PTSD moderates the association between subjective cognitive decline and Alzheimer’s disease biomarkers in older veterans
Bibliographic record
Abstract
OBJECTIVES: Post-traumatic stress disorder (PTSD) and subjective cognitive decline (SCD) are independent risk factors for Alzheimer's disease (AD) and dementia, but the association of their interaction on AD biomarkers have yet to be characterized. This study aimed to examine the impact of PTSD on the association between SCD and tau and amyloid positron emission tomography (PET) as well as global cognition in older Veterans. METHOD: This study included 87 Vietnam-Era Veterans without dementia (42 with PTSD; 45 without PTSD) from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative. All participants had both tau and amyloid PET imaging as well as cognitive testing. SCD was measured using the Everyday Cognition questionnaire. RESULTS: While SCD was associated with tau PET, amyloid PET, and global cognition, PTSD moderated these associations for tau and amyloid PET levels. Specifically, Veterans without PTSD had a stronger positive relationship between SCD and AD biomarkers when compared to those with PTSD. CONCLUSION: Higher SCD was associated with greater tau and amyloid burden and worse cognitive performance across the sample, though the tau and amyloid associations were stronger for Veterans without PTSD. Results highlight the potential benefit of comprehensive clinical assessments including consideration of mental health among older Veterans with SCD to understand the underlying cause of the cognitive concerns. Additionally, more work is needed to understand alternative mechanisms driving SCD in older Veterans with PTSD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".