Determining Whether Sex and Zygosity Modulates the Association between APOE4 and Psychosis in a Neuropathologically-Confirmed Alzheimer’s Disease Cohort
Bibliographic record
Abstract
Background: The APOE4 allele is a genetic risk factor for developing late-onset Alzheimer’s disease (AD). Previous work by our group revealed that female APOE4 homozygotes with Lewy body (LB) pathology were more likely to experience psychosis compared to female APOE4 non-carriers, whereas in males there was no APOE4 dose-dependent significant effect. The objective of this study was to refine our previous findings by adjusting for covariates and determining the probability of an APOE4 sex-mediated effect on psychosis. Methods: Neuropathologically confirmed AD patients with LB pathology (n = 491) and without LB pathology (n = 716) were extracted from the National Alzheimer’s Coordinating Center (NACC). Patients were classified as psychotic if they scored positively for delusions and/or hallucinations on the Neuropsychiatric Inventory. Analysis consisted of a preliminary unadjusted binary logistic regression and a Generalized Additive binary logistic regression Model (GAM) to predict the relationship between APOE4 status and sex on the presence of psychosis in both cohorts, adjusting for age, education and MMSE. Results: In the cohort with LB pathology, female APOE4 homozygotes were significantly more likely to experience psychosis compared to female APOE4 non-carriers (OR = 4.15, 95%CI [1.21, 14.2], p = 0.023). Female heterozygotes were also more likely to experience psychosis compared to female APOE4 non-carriers, but to a lesser extent (OR = 2.37, 95%CI [1.01, 5.59], p = 0.048). There was no significant difference in males with LB pathology or in any sex in the cohort without LB pathology. Conclusions: Sex and zygosity influence the effect of APOE4 on psychosis in neuropathologically confirmed AD patients, with the effect being limited to females with LB pathology.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".