P4‐225: Relation of plasmalogens, ApoE genotype, and Alzheimer's disease pathology to cognition: A post‐mortem analysis
Bibliographic record
Abstract
Presence of the ApoE ε4 allele, ethanolamine plasmalogen (PlsEtn) levels, and amyloid plaques or neurofibrillary tangles density in the brain are associated with the severity of dementia and AD pathology. The independent and combined associations of these factors on cognition and AD pathology was investigated. PlsEtn, amyloid, tangles, ApoE genotype, and mRNA transcripts for enzyme, and transport proteins involved in plasmalogen synthesis were determined in the temporal cortex of 100 subjects who had completed comprehensive cognitive testing prior to death. Subjects were grouped into one of three ApoE subgroups (ε2=ε2ε3, ε3=ε3ε3, ε4=ε3ε4+ ε4ε4) and ε3 was used as the reference. After adjusting for only demographic variables (age, education, gender), the key variables associated with cognition were: docosahexaenoic acid (DHA)-PlsEtn (Coef:0.620, p=8.7E-09, r=0.329, n=99), tangles (Coef: -0.552, p=4.0E-06, r=0.267, n=99), amyloid (Coef: -0.394, p=1.1E-04, r=0.150, n=99), ApoE ε4 (Coef: -0.369, p=4.2E-03, r=0.131, n=91), Dihydroxyacetone phosphate alkyltransferase (DHAPAT, Coef: 0.307, p=2.7E-02, r=0.109, n=94). Neither amyloid nor ApoE ε4 was associated with cognition in combined models of these variables where brain DHA-PlsEtn level, tangle density and age showed independent associations with cognition. ApoE ε4 was the dominant variable associated with amyloid (Coef: 1.185, p=5.3E-07, r=0.297, n=91). Overall, 46% of the variance in cognition was associated with DHA-PlsEtn, tangles, DHAPAT, and age. Amyloid (Coef:-0.025 p=1.4E-03, r=0.084, n=99), ApoE ε4 (Coef: -0.044, p=2.1E-02, r=0.081, n=92), and tangles (Coef:-0.044 p=1.1E-04, r=0.153, n=100) were associated with DHA-PlsEtn levels. Of the variables investigated, temporal cortex DHA-PlsEtn level exhibited the strongest association with cognition. Only tangles and age were associated with cognition independent of brain DHA-PlsEtn levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".