Telomere length and brain aging: A systematic review and meta-analysis
Bibliographic record
Abstract
The current evidence on the association of leukocyte telomere length (LTL) with age-related structural and cognitive changes in the brain is mixed. Herein conforming to PRISMA 2020 guidelines, we performed a systematic review and meta-analysis using data from 27 observational studies in non-demented individuals. We used effect size and p-value based meta-analysis methods considering marked heterogeneity among studies. We found that the longer LTL was associated with higher brain volume (β = 0.43, 95%CI: 0.36-0.50%, p = 0.008, N = 1102) and with higher global cognition (β = 0.01; 95%CI: 0.00-0.02, p = 0.03, N = 19609) by effect size based meta-analysis and with brain volume, hippocampal volume, global cognition, cognitive domains of attention/speed as well as executive functions by p-value based meta-analysis. No significant association of LTL with brain white matter hyperintensities was detected. Furthermore, the evidence strongly suggests a subgroup-specific canonical effect of telomeres, notably in older individuals and females. In conclusion, we provide meta-analytic evidence on the beneficial effect of telomeres on brain structure as well as cognition and advocate for a beneficial subgroup-specific effect that warrants further attention.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.020 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".