P1‐005: Memory Resilience in Carriers of Alzheimer's Genetic Risk: Predictors Vary for Female and Male Older Adults
Bibliographic record
Abstract
Apolipoprotein E (APOE) ɛ4 and Clusterin (CLU) C alleles are established genetic risk factors for both Alzheimer’s disease (AD) and non-demented episodic memory (EM) decline. We investigated whether memory resilience to AD genetic risk (i.e., APOE ɛ4 and CLU CC) is predicted by modifiable factors that are sex-specific and genetically robust. The data included non-demented older adults in the Victoria Longitudinal Study (n=642 eligible cases, aged 53-95; 3 waves, 9 years). All analyses were stratified by sex. We used growth mixture modelling to analyze 9-year latent variable memory level and trajectories. Participants with higher (level) and sustained (slope) EM performance were differentiated from those with lower and declining EM performance. We classified participants as memory resilient if they (1) had the APOE or CLU AD risk allele(s) and (2) were included in the higher and sustained memory performance group. We examined resilience group differences for a set of factors derived from four documented AD risk domains: (1) demographic (e.g., education), (2) functional (e.g., pulse pressure), (3) health (e.g., mobility), and (4) lifestyle (e.g., cognitive activity). We used random forest analysis to test the relative predictive importance of these factors for memory resilience. Memory level and stability over nine years was maintained in 67.6% of female participants (slope=0.00±0.01, intercept=0.60±0.61) and 52.8% of male participants (slope=0.00±0.01, intercept=0.10±0.59). Memory resilience was reliably predicted by younger age, higher educational level, and lifestyle-related cognitive activity across sex for both genetic variants. Selectively for females, memory resilience was also predicted by selected functional, health, and social factors. For males, an additional functional factor (muscle tone) was an important predictor. Prediction patterns of memory resilience were robust across these two genetic variants. Long-term memory resilience in non-demented aging is predicted by risk and protective factors that are both common and unique to females and males. To the extent these factors are modifiable, the greater number and breadth identified for females may enhance opportunities for sex-specific multi-factorial interventions to promote functional maintenance and delay cognitive decline. Identifying factors that promote cognitive resilience is especially crucial for aging adults with AD genetic risk.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".