SNAP25 reflects amyloid‐ and tau‐related synaptic damage: Associations between PET, VBM and cerebrospinal fluid biomarkers of synaptic disfunction in the Alzheimer’s disease spectrum
Bibliographic record
Abstract
Abstract Background It is widely accepted that synaptic dysfunction is an early core feature of Alzheimer’s disease (AD). Cerebrospinal fluid (CSF) biomarkers of synaptic damage have already been associated with amyloid and tau pathologies as well as with cognitive decline in the AD spectrum. However, to the best of our knowledge, no study has yet shown the relationship between CSF biomarkers and PET biomarkers at the voxel‐level for these pathologies. Thus, we aim to investigate the association between several biomarkers of synaptic damage and amyloid and tau, in the AD spectrum, using data from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. Method 163 participants (23 young controls, 77 normal controls, 37 mild cognitive impairment, 22 AD and 9 FTD) were evaluated with cross‐sectional CSF biomarkers, [18F]MK6240 and [18F]AZD4694 PET as well as white(WM) and grey matter(GM) MRI voxel‐based morphometry (VBM). For PET, SUVRs were determined using the cerebellar cortex as reference tissue. The CSF biomarkers were quantified by in‐house immunoassays for neurogranin and neuromodulin (GAP‐43), whereas SNAP‐25 and synaptotagmin‐1 (SYT1) were quantified using an immunoprecipitation mass spectrometry method. Linear models were applied to evaluate group differences in CSF biomarker concentrations, adjusting by age and sex. Voxel‐wise linear regressions were also implemented, using VoxelStats, to examine the association between CSF‐ and imaging‐based measures. Result Comparison between groups showed increased concentrations of the CSF biomarkers across disease stages (Figure 1). At the voxel level, consistent associations were found between CSF biomarkers and PET amyloid in AD‐related regions, with the SNAP‐25 biomarkers demonstrating the strongest correlations (Figure 2). Regions with clear associations between tau PET and CSF biomarkers were the inferior temporal, frontal and inferior‐parietal cortices. Again, associated regions were common to all biomarkers, with the strongest correlations found with the SNAP‐25 biomarkers (Figure 3). CSF biomarkers also correlated with GM, but not WM, VBM, being the associated areas in regions commonly affected by AD pathophysiology (Figure 4). Further analyses with SV2A PET should corroborate current findings. Conclusion These results suggest that CSF SNAP‐25 reflects synaptic degeneration and loss in cortical regions affected by amyloid and tau pathology throughout the continuum.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".