APOE ε4 and the Influence of Sex, Age, Vascular Risk Factors, and Ethnicity on Cognitive Decline
Bibliographic record
Abstract
We aimed to examine the relationship between Apolipoprotein E ε4 (APOE*4) carriage on cognitive decline, and whether these associations were moderated by sex, baseline age, ethnicity, and vascular risk factors. Participants were 19,225 individuals aged 54-103 years from 15 longitudinal cohort studies with a mean follow-up duration ranging between 1.2 and 10.7 years. Two-step individual participant data meta-analysis was used to pool results of study-wise analyses predicting memory and general cognitive decline from carriage of one or two APOE*4 alleles, and moderation of these associations by age, sex, vascular risk factors, and ethnicity. Separate pooled estimates were calculated in both men and women who were younger (ie, 62 years) and older (ie, 80 years) at baseline. Results showed that APOE*4 carriage was related to faster general cognitive decline in women, and faster memory decline in men. A stronger dose-dependent effect was observed in older men, with faster general cognitive and memory decline in those carrying two versus one APOE*4 allele. Vascular risk factors were related to an increased effect of APOE*4 on memory decline in younger women, but a weaker effect of APOE*4 on general cognitive decline in older men. The relationship between APOE*4 carriage and memory decline was larger in older-aged Asians than Whites. In sum, APOE*4 is related to cognitive decline in men and women, although these effects are enhanced by age and carriage of two APOE*4 alleles in men, a higher numbers of vascular risk factors during the early stages of late adulthood in women, and Asian ethnicity.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| 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) | 0.001 | 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".