Heritable variation in telomere length predicts mortality in Soay sheep
Bibliographic record
Abstract
Telomere length (TL) is considered an important biomarker of whole-organism health and aging. Across humans and other vertebrates, short telomeres are associated with increased subsequent mortality risk, but the processes responsible for this correlation remain uncertain. A key unanswered question is whether TL-mortality associations arise due to positive effects of genes or early-life environment on both an individual's average lifetime TL and their longevity, or due to more immediate effects of environmental stressors on within-individual TL loss and increased mortality risk. Addressing this question requires longitudinal TL and life history data across the entire lifetimes of many individuals, which are difficult to obtain for long-lived species like humans. Using longitudinal data and samples collected over nearly two decades, as part of a long-term study of wild Soay sheep, we dissected an observed positive association between TL and subsequent survival using multivariate quantitative genetic models. We found no evidence that telomere attrition was associated with increased mortality risk, suggesting that TL is not an important marker of biological aging or exposure to environmental stress in our study system. Instead, we find that among-individual differences in average TL are associated with increased lifespan. Our analyses suggest that this correlation between an individual's average TL and lifespan has a genetic basis. This demonstrates that TL has the potential to evolve under natural conditions, and suggests an important role of genetics underlying the widespread observation that short telomeres predict mortality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".