Mood disturbance and tau pathology in older women at risk for Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Neuropsychiatric symptoms, particularly depression, have been associated with Alzheimer’s disease (AD) biomarkers in individuals on the AD continuum. Although mood changes are a clinical manifestation of AD, research examining how the spectrum of common mood symptoms relates to AD biomarkers is limited. We examined the association between mood disturbance and tau pathology measured with positron emission tomography (PET) in older women at risk for AD and particular mood domains driving any associations. Method Participants included 18 women (Mage = 71.5, SDage = 3.3 years) with higher AD genetic risk (polygenetic hazard score ≥50th percentile) and mild impairment on the Montreal Cognitive Assessment who had completed the Profile of Mood States (POMS) questionnaire and a PET Scan as part of a larger research study. Those with formal psychiatric or neurodegenerative diagnoses were excluded. The POMS assessed six mood subcategories. The Total Mood Disturbance (TMD) was calculated as the sum of Tension, Depression, Anger, Fatigue, and Confusion subscores, minus the Vigor subscore. Tau standardized uptake value ratio (SUVR) were calculated for each Braak region of interest (ROI) (i.e., Braak 1‐2: transentorhinal stage, Braak 3‐4: limbic stage, and Braak 5‐6: isocortical stage). Linear regression models were conducted with TMD as the predictor and each Braak‐derived ROI as the outcome while controlling for age. Significant relationships were further probed by repeating analyses with each POMS subcategory as the predictor. Result Higher POMS TMD scores significantly predicted higher tau‐PET SUVRs in Braak 1‐2 (β = 0.73, p<0.01), Braak 3‐4 (β = 0.88, p<0.001), and Braak 5‐6 (β = 0.72, p<0.01) (Figure 1). Further analysis showed that the Tension subscore significantly predicted tau‐PET in all three regions (Figure 2) and Confusion significantly predicted tau‐PET in Braak 1‐2 and Braak 5‐6 (Figure 3). Conclusion Mood disturbance was consistently associated with higher tau across all Braak regions in older women with higher AD risk. These relationships were strongest when reflecting the combination of mood symptoms, but tension may have a stronger influence than other subcategories. Longitudinal research should be done to assess the directionality of this relationship and to explore whether treatments for mood symptoms may have protective effects on Alzheimer’s pathogenesis before diagnosis.
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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".