Paternal age is positively linked to telomere length of children
Bibliographic record
Abstract
Telomere length is linked to age-associated diseases, with shorter telomeres in blood associated with an increased probability of mortality from infection or heart disease. Little is known about how human telomere length is regulated despite convincing data from twins that telomere length is largely heritable, uniform in various tissues during development until birth and variable between individuals. As sperm cells show increasing telomere length with age, we investigated whether age of fathers at conception correlated with telomere length of their offspring. Telomere length in blood from 125 random subjects was shown to be positively associated with paternal age (+22 bp yr -1, 95% confidence interval 5.2-38.3, P = 0.010), and paternal age was calculated to affect telomere length by up to 20% of average telomere length per generation. Males lose telomeric sequence faster than females (31 bp yr -1, 17.6-43.8, P < 0.0001 vs. 14 bp yr -1, 3.5-24.8, P < 0.01) and the rate of telomere loss slows throughout the human lifespan. These data indicate that paternal age plays a role in the vertical transmission of telomere length and may contribute significantly to the variability of telomere length seen in the human population, particularly if effects are cumulative through generations.
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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 | 0.006 |
| 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) | 0.003 | 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".