Longitudinal changes in epigenetic clocks predict survival in the InCHIANTI cohort
Bibliographic record
Abstract
Abstracts Importance Cross-sectional assessment of epigenetic clocks provides information on the pace of aging. Whether longitudinal acceleration or deceleration of epigenetic clocks over time provides additional mortality prediction is unknown. Objective To test the independent associations of baseline levels and longitudinal changes in epigenetic clocks with mortality Design Longitudinal study Setting InCHIANTI, a population-based study of community dwelling individuals in Tuscany, Italy. Participants 699 InCHIANTI study participants aged 21-95 years at baseline with longitudinal measurements of DNA methylation. Exposure Baseline levels and longitudinal changes in seven epigenetic clocks, including two first-generation clocks developed using chronological age for reference (Hannum Clock, Horvath Clock), three second-generation clocks developed using time-to-death for references (DNAmPhenoAge, DNAmGrimAge, DNAmGrimAge Version 2), and two third-generation clocks developed using longitudinal rate of change of multiple phenotypes for reference (DunedinPOAm_38, DunedinPACE). Main Outcomes and Measures Mortality was the primary outcome. Cox regression was used to estimate independent associations of baseline and longitudinal changes in epigenetic clocks with mortality. Results Adjusting for age, sex, study sites, and epigenetic clock at the baseline, longitudinal changes of the following epigenetic clocks were associated with mortality: Hannum clock (aHR = 1.14, 95% CI:[1.03, 1.26]), DNAmPhenoAge (aHR = 1.23, 95% CI: [1.10,1.37]), DNAmGrimAge (aHR = 1.13, 95% CI: [1.02,1.26]), DNAmGrimAge Version 2 (aHR = 1.18, 95% CI:[1.06,1.31]), and DunedinPOAm_38 (aHR = 1.15, 95%CI: [1.01,1.30]). Conclusions and Relevance Our findings confirm that epigenetic clocks capture a dimension of health that is predictive of mortality and add the notion that time changes of epigenetic age reflect changes in health that additionally and independently contribute to mortality prediction. Future studies should test whether interventions that slow down the rate of epigenetic aging are associated with longer healthspan and lifespan. Key Points Question: Is the rate of change in epigenetic clock associated with differential mortality? Findings: In 699 adults with followed for up to 24 years, faster longitudinal changes in epigenetic clocks (Hannum clock, DNAmPhenoAge, DNAmGrimAge, DNAmGrimAge version 2, DunedinPOAm_38, DunedinPACE) were significantly associated with higher mortality, independent of baseline epigenetic age and other confounders. Meaning: Independent of chronological age, epigenetic clock and change over time of epigenetic clock independently predicted the risk of death. Interventions that slow down the pace of epigenetic aging may enhance healthy longevity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".