitudinal PPMI model, baseline serotoninergic medication use associated with a reduced risk of cognitive decline (t = −2.03, p = 0.043) after controlling for covariates. Interpretation Cortical Aβ burden in PD associates inversely with serotoninergic innervation. Serotoninergic medications may alter Aβ metabolism and reduce the risk of PD cognitive decline. Ann Neurol 2018;83:994–1002
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".