Potential Sex-Specific Effects of Apolipoprotein E ɛ4 on Cognitive Decline in Early Parkinson’s Disease
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: To compare the longitudinal trajectories of cognition according to the presence of the apolipoprotein E (APOE) ɛ4 allele in male and female Parkinson's disease (PD) patients. METHODS: This study included a total of 361 patients with recently diagnosed de novo PD (mean age [standard deviation], 61.4 [9.8] years). The patients were classified into the following groups: APOEɛ4 + /M (n = 65), APOEɛ4-/M (n = 173), APOEɛ4 + /F (n = 25), and APOEɛ4-/F (n = 98). Cognitive decline was assessed annually over 5 years of follow-up using the Montreal Cognitive Assessment (MoCA). To assess the sex-specific impacts of the APOEɛ4 status on cognitive decline, we used generalized linear mixed effects (GLME) models separately for men, women, and the two sexes combined. RESULTS: In the sex-stratified GLME models adjusted for covariates, the interaction results showed that the males with APOEɛ4 had a steeper rate of cognitive decline than those without APOEɛ4. In contrast, there was no significant interaction between APOEɛ4 and time on longitudinal MoCA performance in the females. The main effect of APOEɛ4 on the change in the MoCA score was not significant for either men or women. When the data from both men and women were used, the APOEɛ4 + /M group exhibited a steeper rate of cognitive decline than did the APOEɛ4 + /F and APOEɛ4-/F groups. These results were consistent with those of sensitivity analyses. CONCLUSION: Sex may be considered when APOEɛ4-related vulnerability to early cognitive decline is evaluated in PD patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| 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 | 0.000 | 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".