Regional effects of gantenerumab on neuroimaging biomarkers in the DIAN‐TU‐001 trial
Bibliographic record
Abstract
INTRODUCTION: Monoclonal anti-amyloid therapies are now accessible, but how these treatments influence changes within the brain is still not clear. We investigated overall and regional change in amyloid removal, glucose metabolism, and atrophy in trial participants with dominantly inherited Alzheimer's disease (DIAD). METHODS: F]-fluoro-2-deoxyglucose (FDG) PET, and magnetic resonance imaging (MRI). RESULTS: Gantenerumab significantly reduced PiB-PET uptake overall and in most regions and showed no changes in FDG-PET or MRI measures. Drug effects were associated with baseline PiB-PET uptake, and the largest effects occurred in medial regions. DISCUSSION: Treated DIAD participants, and especially those with higher amyloid burden, showed a decrease in PiB-PET uptake, which was more pronounced in the basal ganglia and medial frontal structures. These results may inform patient response and future drug trial design. HIGHLIGHTS: Gantenerumab unevenly decreased Aβ burden as measured by PiB-PET across brain regions. The strongest decrease in PiB-PET uptake was in basal ganglia and medial frontal structures. Variable drug effect on Aβ was partly due to the amount of burden present before treatment. There was no regional effect on FDG-PET metabolism or MRI volumetrics after 4 years.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".