The cholinergic system and treatment response in subtypes of Alzheimer’s disease
Bibliographic record
Abstract
Abstract BACKGROUND The heterogeneity within Alzheimer’s disease (AD) seriously challenges the development of disease modifying treatments. We investigated volume of the basal forebrain, hippocampus, and precuneus in atrophy subtypes of AD, and explored the relevance of subtype stratification in a clinical trial on encapsulated cell biodelivery (ECB) of nerve growth factor (NGF) to the basal forebrain. METHODS Structural MRI data was collected for 90 amyloid-positive patients and 69 amyloid-negative healthy controls at baseline, 6-, 12-, and 24-month follow-up. The effect of the NGF treatment was investigated in 10 biopsy verified AD patients with structural MRI data at baseline and at 6- or 12-months follow-up. Patients were classified as typical, limbic-predominant, hippocampal-sparing, or minimal atrophy AD, using a validated visual assessment method. Volumetric analyses were performed using a region-of-interest approach. RESULTS All AD subtypes showed reduced basal forebrain volume as compared with controls. Limbic-predominant subtype showed fastest basal forebrain atrophy rate, whereas minimal atrophy subtype did not show significant volume decline over time. Atrophy rates of hippocampus and precuneus also differed across subtypes. The NGF treatment seemed to slow the rate of atrophy in precuneus and hippocampus, particularly in the hippocampal-sparing AD subtype. CONCLUSIONS The cholinergic system is differentially affected in distinct atrophy subtypes of AD, possibly contributing to their differential response to cholinergic treatment. Our findings suggest that future clinical trials should target specific subtypes of AD, or at least report treatment effects stratifying by subtype. Trial registration ClinicalTrials.gov identifier: NCT01163825 . Registered 14 July 2010 - https://clinicaltrials.gov/ct2/show/NCT01163825
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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 | 0.002 |
| 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) | 0.001 | 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".