Apolipoprotein E (APOE) and Alzheimer’s disease risk in a Ugandan population: A pilot case-control study
Bibliographic record
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by cognitive decline and progressive functional impairment. The Apolipoprotein E (APOE) gene, particularly its ε2, ε3, and ε4 alleles, plays a crucial role in lipid metabolism, and has been implicated in AD pathogenesis. Although the APOE ε4 status is associated with an increased risk of AD, its impact varies across populations. This study investigated the prevalence of and association between APOE alleles and AD risk in a Ugandan cohort. This case-control study was conducted in Uganda, and included 87 participants (45 patients with AD and 42 healthy controls). Cognitive assessment was performed using the Montreal Cognitive Assessment (MoCA) and clinical diagnoses were based on the ICD-11 and DSM-5 criteria. Venous blood was collected for APOE genotyping by polymerase chain reaction. Statistical analyses, including logistic regression and generalized additive models (GAMs), were used to assess the association between APOE alleles and AD risk after adjusting for age, education, and sex. This study included 45 patients with AD and 42 healthy controls. The AD group was significantly older than controls (79.6 vs 73.0 years; P = .0006). The ε4 allele was common in both the AD (42.2%) and control groups (44.0%), which was higher than the 1000 Genomes African ancestry data. No significant association was found between the APOE genotype or allele dosage and AD risk after adjusting for age, sex, and education. However, the probability of AD increases with age, particularly among ε4 carriers with lower educational levels. While APOE ε4 status was associated with a higher predicted probability of AD in older adults, no statistically significant relationship was observed in the Ugandan cohort. These findings support the need for larger population-specific studies to explore APOE's role of APOE in AD risk across sub-Saharan Africa.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".