Nerve growth factor precursor alterations in neuron‐derived extracellular vesicles from individuals with Down syndrome along the Alzheimer's disease continuum
Bibliographic record
Abstract
BACKGROUND: In Down syndrome (DS) and Alzheimer's disease (AD), nerve growth factor precursor protein (proNGF) accumulates in the brain. However, its non-invasive detection using neuron-derived extracellular vesicles (NDEVs) from plasma remains unexplored. METHODS: We included 139 adults with DS (45 asymptomatic [aDS], 94 symptomatic for AD [sDS]) and 37 healthy controls. NDEVs were isolated from plasma. ProNGF and tetraspanin (CD81) were quantified by enzyme-linked immunosorbent assay. We assessed proNGF/CD81 changes with age, along the AD continuum (aDS and sDS), and associations with cerebrospinal fluid (CSF), plasma biomarkers, episodic memory, and basal forebrain volume. RESULTS: In DS, proNGF/CD81 levels increased with age and were higher in NDEVs from asymptomatic and symptomatic individuals compared to controls, with the highest levels in the symptomatic group. ProNGF correlated with CSF phosphorylated tau (p-tau)181, plasma p-tau217, neurofilament light chain, and episodic memory. DISCUSSION: ProNGF/CD81 levels in NDEVs increase along the AD continuum in DS and parallel tau pathology, indicating the potential as a promising biomarker for monitoring disease progression in plasma. HIGHLIGHTS: Nerve growth factor precursor protein (ProNGF)/tetraspanin (CD81) ratio increased in the third decade of life, 20 years before Alzheimer's disease (AD) symptom onset in Down syndrome (DS). proNGF/CD81 concentrations were significantly higher in individuals with DS compared to controls and were notably elevated in individuals with DS and symptomatic AD compared to asymptomatic AD. proNGF/CD81 concentrations were associated with tau pathology and neuronal injury.
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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 | 0.000 | 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 | 0.000 | 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".