Meta-analysis of the Connection Between Alzheimer Disease and Telomeres
Bibliographic record
Abstract
BACKGROUND: Alzheimer disease (AD) is the most common neurodegenerative disease of the central nervous system. The stability of the telomere-telomerase system is closely related to AD. A previous meta-analysis indicated that AD patients had shorter telomere length (TL) than control subjects. However, there are no consistent telomerase activity findings in AD patients, and the published telomerase studies were not meta-analyzed yet. METHODS: We searched all the related studies that probed into TL and/or telomerase activity in AD patients based on PubMed and Embase database from the establishment to September 2020. The Chinese National Knowledge Infrastructure, Wanfang and China Science and Technology Journal Database were also utilized. The quality of the included studies was evaluated by using Newcastle-Ottawa Scale. All the statistical analyses of this meta-analysis were performed using Stata version 15.0. RESULTS: Analyzing 30 TL data from 2248 AD patients and 4865 controls, AD patients had a significantly shorter TL than the controls, with a standardized mean difference of -0.70 (confidence interval: -0.95 to -0.46; P<0.05). The meta-analysis included 3 primary studies and did not find a significant difference in the telomerase activity between 233 AD patients and 132 controls, but AD patients had a trend of increased telomerase activity compared with controls (standardized mean difference: 0.47; confidence interval: -0.29 to 1.23; P>0.05). CONCLUSION: Our results showed that compared with the control group, the AD group had a shorter TL and may have higher telomerase activity.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.050 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".