Marital dissolution and cognition: The mediating effect of Aβ neuropathology
Bibliographic record
Abstract
Abstract Background Widowhood and divorce are extremely stressful life events and have been associated with high risk of dementia and cognitive impairment. However, the neurobiological mechanisms underlying how this risk is conferred requires further investigation. Alzheimer’s disease (AD) pathology, such as β-amyloid (Aβ), may explain influences of chronic stress, such as those seen in disruptive marital transitions, on declines in cognition. Therefore, we examined whether Aβ mediates associations between marital dissolution (through widowhood or divorce) and executive functioning (EF) and episodic memory (EM) performance in cognitively normal (CN) individuals. Methods Data from 543 CN participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were analysed. Outcomes included marital status, Aβ PET tracer uptake, and composite EF and EM scores. Primary analyses assessed relationships between marital dissolution and Aβ pathology, and marital dissolution and cognitive performance, and explored whether Aβ mediated associations between the latter. Results Marriage dissolution was associated with increased Aβ burden (β= 0.56; 95% CI: 0.11 to 1.02; P = 0.015) and worse EM performance (β= –0.09; 95% CI: –0.15 to –0.03; P = 0.003). Level of Aβ neuropathology was also identified as a significant mediator for the relationship between marriage dissolution and EM (ACME= –0.007; P = 0.029). Conclusions Aβ pathology was identified as a potential neurobiological mediator for the impacts of chronic stress due to marital dissolution on poorer memory performance. This suggests that stressful life events, such as the dissolution of one’s marriage might exert a direct effect on AD proteinopathy, which may subsequently influence poor cognition.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".