Frequency of the Apolipoprotein E ε4 Allele in a Memory Clinic Cohort in Beijing: A Naturalistic Descriptive Study
Bibliographic record
Abstract
OBJECTIVES: To describe the distribution of apolipoprotein E (APOE) genotypes among an elderly Chinese patient population with memory complaints treated in a memory clinic in Beijing and to compare the ε4 allele frequency among individuals with subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and Alzheimer's disease (AD). METHODS: A total of 385 subjects with memory complaints participated in the study, including 216 patients with AD, 56 with MCI, 17 with SCI, and 96 with other types of cognitive impairment. A total of 75 healthy elderly control subjects were also recruited. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique was used to investigate the APOE genotypes. RESULTS: The frequency of the ε4 allele was 19.6 percent for the entire sample of patients who had memory complaints. The APOE allele distribution differed between women and men (22.6% and 14.9%, respectively; p<0.05) in the individuals with memory complaints. Compared with the control group (7.3%), the prevalence of the APOE ε4 allele was significantly higher in the AD (23.6%) and MCI (21.4%) groups and was slightly increased in the SCI (14.7%) group. CONCLUSIONS: In the memory clinic, we observed a higher prevalence of the APOE ε4 allele among Chinese AD and MCI patients. A similar trend was observed in patients with SCI. These findings suggest that nondemented APOE ε4 allele carriers with memory complaints may have a greater genetic risk for AD and should be monitored more closely.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".