Synaptic proteins in pre‐symptomatic Alzheimer’s disease: biomarkers for early detection of Cognitive Decline
Bibliographic record
Abstract
Abstract Background Synaptic proteins in the cerebrospinal fluid (CSF) may reveal changes in the pre‐symptomatic stages of Alzheimer’s disease (AD), thus may be candidate biomarkers for early detection of the disease. Method The PREVENT‐AD cohort includes symptom‐free (upon enrolment) elderly participants who are at risk of developing AD from their family history. We used enzyme‐linked immunosorbent assay kits to assess CSF samples from 129 such participants for the “classical” AD biomarkers total tau, phosphorylated (181) tau and Aβ42. We also used neuroimaging data (MRI, PET) and neuropsychological assessments (MMSE, RBANS) as potential indicators disease progression. We then used in the CSF samples to measure the soluble synaptic biomarkers ADAM 22 (post‐synaptic), ADAM23 (pre‐synaptic). Immunoprecipitated SYT1 (pre‐synaptic) from CSF were analyyzed using high‐resolution selected ion monitoring analyses on a quadrupole–orbitrap mass spectrometer Q Exactive. Statistical analysis of the association of these markers with evidence of disease in analyses were done included sex and APOE e4 status as covariates. Result Among participants who remained cognitively unimpaired, we observed significant correlations between baseline CSF ADAM 22 levels and t‐tau (R2 = 0.22, p < 0.0001), p‐tau (R2 = 0.22, p < 0.0001), and Aβ42 (R2 = 0.06, p = 0.01488). We also found similarly suggestive correlations also between CSF ADAM 23, CSF SYT1 and the same disease markers. Covariate analyses suggested little or no variation in the associations between these synaptic proteins with t‐tau and p‐tau by sex, APOE e4 status, negative PET amyloid positivity (standardized uptake value ratio ≤ 1.37) and negative CSF total tau positivity (≤ 335pg/ul). PET amyloid positivity was significantly associated with ADAM22 and p‐tau interactions whereas SYT1 was significantly associated with t‐tau and p‐tau in CSF tau‐positive participants. In linear regression analyses, baseline CSF ADAM22 levels correlated with the language cognitive performance trajectory slopes estimated over the course of 5 to 8 years on the RBANS (R2 = 0.04, p = 0.03912). We found no significant interaction between other baseline CSF synaptic protein levels and other subscales of the RBANS. Conclusion CSF synaptic protein levels show promising correlation with landmark AD proteins and emerging cognitive deficits.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".