Self and informant‐rated mild behavioral impairment and genetic risk for AD: The respondent matters
Bibliographic record
Abstract
Abstract Background Late‐life onset neuropsychiatric symptoms (NPS) have received increasing attention in recent years because of their prognostic potential for neurodegenerative disease. As focus intensifies, appropriate measurement will be critical. The emergence of Mild Behavioral Impairment ‐ which describes late‐life onset apathy, mood/anxiety symptoms, impulse dyscontrol, social inappropriateness, and psychosis ‐ and the MBI‐Checklist (MBI‐C), developed to capture these symptoms in accordance with the ISTAART‐AA MBI criteria, has been a step forward. Previous work has demonstrated only modest correlation between proxy informant and self‐rated MBI‐C responses, but the significance of these differences in responses is not yet understood. Moreover, there is relatively less work examining non‐affective late‐life NPS. To explore both of these factors, we examined the relationship between genetic risk for Alzheimer’s disease and the five MBI domains in a sample of cognitively normal older adults. Method Genetic and clinical data from 2,529 cognitively normal participants aged ≥65 in the PROTECT study were analysed. MBI was evaluated using the MBI‐C; individual domain scores were calculated, and participants dichotomised into domain ‘present’ or ‘absent’. Polygenic risk scores (PRS) for Alzheimer’s disease were used as predictors in binary logistic regression models with the MBI domains, each rated by self and by proxy, as separate outcomes. To evaluate whether AD PRS was associated with depression, the most commonly considered NPS in older adults, we also tested the association between AD PRS and PHQ‐9 score (>=5 or <5). Result AD PRS was associated with a greater risk of apathy and impulse dyscontrol in proxy MBI‐C ratings but not in self‐report MBI‐C ratings (OR: 1.2 [95% CI: 1.06‐1.40], p=0.004; OR: 1.12 [95% CI: 1.01‐1.24], p=0.03, respectively). There was no association between AD PRS and PHQ‐9 symptoms. Conclusion Proxy informant and self‐reported MBI‐C elicit different associations in analysis of AD genetic risk. These findings suggest that even in cognitively normal older adults, proxy informant ratings are important to consider in the evaluation of NPS and risk of dementia. There was no association between PHQ‐9 symptoms and AD PRS, highlighting the importance of the multi‐domain MBI‐C as a specific tool to capture late‐life NPS as risk factors for dementia.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".