Neurite Degradation Mediates the Effect of Amyloid Deposition on Global Cognition in Asymptomatic Older Adults
Bibliographic record
Abstract
Abstract This study investigates whether amyloid deposition is associated with neurite degradation in cognitively unimpaired (asymptomatic) older adults, with a focus on brain regions critical for memory and cognition. Using data from the ADNI3 cohort (n = 65; mean age 69.5±5.5), we examined the relationship between amyloid levels (from PET imaging), neurite density (derived from diffusion MRI-based Neurite Orientation Dispersion and Density Imaging, NODDI), and global cognition (MoCA scores). NODDI is a biophysical diffusion MRI model that quantifies microstructural features of brain tissue through metrics like neurite density index (NDI) that may sensitively capture early neurodegenerative changes leading up to Alzheimer’s Disease (AD). Spearman correlation analyses showed significant negative associations between amyloid and NDI in the right entorhinal cortex (ρ = -0.29; p = 0.02) and left fusiform gyrus (ρ = -0.26; p = 0.04). Amyloid also correlated with ODI in the left (ρ = -0.31; p = 0.011) and right fusiform gyrus (ρ = -0.33; p = 0.006). Mediation analyses revealed significant effects for NDI in the left entorhinal cortex (p = 0.02) and left fusiform gyrus (p = 0.006), and for ODI in the left fusiform gyrus (p = 0.044). These findings indicate that even in the absence of clinical symptoms, amyloid deposition may contribute to microstructural degradation in key brain areas, which in turn relates to cognitive function. NDI specifically may hold promise as an early imaging marker for identifying individuals at risk and tracking AD progression. Significance Statement This study demonstrates that neurite degradation, measured by neurite density index (NDI), mediates the relationship between amyloid deposition and global cognitive function in asymptomatic older adults, highlighting NDI as a promising early marker of microstructural vulnerability in preclinical Alzheimer’s disease.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".