CSF total tau is more closely associated with synaptic dysfunction than overt neurodegeneration
Bibliographic record
Abstract
Abstract Background CSF total tau (t‐tau) is postulated as a marker of neuronal degeneration in the ATN criteria. Here, we hypothesize that CSF t‐tau is more closely related to synaptic loss than over neurodegeneration. Method We evaluated 128 older individuals (75 CU,33 MCI,20 AD) in the TRIAD cohort (McGill, Canada) with CSF t‐tau, SNAP25long and Neurofilament Light (NfL), Amyloid‐beta (Aβ) positron emission tomography and magnetic resonance imaging, and clinical assessments. We used increased SNAP25long as an index of synaptic dysfunction (S+) and reduced hippocampal volume as neurodegeneration (N+). S and N positivity were determined using a cutoff anchored in young CU individuals. Linear regression models were used to test the association between CSF t‐tau, SNAP25long and NfL levels and hippocampal volume, adjusted for age, sex, and cognitive status. ANCOVA was employed to inspect CSF t‐tau levels across the groups 1) S‐N‐; 2) S+N‐; 3) S‐N+; 4) S+N+, adjusted for age, sex, cognitive status, and Aβ burden. Result We found that a model with the addition of SNAP25long to the covariates explained 65% of the variance (p‐value<0.0001) of CSF t‐tau. Alternatively, hippocampal volume (R2 = 0.2187; p‐value<0.0001) and NfL (R2 = 0.3671; p‐value<0.0001) alone or in combination explained less than 40% of the variance of CSF t‐tau (R2 = 0.3597; p‐value<0.0001) (Figure 1). Interestingly, we observed an increase of CSF t‐tau in the S+N‐ group but not in the S‐N+, further supporting that CSF t‐tau is abnormal in the presence of synaptic dysfunction rather than neurodegeneration. Additionally, Loess regression lines confirm a larger magnitude of change of synaptic dysfunction as a function of t‐tau, compared with neurodegeneration (Figure 3). Conclusion Our results suggest that CSF t‐tau may reflect synaptic loss rather than neuronal degeneration. This has implications for the interpretability of results obtained with CSF t‐tau in biomarker studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".