Genetically Proxied Telomere Length but Not Epigenetic Aging Acceleration Causally Influences Healthspan: A Mendelian Randomization Study
Bibliographic record
Abstract
Abstract Objective To assess the causal effects of leukocyte telomere length (TL) and epigenetic age acceleration (EAA) on healthspan. Methods We performed two-sample Mendelian randomization (MR) analyses in accordance with STROBE-MR guidelines. Genetic instrumental variables (IVs) for TL and four EAA biomarkers (Hannum, GrimAge, PhenoAge, and intrinsic EAA) were derived from published genome-wide association study (GWAS) summary statistics involving up to 472,174 individuals for TL and approximately 35,000 individuals for each EAA biomarker. GWAS summary statistics for healthspan, defined as age at first diagnosis of any of eight major chronic conditions or death, were obtained from the UK Biobank (N=300,477 unrelated European-ancestry participants). The primary MR estimates were obtained using the inverse-variance weighted (IVW) method, complemented by various sensitivity analyses to assess pleiotropy, instrument heterogeneity, and robustness of causal inference. The strength of the IVs was evaluated using F-statistics, and causal directionality was validated using Steiger filtering. Results Genetically predicted longer TL was causally associated with extended healthspan (IVW β=0.106; 95% CI: 0.053–0.159; p=6.9×10 -5 ). The association was robust across multiple sensitivity analyses, with no indication of directional pleiotropy (MR-Egger intercept p=0.47), no influential outliers identified by MR-PRESSO, and consistent causal direction confirmed by Steiger tests. In contrast, none of the four EAA biomarkers demonstrated convincing causal effects on health span (all IVW p-values >0.05), and results were inconsistent across sensitivity analyses, suggesting their role as correlates rather than causal determinants of healthy longevity. Conclusions This MR study provides robust evidence supporting a causal role of genetically determined telomere length in extending healthspan, while no such effect was observed for four commonly studied EAA biomarkers. These findings underscore the central role of telomere biology in healthy aging and indicate that telomere maintenance may represent a promising target for interventions aimed at delaying the onset of age-related diseases.
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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 | 0.025 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".