Effects of Cognitive- and Sleep- Related Single Nucleotide Polymorphisms on Cognitive Functions in the Han Chinese Community-dwelling Elderly
Bibliographic record
Abstract
Abstract Objective: The genetic biomarkers on Alzheimer’s disease (AD) have been widely studied in different groups. Since the lack of efficacy therapeutic methods for AD, early recognition in preclinical stage becomes increasingly important. Evidence of AD and cognitive-related single nucleotide polymorphisms (SNPs) in high risk population is insufficiency. Our aim was to assess whether these SNPs within cognitive- and sleep- associated genes are correlated with cognitive impairment independently or through gene-gene interactions in community-dwelling elderly in Beijing. Methods: Eight single-nucleotide polymorphisms (SNPs) were genotyped in 2133 Northen Han Chinese elderly from ten communites in Chaoyang District, Beijing. The short version of the Montreal Cognitive Assessment-Beijing (MoCA-s), Ascertain Dementia 8 (AD8), Digit Span Backwards (DSB), Digital Symbol Substitution Test (DSST), and Paired Associative Learning Test (PALT) were used to detect different cognitive domains.Results: Logistic regression analyses showed a significant correlation between APOE (rs429358), ABCC9 (rs11046205) and cognitive impairment, and an interaction between ABCC9 (rs11046205)/APOE promoter (rs405509) and APOE ε4 status. Additionally, we found a significant negative association between the additive model of APOE (rs429358) and MMSE score. Moreover, our analysis revealed that the gene-gene interaction between ABCC9 (rs11046205) and APOE (429358) may contribute to the etiology of congnitive impairment.Conclusions: This study confirmed the independent contribution of AD, memory and sleep-related genes in the cognitive impairment of the community-dwelling elderly in China, as well as through gene-gene interactions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".