Genetic risk for Alzheimer's disease, cognition, and mild behavioral impairment in healthy older adults
Bibliographic record
Abstract
Abstract Background The neuropsychiatric syndrome mild behavioral impairment (MBI) describes an at‐risk state for dementia and may be a useful screening tool for sample enrichment. We hypothesized that stratifying a cognitively normal sample on MBI status would enhance the association between genetic risk for Alzheimer's disease (AD) and cognition. Methods Data from 4458 participants over age 50 without dementia was analyzed. A cognitive composite score was constructed and the MBI Checklist was used to stratify those with MBI and those without. Polygenic scores for AD were generated using summary statistics from the IGAP study. Results AD genetic risk was associated with worse cognition in the MBI group but not in the no MBI group (MBI: β = –0.09, 95% confidence interval: –0.13 to –0.03, P = 0.002, R 2 = 0.003). The strongest association was in those with more severe MBI aged ≥65. Conclusions MBI is an important feature of aging; screening on MBI may be a useful sample enrichment strategy for clinical research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".