Associations of Anxiety with Amyloid, Tau, and Neurodegeneration in Older Adults without Dementia: A Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: The pathophysiological process of amyloid-β, tau deposition, and neurodegeneration of Alzheimer's disease (AD) begin in a preclinical phase, while anxiety is associated with an increased risk of AD in preclinical phase. OBJECTIVE: To examine the relationships between anxiety and amyloid-β, tau deposition, and neurodegeneration. To test the hypothesis that anxiety could predict clinical progression in the elderly without dementia. METHODS: 1,400 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were included in the study and were studied over a median period of 3 years. In multivariable models, the cross-sectional and longitudinal associations between anxiety and amyloid-β PET, tau PET, and FDG PET SUVRs in participants without dementia were explored using Spearman rank correlation, logistic regression model, multiple linear regression model, Kaplan-Meier survival curves, and Cox proportional hazards model. The association between baseline anxiety and clinical progression was also explored. RESULTS: There was a positive correlation between anxiety and amyloid-β deposition (r = 0.11, p = 0.0017) and a negative correlation between anxiety and neurodegeneration (r = -0.13, p = 0.00022). MCI participants with anxiety showed a faster clinical progression of dementia (HR = 1.56, p = 0.04). Non-anxious participants with more amyloid-β deposition or more severe neurodegeneration displayed accelerated development into anxiety (HR = 2.352, p < 0.0001; HR = 2.254, p < 0.0001). CONCLUSION: Anxiety was associated with amyloid-β deposition and neurodegeneration in non-dementia elderly. Anxiety in MCI predicted conversion to dementia. Anxiety may play a selective role and prediction of disease progression in the early phase of AD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".