Amyloid pathology modulates the relationship between subsyndromal symptomatic depression and tau accumulation in non-demented older adults
Bibliographic record
Abstract
Objective Subsyndromal symptomatic depression (SSD) has been increasingly implicated in the pathophysiological processes of Alzheimer’s disease (AD). However, it remains unclear whether SSD and amyloid-β (Aβ) pathology jointly contribute to tau deposition. This study aimed to investigate the interaction between SSD and Aβ status on regional tau accumulation in non-demented older adults. Materials and methods We analyzed data from 391 non-demented older adults in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who underwent Aβ and tau positron emission tomography (PET) scans, as well as Geriatric Depression Scale (GDS-15) assessments. Aβ positivity (Aβ+) was defined by established tracer-specific standardized uptake value ratio (SUVR) thresholds (≥1.11 for 18 F-florbetapir or ≥1.08 for 18 F-florbetaben). SSD was defined as a GDS-15 score of 1–5. Linear mixed-effects models were applied to assess the longitudinal effects of SSD and Aβ status on regional tau accumulation over 2 years. Results At baseline, significant interactions between SSD and Aβ status were observed for regional tau SUVRs, with the Aβ+/SSD+ group exhibiting significantly higher tau levels across all Braak stages compared with the other groups. Longitudinal analyses identified a significant three-way interaction among SSD, Aβ status, and time in the Braak III/IV and Braak V/VI regions. Moreover, the Aβ+/SSD+ group demonstrated significantly faster tau accumulation compared to all other groups. The Aβ+/SSD− group also exhibited greater tau accumulation than the Aβ−/SSD− group, whereas no significant differences were observed between the Aβ− groups. Conclusion These findings suggest that SSD is associated with greater early tau accumulation in individuals with Aβ pathology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".