Determining the Role of Sex and APOE4 status on Psychosis in Alzheimer’s Disease
Bibliographic record
Abstract
Background Psychosis occurs in approximately 41% of patients living with Alzheimer’s disease. Previous findings from our group based on analyses of a neuropathological cohort suggest that among AD patients with Lewy Body pathology, female APOE4 homozygotes are at significantly greater risk of psychosis. This study aims to replicate this finding in a clinical cohort using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Methods Our group used data from a sample of patients with AD in the ADNI database from the ADNI1, ADNI2, ADNI3, and ADNIGO studies. We defined psychosis status as experiencing hallucinations or delusions at one time point based on the Neuropsychiatric Inventory. We then used forward binary logistic regression to determine if sex and APOE4 status are predictors of AD + P. Results In total there were 204 participants who met the inclusion criteria, 133 of which were male, and 71 of which were female. Fifty-six patients were APOE4 non-carriers, 109 patients were APOE4 heterozygote carriers, and 39 were APOE4 homozygote carriers. In total, there were 59 patients with psychosis. When adjusting for mini mental state examination score, adjusted hippocampal volume, and age, we demonstrate that female APOE4 homozygotes have a significantly increased risk of psychosis compared to other groups ( P = 0.0264, OR = 19.50). Discussion The results of our study demonstrate a significant association between psychosis risk and female APOE4 homozygotes, thus corroborating findings from a neuropathological cohort. The effects of APOE ε4 on psychosis risk are significant only in females, and not in males.
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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 | 0.005 |
| 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 | 0.000 |
| 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".