14-3-3 $$\upzeta /\updelta$$ ζ / δ -reported early synaptic injury in Alzheimer’s disease is independently mediated by sTREM2
Bibliographic record
Abstract
Abstract Introduction Synaptic loss is closely associated with tau aggregation and microglia activation in later stages of Alzheimer’s disease (AD). However, synaptic damage happens early in AD at the very early stages of tau accumulation. It remains unclear whether microglia activation independently causes synaptic cleavage before tau aggregation appears. Methods We investigated 104 participants across the AD continuum by measuring 14-3-3 zeta/delta ( $$\upzeta /\updelta$$ ζ / δ ) as a cerebrospinal fluid biomarker for synaptic degradation, and fluid and imaging biomarkers of tau, amyloidosis, astrogliosis, neurodegeneration, and inflammation. We performed correlation analyses in cognitively unimpaired and impaired participants and used structural equation models to estimate the impact of microglia activation on synaptic injury in different disease stages. Results 14-3-3 $$\upzeta /\updelta$$ ζ / δ was increased in participants with amyloid pathology at the early stages of tau aggregation before hippocampal volume loss was detectable. 14-3-3 $$\upzeta /\updelta$$ ζ / δ correlated with amyloidosis and tau load in all participants but only with biomarkers of neurodegeneration and memory deficits in cognitively unimpaired participants. This early synaptic damage was independently mediated by sTREM2. At later disease stages, tau and astrogliosis additionally mediated synaptic loss. Conclusions Our results advertise that sTREM2 is mediating synaptic injury at the early stages of tau accumulation, underlining the importance of microglia activation for AD disease propagation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".