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Record W7118328083 · doi:10.1002/alz70856_105493

Synaptic Biomarkers in Alzheimer's Dementia: A Meta‐Analysis

2025· article· en· W7118328083 on OpenAlexaff
Amish Gaur, Jinghan Jenny Chen, Melissa H. Wong, Yejin Kang, Danielle Tahoulas, Damien Gallagher, Nathan Herrmann, Krista L. Lanctôt

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of TorontoSunnybrook HospitalUniversity of Ottawa
Fundersnot available
KeywordsBiomarkerMicrovesiclesCerebrospinal fluidDementiaPathologicalCognitive declineSynapseExosome

Abstract

fetched live from OpenAlex

Abstract Background Alzheimer's dementia (AD) is a neurodegenerative condition characterized by progressive cognitive decline. Synaptopathy—defined as loss and dysfunction of existing synapses—is a hallmark pathological feature of AD and can directly contribute to underlying cognitive deficits. In this study, we meta‐analyzed several cerebrospinal fluid (CSF) and blood exosomal biomarkers associated with synaptopathy in AD and healthy controls (HCs). Method Original peer‐reviewed articles that reported synaptic biomarker concentrations in CSF or blood exosomes were reviewed. Specifically, synaptosome associated protein‐25 (SNAP‐25), growth associated protein‐43 (GAP‐43), neuronal pentraxin receptor (NPTXR), neuronal pentraxin‐1 (NPTX‐1), neuronal pentraxin‐2 (NPTX‐2), complexin‐2, syntaxin‐1B, syntaxin‐7, and vesicle‐associated membrane protein‐2 (VAMP‐2) in AD and HCs were included for meta‐analysis. A random‐effects model was used to determine standardized mean differences (SMDs) and 95% confidence intervals (CIs). Heterogeneity was quantified using I 2 . Result The meta‐analysis included 43 study cohorts. In CSF, concentrations of SNAP‐25 (N AD /N HC = 394/539, SMD [95% CI] = 1.08 [0.73, 1.42], p < 0.001; I 2 = 81.43%), GAP‐43 (N AD /N HC = 851/557, SMD [95% C] = 1.02 [0.69, 1.34], p < 0.001; I 2 = 83.97%), and VAMP‐2 (N AD /N HC = 398/490, SMD [95% CI] = 0.32 [0.05, 0.60], p = 0.02; I 2 = 64.91%) were elevated, and NPTXR (N AD /N HC = 575/470, SMD [95% CI] = ‐0.68 [‐0.96, ‐0.40], p < 0.001; I 2 = 75.59%), NPTX‐1 (N AD /N HC = 344/333, SMD [95% CI] = ‐0.48 [‐0.64, ‐0.31], p < 0.001; I 2 = 9.05%), and NPTX‐2 (N AD /N HC = 462/496, SMD [95% CI] = ‐0.78 [‐1.02, ‐0.54], p < 0.001; I 2 = 66.43%) were decreased in AD compared to HCs. In blood exosomes, SNAP‐25 (N AD /N HC = 161/159, SMD [95% CI] = ‐1.05 [‐1.28, ‐0.82], p < 0.001; I 2 = 0%) and GAP‐43 (N AD /N HC = 110/110, SMD [95% CI] = ‐1.66 [‐2.43, ‐0.88], p < 0.001; I 2 = 77%) concentrations were decreased in AD. Conclusion This study found that several synaptic biomarkers were significantly altered in AD in CSF and blood exosomes. There was significant heterogeneity for most comparisons (with the exception of CSF NPTX‐1 and blood exosome SNAP‐25) that remains to be explored. Nonetheless, further review of the identified biomarkers may provide fundamental insight into AD pathophysiology and disease trajectory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysismedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.024
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0140.056
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.047
GPT teacher head0.334
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical · Review

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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