Author response: High social status males experience accelerated epigenetic aging in wild baboons
Bibliographic record
Abstract
For most animals, age is one of the strongest predictors of health and survival, but not all individuals age at the same rate. In fact, animals of the same species can have different 'biological ages' even when they have lived the same number of years. In humans and other mammals this variation in aging shows up in chemical modifications known as DNA methylation marks. Some researchers call these marks 'epigenetic', which literally means 'upon the genes'. And some DNA methylation marks change with age, so their combined pattern of change is often called the ‘epigenetic clock’. Environmental stressors, such as smoking or lack of physical activity, can make the epigenetic clock ‘tick’ faster, making the DNA of some individuals appear older than expected based on their actual age in years. These ‘biologically older’ individuals may also experience a higher risk of age-related disease. Studies in humans have revealed some of the reasons behind this fast biological aging, but it is unclear whether these results apply in the wild. It is possible that early life events trigger changes in the epigenetic clock, affecting health in adulthood. In primates, for example, adversity in early life has known effects on fertility and survival. Low social status also has a negative effect on health. To find out whether early experiences and the social environment affect the epigenetic clock, Anderson, Johnston et al. tracked DNA methylation marks in baboons. This revealed that epigenetic clocks are strong predictors of age in wild primates, but neither early adversity nor the strength of social bonds affected the rate at which the clocks ticked. In fact, it was competition for social status that had the most dramatic effect on the clock’s speed. Samples of males taken at different times during their lives showed that their epigenetic clocks sped up or slowed down as they moved up or down the social ladder, reflecting recent social experiences, rather than events early in their lives. On average, epigenetic clock measurements overestimated the age in years of alpha males by almost a year, showing that fighting to be on top comes at a cost. This study highlights one way in which the social environment can influence aging. The next step is to understand how health is affected by the ways that animals attain social status. This could help researchers who study evolution understand how social interactions and environmental conditions affect survival and reproduction. It could also provide insight into the effects of social status on human health and aging.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.077 | 0.011 |
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".