AD and non‐AD mediators of the pathway between the <i>APOE</i> genotype and cognition
Bibliographic record
Abstract
INTRODUCTION: The apolipoprotein E (APOE) genotype is a driver of cognitive decline and dementia. We used causal mediation methods to characterize pathways linking the APOE genotype to late-life cognition through Alzheimer's disease (AD) and non-AD neuropathologies. METHODS: We analyzed autopsy data from 1671 individuals from the Religious Orders Study, Memory and Aging Project, and Minority Aging Research Study (ROS/MAP/MARS) studies with cognitive assessment within 5 years of death and autopsy measures of AD (amyloid beta (Aβ), neurofibrillary tangles), vascular (athero/arteriolo-sclerosis, micro-infarcts/macro-infarcts), and non-AD neurodegenerative neuropathologies (TAR DNA protein 43 [TDP-43], Lewy bodies, amyloid angiopathy, hippocampal sclerosis). RESULTS: The detrimental effect of APOE ε4 on cognition was mediated by summary measures of AD and non-AD neurodegenerative neuropathologies but not vascular neuropathologies; effects were strongest in individuals with dementia. The protective effect of APOE ε2 was partly mediated by AD neuropathology and stronger in women than in men. DISCUSSION: The APOE genotype influences cognition and dementia through multiple neuropathological pathways, with implications for different therapeutic strategies targeting people at increased risk for dementia. HIGHLIGHTS: Both apolipoprotein E (APOE) ε2 and APOE ε4 effects on late-life cognition are mediated by AD neuropathology. The estimated mediated effects of most measures of AD neuropathology were similar. Non-Alzheimer's disease (AD) neurodegenerative pathologies mediate the effect of ε4 independently from AD. Non-AD vascular pathologies did not mediate the effect of the APOE genotype on cognition. The protective effect of APOE ε2 on cognition was stronger in women.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".